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1. Nicotine and Chromium Co-exposure Lead to Hepatotoxicity in Male Albino Rats

Author: S. Dey, A. Nandi, S. Das, S. K. Sinha, and S. K. Dey
Subjects: nicotine, chromium, liver, toxicity, oxidative stress, Biochemistry, QD415-436
Abstract: Nicotine is one of the major constituents of different types of smoking and is the more toxic part also. Thirty metals including chromium and some chromium compounds have been detected in tobacco smoke are causally associated with cancer in humans. In the present investigation, we evaluate the individual and combined effect of nicotine and chromium (VI) on the toxicity of liver in animal. In this study, a group of male albino rats (80-100 g) were induced by intraperitonial injection of vehicle (0.9% NaCl), nicotine tartrate (0.2 mg / 100 g body weight / day), K2Cr2O7 (0.8 mg / 100 g body weight / day), and combined exposure of K2Cr2O7 and nicotine tartrate at an interval of six hours for a period of 28 days. After the treatment the liver tissues were collected to measure the hepatotoxicity. It was showed that individual and combined exposure of chromium (VI) and nicotine marked decreased the activities of GOT, GPT, ALP and LDH in liver tissue. It was also noted that the level of MDA, CD and NO production increased significantly in response to individual and combined exposure of nicotine and chromium. On the other hand, it was observed that individual and combined exposure of nicotine and chromium (VI) marked decreased the GSH and GSSG content, and also the antioxidant enzymes (SOD, CAT, GPx, GR and GST) in tested organ. The present study suggests that nicotine and chromium exhibited significant changes during individual exposure whereas co-exposure showed a marked alteration of the toxicity of liver in male albino rats.
Published: 2023

2. DESIGNING OF MULTI-EPITOPE VACCINE CONSTRUCT EMPLOYING IMMUNOINFORMATICS APPROACH TO COMBAT MULTI-TICK SPECIES INFESTATIONS

Author: A. Nandi, Manisha, V. Solanki, V. Tiwari, B. Sajjanar, M. Sankar, M. Saini, S. Shrivastava, S. K. Bhure, and S. Ghosh
Subjects: multi-tick species, immuno-informatics, multi-epitopic vaccine, Veterinary medicine, SF600-1100
Abstract: Ticks have an exceptional ability to parasitize diverse animal and human lives and cause direct losses by transmitting a wide variety of pathogens to their host. For the management of the tick a vaccine using mid-gut antigen, Bm86 was developed which provided a variable degree of efficacy against different strains of the cattle tick, Rhipicephalus microplus. Contrary to a single antigen-based vaccine, it is expedient to use multi-epitopes vaccine targeting multiple functions of ticks. To develop a universal tick vaccine against multi-species, multiepitopic construct using immunodominant conserved tick proteins with B and T-cell epitopes were designed employing various immuno-informatics techniques. The 3D structure of the final construct was predicted, refined, and validated by different computational techniques. Molecular docking of the construct was carried out with TLR-2 receptor to predict efficient cell mediate the immune response. The findings manifest that the multi-epitopic construct might be active against multi-tick species infestations, a problem faced by many tropical and subtropical countries.
Published: 2022
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3. The Mediating Role of Job Satisfaction between Leadership and Organizational Performance and the Moderating Effect of Educational Context

Author: Fahrettin Giliç, Sedat Kanadli, Yüksel Gündüz, and Yusuf I?Nandi
Abstract: Background/purpose: Leadership behaviors correlate with job satisfaction, which is supposed to have impact on overall organizational performance. This study aimed to establish a model to explain organizational performance by determining the relational effect size between transformational and transactional leadership, job satisfaction, and organizational performance, and to examine the moderating effect of educational context. Materials/methods: Meta-analytic structural equation modeling (MASEM) technique was used to determine the effect size of the relationship between transformational and transactional leadership, job satisfaction, and organizational performance. The model-data fit of the models established between these variables was then examined. Correlation coefficients from 25 primary studies were combined according to the random effects model. Results: Analysis showed that significant effect sizes (p < .05) were found between transformational and transactional leadership, job satisfaction, and organizational performance. The model constructed between these variables was found to have a good model-data fit. Transformational and transactional leadership affects employees' job satisfaction, and job satisfaction affects their organizational performance. The primary findings of the study are that employee job satisfaction is a partial mediator of the indirect effect of transformational leadership on organizational performance, and that leadership context does not significantly moderate the effect between these variables. Conclusion: Organizational leaders need to consider the job satisfaction level of their subordinates in order to enhance organizational performance.
Published: 2024

4. NEW ETHNOMEDICINAL INFORMATION FROM LEPCHA COMMUNITY OF DZONGU, SIKKIM

Author: D.K. Pradhan, N. Lepcha, J. Ghosh, D. Banerjee, M. Midday, S. Naskar, D. Maity, and A. Nandi
Subjects: dzongu, ethnomedicine, itk, lepcha, sikkim, medicinal plants, Veterinary medicine, SF600-1100
Abstract: The Lepcha community of Sikkim is primarily confined to the Dzongu area of the state. The people of this community are mostly dependent on the forest produces for their livelihood since the ancient times and used plant resources to cure daily ailments. In the present work, extensive field surveys conducted in different corners of Dzongu to document the ethnomedicinal plants and their uses from the traditional practitioners as well as the local people. As a result of which new information on the ethnomedicinal uses of 40 plant species have been recorded and these are presented here for future reference. The uses of plants have been validated statistically following Use Value (UV) and Fidelity Level (FL) methods.
Published: 2022
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5. SplatR : Experience Goal Visual Rearrangement with 3D Gaussian Splatting and Dense Feature Matching

Author: S, Arjun P, Melnik, Andrew, and Nandi, Gora Chand
Subjects: Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract: Experience Goal Visual Rearrangement task stands as a foundational challenge within Embodied AI, requiring an agent to construct a robust world model that accurately captures the goal state. The agent uses this world model to restore a shuffled scene to its original configuration, making an accurate representation of the world essential for successfully completing the task. In this work, we present a novel framework that leverages on 3D Gaussian Splatting as a 3D scene representation for experience goal visual rearrangement task. Recent advances in volumetric scene representation like 3D Gaussian Splatting, offer fast rendering of high quality and photo-realistic novel views. Our approach enables the agent to have consistent views of the current and the goal setting of the rearrangement task, which enables the agent to directly compare the goal state and the shuffled state of the world in image space. To compare these views, we propose to use a dense feature matching method with visual features extracted from a foundation model, leveraging its advantages of a more universal feature representation, which facilitates robustness, and generalization. We validate our approach on the AI2-THOR rearrangement challenge benchmark and demonstrate improvements over the current state of the art methods
Published: 2024

