Author: "Rafferty" / Publication Type: Reports - Searchworks@Jio Institute Digital Library Search Results

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1. Uncertainty-preserving deep knowledge tracing with state-space models

Author: Christie, S. Thomas, Cook, Carson, and Rafferty, Anna N.
Subjects: Computer Science - Computers and Society, Computer Science - Machine Learning
Abstract: A central goal of both knowledge tracing and traditional assessment is to quantify student knowledge and skills at a given point in time. Deep knowledge tracing flexibly considers a student's response history but does not quantify epistemic uncertainty, while IRT and CDM compute measurement error but only consider responses to individual tests in isolation from a student's past responses. Elo and BKT could bridge this divide, but the simplicity of the underlying models limits information sharing across skills and imposes strong inductive biases. To overcome these limitations, we introduce Dynamic LENS, a modeling paradigm that combines the flexible uncertainty-preserving properties of variational autoencoders with the principled information integration of Bayesian state-space models. Dynamic LENS allows information from student responses to be collected across time, while treating responses from the same test as exchangeable observations generated by a shared latent state. It represents student knowledge as Gaussian distributions in high-dimensional space and combines estimates both within tests and across time using Bayesian updating. We show that Dynamic LENS has similar predictive performance to competing models, while preserving the epistemic uncertainty - the deep learning analogue to measurement error - that DKT models lack. This approach provides a conceptual bridge across an important divide between models designed for formative practice and summative assessment., Comment: In Proceedings of the 17th International Conference on Educational Data Mining (EDM 2024)
Published: 2024

2. Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms

Author: Kumar, Harsh, Xiao, Ruiwei, Lawson, Benjamin, Musabirov, Ilya, Shi, Jiakai, Wang, Xinyuan, Luo, Huayin, Williams, Joseph Jay, Rafferty, Anna, Stamper, John, and Liut, Michael
Subjects: Computer Science - Computers and Society
Abstract: Self-reflection on learning experiences constitutes a fundamental cognitive process, essential for the consolidation of knowledge and the enhancement of learning efficacy. However, traditional methods to facilitate reflection often face challenges in personalization, immediacy of feedback, engagement, and scalability. Integration of Large Language Models (LLMs) into the reflection process could mitigate these limitations. In this paper, we conducted two randomized field experiments in undergraduate computer science courses to investigate the potential of LLMs to help students engage in post-lesson reflection. In the first experiment (N=145), students completed a take-home assignment with the support of an LLM assistant; half of these students were then provided access to an LLM designed to facilitate self-reflection. The results indicated that the students assigned to LLM-guided reflection reported increased self-confidence and performed better on a subsequent exam two weeks later than their peers in the control condition. In the second experiment (N=112), we evaluated the impact of LLM-guided self-reflection against other scalable reflection methods, such as questionnaire-based activities and review of key lecture slides, after assignment. Our findings suggest that the students in the questionnaire and LLM-based reflection groups performed equally well and better than those who were only exposed to lecture slides, according to their scores on a proctored exam two weeks later on the same subject matter. These results underscore the utility of LLM-guided reflection and questionnaire-based activities in improving learning outcomes. Our work highlights that focusing solely on the accuracy of LLMs can overlook their potential to enhance metacognitive skills through practices such as self-reflection. We discuss the implications of our research for the Edtech community., Comment: Accepted at L@S'24
Published: 2024

3. Sustainable business decision modelling with blockchain and digital twins: A survey

Author: Wickremasinghe, Gyan, Frost, Siofra, Rafferty, Karen, and Sharma, Vishal
Subjects: Computer Science - Networking and Internet Architecture, Computer Science - Emerging Technologies
Abstract: Industry 4.0 and beyond will rely heavily on sustainable Business Decision Modelling (BDM) that can be accelerated by blockchain and Digital Twin (DT) solutions. BDM is built on models and frameworks refined by key identification factors, data analysis, and mathematical or computational aspects applicable to complex business scenarios. Gaining actionable intelligence from collected data for BDM requires a carefully considered infrastructure to ensure data transparency, security, accessibility and sustainability. Organisations should consider social, economic and environmental factors (based on the triple bottom line approach) to ensure sustainability when integrating such an infrastructure. These sustainability features directly impact BDM concerning resource optimisation, stakeholder engagement, regulatory compliance and environmental impacts. To further understand these segments, taxonomies are defined to evaluate blockchain and DT sustainability features based on an in-depth review of the current state-of-the-art research. Detailed comparative evaluations provide insight into the reachability of the sustainable solution in terms of ideologies, access control and performance overheads. Several research questions are put forward to motivate further research that significantly impacts BDM. Finally, a case study based on an exemplary supply chain management system is presented to show the interoperability of blockchain and DT with BDM., Comment: 34 pages, 19 figures, 7 tables
Published: 2024

4. Transparent and Clinically Interpretable AI for Lung Cancer Detection in Chest X-Rays

Author: Rafferty, Amy, Ramaesh, Rishi, and Rajan, Ajitha
Subjects: Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract: The rapidly advancing field of Explainable Artificial Intelligence (XAI) aims to tackle the issue of trust regarding the use of complex black-box deep learning models in real-world applications. Existing post-hoc XAI techniques have recently been shown to have poor performance on medical data, producing unreliable explanations which are infeasible for clinical use. To address this, we propose an ante-hoc approach based on concept bottleneck models which introduces for the first time clinical concepts into the classification pipeline, allowing the user valuable insight into the decision-making process. On a large public dataset of chest X-rays and associated medical reports, we focus on the binary classification task of lung cancer detection. Our approach yields improved classification performance in lung cancer detection when compared to baseline deep learning models (F1 > 0.9), while also generating clinically relevant and more reliable explanations than existing techniques. We evaluate our approach against post-hoc image XAI techniques LIME and SHAP, as well as CXR-LLaVA, a recent textual XAI tool which operates in the context of question answering on chest X-rays., Comment: 12 pages, 10 figures
Published: 2024

5. Generative AI for Education (GAIED): Advances, Opportunities, and Challenges

Author: Denny, Paul, Gulwani, Sumit, Heffernan, Neil T., Käser, Tanja, Moore, Steven, Rafferty, Anna N., and Singla, Adish
Subjects: Computer Science - Computers and Society, Computer Science - Artificial Intelligence
Abstract: This survey article has grown out of the GAIED (pronounced "guide") workshop organized by the authors at the NeurIPS 2023 conference. We organized the GAIED workshop as part of a community-building effort to bring together researchers, educators, and practitioners to explore the potential of generative AI for enhancing education. This article aims to provide an overview of the workshop activities and highlight several future research directions in the area of GAIED.
Published: 2024

6. Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health

Author: Kumar, Harsh, Li, Tong, Shi, Jiakai, Musabirov, Ilya, Kornfield, Rachel, Meyerhoff, Jonah, Bhattacharjee, Ananya, Karr, Chris, Nguyen, Theresa, Mohr, David, Rafferty, Anna, Villar, Sofia, Deliu, Nina, and Williams, Joseph Jay
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning
Abstract: Digital mental health (DMH) interventions, such as text-message-based lessons and activities, offer immense potential for accessible mental health support. While these interventions can be effective, real-world experimental testing can further enhance their design and impact. Adaptive experimentation, utilizing algorithms like Thompson Sampling for (contextual) multi-armed bandit (MAB) problems, can lead to continuous improvement and personalization. However, it remains unclear when these algorithms can simultaneously increase user experience rewards and facilitate appropriate data collection for social-behavioral scientists to analyze with sufficient statistical confidence. Although a growing body of research addresses the practical and statistical aspects of MAB and other adaptive algorithms, further exploration is needed to assess their impact across diverse real-world contexts. This paper presents a software system developed over two years that allows text-messaging intervention components to be adapted using bandit and other algorithms while collecting data for side-by-side comparison with traditional uniform random non-adaptive experiments. We evaluate the system by deploying a text-message-based DMH intervention to 1100 users, recruited through a large mental health non-profit organization, and share the path forward for deploying this system at scale. This system not only enables applications in mental health but could also serve as a model testbed for adaptive experimentation algorithms in other domains.
Published: 2023
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7. Getting too personal(ized): The importance of feature choice in online adaptive algorithms

Author: Li, ZhaoBin, Yee, Luna, Sauerberg, Nathaniel, Sakson, Irene, Williams, Joseph Jay, and Rafferty, Anna N.
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract: Digital educational technologies offer the potential to customize students' experiences and learn what works for which students, enhancing the technology as more students interact with it. We consider whether and when attempting to discover how to personalize has a cost, such as if the adaptation to personal information can delay the adoption of policies that benefit all students. We explore these issues in the context of using multi-armed bandit (MAB) algorithms to learn a policy for what version of an educational technology to present to each student, varying the relation between student characteristics and outcomes and also whether the algorithm is aware of these characteristics. Through simulations, we demonstrate that the inclusion of student characteristics for personalization can be beneficial when those characteristics are needed to learn the optimal action. In other scenarios, this inclusion decreases performance of the bandit algorithm. Moreover, including unneeded student characteristics can systematically disadvantage students with less common values for these characteristics. Our simulations do however suggest that real-time personalization will be helpful in particular real-world scenarios, and we illustrate this through case studies using existing experimental results in ASSISTments. Overall, our simulations show that adaptive personalization in educational technologies can be a double-edged sword: real-time adaptation improves student experiences in some contexts, but the slower adaptation and potentially discriminatory results mean that a more personalized model is not always beneficial., Comment: 11 pages, 6 figures. Correction to the original article published at https://files.eric.ed.gov/fulltext/ED607907.pdf : The Thompson sampling algorithm in the original article overweights older data resulting in an overexploitative multi-armed bandit. This arxiv version uses a normal Thompson sampling algorithm
Published: 2023

8. Single Flux Quantum-Based Digital Control of Superconducting Qubits in a Multi-Chip Module

Author: Liu, Chuan-Hong, Ballard, Andrew, Olaya, David, Schmidt, Daniel R., Biesecker, John, Lucas, Tammy, Ullom, Joel, Patel, Shravan, Rafferty, Owen, Opremcak, Alexander, Dodge, Kenneth, Iaia, Vito, McBroom, Tianna, Dubois, Jonathan L., Hopkins, Pete F., Benz, Samuel P., Plourde, Britton L. T., and McDermott, Robert
Subjects: Quantum Physics, Condensed Matter - Superconductivity
Abstract: The single flux quantum (SFQ) digital superconducting logic family has been proposed for the scalable control of next-generation superconducting qubit arrays. In the initial implementation, SFQ-based gate fidelity was limited by quasiparticle (QP) poisoning induced by the dissipative on-chip SFQ driver circuit. In this work, we introduce a multi-chip module architecture to suppress phonon-mediated QP poisoning. Here, the SFQ elements and qubits are fabricated on separate chips that are joined with In bump bonds. We use interleaved randomized benchmarking to characterize the fidelity of SFQ-based gates, and we demonstrate an error per Clifford gate of 1.2(1)%, an order-of-magnitude reduction over the gate error achieved in the initial realization of SFQ-based qubit control. We use purity benchmarking to quantify the contribution of incoherent error at 0.96(2)%; we attribute this error to photon-mediated QP poisoning mediated by the resonant mm-wave antenna modes of the qubit and SFQ-qubit coupler. We anticipate that a straightforward redesign of the SFQ driver circuit to limit the bandwidth of the SFQ pulses will eliminate this source of infidelity, allowing SFQ-based gates with fidelity approaching theoretical limits, namely 99.9% for resonant sequences and 99.99% for more complex pulse sequences involving variable pulse-to-pulse separation., Comment: 15 pages, 8+4 figures, 1 table
Published: 2023
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9. Adversarial Bandits for Drawing Generalizable Conclusions in Non-Adversarial Experiments: An Empirical Study

Author: Zhi-Han, Yang, Zhang, Shiyue, and Rafferty, Anna N.
Abstract: Online educational technologies facilitate pedagogical experimentation, but typical experimental designs assign a fixed proportion of students to each condition, even if early results suggest some are ineffective. Experimental designs using multi-armed bandit (MAB) algorithms vary the probability of condition assignment for a new student based on prior results, placing more students in more effective conditions. While stochastic MAB algorithms have been used for educational experiments, they collect data that decreases power and increases false positive rates [22]. Instead, we propose using adversarial MAB algorithms, which are less exploitative and thus may exhibit more robustness. Through simulations involving data from 20+ educational experiments [29], we show data collected using adversarial MAB algorithms does not have the statistical downsides of that from stochastic MAB algorithms. Further, we explore how differences in condition variability (e.g., performance gaps between students being narrowed by an intervention) impact MAB versus uniform experimental design. Data from stochastic MAB algorithms systematically reduce power when the better arm is less variable, while increasing it when the better arm is more variable; data from the adversarial MAB algorithms results in the same statistical power as uniform assignment. Overall, these results demonstrate that adversarial MAB algorithms are a viable "off-the-shelf" solution for researchers who want to preserve the statistical power of standard experimental designs while also benefiting student participants. [For the full proceedings, see ED623995.]
Published: 2022

10. A Robust Bias Mitigation Procedure Based on the Stereotype Content Model

Author: Ungless, Eddie L., Rafferty, Amy, Nag, Hrichika, and Ross, Björn
Subjects: Computer Science - Computation and Language
Abstract: The Stereotype Content model (SCM) states that we tend to perceive minority groups as cold, incompetent or both. In this paper we adapt existing work to demonstrate that the Stereotype Content model holds for contextualised word embeddings, then use these results to evaluate a fine-tuning process designed to drive a language model away from stereotyped portrayals of minority groups. We find the SCM terms are better able to capture bias than demographic agnostic terms related to pleasantness. Further, we were able to reduce the presence of stereotypes in the model through a simple fine-tuning procedure that required minimal human and computer resources, without harming downstream performance. We present this work as a prototype of a debiasing procedure that aims to remove the need for a priori knowledge of the specifics of bias in the model.
Published: 2022

11. CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection

Author: Hwang, Jyh-Jing, Kretzschmar, Henrik, Manela, Joshua, Rafferty, Sean, Armstrong-Crews, Nicholas, Chen, Tiffany, and Anguelov, Dragomir
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Robotics
Abstract: Robust 3D object detection is critical for safe autonomous driving. Camera and radar sensors are synergistic as they capture complementary information and work well under different environmental conditions. Fusing camera and radar data is challenging, however, as each of the sensors lacks information along a perpendicular axis, that is, depth is unknown to camera and elevation is unknown to radar. We propose the camera-radar matching network CramNet, an efficient approach to fuse the sensor readings from camera and radar in a joint 3D space. To leverage radar range measurements for better camera depth predictions, we propose a novel ray-constrained cross-attention mechanism that resolves the ambiguity in the geometric correspondences between camera features and radar features. Our method supports training with sensor modality dropout, which leads to robust 3D object detection, even when a camera or radar sensor suddenly malfunctions on a vehicle. We demonstrate the effectiveness of our fusion approach through extensive experiments on the RADIATE dataset, one of the few large-scale datasets that provide radar radio frequency imagery. A camera-only variant of our method achieves competitive performance in monocular 3D object detection on the Waymo Open Dataset., Comment: ECCV 2022
Published: 2022

12. Representing Camera Response Function by a Single Latent Variable and Fully Connected Neural Network

Author: Zhao, Yunfeng, Ferguson, Stuart, Zhou, Huiyu, and Rafferty, Karen
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Modelling the mapping from scene irradiance to image intensity is essential for many computer vision tasks. Such mapping is known as the camera response. Most digital cameras use a nonlinear function to map irradiance, as measured by the sensor to an image intensity used to record the photograph. Modelling of the response is necessary for the nonlinear calibration. In this paper, a new high-performance camera response model that uses a single latent variable and fully connected neural network is proposed. The model is produced using unsupervised learning with an autoencoder on real-world (example) camera responses. Neural architecture searching is then used to find the optimal neural network architecture. A latent distribution learning approach was introduced to constrain the latent distribution. The proposed model achieved state-of-the-art CRF representation accuracy in a number of benchmark tests, but is almost twice as fast as the best current models when performing the maximum likelihood estimation during camera response calibration due to the simple yet efficient model representation., Comment: 11 pages, 4 figures, 3 tables. Accepted by Signal, Image and Video Processing
Published: 2022

13. Using Adaptive Experiments to Rapidly Help Students

Author: Zavaleta-Bernuy, Angela, Zheng, Qi Yin, Shaikh, Hammad, Nogas, Jacob, Rafferty, Anna, Petersen, Andrew, and Williams, Joseph Jay
Subjects: Computer Science - Machine Learning, Computer Science - Computers and Society, Computer Science - Human-Computer Interaction
Abstract: Adaptive experiments can increase the chance that current students obtain better outcomes from a field experiment of an instructional intervention. In such experiments, the probability of assigning students to conditions changes while more data is being collected, so students can be assigned to interventions that are likely to perform better. Digital educational environments lower the barrier to conducting such adaptive experiments, but they are rarely applied in education. One reason might be that researchers have access to few real-world case studies that illustrate the advantages and disadvantages of these experiments in a specific context. We evaluate the effect of homework email reminders in students by conducting an adaptive experiment using the Thompson Sampling algorithm and compare it to a traditional uniform random experiment. We present this as a case study on how to conduct such experiments, and we raise a range of open questions about the conditions under which adaptive randomized experiments may be more or less useful., Comment: International Conference on Artificial Intelligence in Education
Published: 2022
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14. Increasing Students' Engagement to Reminder Emails Through Multi-Armed Bandits