6. Simultaneous Estimation of Elliptic Flow Coefficient and Impact Parameter in Heavy-Ion Collisions using CNN

Author: Murali, Praveen, Dash, Sadhana, and Nandi, Basanta Kumar
Subjects: High Energy Physics - Phenomenology, Nuclear Experiment, Nuclear Theory
Abstract: A deep learning based method with Convolutional Neural Network (CNN) algorithm is developed for simultaneous determination of the Elliptic Flow coefficient ($v_{2}$) and the Impact Parameter in Heavy-Ion Collisions at relativistic energies. The proposed CNN is trained on Pb$-$Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with minimum biased events simulated with the AMPT event generator. A total of twelve models were built on different input and output combinations and their performances were evaluated. The predictions of the CNN models were compared to the estimations of the simulated and experimental data. The deep learning model seems to preserve the centrality and $p_{T}$ dependence of $v_{2}$ at the LHC energy together with predicting successfully the impact parameter with low margins of error. This is the first time a CNN is built to predict both $v_{2}$ and the impact parameter simultaneously in heavy-ion system., Comment: First simultaneous estimate of elliptic flow and impact parameter using CNN
Published: 2024

7. Scaling Program Synthesis Based Technology Mapping with Equality Saturation

Author: Smith, Gus Henry, Knizek, Colin, Petrisko, Daniel, Tatlock, Zachary, Balkind, Jonathan, Bernstein, Gilbert Louis, Ni, Haobin, and Nandi, Chandrakana
Subjects: Computer Science - Programming Languages, Computer Science - Hardware Architecture
Abstract: State-of-the-art hardware compilers for FPGAs often fail to find efficient mappings of high-level designs to low-level primitives, especially complex programmable primitives like digital signal processors (DSPs). New approaches apply sketch-guided program synthesis to more optimally map designs. However, this approach has two primary drawbacks. First, sketch-guided program synthesis requires the user to provide sketches, which are challenging to write and require domain expertise. Second, the open-source SMT solvers which power sketch-guided program synthesis struggle with the sorts of operations common in hardware -- namely multiplication. In this paper, we address both of these challenges using an equality saturation (eqsat) framework. By combining eqsat and an existing state-of-the-art program-synthesis-based tool, we produce Churchroad, a technology mapper which handles larger and more complex designs than the program-synthesis-based tool alone, while eliminating the need for a user to provide sketches., Comment: Workshop on Open-Source EDA Technology (WOSET) 2024
Published: 2024

8. An elastoplastic model approach for the relaxation dynamics of active glasses

Author: Ghosh, Tanmoy, Sollich, Peter, and Nandi, Saroj Kumar
Subjects: Condensed Matter - Soft Condensed Matter, Condensed Matter - Disordered Systems and Neural Networks
Abstract: How activity affects the glassy dynamics is crucial for several biological processes. Furthermore, active glasses offer fascinating phenomenologies, extend the scope of equilibrium glasses, and can provide novel insights into the original problem. We introduce a family of novel approaches to investigating the relaxation dynamics of active glasses via an active elastoplastic model (EPM). These approaches describe the relaxation dynamics via local plastic yielding and can provide improved insights as we can study various aspects of the system separately. Activity enters the model via three crucial features: activity-mediated plastic yielding, activated barrier crossing, and persistent rotational dynamics of the yielding direction. We first consider a minimal active EPM that adds the effect of active yielding to a thermal EPM. We show that this active EPM captures the known results of active glasses within a reasonable parameter space. The results also agree well with the analytical results for active glasses when activity is small. The minimal model breaks down at very low temperatures where other effects become important. Looking at the broader model class, we demonstrate that whereas active yielding primarily dominates the relaxation dynamics, the persistence of yielding direction governs the dynamic heterogeneity in active glasses.
Published: 2024

9. Investigating Changing-Look Active Galactic Nuclei with Long-term Optical and X-Ray Observations

Author: Jana, A., Ricci, C., Temple, M. J., Chang, H. -K., Shablovinskaya, E., Trakhtenbrot, B., Diaz, Y., Ilic, D., Nandi, P., and Koss, M.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena
Abstract: Changing-look active galactic nuclei (CLAGNs) show the appearance and disappearance of broad emission lines in their UV/optical spectra on timescales of months to decades. Here, we investigate how CL transitions depend on several AGN parameters such as accretion rate, obscuration properties and black hole mass. We study a sample of 20 nearby optically-identified CLAGNs from the BAT AGN Spectroscopic Survey (BASS), using quasi-simultaneous optical and X-ray observations taken in the last $\sim 40$ years. We find that for all CLAGNs, the transition is accompanied by a change in Eddington ratio. The CL transitions are not associated with changes in the obscuration properties of the AGN. CLAGNs are found to have a median Eddington ratio lower than the AGNs in the BASS sample in which CL transitions were not detected. The median of the transition Eddington ratio (Eddington ratio at which AGN changes its state) is found to be $\sim 0.01$ for type 1 $\leftrightarrow$ 1.8/1.9/2 transition, which is consistent with the hard $\leftrightarrow$ soft state transition in black hole X-ray binaries. Most CL events are constrained to occur within 3-4 years, which is considerably shorter than the expected viscous timescale in AGN accretion disk. The transitions of the optical CLAGNs studied here are likely associated to state changes in the accretion flow, possibly driven by disk-instability., Comment: Accepted for publication in Astronomy & Astrophysics
Published: 2024

10. Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model

Author: Nandi, Subhadip and Agrawal, Neeraj
Subjects: Computer Science - Machine Learning, Computer Science - Information Retrieval
Abstract: Few-Shot Cross-Domain NER is the process of leveraging knowledge from data-rich source domains to perform entity recognition on data scarce target domains. Most previous state-of-the-art (SOTA) approaches use pre-trained language models (PLMs) for cross-domain NER. However, these models are often domain specific. To successfully use these models for new target domains, we need to modify either the model architecture or perform model finetuning using data from the new domains. Both of these result in the creation of entirely new NER models for each target domain which is infeasible for practical scenarios. Recently,several works have attempted to use LLMs to solve Few-Shot Cross-Domain NER. However, most of these are either too expensive for practical purposes or struggle to follow LLM prompt instructions. In this paper, we propose IF-WRANER (Instruction Finetuned Word-embedding based Retrieval Augmented large language model for Named Entity Recognition), a retrieval augmented LLM, finetuned for the NER task. By virtue of the regularization techniques used during LLM finetuning and the adoption of word-level embedding over sentence-level embedding during the retrieval of in-prompt examples, IF-WRANER is able to outperform previous SOTA Few-Shot Cross-Domain NER approaches. We have demonstrated the effectiveness of our model by benchmarking its performance on the open source CrossNER dataset, on which it shows more than 2% F1 score improvement over the previous SOTA model. We have deployed the model for multiple customer care domains of an enterprise. Accurate entity prediction through IF-WRANER helps direct customers to automated workflows for the domains, thereby reducing escalations to human agents by almost 15% and leading to millions of dollars in yearly savings for the company.
Published: 2024

11. Exploring the evolution of red and blue galaxies in different cosmic web environments using IllustrisTNG simulation

Author: Pandey, Biswajit and Nandi, Anindita
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We analyze the evolution of red and blue galaxies in different cosmic web environments from redshift $z=3$ to $z=0$ using the IllustrisTNG simulation. We use Otsu's method to classify the red or blue galaxies at each redshift and determine their geometric environments from the eigenvalues of the deformation tensor. Our analysis shows that initially, blue galaxies are more common in clusters followed by filaments, sheets and voids. However, this trend reverses at lower redshifts, with red fractions rising earlier in denser environments. At $z<1$, most massive galaxies ($\log(\frac{M_{*}}{M_{\odot}})>10.5$) are quenched across all environments. In contrast, low-mass galaxies ( $\log(\frac{M_{*}}{M_{\odot}})<10.5$) are more influenced by their environment, with clusters hosting the highest red galaxy fractions at low redshifts. We observe a slower mass growth for low-mass galaxies in clusters at $z<1$. Filaments show relative red fractions (RRF) comparable to clusters at low masses, but host nearly $60\%$ of low-mass blue galaxies, representing a diverse galaxy population. It implies that less intense environmental quenching in filaments allows galaxies to experience a broader range of evolutionary stages. Despite being the densest environment, clusters display the highest relative blue fraction (RBF) for high-mass galaxies, likely due to interactions or mergers that can temporarily rejuvenate star formation in some of them. The $(u-r)$ colour distribution transitions from unimodal to bimodal by redshift $z=2$ across all environments. At $z<1$, clusters exhibit the highest median colour and lowest median specific star formation rate (sSFR), with stellar mass being the primary driver of colour evolution in massive galaxies. Our study suggests that stellar mass governs quenching in high-mass galaxies, while a complex interplay of mass and environment shapes the evolution of low-mass galaxies., Comment: 27 pages, 17 figures, 2 tables, comments are welcome
Published: 2024

12. Genetic studies through the lens of gene networks

Author: Subirana-Granés, Marc, Hoffman, Jill, Zhang, Haoyu, Akirtava, Christina, Nandi, Sutanu, Fotso, Kevin, and Pividori, Milton
Subjects: Quantitative Biology - Molecular Networks
Abstract: Understanding the genetic basis of complex traits is a longstanding challenge in the field of genomics. Genome-wide association studies (GWAS) have identified thousands of variant-trait associations, but most of these variants are located in non-coding regions, making the link to biological function elusive. While traditional approaches, such as transcriptome-wide association studies (TWAS), have advanced our understanding by linking genetic variants to gene expression, they often overlook gene-gene interactions. Here, we review current approaches to integrate different molecular data, leveraging machine learning methods to identify gene modules based on co-expression and functional relationships. These integrative approaches, like PhenoPLIER, combine TWAS and drug-induced transcriptional profiles to effectively capture biologically meaningful gene networks. This integration provides a context-specific understanding of disease processes while highlighting both core and peripheral genes. These insights pave the way for novel therapeutic targets and enhance the interpretability of genetic studies in personalized medicine., Comment: 26 pages, 4 figures GitHub: https://github.com/pivlab/annual_review_of_biomedical_data_science HTML: https://pivlab.github.io/annual_review_of_biomedical_data_science/
Published: 2024
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13. KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs

Author: Nandi, Ankita, Gandhi, Krishil, Singh, Mahendra Pratap, Chakrabartty, Shantanu, and Thakur, Chetan Singh
Subjects: Electrical Engineering and Systems Science - Systems and Control, Computer Science - Hardware Architecture, Computer Science - Emerging Technologies, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
Abstract: Diverse computing paradigms have emerged to meet the growing needs for intelligent energy-efficient systems. The Margin Propagation (MP) framework, being one such initiative in the analog computing domain, stands out due to its scalability across biasing conditions, temperatures, and diminishing process technology nodes. However, the lack of digital-like automation tools for designing analog systems (including that of MP analog) hinders their adoption for designing large systems. The inherent scalability and modularity of MP systems present a unique opportunity in this regard. This paper introduces KALAM (toolKit for Automating high-Level synthesis of Analog computing systeMs), which leverages factor graphs as the foundational paradigm for synthesizing MP-based analog computing systems. Factor graphs are the basis of various signal processing tasks and, when coupled with MP, can be used to design scalable and energy-efficient analog signal processors. Using Python scripting language, the KALAM automation flow translates an input factor graph to its equivalent SPICE-compatible circuit netlist that can be used to validate the intended functionality. KALAM also allows the integration of design optimization strategies such as precision tuning, variable elimination, and mathematical simplification. We demonstrate KALAM's versatility for tasks such as Bayesian inference, Low-Density Parity Check (LDPC) decoding, and Artificial Neural Networks (ANN). Simulation results of the netlists align closely with software implementations, affirming the efficacy of our proposed automation tool., Comment: 5 Pages, 4 figures
Published: 2024