Author: Yanez, Fernando J., Zavaleta-Bernuy, Angela, Han, Ziwen, Liut, Michael, Rafferty, Anna, and Williams, Joseph Jay
Subjects: Computer Science - Machine Learning, Computer Science - Computers and Society
Abstract: Conducting randomized experiments in education settings raises the question of how we can use machine learning techniques to improve educational interventions. Using Multi-Armed Bandits (MAB) algorithms like Thompson Sampling (TS) in adaptive experiments can increase students' chances of obtaining better outcomes by increasing the probability of assignment to the most optimal condition (arm), even before an intervention completes. This is an advantage over traditional A/B testing, which may allocate an equal number of students to both optimal and non-optimal conditions. The problem is the exploration-exploitation trade-off. Even though adaptive policies aim to collect enough information to allocate more students to better arms reliably, past work shows that this may not be enough exploration to draw reliable conclusions about whether arms differ. Hence, it is of interest to provide additional uniform random (UR) exploration throughout the experiment. This paper shows a real-world adaptive experiment on how students engage with instructors' weekly email reminders to build their time management habits. Our metric of interest is open email rates which tracks the arms represented by different subject lines. These are delivered following different allocation algorithms: UR, TS, and what we identified as TS{\dag} - which combines both TS and UR rewards to update its priors. We highlight problems with these adaptive algorithms - such as possible exploitation of an arm when there is no significant difference - and address their causes and consequences. Future directions includes studying situations where the early choice of the optimal arm is not ideal and how adaptive algorithms can address them., Comment: 6th Educational Data Mining in Computer Science Education (CSEDM) Workshop In conjunction with EDM 2022
Published: 2022

15. How can Email Interventions Increase Students' Completion of Online Homework? A Case Study Using A/B Comparisons

Author: Zavaleta-Bernuy, Angela, Han, Ziwen, Shaikh, Hammad, Zheng, Qi Yin, Lim, Lisa-Angelique, Rafferty, Anna, Petersen, Andrew, and Williams, Joseph Jay
Subjects: Computer Science - Human-Computer Interaction
Abstract: Email communication between instructors and students is ubiquitous, and it could be valuable to explore ways of testing out how to make email messages more impactful. This paper explores the design space of using emails to get students to plan and reflect on starting weekly homework earlier. We deployed a series of email reminders using randomized A/B comparisons to test alternative factors in the design of these emails, providing examples of an experimental paradigm and metrics for a broader range of interventions. We also surveyed and interviewed instructors and students to compare their predictions about the effectiveness of the reminders with their actual impact. We present our results on which seemingly obvious predictions about effective emails are not borne out, despite there being evidence for further exploring these interventions, as they can sometimes motivate students to attempt their homework more often. We also present qualitative evidence about student opinions and behaviours after receiving the emails, to guide further interventions. These findings provide insight into how to use randomized A/B comparisons in everyday channels such as emails, to provide empirical evidence to test our beliefs about the effectiveness of alternative design choices., Comment: 11 pages, 4 figures, 4 tables. Conference: LAK22: 12th International Learning Analytics and Knowledge Conference (LAK22)
Published: 2022
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16. Caring for Students Playbook: Six Recommendations for Caring for Students

Author: Achieving the Dream, Inc., Online Learning Consortium (OLC), Every Learner Everywhere, Adams, S., Bali, M., Eder, Z., Fladd, L., Garrett, K., Garth-McCullough, R., Gibson, A. M., Gunder, A., Iuzzini, J., Knott, J. L., Rafferty, J., and Weber, N. L.
Abstract: This playbook contains resources that can be used by individual instructors to support putting student care into action or by institutions seeking guidance for incorporating caring for students into their campus strategy and instructional development programming. While the impetus for this playbook was the COVID-19 pandemic, the information and resources provided represent high standards of student support regardless of the environment. This playbook provides detailed recommendations broken out into six sections. These recommendations include: (1) Reimagine your syllabus content; (2) Review and revise your course content; (3) Assess your students with care; (4) Develop and enact a communication plan; (5) Integrate institutional supports; and (6) Take time for self-care. Each of these Six Recommendations for Caring for Students provides concrete strategies and resources to support instructors in operationalizing equity-focused, inclusive teaching strategies that put student care into practice by acknowledging student challenges while identifying student assets. [For the companion playbook, "Caring for Students Playbook: Getting Started with Key Terms, Challenges, and Approaches," see ED613432.]
Published: 2021

17. Caring for Students Playbook: Getting Started with Key Terms, Challenges, and Approaches

Author: Achieving the Dream, Inc., Online Learning Consortium (OLC), Every Learner Everywhere, Adams, S., Bali, M., Eder, Z., Fladd, L., Garrett, K., Garth-McCullough, R., Gibson, A. M., Gunder, A., Iuzzini, J., Knott, J. L., Rafferty, J., and Weber, N. L.
Abstract: This resource serves as a companion piece to the "Caring for Students Playbook: Six Recommendations for Caring for Students" (ED613431) and provides a foundation for the approaches and methods offered therein. The content offered in this playbook begins by setting the groundwork for rooting instruction in diversity, equity, and inclusion before focusing on the challenges students are experiencing as they pursue their education in our current climate. It concludes with offering approaches that support engaging culture, acknowledging trauma, and meeting the needs of all learners.
Published: 2021

18. Optimizing High-Quality Digital Learning Experiences: A Playbook for Faculty

Author: Online Learning Consortium (OLC), Association of Public and Land-grant Universities, Every Learner Everywhere, Gunder, Angela, Vignare, Karen, Adams, Susan, McGuire, Abby, and Rafferty, Jennifer Paloma
Abstract: High-quality digital learning experiences are built on the foundational principles of providing equitable, inclusive, accessible learning environments for all students. In addition, high-quality digital learning experiences are well-organized and thoughtfully designed. These experiences rely on instructional design principles and strategies to align learning outcomes with learning assignments, activities, and assessment practices. In these ways, high-quality digital courses provide robust learning experiences for students, not only through strategic design, but also through integrating intentional opportunities for community-building and interaction in the digital environment. Student and faculty feedback from remote teaching during the COVID-19 pandemic further revealed an equity gap and became a call to action to focus on optimizing the quality of digital learning experiences for minoritized students. As a result, more than ever before, it is now essential that faculty meet the learning needs of minoritized students through effective digital course design and teaching strategies. Building on these principles and the urgency to provide improved and equitable digital learning, the focus of this playbook is to help faculty strategically embed technologies with learning outcomes to amplify the effectiveness of student learning experiences, especially for minoritized students. Optimizing online learning experiences to ensure equity, inclusivity, and accessibility, particularly for minoritized students, is a continuous process with many benefits: (1) limiting potential academic disruption if the course modality unexpectedly shifts; (2) providing students course materials in efficient and accessible ways; (3) giving students more flexibility, control, and options regarding when and how they learn; and (4) allowing faculty to engage in the process of building their courses over time. "Optimizing High-Quality Digital Learning Experiences: A Playbook for Faculty" aims to guide faculty in thinking and designing strategically to amplify the opportunities the online environment provides in both their digital spaces and physical classrooms. By integrating teaching and design principles, this guide assists faculty in positively impacting student learning, especially for students who are minoritized because of race, gender, disability, or socioeconomic status.
Published: 2021

19. Quasiparticle Poisoning of Superconducting Qubits from Resonant Absorption of Pair-breaking Photons

Author: Liu, Chuan-Hong, Harrison, David C., Patel, Shravan, Wilen, Christopher D., Rafferty, Owen, Shearrow, Abigail, Ballard, Andrew, Iaia, Vito, Ku, Jaseung, Plourde, Britton L. T., and McDermott, Robert
Subjects: Quantum Physics
Abstract: The ideal superconductor provides a pristine environment for the delicate states of a quantum computer: because there is an energy gap to excitations, there are no spurious modes with which the qubits can interact, causing irreversible decay of the quantum state. As a practical matter, however, there exists a high density of excitations out of the superconducting ground state even at ultralow temperature; these are known as quasiparticles. Observed quasiparticle densities are of order 1~$\mu$m$^{-3}$, tens of orders of magnitude larger than the equilibrium density expected from theory. Nonequilibrium quasiparticles extract energy from the qubit mode and induce discrete changes in qubit offset charge, a potential source of dephasing. Here we show that a dominant mechanism for quasiparticle poisoning in superconducting qubits is direct absorption of high-energy photons at the qubit junction. We use a Josephson junction-based photon source to controllably dose qubit circuits with millimeter-wave radiation, and we use an interferometric quantum gate sequence to reconstruct the charge parity on the qubit island. We find that the structure of the qubit itself acts as a resonant antenna for millimeter-wave radiation, providing an efficient path for photons to generate quasiparticle excitations. A deep understanding of this physics will pave the way to realization of next-generation superconducting qubits that are robust against quasiparticle poisoning and could enable a new class of quantum sensors for dark matter detection., Comment: 13 pages, 11 figures, 3 tables
Published: 2022

20. The LOFAR Two-metre Sky Survey -- V. Second data release

Author: Shimwell, T. W., Hardcastle, M. J., Tasse, C., Best, P. N., Röttgering, H. J. A., Williams, W. L., Botteon, A., Drabent, A., Mechev, A., Shulevski, A., van Weeren, R. J., Bester, L., Brüggen, M., Brunetti, G., Callingham, J. R., Chyży, K. T., Conway, J. E., Dijkema, T. J., Duncan, K., de Gasperin, F., Hale, C. L., Haverkorn, M., Hugo, B., Jackson, N., Mevius, M., Miley, G. K., Morabito, L. K., Morganti, R., Offringa, A., Oonk, J. B. R., Rafferty, D., Sabater, J., Smith, D. J. B., Schwarz, D. J., Smirnov, O., O'Sullivan, S. P., Vedantham, H., White, G. J., Albert, J. G., Alegre, L., Asabere, B., Bacon, D. J., Bonafede, A., Bonnassieux, E., Brienza, M., Bilicki, M., Bonato, M., Rivera, G. Calistro, Cassano, R., Cochrane, R., Croston, J. H., Cuciti, V., Dallacasa, D., Danezi, A., Dettmar, R. J., Di Gennaro, G., Edler, H. W., Enßlin, T. A., Emig, K. L., Franzen, T. M. O., García-Vergara, C., Grange, Y. G., Gürkan, G., Hajduk, M., Heald, G., Heesen, V., Hoang, D. N., Hoeft, M., Horellou, C., Iacobelli, M., Jamrozy, M., Jelić, V., Kondapally, R., Kukreti, P., Kunert-Bajraszewska, M., Magliocchetti, M., Mahatma, V., Małek, K., Mandal, S., Massaro, F., Meyer-Zhao, Z., Mingo, B., Mostert, R. I. J., Nair, D. G., Nakoneczny, S. J., Nikiel-Wroczyński, B., Orrú, E., Pajdosz-Śmierciak, U., Pasini, T., Prandoni, I., van Piggelen, H. E., Rajpurohit, K., Retana-Montenegro, E., Riseley, C. J., Rowlinson, A., Saxena, A., Schrijvers, C., Sweijen, F., Siewert, T. M., Timmerman, R., Vaccari, M., Vink, J., West, J. L., Wołowska, A., Zhang, X., and Zheng, J.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: In this data release from the LOFAR Two-metre Sky Survey (LoTSS) we present 120-168MHz images covering 27% of the northern sky. Our coverage is split into two regions centred at approximately 12h45m +44$^\circ$30' and 1h00m +28$^\circ$00' and spanning 4178 and 1457 square degrees respectively. The images were derived from 3,451hrs (7.6PB) of LOFAR High Band Antenna data which were corrected for the direction-independent instrumental properties as well as direction-dependent ionospheric distortions during extensive, but fully automated, data processing. A catalogue of 4,396,228 radio sources is derived from our total intensity (Stokes I) maps, where the majority of these have never been detected at radio wavelengths before. At 6" resolution, our full bandwidth Stokes I continuum maps with a central frequency of 144MHz have: a median rms sensitivity of 83$\mu$Jy/beam; a flux density scale accuracy of approximately 10%; an astrometric accuracy of 0.2"; and we estimate the point-source completeness to be 90% at a peak brightness of 0.8mJy/beam. By creating three 16MHz bandwidth images across the band we are able to measure the in-band spectral index of many sources, albeit with an error on the derived spectral index of +/-0.2 which is a consequence of our flux-density scale accuracy and small fractional bandwidth. Our circular polarisation (Stokes V) 20" resolution 120-168MHz continuum images have a median rms sensitivity of 95$\mu$Jy/beam, and we estimate a Stokes I to Stokes V leakage of 0.056%. Our linear polarisation (Stokes Q and Stokes U) image cubes consist of 480 x 97.6 kHz wide planes and have a median rms sensitivity per plane of 10.8mJy/beam at 4' and 2.2mJy/beam at 20"; we estimate the Stokes I to Stokes Q/U leakage to be approximately 0.2%. Here we characterise and publicly release our Stokes I, Q, U and V images in addition to the calibrated uv-data., Comment: 23 figures, 1 table and 29 pages. The catalogues, images and uv-data associated with this data release are publicly available via https://lofar-surveys.org/
Published: 2022
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21. Colour alignment for relative colour constancy via non-standard references

Author: Zhao, Yunfeng, Ferguson, Stuart, Zhou, Huiyu, Elliott, Chris, and Rafferty, Karen
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract: Relative colour constancy is an essential requirement for many scientific imaging applications. However, most digital cameras differ in their image formations and native sensor output is usually inaccessible, e.g., in smartphone camera applications. This makes it hard to achieve consistent colour assessment across a range of devices, and that undermines the performance of computer vision algorithms. To resolve this issue, we propose a colour alignment model that considers the camera image formation as a black-box and formulates colour alignment as a three-step process: camera response calibration, response linearisation, and colour matching. The proposed model works with non-standard colour references, i.e., colour patches without knowing the true colour values, by utilising a novel balance-of-linear-distances feature. It is equivalent to determining the camera parameters through an unsupervised process. It also works with a minimum number of corresponding colour patches across the images to be colour aligned to deliver the applicable processing. Two challenging image datasets collected by multiple cameras under various illumination and exposure conditions were used to evaluate the model. Performance benchmarks demonstrated that our model achieved superior performance compared to other popular and state-of-the-art methods., Comment: 14 pages, 8 figures, 2 tables, accepted by IEEE Transactions on Image Processing
Published: 2021
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22. Algorithms for Adaptive Experiments that Trade-off Statistical Analysis with Reward: Combining Uniform Random Assignment and Reward Maximization

Author: Li, Tong, Nogas, Jacob, Song, Haochen, Kumar, Harsh, Durand, Audrey, Rafferty, Anna, Deliu, Nina, Villar, Sofia S., and Williams, Joseph J.
Subjects: Computer Science - Machine Learning, Statistics - Machine Learning
Abstract: Multi-armed bandit algorithms like Thompson Sampling (TS) can be used to conduct adaptive experiments, in which maximizing reward means that data is used to progressively assign participants to more effective arms. Such assignment strategies increase the risk of statistical hypothesis tests identifying a difference between arms when there is not one, and failing to conclude there is a difference in arms when there truly is one. We tackle this by introducing a novel heuristic algorithm, called TS-PostDiff (Posterior Probability of Difference). TS-PostDiff takes a Bayesian approach to mixing TS and Uniform Random (UR): the probability a participant is assigned using UR allocation is the posterior probability that the difference between two arms is 'small' (below a certain threshold), allowing for more UR exploration when there is little or no reward to be gained. We evaluate TS-PostDiff against state-of-the-art strategies. The empirical and simulation results help characterize the trade-offs of these approaches between reward, False Positive Rate (FPR), and statistical power, as well as under which circumstances each is effective. We quantify the advantage of TS-PostDiff in performing well across multiple differences in arm means (effect sizes), showing the benefits of adaptively changing randomization/exploration in TS in a "Statistically Considerate" manner: reducing FPR and increasing statistical power when differences are small or zero and there is less reward to be gained, while exploiting more when differences may be large. This highlights important considerations for future algorithm development and analysis to better balance reward and statistical analysis.
Published: 2021