14. Fluctuation-dominated phase ordering in the one dimensional Truncated Inverse Distance Square Ising (TIDSI) model

Author: Sadhukhan, Souvik, Barma, Mustansir, and Nandi, Saroj Kumar
Subjects: Condensed Matter - Statistical Mechanics, Condensed Matter - Soft Condensed Matter, Physics - Biological Physics
Abstract: Many physical systems, including some examples of active matter, granular assemblies, and biological systems, show fluctuation-dominated phase ordering (FDPO), where macroscopic fluctuations coexist with long-range order. Most of these systems are out of equilibrium. By contrast, a recent work has analytically demonstrated that an equilibrium one-dimensional Truncated Inverse Distance Square Ising (TIDSI) model shows FDPO. The analytical results rely on a cluster representation of the model that we term TIDSI-CL and are governed by the ratio, $c$, of the long-range interaction strength to the critical temperature. We show that the allowed range of $c$ is very narrow in the TIDSI model while it is unbounded in TIDSI-CL. We perform Monte-Carlo simulations for the TIDSI model and show consistency with the analytical results in the allowed range of $c$. The correlation length grows strongly on approaching the critical point, leading to a broad near-critical region. Within this region, $\alpha$, which is the cusp exponent of the power-law decay of the scaled correlation function at criticality, changes to $\alpha^\text{eff}$. We also investigate the coarsening dynamics of the model: the correlation function, domain size distribution, and aging behavior are consistent with the equilibrium properties upon replacing the system size, $L$, with the coarsening length, $\mathcal{L}(t)$. The mean largest cluster size shows logarithmic corrections due to finite $L$ and waiting time, $t_w$. The aging autocorrelation function exhibits two different scaling forms, characterized by exponents $\beta$ and $\gamma$, at short and long times compared to $t_w$, where $\beta=\alpha/2$., Comment: 11 Pages, 9 Figures
Published: 2024

15. $CdTe_{0.25}Se_{0.75}$ Quantum Dots as Efficient Room Temperature Single Photon Source for Quantum Technology

Author: Kaushik, Kush, Mondal, Jiban, Bag, Ritesh Kumar, Sharma, Shagun, Salam, Abdul, and Nandi, Chayan Kanti
Subjects: Physics - Chemical Physics, Physics - Applied Physics
Abstract: Room temperature single photon sources (SPS) are crucial for developing the next generation quantum technologies. Quantum dots (QDs), recently, have been reported as promising materials as SPS at room temperature. By optimizing the single particle optical properties of a series of water-soluble, $CdTe_{x}Se_{1-x}$, here we provide an efficient SPS with increased single photon purity. The data revealed that second order photon correlation, $g^2(0)$ value decreases substantially from 0.21 in CdTe to 0.02 in $CdTe_{0.25}Se_{0.75}$ QDs. They also exhibited deterministic emissions with an increase in ON time exceeding 95% of the total time. This was accompanied by an increased photon count rate, substantially reduced blinking events, and extended single particle ON-time. The increased single photon emission in $CdTe_{x}Se_{1-x}$ is attributed to very fast electron trapping to dense trap states, which suppresses the multiexciton recombination., Comment: 30 pages, 13 figures, 1 schematic, 1 graphical abstract, 1 table
Published: 2024

16. Search for gravitational waves emitted from SN 2023ixf

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. 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L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchikata, N., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the GW emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-5} M_{\odot} c^2$ and luminosity $4 \times 10^{-5} M_{\odot} c^2/\text{s}$ for a source emitting at 50 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as $1.04$, at frequencies above $1200$ Hz, surpassing results from SN 2019ejj., Comment: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table
Published: 2024

17. Probing the onset of hydrodynamization in peripheral p-Pb collisions at $\sqrt{s_{NN}} =$ 5.02 TeV

Author: Hatwar, Nikhil, Dash, Sadhana, and Nandi, Basanta Kumar
Subjects: High Energy Physics - Phenomenology, Nuclear Theory
Abstract: An attempt has been made to estimate the minimum size of the de-confined matter of Quark-Gluon Plasma (QGP) in small system that could be satisfactorily modeled with low-order hydrodynamics. The elliptic flow coefficient has been studied for the variation of second order transport coefficient called the shear relaxation time, which acts as a regulator of the non-hydrodynamic mode of theory. The small system of p-Pb collision at $\sqrt{s_{NN}} =$ 5.02 TeV is simulated on the state-of-art framework of JETSCAPE. We modeled the soft sector dynamics using an initial condition, a pre-equilibrium stage, hydrodynamics and a hadron afterburner. We generated results of transverse momentum spectra and rapidity spectra of light particles to match the simulated system with the experimental data. We looked at elliptic flow variation for extreme values of shear relaxation time for peripheral collision centralities. The increase in elliptic flow fluctuations indicate breakdown of fluid behavior at around $dN/dy \approx 8$ for p-Pb collision at $\sqrt{s_{NN}} =$ 5.02 TeV.
Published: 2024

18. Active Inhomogeneous Mode-Coupling Theory (aIMCT) for Dense Systems of Self-Propelled Particles

Author: Kolya, Soumitra, Pareek, Puneet, and Nandi, Saroj Kumar
Subjects: Condensed Matter - Soft Condensed Matter, Condensed Matter - Disordered Systems and Neural Networks
Abstract: Glassy dynamics in a dense system of active particles with self-propulsion force $f_0$ and persistence time $\tau_p$ are crucial for many biological processes. Recent studies have shown that, unlike relaxation dynamics, dynamic heterogeneity (DH) in active glasses exhibits nontrivial behavior. However, the mechanism by which activity affects DH remains unknown. We have developed an active inhomogeneous mode-coupling theory (aIMCT) for DH in active glasses. We show that the nontrivial behavior of DH comes from a novel nonequilibrium effect of activity that leads to distinct behaviors of DH and relaxation dynamics in active glasses. When activity is small, DH exhibits equilibrium-like behavior with a power-law divergence of the peak height of the four-point correlation function, $\chi_C^\text{peak}$, and the aIMCT value of the exponent, $\mu\simeq 1.0$, is consistent with the existing and our new simulations of active glasses. However, $\chi_C^\text{peak}$ deviates from the scaling relations at higher $f_0$ values because of the novel effect on DH, although the deviation with varying $\tau_p$ is relatively weak.
Published: 2024

19. The Propensity for Density in Feed-forward Models

Author: Schoots, Nandi, Jackson, Alex, Kholmovaia, Ali, McBurney, Peter, and Shanahan, Murray
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Does the process of training a neural network to solve a task tend to use all of the available weights even when the task could be solved with fewer weights? To address this question we study the effects of pruning fully connected, convolutional and residual models while varying their widths. We find that the proportion of weights that can be pruned without degrading performance is largely invariant to model size. Increasing the width of a model has little effect on the density of the pruned model relative to the increase in absolute size of the pruned network. In particular, we find substantial prunability across a large range of model sizes, where our biggest model is 50 times as wide as our smallest model. We explore three hypotheses that could explain these findings.
Published: 2024
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20. A search using GEO600 for gravitational waves coincident with fast radio bursts from SGR 1935+2154