23. Getting Too Personal(ized): The Importance of Feature Choice in Online Adaptive Algorithms

Author: Li, ZhaoBin, Yee, Luna, Sauerberg, Nathaniel, Sakson, Irene, Williams, Joseph Jay, and Rafferty, Anna N.
Abstract: Digital educational technologies offer the potential to customize students' experiences and learn what works for which students, enhancing the technology as more students interact with it. We consider whether and when attempting to discover how to personalize has a cost, such as if the adaptation to personal information can delay the adoption of policies that benefit all students. We explore these issues in the context of using multi-armed bandit (MAB) algorithms to learn a policy for what version of an educational technology to present to each student, varying the relation between student characteristics and outcomes and also whether the algorithm is aware of these characteristics. Through simulations, we demonstrate that the inclusion of student characteristics for personalization can be beneficial when those characteristics are needed to learn the optimal action. In other scenarios, this inclusion decreases performance and increases variation in student experiences. Moreover, including unneeded student characteristics can systematically disadvantage students with less common values for these characteristics. Our simulations do however suggest that real-time personalization will be helpful in particular real-world scenarios, and we illustrate this through case studies using existing experimental results in ASSISTments. Overall, our simulations show that adaptive personalization in educational technologies can be a double-edged sword: real-time adaptation improves student experiences in some contexts, but the slower adaptation and increased variability mean that a more personalized model is not always beneficial. [For the full proceedings, see ED607784.]
Published: 2020

24. Proceedings of the International Conference on Educational Data Mining (EDM) (13th, Online, July 10-13, 2020)

Author: International Educational Data Mining Society, Rafferty, Anna N., Whitehill, Jacob, Romero, Cristobal, and Cavalli-Sforza, Violetta
Abstract: The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of presentations all paper presenters pre-recorded their presentation as a video and then hosted it on YouTube with closed-captioning (CC). The official theme of this year's conference is Improving Learning Outcomes for All Learners. The theme comprises two parts: (1) Identifying actionable learning or teaching strategies that can be used to "improve" learning outcomes, not just predict them; (2) Using EDM to promote more "equitable" learning across diverse groups of learners, and to benefit underserved communities in particular. This year's conference features three invited talks: Alina von Davier, Chief Officer at ACTNext; Abelardo Pardo, Professor and Dean of Programs (Engineering), at UniSA STEM, University of South Australia; and Kobi Gal, Associate Professor at the Department of Software and Information Systems Engineering at Ben-Gurion University of the Negev, and Reader at the School of Informatics at the University of Edinburgh.
Published: 2020

25. Delivering High-Quality Instruction Online in Response to COVID-19: Faculty Playbook

Author: Online Learning Consortium (OLC), Association of Public and Land-grant Universities, O'Keefe, L., Rafferty, J., Gunder, A., and Vignare, K.
Abstract: Today, as educators are transitioning into a new phase of planning for an uncertain summer and fall, they can be more thoughtful about how to deliver high quality online learning. On the positive side, online delivery as an instructional modality is not new. In fact, many colleges and universities have been developing and delivering successful online programs for years. However, despite the growth in online learning, research on student, faculty, and institutional readiness for online learning makes it clear that educators and institutions need more help understanding how to effectively design, develop, and deliver high-quality instruction online. This need is greatest for educators at institutions serving low-income students, first-generation students, and students of color who will likely be disproportionately affected by the current crisis because they lack access to needed resources and technology. This playbook is designed to serve as a concise guide in addressing faculty needs for online course design, teaching, and continuous improvement. This guide will provide teachers with the information they need to get started (and keep going!) at any level, along with resources for more in-depth information or assistance. [This playbook is a collaboration between the Online Learning Consortium (OLC), the Association of Public and Land-grant Universities (APLU), and the Every Learner Everywhere Network.]
Published: 2020

26. Reinforcement Learning for Education: Opportunities and Challenges

Author: Singla, Adish, Rafferty, Anna N., Radanovic, Goran, and Heffernan, Neil T.
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: This survey article has grown out of the RL4ED workshop organized by the authors at the Educational Data Mining (EDM) 2021 conference. We organized this workshop as part of a community-building effort to bring together researchers and practitioners interested in the broad areas of reinforcement learning (RL) and education (ED). This article aims to provide an overview of the workshop activities and summarize the main research directions in the area of RL for ED.
Published: 2021

27. Neutron Imaging of Paramagnetic Ions: Electrosorption by Carbon Aerogels and Macroscopic Magnetic Forces

Author: Butcher, T. A., Prendeville, L., Rafferty, A., Trtik, P., Boillat, P., and Coey, J. M. D.
Subjects: Physics - Chemical Physics
Abstract: The electrosorption of Gd$^{3+}$ ions from aqueous 70 mM Gd(NO$_3$)$_3$ solution in monolithic carbon aerogel electrodes was recorded by dynamic neutron imaging. The aerogels have a bimodal pore size distribution consisting of macropores and mesopores centered at 115 nm and 15 nm, respectively. After the uptake of Gd$^{3+}$ ions by the negatively charged surface of the porous structure, an inhomogeneous magnetic field was applied to the system of discharging electrodes. This led to a convective flow and confinement of Gd(NO$_3$)$_3$ solution in the magnetic field gradient. Thus, a way to desalt and capture paramagnetic ions from an initially homogeneous solution is established.
Published: 2021
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28. Ultrafast Proton Transport between a Hydroxy Acid and a Nitrogen Base along Solvent Bridges Governed by Hydroxide/Methoxide Transfer Mechanism

Author: Ekimova, Maria, Hoffmann, Felix, Bekçioğlu-Neff, Gül, Rafferty, Aidan, Kornilov, Oleg, Nibbering, Erik T. J., and Sebastiani, Daniel
Subjects: Physics - Chemical Physics
Abstract: Aqueous proton transport plays a key role in acid-base neutralization, and energy transport through biological membranes and hydrogen fuel cells. Extensive experimental and theoretical studies have resulted in a highly detailed elucidation of one of the underlying microscopic mechanisms for aqueous excess proton transport, known as the von Grotthuss mechanism, involving different hydrated proton configurations with associated high fluxional structural dynamics. Hydroxide transport, with approximately two-fold lower bulk diffusion rates than those of excess protons, has received much less attention. We present femtosecond UV/IR pump-probe experiments and ab initio molecular dynamics simulations of different proton transport pathways of the bifunctional photoacid 7-hydroxyquinoline (7HQ) in water-methanol mixtures. For 7HQ solvent-dependent photoacidity, free energy-reactivity correlation behaviour and QM/MM trajectories point to a dominant OH-/CH3O- transport pathway, for all water-methanol mixing ratios investigated. This provides conclusive evidence for the hydrolysis/methanolysis acid-base neutralization pathway formulated by Manfred Eigen half a century ago., Comment: 44 pages, 14 figures
Published: 2021

29. Investigating ionospheric calibration for LOFAR 2.0 with simulated observations

Author: Edler, H. W., de Gasperin, F., and Rafferty, D.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: A number of hardware upgrades for the Low-Frequency Array (LOFAR) are currently under development. These upgrades are collectively referred to as the LOFAR 2.0 upgrade. The first stage of LOFAR 2.0 will introduce a distributed clock signal and allow for simultaneous observation with all the low-band and high-band antennas of the array. Our aim is to provide a tool for accurate simulations of LOFAR 2.0. We present a software to simulate LOFAR and LOFAR 2.0 observations, which includes realistic models for all important systematic effects such as the first and second order ionospheric corruptions, time-variable primary-beam attenuation, station based delays and bandpass response. The ionosphere is represented as a thin layer of frozen turbulence. Furthermore, thermal noise can be added to the simulation at the expected level. We simulate a full 8-hour simultaneous low- and high-band antenna observation of a calibrator source and a target field with the LOFAR 2.0 instrument. The simulated data is calibrated using readjusted LOFAR calibration strategies. We examine novel approaches of solution-transfer and joint calibration to improve direction-dependent ionospheric calibration for LOFAR. We find that the calibration of the simulated data behaves very similarly to a real observation and reproduces characteristic properties of LOFAR data such as realistic solutions and image quality. We analyze strategies for direction-dependent calibration of LOFAR 2.0 and find that the ionospheric parameters can be determined most accurately when combining the information of the high-band and low-band in a joint calibration approach. In contrast, the transfer of total electron content solutions from the high-band to the low-band shows good convergence but is highly susceptible to the presence of non-ionospheric phase errors in the data., Comment: 15 pages, 16 figures, accepted for publication in A&A (Section 15. Numerical methods and codes of Astronomy and Astrophysics)
Published: 2021
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30. LOFAR imaging of Cygnus A -- Direct detection of a turnover in the hotspot radio spectra

Author: McKean, J. P., Godfrey, L. E. H., Vegetti, S., Wise, M. W., Morganti, R., Hardcastle, M. J., Rafferty, D., Anderson, J., Avruch, I. M., Beck, R., Bell, M. E., van Bemmel, I., Bentum, M. J., Bernardi, G., Best, P., Blaauw, R., Bonafede, A., Breitling, F., Broderick, J. W., Bruggen, M., Cerrigone, L., Ciardi, B., de Gasperin, F., Deller, A., Duscha, S., Engels, D., Falcke, H., Fallows, R. A., Frieswijk, W., Garrett, M. A., Griessmeier, J. M., van Haarlem, M. P., Heald, G., Hoeft, M., van der Horst, A. J., Iacobelli, M., Intema, H., Juette, E., Karastergiou, A., Kondratiev, V. I., Koopmans, L. V. E., Kuniyoshi, M., Kuper, G., van Leeuwen, J., Maat, P., Mann, G., Markoff, S., McFadden, R., McKay-Bukowski, D., Mulcahy, D. D., Munk, H., Nelles, A., Orru, E., Paas, H., Pandey-Pommier, M., Pietka, M., Pizzo, R., Polatidis, A. G., Reich, W., Rottgering, H. J. A., Rowlinson, A., Scaife, A. M. M., Serylak, M., Shulevski, A., Sluman, J., Smirnov, O., Steinmetz, M., Stewart, A., Swinbank, J., Tagger, M., Thoudam, S., Toribio, M. C., Vermeulen, R., Vocks, C., van Weeren, R. J., Wucknitz, O., Yatawatta, S., and Zarka, P.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: The low-frequency radio spectra of the hotspots within powerful radio galaxies can provide valuable information about the physical processes operating at the site of the jet termination. These processes are responsible for the dissipation of jet kinetic energy, particle acceleration, and magnetic-field generation. Here we report new observations of the powerful radio galaxy Cygnus A using the Low Frequency Array (LOFAR) between 109 and 183 MHz, at an angular resolution of ~3.5 arcsec. The radio emission of the lobes is found to have a complex spectral index distribution, with a spectral steepening found towards the centre of the source. For the first time, a turnover in the radio spectrum of the two main hotspots of Cygnus A has been directly observed. By combining our LOFAR imaging with data from the Very Large Array at higher frequencies, we show that the very rapid turnover in the hotspot spectra cannot be explained by a low-energy cut-off in the electron energy distribution, as has been previously suggested. Thermal (free-free) absorption or synchrotron self absorption models are able to describe the low-frequency spectral shape of the hotspots, however, as with previous studies, we find that the implied model parameters are unlikely, and interpreting the spectra of the hotspots remains problematic., Comment: 9 pages, 3 figures, accepted for publication in MNRAS
Published: 2021
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31. Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments

Author: Williams, Joseph Jay, Nogas, Jacob, Deliu, Nina, Shaikh, Hammad, Villar, Sofia S., Durand, Audrey, and Rafferty, Anna
Subjects: Computer Science - Machine Learning, Statistics - Applications
Abstract: Multi-armed bandit algorithms have been argued for decades as useful for adaptively randomized experiments. In such experiments, an algorithm varies which arms (e.g. alternative interventions to help students learn) are assigned to participants, with the goal of assigning higher-reward arms to as many participants as possible. We applied the bandit algorithm Thompson Sampling (TS) to run adaptive experiments in three university classes. Instructors saw great value in trying to rapidly use data to give their students in the experiments better arms (e.g. better explanations of a concept). Our deployment, however, illustrated a major barrier for scientists and practitioners to use such adaptive experiments: a lack of quantifiable insight into how much statistical analysis of specific real-world experiments is impacted (Pallmann et al, 2018; FDA, 2019), compared to traditional uniform random assignment. We therefore use our case study of the ubiquitous two-arm binary reward setting to empirically investigate the impact of using Thompson Sampling instead of uniform random assignment. In this setting, using common statistical hypothesis tests, we show that collecting data with TS can as much as double the False Positive Rate (FPR; incorrectly reporting differences when none exist) and the False Negative Rate (FNR; failing to report differences when they exist)...
Published: 2021

32. Spurious Antenna Modes of the Transmon Qubit

Author: Rafferty, O., Patel, S., Liu, C. H., Abdullah, S., Wilen, C. D., Harrison, D. C., and McDermott, R.
Subjects: Quantum Physics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract: Superconducting qubits are resonant absorbers of pair-breaking radiation. The metal pads that form the qubit capacitance support standing wave modes at frequencies of order 100~GHz; these modes are strongly coupled to free-space impedance through their electric dipole moment. While the antenna mode of the 3D transmon qubit is easily seen to be a resonant dipole, other 2D qubit types can be understood as the aperture duals of wire loop antennas or folded dipoles. For typical Josephson junction parameters, the junction provides a reasonable conjugate match to the fundamental antenna mode. We calculate the contribution to quasiparticle poisoning from resonant absorption of blackbody radiation. We extend our analysis to dissipation at the qubit frequency, where radiative losses provide an ultimate limit to qubit energy relaxation time. A clear understanding of the spurious antenna modes of qubits will allow designs that are insensitive to pair-breaking radiation and that display reduced radiative losses at the qubit frequency., Comment: 9 pages, 6 figures, LaTex; figure 1 updated, section 5 clarification added, reference added, bibliography updated; submitted to Phys. Rev. X
Published: 2021

33. Determination of angular distributions from the high efficiency solenoidal separator SOLITAIRE

Author: Bezzina, L. T., Simpson, E. C., Hinde, D. J., Dasgupta, M., Carter, I. P., and Rafferty, D. C.
Subjects: Physics - Instrumentation and Detectors, Nuclear Experiment
Abstract: A novel fusion product separator, based on a gas-filled 8 T superconducting solenoid has been developed at the Australian National University. Though the transmission efficiency of the solenoid is very high, precision cross section measurements require knowledge of the angular distribution of the evaporation residues. A method has been developed to deduce the angular distribution of the evaporation residues from the laboratory-frame velocity distribution of the evaporation residues measured at the exit of the separator. The features of this method are presented, focusing on the example of $^{34}$S+$^{89}$Y which is compared to an independent measurement of the angular distribution. The establishment of this method now allows the novel solenoidal separator to be used to obtain reliable, precision fusion cross-sections.
Published: 2021
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34. Tests of General Relativity with Binary Black Holes from the second LIGO-Virgo Gravitational-Wave Transient Catalog

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, A., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antelis, J. M., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Bagnasco, S., Baird, J., Ball, M., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barnum, S., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Becher, B. R., Bécsy, B., Bedakihale, V. M., Bejger, M., Belahcene, I., Beniwal, D., Benjamin, M. G., Benkel, R., Bennett, T. F., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bhattacharjee, D., Bidler, J., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Blanch, O., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Boldrini, M., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Borhanian, S., Bork, R., Boschi, V., Bose, N., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buskulic, D., Byer, R. L., Cabero, M., Cadonati, L., Caesar, M., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Cannon, K. C., Cao, H., Cao, J., Carapella, G., Carbognani, F., Carney, M. F., Carpinelli, M., Carullo, G., Carver, T. L., Diaz, J. Casanueva, Casentini, C., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakravarti, K., Chan, C. -L., Chan, C., Chandra, K., Chanial, P., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, D., Chaturvedi, M., Chatziioannou, K., Chen, A., Chen, H. Y., Chen, X., Chen, Y., Cheng, H. -P., Cheong, C. K., Chia, H. Y., Chiadini, F., Chierici, R., Chincarini, A., Chiummo, A., Cho, G., Cho, H. S., Cho, M., Choate, S., Christensen, N., Chu, Q., Chua, S., Chung, K. W., Chung, S., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, E. N., Clark, J. A., Clarke, L., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Cohadon, P. -F., Cohen, D. E., Colleoni, M., Collette, C. G., Collins, C., Colpi, M., Constancio Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Corley, K. R., Cornish, N., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coughlin, S. B., Coulon, J. -P., Countryman, S. T., Couvares, P., Covas, P. B., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Croquette, M., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Cury{l}o, M., Canton, T. Dal, Dálya, G., Dana, A., DaneshgaranBajastani, L. M., D'Angelo, B., Danilishin, S. L., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Dattilo, V., Dave, I., Davier, M., Davies, G. S., Davis, D., Daw, E. J., Dean, R., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., De Lillo, N., Del Pozzo, W., DeMarchi, L. M., De Matteis, F., D'Emilio, V., Demos, N., Denker, T., Dent, T., Depasse, A., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., de Varona, O., Dhani, A., Dhurandhar, S., Díaz, M. C., Diaz-Ortiz Jr., M., Didio, N. A., Dietrich, T., Di Fiore, L., DiFronzo, C., Di Giorgio, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Di Lieto, A., Ding, B., Di Pace, S., Di Palma, I., Di Renzo, F., Divakarla, A. K., Dmitriev, A., Doctor, Z., D'Onofrio, L., Donovan, F., Dooley, K. L., Doravari, S., Dorrington, I., Downes, T. P., Drago, M., Driggers, J. C., Du, Z., Ducoin, J. -G., Dudi, R., Dupej, P., Durante, O., D'Urso, D., Duverne, P. -A., Dwyer, S. E., Easter, P. J., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etienne, Z. B., Etzel, T., Evans, M., Evans, T. M., Ewing, B. E., Fafone, V., Fair, H., Fairhurst, S., Fan, X., Farah, A. M., Farinon, S., Farr, B., Farr, W. M., Fauchon-Jones, E. J., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Feng, F., Fenyvesi, E., Ferguson, D. L., Fernandez-Galiana, A., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, I., Fiorucci, D., Fishbach, M., Fisher, R. P., Fishner, J. M., Fittipaldi, R., Fitz-Axen, M., Fiumara, V., Flaminio, R., Floden, E., Flynn, E., Fong, H., Font, J. A., Forsyth, P. W. F., Fournier, J. -D., Frasca, S., Frasconi, F., Frei, Z., Freise, A., Frey, R., Frey, V., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fulda, P., Fyffe, M., Gabbard, H. A., Gadre, B. U., Gaebel, S. M., Gair, J. R., Gais, J., Galaudage, S., Gamba, R., Ganapathy, D., Ganguly, A., Gaonkar, S. G., Garaventa, B., García-Quirós, C., Garufi, F., Gateley, B., Gaudio, S., Gayathri, V., Gemme, G., Gennai, A., George, D., George, J., George, R. N., Gergely, L., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, S., Giacomazzo, B., Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Gill, K., Giri, P., Glanzer, J., Gleckl, A. E., Godwin, P., Goetz, E., Goetz, R., Gohlke, N., Goncharov, B., González, G., Gopakumar, A., Gossan, S. E., Gosselin, M., Gouaty, R., Grace, B., Grado, A., Granata, M., Granata, V., Grant, A., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, R., Gretarsson, E. M., Griggs, H. L., Grignani, G., Grimaldi, A., Grimes, E., Grimm, S. J., Grote, H., Grunewald, S., Gruning, P., Guerrero, J. G., Guidi, G. M., Guimaraes, A. R., Guixé, G., Gulati, H. K., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, P., Gustafson, E. K., Gustafson, R., Guzman, F., Haegel, L., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Haney, M., Hanke, M. M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hannuksela, O., Hansen, H., Hansen, T. J., Hanson, J., Harder, T., Hardwick, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Hasskew, R. K., Haster, C. -J., Haughian, K., Hayes, F. J., Healy, J., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J., Hennig, M. H., Vivanco, F. Hernandez, Heurs, M., Hild, S., Hill, P., Hines, A. S., Hochheim, S., Hofgard, E., Hofman, D., Hohmann, J. N., Holgado, A. M., Holland, N. A., Hollows, I. 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J., Yeeles, D. W., Yoon, A., Yu, Hang, Yu, Haocun, Yuen, S. H. R., Zadrożny, A., Zanolin, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhao, C., Zhao, G., Zhou, M., Zhou, Z., Zhu, X. J., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena
Abstract: Gravitational waves enable tests of general relativity in the highly dynamical and strong-field regime. Using events detected by LIGO-Virgo up to 1 October 2019, we evaluate the consistency of the data with predictions from the theory. We first establish that residuals from the best-fit waveform are consistent with detector noise, and that the low- and high-frequency parts of the signals are in agreement. We then consider parametrized modifications to the waveform by varying post-Newtonian and phenomenological coefficients, improving past constraints by factors of ${\sim}2$; we also find consistency with Kerr black holes when we specifically target signatures of the spin-induced quadrupole moment. Looking for gravitational-wave dispersion, we tighten constraints on Lorentz-violating coefficients by a factor of ${\sim}2.6$ and bound the mass of the graviton to $m_g \leq 1.76 \times 10^{-23} \mathrm{eV}/c^2$ with 90% credibility. We also analyze the properties of the merger remnants by measuring ringdown frequencies and damping times, constraining fractional deviations away from the Kerr frequency to $\delta \hat{f}_{220} = 0.03^{+0.38}_{-0.35}$ for the fundamental quadrupolar mode, and $\delta \hat{f}_{221} = 0.04^{+0.27}_{-0.32}$ for the first overtone; additionally, we find no evidence for postmerger echoes. Finally, we determine that our data are consistent with tensorial polarizations through a template-independent method. When possible, we assess the validity of general relativity based on collections of events analyzed jointly. We find no evidence for new physics beyond general relativity, for black hole mimickers, or for any unaccounted systematics., Comment: 24 pages + appendices, 19 figures; journal version
Published: 2020
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35. Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, A., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antelis, J. M., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Bagnasco, S., Baird, J., Ball, M., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barnum, S., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Becher, B. R., Bécsy, B., Bedakihale, V. M., Bejger, M., Belahcene, I., Beniwal, D., Benjamin, M. G., Bennett, T. F., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bhattacharjee, D., Bidler, J., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Blanch, O., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Boldrini, M., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. 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R., Zadrożny, A., Zanolin, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhao, C., Zhao, G., Zhou, M., Zhou, Z., Zhu, X. J., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We report on the population of the 47 compact binary mergers detected with a false-alarm rate 1/yr in the second LIGO--Virgo Gravitational-Wave Transient Catalog, GWTC-2. We observe several characteristics of the merging binary black hole (BBH) population not discernible until now. First, we find that the primary mass spectrum contains structure beyond a power-law with a sharp high-mass cut-off; it is more consistent with a broken power law with a break at $39.7^{+20.3}_{-9.1}\,M_\odot$, or a power law with a Gaussian feature peaking at $33.1^{+4.0}_{-5.6}\,M_\odot$ (90\% credible interval). While the primary mass distribution must extend to $\sim65\,M_\odot$ or beyond, only $2.9^{+3.5}_{1.7}\%$ of systems have primary masses greater than $45\,M_\odot$. Second, we find that a fraction of BBH systems have component spins misaligned with the orbital angular momentum, giving rise to precession of the orbital plane. Moreover, 12% to 44% of BBH systems have spins tilted by more than $90^\circ$, giving rise to a negative effective inspiral spin parameter $\chi_\mathrm{eff}$. Under the assumption that such systems can only be formed by dynamical interactions, we infer that between 25% and 93% of BBH with non-vanishing $|\chi_\mathrm{eff}| > 0.01$ are dynamically assembled. Third, we estimate merger rates, finding $\mathcal{R}_\text{BBH} = 23.9^{+14.3}_{8.6}$ Gpc$^{-3}$ yr$^{-1}$ for BBH and $\mathcal{R}_\text{BNS}= 320^{+490}_{-240}$ Gpc$^{-3}$ yr$^{-1}$ for binary neutron stars. We find that the BBH rate likely increases with redshift ($85\%$ credibility), but not faster than the star-formation rate ($86\%$ credibility). Additionally, we examine recent exceptional events in the context of our population models, finding that the asymmetric masses of GW190412 and the high component masses of GW190521 are consistent with our models, but the low secondary mass of GW190814 makes it an outlier., Comment: 53 pages, including 24 pages main text, 18 pages appendix, 30 figures
Published: 2020
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36. GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run