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Azrad, D., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. 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Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R. ., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghonge, S., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. 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Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. 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Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs., Comment: 15 pages of text including references, 4 figures, 5 tables
Published: 2024

21. Optimizing search processes in systems with state toggling: exact condition delimiting the efficacy of stochastic resetting strategy

Author: Barman, Hillol kumar, Nandi, Amitabha, and Das, Dibyendu
Subjects: Condensed Matter - Statistical Mechanics
Abstract: Will the strategy of resetting} help a stochastic process to reach its target efficiently, with its environment continually toggling between a strongly favourable and an unfavourable (or weakly favourable) state? A diffusive run-and-tumble motion, transport of molecular motors on or off a filament, and motion under flashing optical traps are special examples of such state toggling. For any general process with toggling under Poisson reset, we derive a mathematical condition for continuous transitions where the advantage rendered by resetting vanishes. For the case of diffusive motion with linear potentials of unequal strength, we present exact solutions which reveal that there is quite generically a re-entrance of the advantage of resetting as a function of the strength of the strongly favourable potential. This result is shown to be valid for quadratic potential traps by using the general condition of transition.
Published: 2024

22. Suppression of Generation-Recombination Noise in Topological Insulators Through Indium Substitution

Author: Sharma, Kanav, Banerjee, Ritam, Nandi, Anuvab, Gopal, Radha Krishna, and Mitra, Chiranjib
Subjects: Condensed Matter - Materials Science
Abstract: In this work we carry out low-frequency noise spectroscopy (1/f) of highly bulk insulating and disordered thin films of (Bi0.3Sb0.7)2Te3(BST) topological insulator and compare these experimental results of these thin films with the In-doped In0.14(Bi0.3Sb0.7)1.86Te3(IBST) which has enhanced bulk insulating character. The thickness of these thin films is kept around 20nm and temperature-dependent resistance measurements show a highly bulk insulating character where the fermi level is located in the bulk band gap intersecting the Dirac cone only. The analysis of temperature-dependent power spectral density of the two thin films reveals a significant role of Indium (In) substitution in reducing the noise spectra caused by the generation-recombination mechanism in these ternary topological insulator thin films. These results offer potential for exploring topological quantum phase transitions through noise spectroscopy and suggest promising applications in the development of efficient, low-power spintronic devices that can operate near room temperature.
Published: 2024

23. Unearthing Neutrino Decoherence from Quantum Spacetime: An Open Quantum Systems Perspective

Author: Nandi, Partha and Bhattacharyya, Tiasha
Subjects: High Energy Physics - Phenomenology, General Relativity and Quantum Cosmology, High Energy Physics - Theory
Abstract: We investigated the influence of $\kappa$ Minkowski-type quantum spacetime on neutrino oscillations, revealing that spacetime fluctuations introduce a unique energy-dependent power law, $E^{-4}$, in the decoherence effect for relic neutrinos. This effect is particularly pronounced for low-energy neutrinos, such as those from the cosmic neutrino background ($C\nu B$). Our results indicate the potential for new models of low-energy quantum gravity-induced decoherence, which could pave the way for future experiments, such as IceCube-Gen2 and KM3NeT, to further constrain the deformation parameter., Comment: 8 pages
Published: 2024

24. Hidden in Plain Text: Emergence & Mitigation of Steganographic Collusion in LLMs

Author: Mathew, Yohan, Matthews, Ollie, McCarthy, Robert, Velja, Joan, de Witt, Christian Schroeder, Cope, Dylan, and Schoots, Nandi
Subjects: Computer Science - Computation and Language, Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract: The rapid proliferation of frontier model agents promises significant societal advances but also raises concerns about systemic risks arising from unsafe interactions. Collusion to the disadvantage of others has been identified as a central form of undesirable agent cooperation. The use of information hiding (steganography) in agent communications could render collusion practically undetectable. This underscores the need for evaluation frameworks to monitor and mitigate steganographic collusion capabilities. We address a crucial gap in the literature by demonstrating, for the first time, that robust steganographic collusion in LLMs can arise indirectly from optimization pressure. To investigate this problem we design two approaches -- a gradient-based reinforcement learning (GBRL) method and an in-context reinforcement learning (ICRL) method -- for reliably eliciting sophisticated LLM-generated linguistic text steganography. Importantly, we find that emergent steganographic collusion can be robust to both passive steganalytic oversight of model outputs and active mitigation through communication paraphrasing. We contribute a novel model evaluation framework and discuss limitations and future work. Our findings imply that effective risk mitigation from steganographic collusion post-deployment requires innovation in passive and active oversight techniques.
Published: 2024

25. Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System

Author: Madduri, Ravi, Li, Zilinghan, Nandi, Tarak, Kim, Kibaek, Ryu, Minseok, and Rodriguez, Alex
Subjects: Computer Science - Cryptography and Security, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: The concept of a learning healthcare system (LHS) envisions a self-improving network where multimodal data from patient care are continuously analyzed to enhance future healthcare outcomes. However, realizing this vision faces significant challenges in data sharing and privacy protection. Privacy-Preserving Federated Learning (PPFL) is a transformative and promising approach that has the potential to address these challenges by enabling collaborative learning from decentralized data while safeguarding patient privacy. This paper proposes a vision for integrating PPFL into the healthcare ecosystem to achieve a truly LHS as defined by the Institute of Medicine (IOM) Roundtable.
Published: 2024

26. Nature of the activity-mediated unjamming transition in confluent cell monolayers

Author: Sadhukhan, Souvik, Dasgupta, Chandan, and Nandi, Saroj Kumar
Subjects: Condensed Matter - Soft Condensed Matter, Physics - Biological Physics
Abstract: Activity-mediated unjamming transition in confluent systems is crucial for embryogenesis, wound healing, cancer metastasis, etc. During these processes, the cells progressively change their junction properties, characterized by an interaction parameter $p_0$, and become motile. How does activity affect this unjamming transition? Using molecular dynamics simulations of the active Vertex model and analytical mode-coupling theory (MCT), we show that the nature of the transition in the presence of activity remains similar to that in equilibrium. The agreement of the simulation results with the MCT predictions demonstrates that the structure-dynamics feedback mechanism controls the relaxation dynamics. In addition, we present the first computation of a dynamic length scale, $\xi_d$, and show that the growing relaxation time accompanies an increasing $\xi_d$. Furthermore, unlike particulate glasses, the static length is proportional to $\xi_d$. Our results highlight the unique nature of the glassy dynamics in confluent systems and rationalize the existing experimental data.
Published: 2024

27. Training Neural Networks for Modularity aids Interpretability

Author: Golechha, Satvik, Cope, Dylan, and Schoots, Nandi
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: An approach to improve network interpretability is via clusterability, i.e., splitting a model into disjoint clusters that can be studied independently. We find pretrained models to be highly unclusterable and thus train models to be more modular using an ``enmeshment loss'' function that encourages the formation of non-interacting clusters. Using automated interpretability measures, we show that our method finds clusters that learn different, disjoint, and smaller circuits for CIFAR-10 labels. Our approach provides a promising direction for making neural networks easier to interpret., Comment: 4 pages, preprint
Published: 2024

28. Structural response of neutron stars to rapid rotation and its impact on the braking index

Author: Basu, Avishek, Char, Prasanta, and Nandi, Rana
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Pulsars are rotating neutron stars that are observed to be slowing down, implying a loss of their kinetic energy. There can be several different physical mechanisms involved in their spin-down process. The properties of fast-rotating pulsars depend on the nature of the neutron star matter, which can also affect the spin-down mechanisms. In this work, we examine three different physical phenomena contributing to the spin-down: magnetic dipole radiation, gravitational mass quadrupole radiation due to the ``mountain" formation, gravitational mass current quadrupole radiation or the r-modes, and calculate the expressions for the braking indices due to all of them. We have also considered jointly the implications of the uncertainties of the equation of the state of neutron star matter and rapid rotation on the braking indices corresponding to the aforementioned processes and their combinations. In all cases, the rapid rotation results in a departure from the standard values in the literature for the braking index when the rotational effects are ignored. If generated with a saturation amplitude within the range of $10^{-4} - 10^{-1}$, the r-mode oscillations dominate the spin-down of millisecond pulsars. We also explore the braking index in the context of millisecond magnetars. This study examines two braking index measurements in the context of newly born millisecond magnetars from two observed short $\gamma$-ray bursts. The measured braking indices for these objects are consistent with our estimation, which allows us to conclude that the spin frequency of the remnants is within the range of $\sim 550-850$ Hz.
Published: 2024

29. About almost covering subsets of the hypercube

Author: Ghosh, Arijit, Kayal, Chandrima, and Nandi, Soumi
Subjects: Mathematics - Combinatorics, Computer Science - Discrete Mathematics, 05D40, 51D20, F.2.2, G.2.1
Abstract: Let $\mathbb{F}$ be a field, and consider the hypercube $\{ 0, 1 \}^{n}$ in $\mathbb{F}^{n}$. Sziklai and Weiner (Journal of Combinatorial Theory, Series A 2022) showed that if a polynomial $P ( X_{1}, \dots, X_{n} ) \in \mathbb{F}[ X_{1}, \dots, X_{n}]$ vanishes on every point of the hypercube $\{0,1\}^{n}$ except those with at most $r$ many ones then the degree of the polynomial will be at least $n-r$. This is a generalization of Alon and F\"uredi's fundamental result (European Journal of Combinatorics 1993) about polynomials vanishing on every point of the hypercube except at the origin (point with all zero coordinates). Sziklai and Weiner proved their interesting result using M\"{o}bius inversion formula and the Zeilberger method for proving binomial equalities. In this short note, we show that a stronger version of Sziklai and Weiner's result can be derived directly from Alon and F\"{u}redi's result., Comment: 2 pages. Fixed a typo in the proof of Theorem 4. Results unchanged
Published: 2024

30. LIGO Detector Characterization in the first half of the fourth Observing run

Author: Soni, S., Berger, B. K., Davis, D., Renzo, F. Di., Effler, A., Ferreira, T. A., Glanzer, J., Goetz, E., González, G., Helmling-Cornell, A., Hughey, B., Huxford, R., Mannix, B., Mo, G., Nandi, D., Neunzert, A., Nichols, S., Pham, K., Renzini, A. I., Schofield, R. M. S., Stuver, A, Trevor, M., Álvarez-López, S., Beda, R., Berry, C. P. L., Bhuiyan, S., Bruntz, R., Christensen, N., Blagg, L., Chan, M., Charlton, P., Connolly, G., Dhatri, R., Ding, J., Garg, V., Holley-Bockelmann, K., Hourihane, S., Jani, K., Janssens, K., Jarov, S., Knee, A. M., Lattal, A., Lecoeuche, Y., Littenberg, T., Liyanage, A., Lott, B., Macas, R., Malakar, D., McGowan, K., McIver, J., Millhouse, M., Nuttall, L., Nykamp, D., Ota, I., Rawcliffe, C., Scully, B., Tasson, J., Tejera, A., Thiele, S., Udall, R., Winborn, C., Yarbrough, Z., Zhang, Z., Abbott, R., Abouelfettouh, I., Adhikari, R. X., Ananyeva, A., Appert, S., Arai, K., Aritomi, N., Aston, S. M., Ball, M., Ballmer, S. W., Barker, D., Barsotti, L., Betzwieser, J., Billingsley, G., Biscans, S., Bode, N., Bonilla, E., Bossilkov, V., Branch, A., Brooks, A. F., Brown, D. D., Bryant, J., Cahillane, C., Cao, H., Capote, E., Clara, F., Collins, J., Compton, C. M., Cottingham, R., Coyne, D. C., Crouch, R., Csizmazia, J., Cullen, T. J., Dartez, L. P., Demos, N., Dohmen, E., Driggers, J. C., Dwyer, S. E., Ejlli, A., Etzel, T., Evans, M., Feicht, J., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fulda, P., Fyffe, M., Ganapathy, D., Gateley, B., Giaime, J. A., Giardina, K. D., Goetz, R., Goodwin-Jones, A. W., Gras, S., Gray, C., Griffith, D., Grote, H., Guidry, T., Hall, E. D., Hanks, J., Hanson, J., Heintze, M. C., Holland, N. A., Hoyland, D., Huang, H. Y., Inoue, Y., James, A. L., Jennings, A., Jia, W., Karat, S., Karki, S., Kasprzack, M., Kawabe, K., Kijbunchoo, N., King, P. J., Kissel, J. S., Komori, K., Kontos, A., Kumar, Rahul, Kuns, K., Landry, M., Lantz, B., Laxen, M., Lee, K., Lesovsky, M., Llamas, F., Lormand, M., Loughlin, H. A., MacInnis, M., Makarem, C. N., Mansell, G. L., Martin, R. M., Mason, K., Matichard, F., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McRae, T., Mera, F., Merilh, E. L., Meylahn, F., Mittleman, R., Moraru, D., Moreno, G., Mullavey, A., Nakano, M., Nelson, T. J. N., Notte, J., Oberling, J., O'Hanlon, T., Osthelder, C., Ottaway, D. J., Overmier, H., Parker, W., Pele, A., Pham, H., Pirello, M., Quetschke, V., Ramirez, K. E., Reyes, J., Richardson, J. W., Robinson, M., Rollins, J. G., Romel, C. L., Romie, J. H., Ross, M. P., Ryan, K., Sadecki, T., Sanchez, A., Sanchez, E. J., Sanchez, L. E., Savage, R. L., Schaetzl, D., Schiworski, M. G., Schnabel, R., Schwartz, E., Sellers, D., Shaffer, T., Short, R. W., Sigg, D., Slagmolen, B. J. J., Soike, C., Srivastava, V., Sun, L., Tanner, D. B., Thomas, M., Thomas, P., Thorne, K. A., Torrie, C. I., Traylor, G., Ubhi, A. S., Vajente, G., Vanosky, J., Vecchio, A., Veitch, P. J., Vibhute, A. M., von Reis, E. R. G., Warner, J., Weaver, B., Weiss, R., Whittle, C., Willke, B., Wipf, C. C., Xu, V. A., Yamamoto, H., Zhang, L., and Zucker, M. E.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology
Abstract: Progress in gravitational-wave astronomy depends upon having sensitive detectors with good data quality. Since the end of the LIGO-Virgo-KAGRA third Observing run in March 2020, detector-characterization efforts have lead to increased sensitivity of the detectors, swifter validation of gravitational-wave candidates and improved tools used for data-quality products. In this article, we discuss these efforts in detail and their impact on our ability to detect and study gravitational-waves. These include the multiple instrumental investigations that led to reduction in transient noise, along with the work to improve software tools used to examine the detectors data-quality. We end with a brief discussion on the role and requirements of detector characterization as the sensitivity of our detectors further improves in the future Observing runs., Comment: 35 pages, 18 figures
Published: 2024