Author: Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, A., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akcay, S., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antelis, J. M., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Bagnasco, S., Baird, J., Ball, M., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barnum, S., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Becher, B. R., Bécsy, B., Bedakihale, V. M., Bejger, M., Belahcene, I., Beniwal, D., Benjamin, M. G., Bennett, T. F., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bhattacharjee, D., Bidler, J., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Blanch, O., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Boldrini, M., Bondu, F., Bonnand, R., Bonilla, E., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buscicchio, R., Buskulic, D., Byer, R. L., Cabero, M., Cadonati, L., Caesar, M., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Cannon, K. C., Cao, H., Cao, J., Carapella, G., Carbognani, F., Carney, M. F., Carpinelli, M., Carullo, G., Carver, T. L., Diaz, J. Casanueva, Casentini, C., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakravarti, K., Chan, C. -L., Chan, C., Chandra, K., Chanial, P., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, D., Chattopadhyay, D., Chaturvedi, M., Chatziioannou, K., Chen, A., Chen, H. Y., Chen, X., Chen, Y., Cheng, H. -P., Cheong, C. K., Chia, H. Y., Chiadini, F., Chierici, R., Chincarini, A., Chiummo, A., Cho, G., Cho, H. S., Cho, M., Choate, S., Christensen, N., Chu, Q., Chua, S., Chung, K. W., Chung, S., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, E. N., Clark, J. A., Clarke, L., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Cohadon, P. -F., Cohen, D. E., Colleoni, M., Collette, C. G., Collins, C., Colpi, M., Constancio Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Corley, K. R., Cornish, N., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coughlin, S. B., Coulon, J. -P., Countryman, S. T., Cousins, B., Couvares, P., Covas, P. B., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Croquette, M., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Curylo, M., Canton, T. Dal, Dálya, G., Dana, A., DaneshgaranBajastani, L. M., D'Angelo, B., Danila, B., Danilishin, S. L., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Dattilo, V., Dave, I., Davier, M., Davies, G. S., Davis, D., Daw, E. J., Dean, R., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., De Lillo, N., Del Pozzo, W., DeMarchi, L. M., De Matteis, F., D'Emilio, V., Demos, N., Denker, T., Dent, T., Depasse, A., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., de Varona, O., Dhurandhar, S., Díaz, M. C., Diaz-Ortiz Jr., M., Didio, N. A., Dietrich, T., Di Fiore, L., DiFronzo, C., Di Giorgio, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Di Lieto, A., Ding, B., Di Pace, S., Di Palma, I., Di Renzo, F., Divakarla, A. K., Dmitriev, A., Doctor, Z., D'Onofrio, L., Donovan, F., Dooley, K. L., Doravari, S., Dorrington, I., Downes, T. P., Drago, M., Driggers, J. C., Du, Z., Ducoin, J. -G., Dupej, P., Durante, O., D'Urso, D., Duverne, P. -A., Dwyer, S. E., Easter, P. J., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etienne, Z. B., Etzel, T., Evans, M., Evans, T. M., Ewing, B. E., Fafone, V., Fair, H., Fairhurst, S., Fan, X., Farah, A. M., Farinon, S., Farr, B., Farr, W. M., Fauchon-Jones, E. J., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Feng, F., Fenyvesi, E., Ferguson, D. L., Fernandez-Galiana, A., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, I., Fiorucci, D., Fishbach, M., Fisher, R. P., Fishner, J. M., Fittipaldi, R., Fitz-Axen, M., Fiumara, V., Flaminio, R., Floden, E., Flynn, E., Fong, H., Font, J. A., Forsyth, P. W. F., Fournier, J. -D., Frasca, S., Frasconi, F., Frei, Z., Freise, A., Frey, R., Frey, V., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fulda, P., Fyffe, M., Gabbard, H. A., Gadre, B. U., Gaebel, S. M., Gair, J. R., Gais, J., Galaudage, S., Gamba, R., Ganapathy, D., Ganguly, A., Gaonkar, S. G., Garaventa, B., García-Quirós, C., Garufi, F., Gateley, B., Gaudio, S., Gayathri, V., Gemme, G., Gennai, A., George, D., George, J., George, R. N., Gergely, L., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, S., Giacomazzo, B., Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Gill, K., Giri, P., Glanzer, J., Gleckl, A. E., Godwin, P., Goetz, E., Goetz, R., Gohlke, N., Goncharov, B., González, G., Gopakumar, A., Gossan, S. E., Gosselin, M., Gouaty, R., Grace, B., Grado, A., Granata, M., Granata, V., Grant, A., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, R., Gretarsson, E. M., Griggs, H. L., Grignani, G., Grimaldi, A., Grimes, E., Grimm, S. J., Grote, H., Grunewald, S., Gruning, P., Guerrero, J. G., Guidi, G. M., Guimaraes, A. R., Guixé, G., Gulati, H. K., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, P., Gustafson, E. K., Gustafson, R., Guzman, F., Haegel, L., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Haney, M., Hanke, M. M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hannuksela, O., Hansen, H., Hansen, T. J., Hanson, J., Harder, T., Hardwick, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Hasskew, R. K., Haster, C. -J., Haughian, K., Hayes, F. J., Healy, J., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J., Hennig, M. H., Vivanco, F. Hernandez, Heurs, M., Hild, S., Hill, P., Hines, A. S., Hochheim, S., Hofgard, E., Hofman, D., Hohmann, J. N., Holgado, A. M., Holland, N. A., Hollows, I. J., Holmes, Z. J., Holt, K., Holz, D. E., Hopkins, P., Horst, C., Hough, J., Howell, E. J., Hoy, C. G., Hoyland, D., Huang, Y., Hübner, M. T., Huddart, A. D., Huerta, E. A., Hughey, B., Hui, V., Husa, S., Huttner, S. H., Hutzler, B. M., Huxford, R., Huynh-Dinh, T., Idzkowski, B., Iess, A., Imperato, S., Inchauspe, H., Ingram, C., Intini, G., Isi, M., Iyer, B. R., JaberianHamedan, V., Jacqmin, T., Jadhav, S. J., Jadhav, S. P., James, A. L., Jani, K., Janssens, K., Janthalur, N. N., Jaranowski, P., Jariwala, D., Jaume, R., Jenkins, A. C., Jeunon, M., Jiang, J., Johns, G. R., Johnson-McDaniel, N. K., Jones, A. W., Jones, D. I., Jones, J. D., Jones, P., Jones, R., Jonker, R. J. G., Ju, L., Junker, J., Kalaghatgi, C. V., Kalogera, V., Kamai, B., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karathanasis, C., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Katsanevas, S., Katsavounidis, E., Katzman, W., Kawabe, K., Kéfélian, F., Keitel, D., Key, J. S., Khadka, S., Khalili, F. Y., Khan, I., Khan, S., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, C., Kim, G. J., Kim, J. C., Kim, K., Kim, W. S., Kim, Y. -M., Kimball, C., King, P. J., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kleybolte, L., Klimenko, S., Knowles, T. D., Knyazev, E., Koch, P., Koehlenbeck, S. M., Koekoek, G., Koley, S., Kolstein, M., Komori, K., Kondrashov, V., Kontos, A., Koper, N., Korobko, M., Korth, W. Z., Kovalam, M., Kozak, D. B., Krämer, C., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kumar, A., Kumar, P., Kumar, Rahul, Kumar, Rakesh, Kuns, K., Kwang, S., Lackey, B. D., Laghi, D., Lalande, E., Lam, T. L., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., Lanza, R. K., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, J., Lee, K., Lehmann, J., Leon, E., Leroy, N., Letendre, N., Levin, Y., Li, A., Li, J., Li, K. J. L., Li, T. G. F., Li, X., Linde, F., Linker, S. D., Linley, J. N., Littenberg, T. B., Liu, J., Liu, X., Llorens-Monteagudo, M., Lo, R. K. L., Lockwood, A., London, L. T., Longo, A., Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lough, J. D., Lousto, C. O., Lovelace, G., Lück, H., Lumaca, D., Lundgren, A. P., Ma, Y., Macas, R., MacInnis, M., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Hernandez, I. Magaña, Magaña-Sandoval, F., Magazzù, C., Magee, R. M., Majorana, E., Maksimovic, I., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mansell, G. L., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Marion, F., Márka, S., Márka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, M., Martinez, V., Martynov, D. V., Masalehdan, H., Mason, K., Massera, E., Masserot, A., Massinger, T. J., Masso-Reid, M., Mastrogiovanni, S., Matas, A., Mateu-Lucena, M., Matichard, F., Matiushechkina, M., Mavalvala, N., Maynard, E., McCann, J. J., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McGuire, S. C., McIsaac, C., McIver, J., McManus, D. J., McRae, T., McWilliams, S. T., Meacher, D., Meadors, G. D., Mehmet, M., Mehta, A. K., Melatos, A., Melchor, D. A., Mendell, G., Menendez-Vazquez, A., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Meshkov, S., Messenger, C., Messick, C., Metzdorff, R., Meyers, P. M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Middleton, H., Milano, L., Miller, A. L., Millhouse, M., Mills, J. C., Milotti, E., Milovich-Goff, M. C., Minazzoli, O., Minenkov, Y., Mir, Ll. M., Mishkin, A., Mishra, C., Mistry, T., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Mo, G., Mogushi, K., Mohapatra, S. R. P., Mohite, S. R., Molina, I., Molina-Ruiz, M., Mondin, M., Montani, M., Moore, C. J., Moraru, D., Morawski, F., Moreno, G., Morisaki, S., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Soma, Mukherjee, Subroto, Mukund, N., Mullavey, A., Munch, J., Muñiz, E. A., Murray, P. G., Nadji, S. L., Nagar, A., Nardecchia, I., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelemans, G., Nelson, T. J. N., Nery, M., Neunzert, A., Nitz, A. H., Ng, K. Y., Ng, S., Nguyen, C., Nguyen, P., Nguyen, T., Nichols, S. A., Nissanke, S., Nocera, F., Noh, M., North, C., Nothard, D., Nuttall, L. K., Oberling, J., O'Brien, B. D., O'Dell, J., Oganesyan, G., Ogin, G. H., Oh, J. J., Oh, S. H., Ohme, F., Ohta, H., Okada, M. A., Olivetto, C., Oppermann, P., Oram, R. J., O'Reilly, B., Ormiston, R. G., Ortega, L. F., O'Shaughnessy, R., Ossokine, S., Osthelder, C., Ottaway, D. J., Overmier, H., Owen, B. J., Pace, A. E., Pagano, G., Page, M. A., Pagliaroli, G., Pai, A., Pai, S. A., Palamos, J. R., Palashov, O., Palomba, C., Pan, H., Panda, P. K., Pang, T. H., Pankow, C., Pannarale, F., Pant, B. C., Paoletti, F., Paoli, A., Paolone, A., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patel, M., Patricelli, B., Payne, E., Pechsiri, T. C., Pedraza, M., Pegoraro, M., Pele, A., Penn, S., Perego, A., Perez, C. J., Périgois, C., Perreca, A., Perriès, S., Petermann, J., Petterson, D., Pfeiffer, H. P., Pham, K. A., Phukon, K. S., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierro, V., Pillant, G., Pilo, F., Pinard, L., Pinto, I. M., Piotrzkowski, K., Pirello, M., Pitkin, M., Placidi, E., Plastino, W., Pluchar, C., Poggiani, R., Polini, E., Pong, D. Y. T., Ponrathnam, S., Popolizio, P., Porter, E. K., Poverman, A., Powell, J., Pracchia, M., Prajapati, A. K., Prasai, K., Prasanna, R., Pratten, G., Prestegard, T., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Punturo, M., Puosi, F., Puppo, P., Pürrer, M., Qi, H., Quetschke, V., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radkins, H., Radulesco, N., Raffai, P., Rafferty, H., Rail, S. X., Raja, S., Rajan, C., Rajbhandari, B., Rakhmanov, M., Ramirez, K. E., Ramirez, T. D., Ramos-Buades, A., Rana, J., Rao, K., Rapagnani, P., Rapol, U. D., Ratto, B., Raymond, V., Razzano, M., Read, J., Regimbau, T., Rei, L., Reid, S., Reitze, D. H., Rettegno, P., Ricci, F., Richardson, C. J., Richardson, J. W., Richardson, L., Ricker, P. M., Riemenschneider, G., Riles, K., Rizzo, M., Robertson, N. A., Robinet, F., Rocchi, A., Rocha, J. A., Rodriguez, S., Rodriguez-Soto, R. D., Rolland, L., Rollins, J. G., Roma, V. J., Romanelli, M., Romano, R., Romel, C. L., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Rose, C. A., Rose, D., Rose, K., Rosell, M. J. B., Rosińska, D., Rosofsky, S. G., Ross, M. P., Rowan, S., Rowlinson, S. J., Roy, Santosh, Roy, Soumen, Ruggi, P., Ryan, K., Sachdev, S., Sadecki, T., Sadiq, J., Sakellariadou, M., Salafia, O. S., Salconi, L., Saleem, M., Samajdar, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sandles, L., Santiago, K. A., Santos, E., Saravanan, T. R., Sarin, N., Sassolas, B., Sathyaprakash, B. S., Sauter, O., Savage, R. L., Savant, V., Sawant, D., Sayah, S., Schaetzl, D., Schale, P., Scheel, M., Scheuer, J., Schindler-Tyka, A., Schmidt, P., Schnabel, R., Schofield, R. M. S., Schönbeck, A., Schreiber, E., Schulte, B. W., Schutz, B. F., Schwarm, O., Schwartz, E., Scott, J., Scott, S. M., Seglar-Arroyo, M., Seidel, E., Sellers, D., Sengupta, A. S., Sennett, N., Sentenac, D., Sequino, V., Sergeev, A., Setyawati, Y., Shaffer, T., Shahriar, M. S., Sharifi, S., Sharma, A., Sharma, P., Shawhan, P., Shen, H., Shikauchi, M., Shink, R., Shoemaker, D. H., Shoemaker, D. M., Shukla, K., ShyamSundar, S., Sieniawska, M., Sigg, D., Singer, L. P., Singh, D., Singh, N., Singha, A., Singhal, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, R. J. E., Somala, S. N., Son, E. J., Soni, K., Soni, S., Sorazu, B., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Sowell, E., Spencer, A. P., Spera, M., Srivastava, A. K., Srivastava, V., Staats, K., Stachie, C., Steer, D. A., Steinhoff, J., Steinke, M., Steinlechner, J., Steinlechner, S., Steinmeyer, D., Stevenson, S. P., Stolle-McAllister, G., Stops, D. J., Stover, M., Strain, K. A., Stratta, G., Strunk, A., Sturani, R., Stuver, A. L., Südbeck, J., Sudhagar, S., Sudhir, V., Suh, H. G., Summerscales, T. Z., Sun, H., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Swinkels, B. L., Szczepańczyk, M. J., Tacca, M., Tait, S. C., Talbot, C., Tanasijczuk, A. J., Tanner, D. B., Tao, D., Tapia, A., Martin, E. N. Tapia San, Tasson, J. D., Taylor, R., Tenorio, R., Terkowski, L., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toland, K., Tolley, A. E., Tonelli, M., Tornasi, Z., Torres-Forné, A., Torrie, C. I., Melo, I. Tosta e, Töyrä, D., Tran, A. T., Trapananti, A., Travasso, F., Traylor, G., Tringali, M. C., Tripathee, A., Trovato, A., Trudeau, R. J., Tsai, D. S., Tsang, K. W., Tse, M., Tso, R., Tsukada, L., Tsuna, D., Tsutsui, T., Turconi, M., Ubhi, A. S., Udall, R. P., Ueno, K., Ugolini, D., Unnikrishnan, C. S., Urban, A. L., Usman, S. A., Utina, A. C., Vahlbruch, H., Vajente, G., Vajpeyi, A., Valdes, G., Valentini, M., Valsan, V., van Bakel, N., van Beuzekom, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Schaaf, L., van Heijningen, J. V., Vardaro, M., Vargas, A. F., Varma, V., Vass, S., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venkateswara, K., Venneberg, J., Venugopalan, G., Verkindt, D., Verma, Y., Veske, D., Vetrano, F., Viceré, A., Viets, A. D., Vijaykumar, A., Villa-Ortega, V., Vinet, J. -Y., Vitale, S., Vo, T., Vocca, H., Vorvick, C., Vyatchanin, S. P., Wade, A. R., Wade, L. E., Wade, M., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Walsh, S., Wang, J. Z., Wang, S., Wang, W. H., Wang, Y. F., Ward, R. L., Warner, J., Was, M., Washington, N. Y., Watchi, J., Weaver, B., Wei, L., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Westhouse, J. W., Wette, K., Whelan, J. T., White, D. D., White, L. V., Whiting, B. F., Whittle, C., Wilken, D. M., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wilson, D. J., Wimmer, M. H., Winkler, W., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wong, I. C. F., Wrangel, J., Wright, J. L., Wu, D. S., Wysocki, D. M., Xiao, L., Yamamoto, H., Yang, L., Yang, Y., Yang, Z., Yap, M. J., Yeeles, D. W., Yoon, A., Yu, Hang, Yu, Haocun, Yuen, S. H. R., Zadrożny, A., Zanolin, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhao, C., Zhao, G., Zheng, Y., Zhou, M., Zhou, Z., Zhu, X. J., Zimmerman, A. B., Zlochower, Y., Zucker, M. E., and Zweizig, J.
Subjects: General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena
Abstract: We report on gravitational wave discoveries from compact binary coalescences detected by Advanced LIGO and Advanced Virgo in the first half of the third observing run (O3a) between 1 April 2019 15:00 UTC and 1 October 2019 15:00. By imposing a false-alarm-rate threshold of two per year in each of the four search pipelines that constitute our search, we present 39 candidate gravitational wave events. At this threshold, we expect a contamination fraction of less than 10%. Of these, 26 candidate events were reported previously in near real-time through GCN Notices and Circulars; 13 are reported here for the first time. The catalog contains events whose sources are black hole binary mergers up to a redshift of ~0.8, as well as events whose components could not be unambiguously identified as black holes or neutron stars. For the latter group, we are unable to determine the nature based on estimates of the component masses and spins from gravitational wave data alone. The range of candidate events which are unambiguously identified as binary black holes (both objects $\geq 3~M_\odot$) is increased compared to GWTC-1, with total masses from $\sim 14~M_\odot$ for GW190924_021846 to $\sim 150~M_\odot$ for GW190521. For the first time, this catalog includes binary systems with significantly asymmetric mass ratios, which had not been observed in data taken before April 2019. We also find that 11 of the 39 events detected since April 2019 have positive effective inspiral spins under our default prior (at 90% credibility), while none exhibit negative effective inspiral spin. Given the increased sensitivity of Advanced LIGO and Advanced Virgo, the detection of 39 candidate events in ~26 weeks of data (~1.5 per week) is consistent with GWTC-1., Comment: This version updates with minor revisions to typographical errors. We would also like to call attention to the updated parameter estimation samples data release here: https://dcc.ligo.org/LIGO-P2000223/public
Published: 2020
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37. Search for Gravitational Waves Associated with Gamma-Ray Bursts Detected by Fermi and Swift During the LIGO-Virgo Run O3a

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aich, A., Aiello, L., Ain, A., Ajith, P., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Asali, Y., Ascenzi, S., Ashton, G., Assiduo, M., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Baird, J., Baldaccini, F., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barkett, K., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Benjamin, M. G., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bianchi, A., Bidler, J., Biggs, E., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bissenbayeva, G., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buskulic, D., Byer, R. L., Cabero, M., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Cao, J., Carapella, G., Carbognani, F., Caride, S., Carney, M. F., Carullo, G., Carver, T. L., Diaz, J. Casanueva, Casentini, C., Castañeda, J., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, O., Chakravarti, K., Chan, C., Chan, M., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, D., Chaturvedi, M., Chen, H. Y., Chen, X., Chen, Y., Cheng, H. -P., Cheong, C. K., Chia, H. Y., Chiadini, F., Chierici, R., Chincarini, A., Chiummo, A., Cho, G., Cho, H. S., Cho, M., Christensen, N., Chu, Q., Chua, S., Chung, K. W., Chung, S., Ciani, G., Ciecielag, P., Cie{ś}lar, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, J. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Cohadon, P. -F., Cohen, D., Colleoni, M., Collette, C. G., Collins, C., Colpi, M., Constancio Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Corley, K. R., Cornish, N., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coughlin, S. B., Coulon, J. -P., Countryman, S. T., Couvares, P., Covas, P. B., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Cripe, J., Croquette, M., Crowder, S. G., Cudell, J. -R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Curylo, M., Canton, T. Dal, Dálya, G., Dana, A., Daneshgaran-Bajastani, L. M., D'Angelo, B., Danilishin, S. 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Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We search for gravitational-wave transients associated with gamma-ray bursts detected by the Fermi and Swift satellites during the first part of the third observing run of Advanced LIGO and Advanced Virgo (1 April 2019 15:00 UTC - 1 October 2019 15:00 UTC). 105 gamma-ray bursts were analyzed using a search for generic gravitational-wave transients; 32 gamma-ray bursts were analyzed with a search that specifically targets neutron star binary mergers as short gamma-ray burst progenitors. We describe a method to calculate the probability that triggers from the binary merger targeted search are astrophysical and apply that method to the most significant gamma-ray bursts in that search. We find no significant evidence for gravitational-wave signals associated with the gamma-ray bursts that we followed up, nor for a population of unidentified subthreshold signals. We consider several source types and signal morphologies, and report for these lower bounds on the distance to each gamma-ray burst., Comment: 17 pages, 5 figures, 2 tables
Published: 2020
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38. Properties and astrophysical implications of the 150 Msun binary black hole merger GW190521

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aich, A., Aiello, L., Ain, A., Ajith, P., Akcay, S., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Baird, J., Baldaccini, F., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barkett, K., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Benjamin, M. G., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bidler, J., Biggs, E., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bissenbayeva, G., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. 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Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: The gravitational-wave signal GW190521 is consistent with a binary black hole merger source at redshift 0.8 with unusually high component masses, $85^{+21}_{-14}\,M_{\odot}$ and $66^{+17}_{-18}\,M_{\odot}$, compared to previously reported events, and shows mild evidence for spin-induced orbital precession. The primary falls in the mass gap predicted by (pulsational) pair-instability supernova theory, in the approximate range $65 - 120\,M_{\odot}$. The probability that at least one of the black holes in GW190521 is in that range is 99.0%. The final mass of the merger $(142^{+28}_{-16}\,M_{\odot})$ classifies it as an intermediate-mass black hole. Under the assumption of a quasi-circular binary black hole coalescence, we detail the physical properties of GW190521's source binary and its post-merger remnant, including component masses and spin vectors. Three different waveform models, as well as direct comparison to numerical solutions of general relativity, yield consistent estimates of these properties. Tests of strong-field general relativity targeting the merger-ringdown stages of coalescence indicate consistency of the observed signal with theoretical predictions. We estimate the merger rate of similar systems to be $0.13^{+0.30}_{-0.11}\,{\rm Gpc}^{-3}\,\rm{yr}^{-1}$. We discuss the astrophysical implications of GW190521 for stellar collapse, and for the possible formation of black holes in the pair-instability mass gap through various channels: via (multiple) stellar coalescence, or via hierarchical merger of lower-mass black holes in star clusters or in active galactic nuclei. We find it to be unlikely that GW190521 is a strongly lensed signal of a lower-mass black hole binary merger. We also discuss more exotic possible sources for GW190521, including a highly eccentric black hole binary, or a primordial black hole binary., Comment: 39 pages, 13 figures; data available at https://dcc.ligo.org/P2000158-v4/public
Published: 2020
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39. GW190521: A Binary Black Hole Merger with a Total Mass of $150 ~ M_{\odot}$

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aich, A., Aiello, L., Ain, A., Ajith, P., Akcay, S., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Baird, J., Baldaccini, F., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barkett, K., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Benjamin, M. G., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bidler, J., Biggs, E., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bissenbayeva, G., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. 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K., Zadrożny, A., Zanolin, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, T., Zhao, C., Zhao, G., Zhou, M., Zhou, Z., Zhu, X. J., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: General Relativity and Quantum Cosmology, Astrophysics - High Energy Astrophysical Phenomena
Abstract: On May 21, 2019 at 03:02:29 UTC Advanced LIGO and Advanced Virgo observed a short duration gravitational-wave signal, GW190521, with a three-detector network signal-to-noise ratio of 14.7, and an estimated false-alarm rate of 1 in 4900 yr using a search sensitive to generic transients. If GW190521 is from a quasicircular binary inspiral, then the detected signal is consistent with the merger of two black holes with masses of $85^{+21}_{-14} M_{\odot}$ and $66^{+17}_{-18} M_{\odot}$ (90 % credible intervals). We infer that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, and has only a 0.32 % probability of being below $65 M_{\odot}$. We calculate the mass of the remnant to be $142^{+28}_{-16} M_{\odot}$, which can be considered an intermediate mass black hole (IMBH). The luminosity distance of the source is $5.3^{+2.4}_{-2.6}$ Gpc, corresponding to a redshift of $0.82^{+0.28}_{-0.34}$. The inferred rate of mergers similar to GW190521 is $0.13^{+0.30}_{-0.11}\,\mathrm{Gpc}^{-3}\,\mathrm{yr}^{-1}$., Comment: Supplementary Material at https://dcc.ligo.org/LIGO-P2000020/Public
Published: 2020
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40. Reaching thermal noise at ultra-low radio frequencies: the Toothbrush radio relic downstream of the shock front