31. UNC-104 transport properties are robust and independent of changes in its cargo binding

Author: Shee, Amir, Sabharwal, Vidur, Koushika, Sandhya P., Nandi, Amitabha, and Chaudhuri, Debasish
Subjects: Physics - Biological Physics, Condensed Matter - Soft Condensed Matter, Condensed Matter - Statistical Mechanics
Abstract: Cargo distribution within eukaryotic cells relies on the active transport mechanisms driven by molecular motors. Despite their critical role, the intricate relationship between motor transport properties and cargo binding - and its impact on motor distribution - remains inadequately understood. Additionally, improper regulation of ubiquitination, a pivotal post-translational modification that affects protein degradation, activation, and localization, is associated with several neurodegenerative diseases. Recent data showed that ubiquitination can alter motor-cargo binding of the Kinesin-3 motor UNC-104 / KIF1A that transports synaptic vesicles. To investigate how ubiquitin-like modifications affect motor protein function, particularly cargo binding, transport properties, and distribution, we utilize the PLM neuron of C. elegans as a model system. Using fluorescent microscopy, we assess the distribution of cargo-bound UNC-104 motors along the axon and probe their dynamics using FRAP experiments. We model cargo binding kinetics with a Master equation and motor density dynamics using a Fokker-Planck approach. Our combined experimental and theoretical analysis reveals that ubiquitin-like knockdowns enhance UNC-104's cooperative binding to its cargo. However, these modifications do not affect UNC-104's transport properties, such as processivity and diffusivity. Thus, while ubiquitin-like modifications significantly impact the cargo-binding of UNC-104, they do not alter its transport dynamics, keeping the homeostatic distribution of UNC-104 unchanged., Comment: 13 pages, 8 figures
Published: 2024

32. Applying the UTAUT Model to Understand Factors Affecting the Use of Learning Management System for Learning Pedagogical Education

Author: Rusman, Rusman O. Setiasih, Nandi, Wawan Setiawardani, and Eri Yusron
Abstract: This study aims to identify factors that can influence students when using the learning management system (LMS) in learning educational pedagogy. The LMS that we mean in this study is Pedagogi.id Platform. The design model in the study uses the UTAUT model. Questionnaires with five UTAUT variables, namely performance expectancy, effort expectancy, social influence, facilitating condition, behavioral intention, and use behavior, were distributed to students at one of the universities in Bandung. Hypothesis testing or data analysis of this study using the Structural Equation Model (SEM) approach with the help of the SmartPLS application. The results showed that the entire hypothesis was accepted or had a significant influence between variables. The most potent factors shown based on the results of the magnitude of influence are the variables facilitating conditions on student usage behavior and performance expectancy on student behavior intention. Therefore, this study recommends learning by utilizing technology, especially in universities, to improve students' knowledge and skills, one of which is using the Pedagogi.id Platform.
Published: 2024

33. Home away from home

Author: Jola, Nandi
Published: 2024

34. Nitrogen accountancy in space agriculture.

Author: Yates, Kevin, Berliner, Aaron, Makrygiorgos, Georgios, Kaiyom, Farrah, McNulty, Matthew, Khan, Imran, Kusuma, Paul, Kinlaw, Claire, Miron, Diogo, Legg, Charles, Wilson, James, Bugbee, Bruce, Mesbah, Ali, Arkin, Adam, Nandi, Somen, and Mcdonald, Karen
Abstract: Food production and pharmaceutical synthesis are posited as essential biotechnologies for facilitating human exploration beyond Earth. These technologies not only offer critical green space and food agency to astronauts but also promise to minimize mass and volume requirements through scalable, modular agriculture within closed-loop systems, offering an advantage over traditional bring-along strategies. Despite these benefits, the prevalent model for evaluating such systems exhibits significant limitations. It lacks comprehensive inventory and mass balance analyses for crop cultivation and life support, and fails to consider the complexities introduced by cultivating multiple crop varieties, which is crucial for enhancing food diversity and nutritional value. Here we expand space agriculture modeling to account for nitrogen dependence across an array of crops and demonstrate our model with experimental fitting of parameters. By adding nitrogen limitations, an extended model can account for potential interruptions in feedstock supply. Furthermore, sensitivity analysis was used to distill key consequential parameters that may be the focus of future experimental efforts.
Published: 2024