Author: de Gasperin, F., Brunetti, G., Bruggen, M., van Weeren, R., Williams, W. L., Botteon, A., Cuciti, V., Dijkema, T. J., Edler, H., Iacobelli, M., Kang, H., Offringa, A., Orru, E., Pizzo, R., Rafferty, D., Rottgering, H., and Shimwell, T.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Ultra-low frequency observations (<100 MHz) are particularly challenging because they are usually performed in a low signal-to-noise ratio regime due to the high sky temperature and because of ionospheric disturbances whose effects are inversely proportional to the observing frequency. Nonetheless, these observations are crucial to study the emission from low-energy populations of cosmic rays. We aim to obtain the first thermal-noise limited (~ 1.5 mJy/beam) deep continuum radio map using the LOFAR Low Band Antenna (LBA) system. Our demonstration observation targeted the galaxy cluster RX J0603.3+4214 (the "Toothbrush" cluster). We used the resulting ultra-low frequency (58 MHz) image to study cosmic-ray acceleration and evolution in the post shock region, as well as their relation with the presence of a radio halo. We describe the data reduction we have used to calibrate LOFAR LBA observations. The resulting image is combined with observations at higher frequencies (LOFAR 150 MHz and VLA 1500 MHz) to extract spectral information. We obtained the first thermal-noise limited image from an observation carried out with the LOFAR LBA system using all Dutch stations at a central frequency of 58 MHz. With 8 hours of data, we reached an rms noise of 1.3 mJy/beam at a resolution of 18" x 11". The procedure we have developed is an important step forward towards routine high-fidelity imaging with the LOFAR LBA. The analysis of the radio spectra shows that the radio relic extends to distances of 800 kpc downstream from the shock front, larger than what allowed by electron cooling time. Furthermore, the shock wave started accelerating electrons already at a projected distance of <300 kpc from the crossing point of the two clusters. These results can be explained if electrons are reaccelerated downstream by background turbulence possibly combined with projection effects., Comment: 15 pages, 19 figures, accepted A&A
Published: 2020
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41. Gravitational-wave constraints on the equatorial ellipticity of millisecond pulsars

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, A., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antelis, J. M., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Bagnasco, S., Baird, J., Ball, M., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barnum, S., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Becher, B. R., Bécsy, B., Bedakihale, V. M., Bejger, M., Belahcene, I., Beniwal, D., Benjamin, M. G., Bennett, T. F., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bhattacharjee, D., Bidler, J., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Blanch, O., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Boldrini, M., Bondu, F., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buskulic, D., Byer, R. L., Cabero, M., Cadonati, L., Caesar, M., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Cannon, K. C., Cao, H., Cao, J., Carapella, G., Carbognani, F., Carney, M. F., Carpinelli, M., Carullo, G., Carver, T. L., Diaz, J. Casanueva, Casentini, C., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakravarti, K., Chan, C. -L., Chan, C., Chandra, K., Chanial, P., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, D., Chaturvedi, M., Chen, A., Chen, H. Y., Chen, X., Chen, Y., Cheng, H. -P., Cheong, C. K., Chia, H. Y., Chiadini, F., Chierici, R., Chincarini, A., Chiummo, A., Cho, G., Cho, H. S., Cho, M., Choate, S., Christensen, N., Chu, Q., Chua, S., Chung, K. W., Chung, S., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, E. N., Clark, J. A., Clarke, L., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Cohadon, P. -F., Cohen, D. E., Colleoni, M., Collette, C. G., Collins, C., Colpi, M., Constancio Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Corley, K. R., Cornish, N., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coughlin, S. B., Coulon, J. -P., Countryman, S. T., Couvares, P., Covas, P. B., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Croquette, M., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Curylo, M., Canton, T. 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W., and Weltevrede, P.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We present a search for continuous gravitational waves from five radio pulsars, comprising three recycled pulsars (PSR J0437-4715, PSR J0711-6830, and PSR J0737-3039A) and two young pulsars: the Crab pulsar (J0534+2200) and the Vela pulsar (J0835-4510). We use data from the third observing run of Advanced LIGO and Virgo combined with data from their first and second observing runs. For the first time we are able to match (for PSR J0437-4715) or surpass (for PSR J0711-6830) the indirect limits on gravitational-wave emission from recycled pulsars inferred from their observed spin-downs, and constrain their equatorial ellipticities to be less than $10^{-8}$. For each of the five pulsars, we perform targeted searches that assume a tight coupling between the gravitational-wave and electromagnetic signal phase evolution. We also present constraints on PSR J0711-6830, the Crab pulsar and the Vela pulsar from a search that relaxes this assumption, allowing the gravitational-wave signal to vary from the electromagnetic expectation within a narrow band of frequencies and frequency derivatives., Comment: 23 pages, 6 figures, 3 tables
Published: 2020
Full Text: View/download PDF

42. GW190814: Gravitational Waves from the Coalescence of a 23 M$_\odot$ Black Hole with a 2.6 M$_\odot$ Compact Object

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aich, A., Aiello, L., Ain, A., Ajith, P., Akcay, S., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Baird, J., Baldaccini, F., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barkett, K., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Benjamin, M. G., Benkel, R., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bidler, J., Biggs, E., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bissenbayeva, G., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. 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E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We report the observation of a compact binary coalescence involving a 22.2 - 24.3 $M_{\odot}$ black hole and a compact object with a mass of 2.50 - 2.67 $M_{\odot}$ (all measurements quoted at the 90$\%$ credible level). The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on August 14, 2019 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network. The source was localized to 18.5 deg$^2$ at a distance of $241^{+41}_{-45}$ Mpc; no electromagnetic counterpart has been confirmed to date. The source has the most unequal mass ratio yet measured with gravitational waves, $0.112^{+0.008}_{-0.009}$, and its secondary component is either the lightest black hole or the heaviest neutron star ever discovered in a double compact-object system. The dimensionless spin of the primary black hole is tightly constrained to $\leq 0.07$. Tests of general relativity reveal no measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at high confidence. We estimate a merger rate density of 1-23 Gpc$^{-3}$ yr$^{-1}$ for the new class of binary coalescence sources that GW190814 represents. Astrophysical models predict that binaries with mass ratios similar to this event can form through several channels, but are unlikely to have formed in globular clusters. However, the combination of mass ratio, component masses, and the inferred merger rate for this event challenges all current models for the formation and mass distribution of compact-object binaries., Comment: 23 pages, 8 figures, accepted by ApJ Letters
Published: 2020
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43. LOFAR Observations of X-ray Cavity Systems

Author: Bîrzan, L., Rafferty, D. A., Brüggen, M., Botteon, A., Brunetti, G., Cuciti, V., Edge, A. C., Morganti, R., Röttgering, H. J. A., and Shimwell, T. W.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present LOFAR observations at 120-168 MHz of 42 systems with possible X-ray cavities in their hot atmosphere, of which 17 are groups or ellipticals, 19 are nearby clusters (z<0.3), and six are higher-redshift clusters (z>0.3). The X-ray cavities, formed by the radio lobes of the central active galactic nucleus (AGN), are evidence of radio-mode AGN feedback. In the groups and ellipticals sample, more than half of the systems have X-ray cavities for which no associated lobe emission was detected. Conversely, we report the discovery of large radio lobes in NGC 6338, extending far beyond the emission reported previously in the literature. In the case of the nearby clusters, our observations show that there is little low-frequency radio emission that extends beyond the cavities (e.g., MS 0735.6+7421 and A2052). For the first time, we report secure cavity-radio associations in 2A 0335+096, ZwCl 2701, and ZwCl 8276 that strengthens their interpretation as AGN-created cavities. However, in some known cavity systems (e.g., A1795 and ZwCl 3146) we report the lack of detectable low-frequency radio emission associated with the cavities. Our sample of higher-redshift systems is small, and unfortunately the present LOFAR observations are not able to resolve the lobes in many of them. Nevertheless, our sample represents one of the best available for investigating the connection between radio and jet power in radio-mode AGN feedback., Comment: 26 pages, 7 figures, 3 tables, MNRAS accepted. Revised to match published version
Published: 2020
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44. Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages

Author: Chang, Tyler A. and Rafferty, Anna N.
Subjects: Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract: We train neural machine translation (NMT) models from English to six target languages, using NMT encoder representations to predict ancestor constituent labels of source language words. We find that NMT encoders learn similar source syntax regardless of NMT target language, relying on explicit morphosyntactic cues to extract syntactic features from source sentences. Furthermore, the NMT encoders outperform RNNs trained directly on several of the constituent label prediction tasks, suggesting that NMT encoder representations can be used effectively for natural language tasks involving syntax. However, both the NMT encoders and the directly-trained RNNs learn substantially different syntactic information from a probabilistic context-free grammar (PCFG) parser. Despite lower overall accuracy scores, the PCFG often performs well on sentences for which the RNN-based models perform poorly, suggesting that RNN architectures are constrained in the types of syntax they can learn., Comment: To appear at the 5th Workshop on Representation Learning for NLP
Published: 2020

45. SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving

Author: Yang, Zhenpei, Chai, Yuning, Anguelov, Dragomir, Zhou, Yin, Sun, Pei, Erhan, Dumitru, Rafferty, Sean, and Kretzschmar, Henrik
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Autonomous driving system development is critically dependent on the ability to replay complex and diverse traffic scenarios in simulation. In such scenarios, the ability to accurately simulate the vehicle sensors such as cameras, lidar or radar is essential. However, current sensor simulators leverage gaming engines such as Unreal or Unity, requiring manual creation of environments, objects and material properties. Such approaches have limited scalability and fail to produce realistic approximations of camera, lidar, and radar data without significant additional work. In this paper, we present a simple yet effective approach to generate realistic scenario sensor data, based only on a limited amount of lidar and camera data collected by an autonomous vehicle. Our approach uses texture-mapped surfels to efficiently reconstruct the scene from an initial vehicle pass or set of passes, preserving rich information about object 3D geometry and appearance, as well as the scene conditions. We then leverage a SurfelGAN network to reconstruct realistic camera images for novel positions and orientations of the self-driving vehicle and moving objects in the scene. We demonstrate our approach on the Waymo Open Dataset and show that it can synthesize realistic camera data for simulated scenarios. We also create a novel dataset that contains cases in which two self-driving vehicles observe the same scene at the same time. We use this dataset to provide additional evaluation and demonstrate the usefulness of our SurfelGAN model.
Published: 2020

46. GW190412: Observation of a Binary-Black-Hole Coalescence with Asymmetric Masses

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aich, A., Aiello, L., Ain, A., Ajith, P., Akcay, S., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Asali, Y., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Baird, J., Baldaccini, F., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barkett, K., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Benjamin, M. G., Benkel, R., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bidler, J., Biggs, E., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bissenbayeva, G., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brito, R., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buskulic, D., Byer, R. L., Cabero, M., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Cannon, K. C., Cao, H., Cao, J., Carapella, G., Carbognani, F., Caride, S., Carney, M. F., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castañeda, J., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, O., Chakravarti, K., Chan, C., Chan, M., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, D., Chaturvedi, M., Chatziioannou, K., Chen, H. Y., Chen, X., Chen, Y., Cheng, H. -P., Cheong, C. K., Chia, H. Y., Chiadini, F., Chierici, R., Chincarini, A., Chiummo, A., Cho, G., Cho, H. S., Cho, M., Christensen, N., Chu, Q., Chua, S., Chung, K. W., Chung, S., Ciani, G., Ciecielag, P., Cie{ś}lar, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, J. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Cohadon, P. -F., Cohen, D., Colleoni, M., Collette, C. G., Collins, C., Colpi, M., Constancio Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Corley, K. R., Cornish, N., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coughlin, S. B., Coulon, J. -P., Countryman, S. T., Couvares, P., Covas, P. B., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Cripe, J., Croquette, M., Crowder, S. G., Cudell, J. -R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Curylo, M., Canton, T. Dal, Dálya, G., Dana, A., Daneshgaran-Bajastani, L. M., D'Angelo, B., Danilishin, S. L., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Dattilo, V., Dave, I., Davier, M., Davies, G. S., Davis, D., Daw, E. J., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Delfavero, M., De Lillo, N., Del Pozzo, W., DeMarchi, L. M., D'Emilio, V., Demos, N., Dent, T., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., de Varona, O., Dhurandhar, S., Díaz, M. C., Diaz-Ortiz Jr., M., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giorgio, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Di Lieto, A., Ding, B., Di Pace, S., Di Palma, I., Di Renzo, F., Divakarla, A. K., Dmitriev, A., Doctor, Z., Donovan, F., Dooley, K. L., Doravari, S., Dorrington, I., Downes, T. P., Drago, M., Driggers, J. C., Du, Z., Ducoin, J. -G., Dupej, P., Durante, O., D'Urso, D., Dwyer, S. E., Easter, P. J., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Ehrens, P., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Errico, L., Essick, R. C., Estelles, H., Estevez, D., Etienne, Z. B., Etzel, T., Evans, M., Evans, T. M., Ewing, B. E., Fafone, V., Fairhurst, S., Fan, X., Farinon, S., Farr, B., Farr, W. M., Fauchon-Jones, E. J., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Feng, F., Fenyvesi, E., Ferguson, D. L., Fernandez-Galiana, A., Ferrante, I., Ferreira, E. C., Ferreira, T. A., Fidecaro, F., Fiori, I., Fiorucci, D., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fitz-Axen, M., Fiumara, V., Flaminio, R., Floden, E., Flynn, E., Fong, H., Font, J. A., Forsyth, P. W. F., Fournier, J. -D., Frasca, S., Frasconi, F., Frei, Z., Freise, A., Frey, R., Frey, V., Fritschel, P., Frolov, V. V., Fronzè, G., Fulda, P., Fyffe, M., Gabbard, H. A., Gadre, B. U., Gaebel, S. M., Gair, J. R., Galaudage, S., Ganapathy, D., Ganguly, A., Gaonkar, S. G., García-Quirós, C., Garufi, F., Gateley, B., Gaudio, S., Gayathri, V., Gemme, G., Genin, E., Gennai, A., George, D., George, J., Gergely, L., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, S., Giacomazzo, B., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Gill, K., Glanzer, J., Gniesmer, J., Godwin, P., Goetz, E., Goetz, R., Gohlke, N., Goncharov, B., González, G., Gopakumar, A., Gossan, S. E., Gosselin, M., Gouaty, R., Grace, B., Grado, A., Granata, M., Grant, A., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, R., Gretarsson, E. M., Griggs, H. L., Grignani, G., Grimaldi, A., Grimm, S. J., Grote, H., Grunewald, S., Gruning, P., Guidi, G. M., Guimaraes, A. R., Guixé, G., Gulati, H. K., Guo, Y., Gupta, A., Gupta, Anchal, Gupta, P., Gustafson, E. K., Gustafson, R., Haegel, L., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Haney, M., Hanke, M. M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hansen, T. J., Hanson, J., Harder, T., Hardwick, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hasskew, R. K., Haster, C. -J., Haughian, K., Hayes, F. J., Healy, J., Heidmann, A., Heintze, M. C., Heinze, J., Heitmann, H., Hellman, F., Hello, P., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J., Heurs, M., Hild, S., Hinderer, T., Hoback, S. Y., Hochheim, S., Hofgard, E., Hofman, D., Holgado, A. M., Holland, N. A., Holt, K., Holz, D. E., Hopkins, P., Horst, C., Hough, J., Howell, E. J., Hoy, C. G., Huang, Y., Hübner, M. T., Huerta, E. A., Huet, D., Hughey, B., Hui, V., Husa, S., Huttner, S. H., Huxford, R., Huynh-Dinh, T., Idzkowski, B., Iess, A., Inchauspe, H., Ingram, C., Intini, G., Isac, J. -M., Isi, M., Iyer, B. R., Jacqmin, T., Jadhav, S. J., Jadhav, S. P., James, A. L., Jani, K., Janthalur, N. N., Jaranowski, P., Jariwala, D., Jaume, R., Jenkins, A. C., Jiang, J., Johns, G. R., Johnson-McDaniel, N. K., Jones, A. W., Jones, D. I., Jones, J. D., Jones, P., Jones, R., Jonker, R. J. G., Ju, L., Junker, J., Kalaghatgi, C. V., Kalogera, V., Kamai, B., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaufer, S., Kawabe, K., Kéfélian, F., Keitel, D., Keivani, A., Kennedy, R., Key, J. S., Khadka, S., Khalili, F. Y., Khan, I., Khan, S., Khan, Z. A., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, Chunglee, Kim, G. J., Kim, J. C., Kim, K., Kim, W., Kim, W. S., Kim, Y. -M., Kimball, C., King, P. J., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kleybolte, L., Klimenko, S., Knowles, T. D., Knyazev, E., Koch, P., Koehlenbeck, S. M., Koekoek, G., Koley, S., Kondrashov, V., Kontos, A., Koper, N., Korobko, M., Korth, W. Z., Kovalam, M., Kozak, D. B., Kringel, V., Krishnendu, N. V., Królak, A., Krupinski, N., Kuehn, G., Kumar, A., Kumar, P., Kumar, Rahul, Kumar, Rakesh, Kumar, S., Kuo, L., Kutynia, A., Lackey, B. D., Laghi, D., Lalande, E., Lam, T. L., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., Lanza, R. K., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., Lecoeuche, Y. K., Lee, C. H., Lee, H. M., Lee, H. W., Lee, J., Lee, K., Lehmann, J., Leroy, N., Letendre, N., Levin, Y., Li, A. K. Y., Li, J., li, K., Li, T. G. F., Li, X., Linde, F., Linker, S. D., Linley, J. N., Littenberg, T. B., Liu, J., Liu, X., Llorens-Monteagudo, M., Lo, R. K. L., Lockwood, A., London, L. T., Longo, A., Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lough, J. D., Lousto, C. O., Lovelace, G., Lück, H., Lumaca, D., Lundgren, A. P., Ma, Y., Macas, R., Macfoy, S., MacInnis, M., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Hernandez, I. Magaña, Magaña-Sandoval, F., Magee, R. M., Majorana, E., Maksimovic, I., Malik, A., Man, N., Mandic, V., Mangano, V., Mansell, G. L., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Marion, F., Márka, S., Márka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, V., Martynov, D. V., Masalehdan, H., Mason, K., Massera, E., Masserot, A., Massinger, T. J., Masso-Reid, M., Mastrogiovanni, S., Matas, A., Matichard, F., Mavalvala, N., Maynard, E., McCann, J. J., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McGuire, S. C., McIsaac, C., McIver, J., McManus, D. J., McRae, T., McWilliams, S. T., Meacher, D., Meadors, G. D., Mehmet, M., Mehta, A. K., Villa, E. Mejuto, Melatos, A., Mendell, G., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Meshkov, S., Messenger, C., Messick, C., Metzdorff, R., Meyers, P. M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Middleton, H., Milano, L., Miller, A. L., Miller, S., Millhouse, M., Mills, J. C., Milotti, E., Milovich-Goff, M. C., Minazzoli, O., Minenkov, Y., Mishkin, A., Mishra, C., Mistry, T., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Mo, G., Mogushi, K., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondin, M., Montani, M., Moore, C. J., Moraru, D., Morawski, F., Moreno, G., Morisaki, S., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, S., Mukherjee, Subroto, Mukund, N., Mullavey, A., Munch, J., Muñiz, E. A., Murray, P. G., Nagar, A., Nardecchia, I., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelemans, G., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, K. Y., Ng, S., Nguyen, C., Nguyen, P., Nichols, D., Nichols, S. A., Nissanke, S., Nocera, F., Noh, M., North, C., Nothard, D., Nuttall, L. K., Oberling, J., O'Brien, B. D., Oganesyan, G., Ogin, G. H., Oh, J. J., Oh, S. H., Ohme, F., Ohta, H., Okada, M. A., Oliver, M., Olivetto, C., Oppermann, P., Oram, Richard J., O'Reilly, B., Ormiston, R. G., Ortega, L. F., O'Shaughnessy, R., Ossokine, S., Osthelder, C., Ottaway, D. J., Overmier, H., Owen, B. J., Pace, A. E., Pagano, G., Page, M. A., Pagliaroli, G., Pai, A., Pai, S. A., Palamos, J. R., Palashov, O., Palomba, C., Pan, H., Panda, P. K., Pang, P. T. H., Pankow, C., Pannarale, F., Pant, B. C., Paoletti, F., Paoli, A., Parida, A., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patricelli, B., Payne, E., Pearlstone, B. L., Pechsiri, T. C., Pedersen, A. J., Pedraza, M., Pele, A., Penn, S., Perego, A., Perez, C. J., Périgois, C., Perreca, A., Perriès, S., Petermann, J., Pfeiffer, H. P., Phelps, M., Phukon, K. S., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierro, V., Pillant, G., Pinard, L., Pinto, I. M., Piotrzkowski, K., Pirello, M., Pitkin, M., Plastino, W., Poggiani, R., Pong, D. Y. T., Ponrathnam, S., Popolizio, P., Porter, E. K., Powell, J., Prajapati, A. K., Prasai, K., Prasanna, R., Pratten, G., Prestegard, T., Principe, M., Prodi, G. A., Prokhorov, L., Punturo, M., Puppo, P., Pürrer, M., Qi, H., Quetschke, V., Quinonez, P. J., Raab, F. J., Raaijmakers, G., Radkins, H., Radulesco, N., Raffai, P., Rafferty, H., Raja, S., Rajan, C., Rajbhandari, B., Rakhmanov, M., Ramirez, K. E., Ramos-Buades, A., Rana, Javed, Rao, K., Rapagnani, P., Raymond, V., Razzano, M., Read, J., Regimbau, T., Rei, L., Reid, S., Reitze, D. H., Rettegno, P., Ricci, F., Richardson, C. J., Richardson, J. W., Ricker, P. M., Riemenschneider, G., Riles, K., Rizzo, M., Robertson, N. A., Robinet, F., Rocchi, A., Rodriguez-Soto, R. D., Rolland, L., Rollins, J. G., Roma, V. J., Romanelli, M., Romano, R., Romel, C. L., Romero-Shaw, I. M., Romie, J. H., Rose, C. A., Rose, D., Rose, K., Rosińska, D., Rosofsky, S. G., Ross, M. P., Rowan, S., Rowlinson, S. J., Roy, P. K., Roy, Santosh, Roy, Soumen, Ruggi, P., Rutins, G., Ryan, K., Sachdev, S., Sadecki, T., Sakellariadou, M., Salafia, O. S., Salconi, L., Saleem, M., Samajdar, A., Sanchez, E. J., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Santiago, K. A., Santos, E., Sarin, N., Sassolas, B., Sathyaprakash, B. S., Sauter, O., Savage, R. L., Savant, V., Sawant, D., Sayah, S., Schaetzl, D., Schale, P., Scheel, M., Scheuer, J., Schmidt, P., Schnabel, R., Schofield, R. M. S., Schönbeck, A., Schreiber, E., Schulte, B. W., Schutz, B. F., Schwarm, O., Schwartz, E., Scott, J., Scott, S. M., Seidel, E., Sellers, D., Sengupta, A. S., Sennett, N., Sentenac, D., Sequino, V., Sergeev, A., Setyawati, Y., Shaddock, D. A., Shaffer, T., Shahriar, M. S., Sharifi, S., Sharma, A., Sharma, P., Shawhan, P., Shen, H., Shikauchi, M., Shink, R., Shoemaker, D. H., Shoemaker, D. M., Shukla, K., ShyamSundar, S., Siellez, K., Sieniawska, M., Sigg, D., Singer, L. P., Singh, D., Singh, N., Singha, A., Singhal, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, R. J. E., Somala, S., Son, E. J., Soni, S., Sorazu, B., Sordini, V., Sorrentino, F., Souradeep, T., Sowell, E., Spencer, A. P., Spera, M., Srivastava, A. K., Srivastava, V., Staats, K., Stachie, C., Standke, M., Steer, D. A., Steinke, M., Steinlechner, J., Steinlechner, S., Steinmeyer, D., Stevenson, S., Stocks, D., Stops, D. J., Stover, M., Strain, K. A., Stratta, G., Strunk, A., Sturani, R., Stuver, A. L., Sudhagar, S., Sudhir, V., Summerscales, T. Z., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Swinkels, B. L., Szczepańczyk, M. J., Tacca, M., Tait, S. C., Talbot, C., Tanasijczuk, A. J., Tanner, D. B., Tao, D., Tápai, M., Tapia, A., Martin, E. N. Tapia San, Tasson, J. D., Taylor, R., Tenorio, R., Terkowski, L., Thirugnanasambandam, M. P., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tinsman, C. L., Saravanan, T. R., Tiwari, Shubhanshu, Tiwari, S., Tiwari, V., Toland, K., Tonelli, M., Tornasi, Z., Torres-Forné, A., Torrie, C. I., Melo, I. Tosta e, Töyrä, D., Trail, E. A., Travasso, F., Traylor, G., Tringali, M. C., Tripathee, A., Trovato, A., Trudeau, R. J., Tsang, K. W., Tse, M., Tso, R., Tsukada, L., Tsuna, D., Tsutsui, T., Turconi, M., Ubhi, A. S., Udall, R., Ueno, K., Ugolini, D., Unnikrishnan, C. S., Urban, A. L., Usman, S. A., Utina, A. C., Vahlbruch, H., Vajente, G., Valdes, G., Valentini, M., van Bakel, N., van Beuzekom, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Schaaf, L., Van Heijningen, J. V., van Veggel, A. A., Vardaro, M., Varma, V., Vass, S., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venkateswara, K., Venugopalan, G., Verkindt, D., Veske, D., Vetrano, F., Viceré, A., Viets, A. D., Vinciguerra, S., Vine, D. J., Vinet, J. -Y., Vitale, S., Vivanco, Francisco Hernandez, Vo, T., Vocca, H., Vorvick, C., Vyatchanin, S. P., Wade, A. R., Wade, L. E., Wade, M., Walet, R., Walker, M., Wallace, G. S., Wallace, L., Walsh, S., Wang, J. Z., Wang, S., Wang, W. H., Ward, R. L., Warden, Z. A., Warner, J., Was, M., Watchi, J., Weaver, B., Wei, L. -W., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Westhouse, J. W., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wilken, D. M., Williams, D., Willis, J. L., Willke, B., Winkler, W., Wipf, C. C., Wittel, H., Woan, G., Woehler, J., Wofford, J. K., Wong, C., Wright, J. L., Wu, D. S., Wysocki, D. M., Xiao, L., Yamamoto, H., Yang, L., Yang, Y., Yang, Z., Yap, M. J., Yazback, M., Yeeles, D. W., Yu, Hang, Yu, Haocun, Yuen, S. H. R., Zadrożny, A. K., Zadrożny, A., Zanolin, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, T., Zhao, C., Zhao, G., Zhou, M., Zhou, Z., Zhu, X. J., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We report the observation of gravitational waves from a binary-black-hole coalescence during the first two weeks of LIGO's and Virgo's third observing run. The signal was recorded on April 12, 2019 at 05:30:44 UTC with a network signal-to-noise ratio of 19. The binary is different from observations during the first two observing runs most notably due to its asymmetric masses: a ~30 solar mass black hole merged with a ~8 solar mass black hole companion. The more massive black hole rotated with a dimensionless spin magnitude between 0.22 and 0.60 (90% probability). Asymmetric systems are predicted to emit gravitational waves with stronger contributions from higher multipoles, and indeed we find strong evidence for gravitational radiation beyond the leading quadrupolar order in the observed signal. A suite of tests performed on GW190412 indicates consistency with Einstein's general theory of relativity. While the mass ratio of this system differs from all previous detections, we show that it is consistent with the population model of stellar binary black holes inferred from the first two observing runs., Comment: 29 pages, 12 figures; data available under https://doi.org/10.7935/20yv-ka61 posterior samples available under https://dcc.ligo.org/P190412/public
Published: 2020
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47. A Joint Fermi-GBM and LIGO/Virgo Analysis of Compact Binary Mergers From the First and Second Gravitational-wave Observing Runs

Author: Team, The Fermi Gamma-ray Burst Monitor, Collaboration, the LIGO Scientific, Collaboration, the Virgo, Hamburg, R., Fletcher, C., Burns, E., Goldstein, A., Bissaldi, E., Briggs, M. S., Cleveland, W. H., Giles, M. M., Hui, C. M., Kocevski, D., Lesage, S., Mailyan, B., Malacaria, C., Poolakkil, S., Preece, R., Roberts, O. J., Veres, P., von Kienlin, A., Wilson-Hodge, C. A., Wood, J., Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aich, A., Aiello, L., Ain, A., Ajith, P., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arene, M., Arnaud, N., Aronson, S. M., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Baird, J., Baldaccini, F., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barkett, K., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Becsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Benjamin, M. G., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bidler, J., Biggs, E., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bissenbayeva, G., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buskulic, D., Byer, R. L., Cabero, M., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderon, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Cannon, K. C., Cao, H., Cao, J., Carapella, G., Carbognani, F., Caride, S., Carney, M. F., Carullo, G., Diaz, J. 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P., Countryman, S. T., Couvares, P., Covas, P. B., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Cripe, J., Croquette, M., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Curylo, M., Canton, T. Dal, Dalya, G., Dana, A., Daneshgaran-Bajastani, L. M., D'Angelo, B., Danilishin, S. L., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Dattilo, V., Dave, I., Davier, M., Davies, G. S., Davis, D., Daw, E. J., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deleglise, S., Delfavero, M., De Lillo, N., Del Pozzo, W., DeMarchi, L. M., D'Emilio, V., Demos, N., Dent, T., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., de Varona, O., Dhurandhar, S., Diaz, M. 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C., Green, R., Gretarsson, E. M., Griggs, H. L., Grignani, G., Grimaldi, A., Grimm, S. J., Grote, H., Grunewald, S., Gruning, P., Guidi, G. M., Guimaraes, A. R., Guixe, G., Gulati, H. K., Guo, Y., Gupta, A., Gupta, Anchal, Gupta, P., Gustafson, E. K., Gustafson, R., Haegel, L., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Haney, M., Hanke, M. M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hansen, T. J., Hanson, J., Harder, T., Hardwick, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hasskew, R. K., Haster, C. -J., Haughian, K., Hayes, F. J., Healy, J., Heidmann, A., Heintze, M. C., Heinze, J., Heitmann, H., Hellman, F., Hello, P., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J., Heurs, M., Hild, S., Hinderer, T., Hoback, S. Y., Hochheim, S., Hofgard, E., Hofman, D., Holgado, A. M., Holland, N. A., Holt, K., Holz, D. E., Hopkins, P., Horst, C., Hough, J., Howell, E. J., Hoy, C. G., Huang, Y., Hubner, M. T., Huerta, E. 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J., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kleybolte, L., Klimenko, S., Knowles, T. D., Koch, P., Koehlenbeck, S. M., Koekoek, G., Koley, S., Kondrashov, V., Kontos, A., Koper, N., Korobko, M., Korth, W. Z., Kovalam, M., Kozak, D. B., Kringel, V., Krishnendu, N. V., Krolak, A., Krupinski, N., Kuehn, G., Kumar, A., Kumar, P., Kumar, Rahul, Kumar, Rakesh, Kumar, S., Kuo, L., Kutynia, A., Lackey, B. D., Laghi, D., Lalande, E., Lam, T. L., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., Lanza, R. K., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., Lecoeuche, Y. K., Lee, C. H., Lee, H. M., Lee, H. W., Lee, J., Lee, K., Lehmann, J., Leroy, N., Letendre, N., Levin, Y., Li, A. K. Y., Li, J., li, K., Li, T. G. F., Li, X., Linde, F., Linker, S. D., Linley, J. N., Littenberg, T. B., Liu, J., Liu, X., Llorens-Monteagudo, M., Lo, R. K. L., Lockwood, A., London, L. 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J., Perigois, C., Perreca, A., Perries, S., Petermann, J., Pfeiffer, H. P., Phelps, M., Phukon, K. S., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierro, V., Pillant, G., Pinard, L., Pinto, I. M., Piotrzkowski, K., Pirello, M., Pitkin, M., Plastino, W., Poggiani, R., Pong, D. Y. T., Ponrathnam, S., Popolizio, P., Porter, E. K., Powell, J., Prajapati, A. K., Prasai, K., Prasanna, R., Pratten, G., Prestegard, T., Principe, M., Prodi, G. A., Prokhorov, L., Punturo, M., Puppo, P., Purrer, M., Qi, H., Quetschke, V., Quinonez, P. J., Raab, F. J., Raaijmakers, G., Radkins, H., Radulesco, N., Raffai, P., Rafferty, H., Raja, S., Rajan, C., Rajbhandari, B., Rakhmanov, M., Ramirez, K. E., Ramos-Buades, A., Rana, Javed, Rao, K., Rapagnani, P., Raymond, V., Razzano, M., Read, J., Regimbau, T., Rei, L., Reid, S., Reitze, D. H., Rettegno, P., Ricci, F., Richardson, C. J., Richardson, J. W., Ricker, P. M., Riemenschneider, G., Riles, K., Rizzo, M., Robertson, N. A., Robinet, F., Rocchi, A., Rodriguez-Soto, R. D., Rolland, L., Rollins, J. G., Roma, V. J., Romanelli, M., Romano, R., Romel, C. L., Romero-Shaw, I. M., Romie, J. H., Rose, C. A., Rose, D., Rose, K., Rosinska, D., Rosofsky, S. G., Ross, M. P., Rowan, S., Rowlinson, S. J., Roy, P. K., Roy, Santosh, Roy, Soumen, Ruggi, P., Rutins, G., Ryan, K., Sachdev, S., Sadecki, T., Sakellariadou, M., Salafia, O. S., Salconi, L., Saleem, M., Samajdar, A., Sanchez, E. J., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Santiago, K. A., Santos, E., Sarin, N., Sassolas, B., Sathyaprakash, B. S., Sauter, O., Savage, R. L., Savant, V., Sawant, D., Sayah, S., Schaetzl, D., Schale, P., Scheel, M., Scheuer, J., Schmidt, P., Schnabel, R., Schofield, R. M. S., Schonbeck, A., Schreiber, E., Schulte, B. W., Schutz, B. F., Schwarm, O., Schwartz, E., Scott, J., Scott, S. M., Seidel, E., Sellers, D., Sengupta, A. S., Sennett, N., Sentenac, D., Sequino, V., Sergeev, A., Setyawati, Y., Shaddock, D. A., Shaffer, T., Shahriar, M. S., Sharma, A., Sharma, P., Shawhan, P., Shen, H., Shikauchi, M., Shink, R., Shoemaker, D. H., Shoemaker, D. M., Shukla, K., ShyamSundar, S., Siellez, K., Sieniawska, M., Sigg, D., Singer, L. P., Singh, D., Singh, N., Singha, A., Singhal, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, R. J. E., Somala, S., Son, E. J., Soni, S., Sorazu, B., Sordini, V., Sorrentino, F., Souradeep, T., Sowell, E., Spencer, A. P., Spera, M., Srivastava, A. K., Srivastava, V., Staats, K., Stachie, C., Standke, M., Steer, D. A., Steinke, M., Steinlechner, J., Steinlechner, S., Steinmeyer, D., Stocks, D., Stops, D. J., Stover, M., Strain, K. A., Stratta, G., Strunk, A., Sturani, R., Stuver, A. L., Sudhagar, S., Sudhir, V., Summerscales, T. Z., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Swinkels, B. L., Szczepanczyk, M. J., Tacca, M., Tait, S. C., Talbot, C., Tanasijczuk, A. J., Tanner, D. B., Tao, D., Tapai, M., Tapia, A., Martin, E. N. Tapia San, Tasson, J. D., Taylor, R., Tenorio, R., Terkowski, L., Thirugnanasambandam, M. P., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tinsman, C. L., Saravanan, T. R., Tiwari, Shubhanshu, Tiwari, S., Tiwari, V., Toland, K., Tonelli, M., Tornasi, Z., Torres-Forne, A., Torrie, C. I., Melo, I. Tosta e, Toyra, D., Trail, E. A., Travasso, F., Traylor, G., Tringali, M. C., Tripathee, A., Trovato, A., Trudeau, R. J., Tsang, K. W., Tse, M., Tso, R., Tsukada, L., Tsuna, D., Tsutsui, T., Turconi, M., Ubhi, A. S., Ueno, K., Ugolini, D., Unnikrishnan, C. S., Urban, A. L., Usman, S. A., Utina, A. C., Vahlbruch, H., Vajente, G., Valdes, G., Valentini, M., van Bakel, N., van Beuzekom, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Schaaf, L., Van Heijningen, J. V., van Veggel, A. A., Vardaro, M., Varma, V., Vass, S., Vasuth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. 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P., Zevin, M., Zhang, J., Zhang, L., Zhang, T., Zhao, C., Zhao, G., Zhou, M., Zhou, Z., Zhu, X. J., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present results from offline searches of Fermi Gamma-ray Burst Monitor (GBM) data for gamma-ray transients coincident with the compact binary coalescences observed by the gravitational-wave (GW) detectors Advanced LIGO and Advanced Virgo during their first and second observing runs. In particular, we perform follow-up for both confirmed events and low significance candidates reported in the LIGO/Virgo catalog GWTC-1. We search for temporal coincidences between these GW signals and GBM triggered gamma-ray bursts (GRBs). We also use the GBM Untargeted and Targeted subthreshold searches to find coincident gamma-rays below the on-board triggering threshold. This work implements a refined statistical approach by incorporating GW astrophysical source probabilities and GBM visibilities of LIGO/Virgo sky localizations to search for cumulative signatures of coincident subthreshold gamma-rays. All search methods recover the short gamma-ray burst GRB 170817A occurring ~1.7 s after the binary neutron star merger GW170817. We also present results from a new search seeking GBM counterparts to LIGO single-interferometer triggers. This search finds a candidate joint event, but given the nature of the GBM signal and localization, as well as the high joint false alarm rate of $1.1 \times 10^{-6}$ Hz, we do not consider it an astrophysical association. We find no additional coincidences., Comment: Accepted for publication in ApJ. 18 pages, 4 figures, 1 table
Published: 2020
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48. Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, Abbott, R., Abbott, T. D., Abraham, S., Acernese, F., Ackley, K., Adams, C., Adhikari, R. X., Adya, V. B., Affeldt, C., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aich, A., Aiello, L., Ain, A., Ajith, P., Allen, G., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Angelova, S. V., Ansoldi, S., Antier, S., Appert, S., Arai, K., Araya, M. C., Areeda, J. S., Arène, M., Arnaud, N., Aronson, S. M., Arun, K. G., Ascenzi, S., Ashton, G., Aston, S. M., Astone, P., Aubin, F., Aufmuth, P., AultONeal, K., Austin, C., Avendano, V., Babak, S., Bacon, P., Badaracco, F., Bader, M. K. M., Bae, S., Baer, A. M., Baird, J., Baldaccini, F., Ballardin, G., Ballmer, S. W., Bals, A., Balsamo, A., Baltus, G., Banagiri, S., Bankar, D., Bankar, R. S., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barkett, K., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Bartos, I., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bejger, M., Belahcene, I., Bell, A. S., Beniwal, D., Benjamin, M. G., Bentley, J. D., Bergamin, F., Berger, B. K., Bergmann, G., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Bhandare, R., Bhandari, A. V., Bidler, J., Biggs, E., Bilenko, I. A., Billingsley, G., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bissenbayeva, G., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blackman, J., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boer, M., Boetzel, Y., Bogaert, G., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, S., Bossilkov, V., Bosveld, J., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brighenti, F., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Buikema, A., Bulik, T., Bulten, H. J., Buonanno, A., Buskulic, D., Byer, R. L., Cabero, M., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Cannon, K. C., Cao, H., Cao, J., Carapella, G., Carbognani, F., Caride, S., Carney, M. F., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castañeda, J., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, O., Chakravarti, K., Chan, C., Chan, M., Chao, S., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, D., Chaturvedi, M., Chen, H. Y., Chen, X., Chen, Y., Cheng, H. -P., Cheong, C. K., Chia, H. Y., Chiadini, F., Chierici, R., Chincarini, A., Chiummo, A., Cho, G., Cho, H. S., Cho, M., Christensen, N., Chu, Q., Chua, S., Chung, K. W., Chung, S., Ciani, G., Ciecielag, P., Cie{ś}lar, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Cirone, A., Clara, F., Clark, J. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Cohadon, P. -F., Cohen, D., Colleoni, M., Collette, C. G., Collins, C., Colpi, M., Constancio Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Corley, K. R., Cornish, N., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Coughlin, M. W., Coughlin, S. B., Coulon, J. -P., Countryman, S. T., Couvares, P., Covas, P. B., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Cripe, J., Croquette, M., Crowder, S. G., Cudell, J. -R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., Curylo, M., Canton, T. Dal, Dálya, G., Dana, A., Daneshgaran-Bajastani, L. M., D'Angelo, B., Danilishin, S. 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J., Hanson, J., Harder, T., Hardwick, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hasskew, R. K., Haster, C. -J., Haughian, K., Hayes, F. J., Healy, J., Heidmann, A., Heintze, M. C., Heinze, J., Heitmann, H., Hellman, F., Hello, P., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J., Heurs, M., Hild, S., Hinderer, T., Hoback, S. Y., Hochheim, S., Hofgard, E., Hofman, D., Holgado, A. M., Holland, N. A., Holt, K., Holz, D. E., Hopkins, P., Horst, C., Hough, J., Howell, E. J., Hoy, C. G., Huang, Y., Hübner, M. T., Huerta, E. A., Huet, D., Hughey, B., Hui, V., Husa, S., Huttner, S. H., Huxford, R., Huynh-Dinh, T., Idzkowski, B., Iess, A., Inchauspe, H., Ingram, C., Intini, G., Isac, J. -M., Isi, M., Iyer, B. R., Jacqmin, T., Jadhav, S. J., Jadhav, S. P., James, A. L., Jani, K., Janthalur, N. N., Jaranowski, P., Jariwala, D., Jaume, R., Jenkins, A. C., Jiang, J., Johns, G. R., Jones, A. W., Jones, D. I., Jones, J. D., Jones, P., Jones, R., Jonker, R. J. G., Ju, L., Junker, J., Kalaghatgi, C. V., Kalogera, V., Kamai, B., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaufer, S., Kawabe, K., Kéfélian, F., Keitel, D., Keivani, A., Kennedy, R., Key, J. S., Khadka, S., Khalili, F. Y., Khan, I., Khan, S., Khan, Z. A., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, Chunglee, Kim, G. J., Kim, J. C., Kim, K., Kim, W., Kim, W. S., Kim, Y. -M., Kimball, C., King, P. J., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kleybolte, L., Klimenko, S., Knowles, T. D., Koch, P., Koehlenbeck, S. M., Koekoek, G., Koley, S., Kondrashov, V., Kontos, A., Koper, N., Korobko, M., Korth, W. Z., Kovalam, M., Kozak, D. B., Kringel, V., Krishnendu, N. V., Królak, A., Krupinski, N., Kuehn, G., Kumar, A., Kumar, P., Kumar, Rahul, Kumar, Rakesh, Kumar, S., Kuo, L., Kutynia, A., Lackey, B. D., Laghi, D., Lalande, E., Lam, T. L., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., Lanza, R. K., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., Lecoeuche, Y. K., Lee, C. H., Lee, H. M., Lee, H. W., Lee, J., Lee, K., Lehmann, J., Leroy, N., Letendre, N., Levin, Y., Li, A. K. Y., Li, J., li, K., Li, T. G. F., Li, X., Linde, F., Linker, S. D., Linley, J. N., Littenberg, T. B., Liu, J., Liu, X., Llorens-Monteagudo, M., Lo, R. K. L., Lockwood, A., London, L. T., Longo, A., Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lough, J. D., Lousto, C. O., Lovelace, G., Lück, H., Lumaca, D., Lundgren, A. P., Ma, Y., Macas, R., Macfoy, S., MacInnis, M., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Hernandez, I. Magaña, Magaña-Sandoval, F., Magee, R. M., Majorana, E., Maksimovic, I., Malik, A., Man, N., Mandic, V., Mangano, V., Mansell, G. 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A., Oliver, M., Olivetto, C., Oppermann, P., Oram, Richard J., O'Reilly, B., Ormiston, R. G., Ortega, L. F., O'Shaughnessy, R., Ossokine, S., Osthelder, C., Ottaway, D. J., Overmier, H., Owen, B. J., Pace, A. E., Pagano, G., Page, M. A., Pagliaroli, G., Pai, A., Pai, S. A., Palamos, J. R., Palashov, O., Palomba, C., Pan, H., Panda, P. K., Pang, P. T. H., Pankow, C., Pannarale, F., Pant, B. C., Paoletti, F., Paoli, A., Parida, A., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patricelli, B., Payne, E., Pearlstone, B. L., Pechsiri, T. C., Pedersen, A. J., Pedraza, M., Pele, A., Penn, S., Perego, A., Perez, C. J., Périgois, C., Perreca, A., Perriès, S., Petermann, J., Pfeiffer, H. P., Phelps, M., Phukon, K. S., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierro, V., Pillant, G., Pinard, L., Pinto, I. M., Piotrzkowski, K., Pirello, M., Pitkin, M., Plastino, W., Poggiani, R., Pong, D. Y. T., Ponrathnam, S., Popolizio, P., Porter, E. 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K., Roy, Santosh, Roy, Soumen, Ruggi, P., Rutins, G., Ryan, K., Sachdev, S., Sadecki, T., Sakellariadou, M., Salafia, O. S., Salconi, L., Saleem, M., Samajdar, A., Sanchez, E. J., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Santiago, K. A., Santos, E., Sarin, N., Sassolas, B., Sathyaprakash, B. S., Sauter, O., Savage, R. L., Savant, V., Sawant, D., Sayah, S., Schaetzl, D., Schale, P., Scheel, M., Scheuer, J., Schmidt, P., Schnabel, R., Schofield, R. M. S., Schönbeck, A., Schreiber, E., Schulte, B. W., Schutz, B. F., Schwarm, O., Schwartz, E., Scott, J., Scott, S. M., Seidel, E., Sellers, D., Sengupta, A. S., Sennett, N., Sentenac, D., Sequino, V., Sergeev, A., Setyawati, Y., Shaddock, D. A., Shaffer, T., Shahriar, M. S., Sharma, A., Sharma, P., Shawhan, P., Shen, H., Shikauchi, M., Shink, R., Shoemaker, D. H., Shoemaker, D. M., Shukla, K., ShyamSundar, S., Siellez, K., Sieniawska, M., Sigg, D., Singer, L. P., Singh, D., Singh, N., Singha, A., Singhal, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, R. J. E., Somala, S., Son, E. J., Soni, S., Sorazu, B., Sordini, V., Sorrentino, F., Souradeep, T., Sowell, E., Spencer, A. P., Spera, M., Srivastava, A. K., Srivastava, V., Staats, K., Stachie, C., Standke, M., Steer, D. A., Steinke, M., Steinlechner, J., Steinlechner, S., Steinmeyer, D., Stocks, D., Stops, D. J., Stover, M., Strain, K. A., Stratta, G., Strunk, A., Sturani, R., Stuver, A. L., Sudhagar, S., Sudhir, V., Summerscales, T. Z., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Swinkels, B. L., Szczepańczyk, M. J., Tacca, M., Tait, S. C., Talbot, C., Tanasijczuk, A. J., Tanner, D. B., Tao, D., Tápai, M., Tapia, A., Martin, E. N. Tapia San, Tasson, J. D., Taylor, R., Tenorio, R., Terkowski, L., Thirugnanasambandam, M. P., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tinsman, C. L., Saravanan, T. 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P., Wade, A. R., Wade, L. E., Wade, M., Walet, R., Walker, M., Wallace, G. S., Wallace, L., Walsh, S., Wang, J. Z., Wang, S., Wang, W. H., Wang, Y. F., Ward, R. L., Warden, Z. A., Warner, J., Was, M., Watchi, J., Weaver, B., Wei, L. -W., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Westhouse, J. W., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wilken, D. M., Williams, D., Williams, R. D., Willis, J. L., Willke, B., Winkler, W., Wipf, C. C., Wittel, H., Woan, G., Woehler, J., Wofford, J. K., Wong, C., Wright, J. L., Wu, D. S., Wysocki, D. M., Xiao, L., Yamamoto, H., Yang, L., Yang, Y., Yang, Z., Yap, M. J., Yazback, M., Yeeles, D. W., Yu, Hang, Yu, Haocun, Yuen, S. H. R., Zadrożny, A. K., Zadrożny, A., Zanolin, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, T., Zhao, C., Zhao, G., Zhou, M., Zhou, Z., Zhu, X. J., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: General Relativity and Quantum Cosmology, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Advanced LIGO and Advanced Virgo are actively monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are the gravitational-wave strain arrays, released as time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software., Comment: 42 pages, 5 figures
Published: 2019
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49. Whether and How Authentic Contexts Using a Virtual Chemistry Lab Support Learning

Author: Davenport, Jodi L., Rafferty, Anna N., and Yaron, David J.
Abstract: How can we help students develop an understanding of chemistry that integrates conceptual knowledge with the experimental and computational procedures needed to apply chemistry in authentic contexts? The current work describes ChemVLab +, a set of online chemistry activities that were developed using promising design principles from chemistry education and learning science research: setting instruction in authentic contexts, connecting concepts with science practices, linking multiple representations, and using formative assessment with feedback. A study with more than 1400 high school students found that students using the online activities demonstrated increased learning as evidenced by improved problem solving and inquiry over the course of the activities and by statistically significant improvements from pre- to posttest. Further, exploratory analyses suggest that students may learn most effectively from these materials when the activities are used after initial exposure to the content and when they work individually rather than in pairs. [This is the online version of an article published in "Journal of Chemical Education."]
Published: 2018
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50. LOFAR first look at the giant radio galaxy 3C 236

Author: Shulevski, A., Barthel, P. D., Morganti, R., Harwood, J. J., Brienza, M., Shimwell, T. W., Röttgering, H. J. A., White, G. J., Callingham, J. R., Mooney, S., and Rafferty, D. A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We have examined the giant radio galaxy 3C~236 using LOFAR at 143 MHz down to an angular resolution of 7", in combination with observations at higher frequencies. We have used the low frequency data to derive spectral index maps with the highest resolution yet at these low frequencies. We confirm a previous detection of an inner hotspot in the north-west lobe and for the first time observe that the south-east lobe hotspot is in fact a triple hotspot, which may point to an intermittent source activity. Also, the spectral index map of 3C 236 shows that the spectral steepening at the inner region of the northern lobe is prominent at low frequencies. The outer regions of both lobes show spectral flattening, in contrast with previous high frequency studies. We derive spectral age estimates for the lobes, as well as particle densities of the IGM at various locations. We propose that the morphological differences between the lobes are driven by variations in the ambient medium density as well as the source activity history., Comment: 10 pages, 6 6figures
Published: 2019
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