35. Impact of cosmic web on galaxy properties and their correlations: Insights from Principal Component Analysis

Author: Nandi, Anindita and Pandey, Biswajit
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We use Principal Component Analysis (PCA) to analyze a volume-limited sample from the SDSS and explore how cosmic web environments affect the interrelations between various galaxy properties, such as $(u-r)$ colour, stellar mass, specific star formation rate, metallicity, concentration index, and $D4000$. Our analysis reveals that the first two principal components (PC1 and PC2) account for approximately $\sim 72\%$ of the data variance. We then classify galaxies into different cosmic web environments based on the eigenvalues of the deformation tensor and compare PC1 and PC2 across these environments, ensuring a mass-matched sample of equal size for each environment. We observe that PC1 displays clear bimodality across all cosmic web environments, with sheets and clusters showing distinct preferences for negative and positive PC1 values, respectively. PC2, on the other hand, shows a positively skewed unimodal distribution in all environments. A Kolmogorov-Smirnov (KS) test confirms that the distributions of PC1 and PC2 differ significantly across environments, with a confidence level exceeding $99.99\%$. Furthermore, we calculate the normalized mutual information (NMI) between the principal components and individual galaxy properties within different cosmic web environments. A two-tailed t-test reveals that for each relationship and each pair of environments, the null hypothesis is rejected with a confidence level $>99.99\%$. Our analysis confirms that cosmic web environments play a significant role in shaping the correlations between galaxy properties., Comment: 22 pages, 8 tables, 9 figures, comments are welcome
Published: 2024

36. Automatic Detection of COVID-19 from Chest X-ray Images Using Deep Learning Model

Author: Das, Alloy, Agarwal, Rohit, Singh, Rituparna, Chowdhury, Arindam, and Nandi, Debashis
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract: The infectious disease caused by novel corona virus (2019-nCoV) has been widely spreading since last year and has shaken the entire world. It has caused an unprecedented effect on daily life, global economy and public health. Hence this disease detection has life-saving importance for both patients as well as doctors. Due to limited test kits, it is also a daunting task to test every patient with severe respiratory problems using conventional techniques (RT-PCR). Thus implementing an automatic diagnosis system is urgently required to overcome the scarcity problem of Covid-19 test kits at hospital, health care systems. The diagnostic approach is mainly classified into two categories-laboratory based and Chest radiography approach. In this paper, a novel approach for computerized corona virus (2019-nCoV) detection from lung x-ray images is presented. Here, we propose models using deep learning to show the effectiveness of diagnostic systems. In the experimental result, we evaluate proposed models on publicly available data-set which exhibit satisfactory performance and promising results compared with other previous existing methods., Comment: Accepted in AIP Conference Proceedings (Vol. 2424, No. 1)
Published: 2024

37. Quark Flavor Balancing in Nuclear Collisions

Author: Patley, Yash, Nandi, Basanta, Dash, Sadhana, Gonzalez, Victor, and Pruneau, Claude
Subjects: High Energy Physics - Phenomenology
Abstract: The notion of charge balance function, originally designed to study the evolution of charge production in heavy-ion collisions, is extended to consider quark flavor balancing. This extension is considered based on simulations performed with the PYTHIA 8 event generator in the context of pp collisions at $\sqrt{s} = 13.6$ TeV but can be trivially applied to any other scenario and implemented in measurements of correlated particle production in pp, pA, and AA collisions at colliders. Correlation of selected flavor balancing pairs are examined as function of the produced charged particle multiplicity. One finds that the amplitude of the correlations increases monotonically with the number of balanced flavors and the actual flavor content of correlated particles.
Published: 2024

38. h4rm3l: A Dynamic Benchmark of Composable Jailbreak Attacks for LLM Safety Assessment

Author: Doumbouya, Moussa Koulako Bala, Nandi, Ananjan, Poesia, Gabriel, Ghilardi, Davide, Goldie, Anna, Bianchi, Federico, Jurafsky, Dan, and Manning, Christopher D.
Subjects: Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Machine Learning, 68, I.2, I.2.0, I.2.1, I.2.5, I.2.7, K.6.5, K.4.2
Abstract: The safety of Large Language Models (LLMs) remains a critical concern due to a lack of adequate benchmarks for systematically evaluating their ability to resist generating harmful content. Previous efforts towards automated red teaming involve static or templated sets of illicit requests and adversarial prompts which have limited utility given jailbreak attacks' evolving and composable nature. We propose a novel dynamic benchmark of composable jailbreak attacks to move beyond static datasets and taxonomies of attacks and harms. Our approach consists of three components collectively called h4rm3l: (1) a domain-specific language that formally expresses jailbreak attacks as compositions of parameterized prompt transformation primitives, (2) bandit-based few-shot program synthesis algorithms that generate novel attacks optimized to penetrate the safety filters of a target black box LLM, and (3) open-source automated red-teaming software employing the previous two components. We use h4rm3l to generate a dataset of 2656 successful novel jailbreak attacks targeting 6 state-of-the-art (SOTA) open-source and proprietary LLMs. Several of our synthesized attacks are more effective than previously reported ones, with Attack Success Rates exceeding 90% on SOTA closed language models such as claude-3-haiku and GPT4-o. By generating datasets of jailbreak attacks in a unified formal representation, h4rm3l enables reproducible benchmarking and automated red-teaming, contributes to understanding LLM safety limitations, and supports the development of robust defenses in an increasingly LLM-integrated world. Warning: This paper and related research artifacts contain offensive and potentially disturbing prompts and model-generated content.
Published: 2024

39. 3D $\mathcal{N}=1$ supergravity from Virasoro TQFT: Gravitational partition function and Out-of-time-order correlator

Author: Bhattacharyya, Arpan, Ghosh, Saptaswa, Nandi, Poulami, and Pal, Sounak
Subjects: High Energy Physics - Theory, General Relativity and Quantum Cosmology, Mathematical Physics, Quantum Physics
Abstract: In this paper, we compute the partition functions of $\mathcal{N}=1$ SUGRA for different boundary topologies, i.e. sphere and torus, using super-Virasoro TQFT. We use fusion and modular kernels of the super-Liouville theory to compute the necklace-channel conformal block and showcase formalism by proving that the inner product holds for superconformal blocks, defined as states in the Hilbert space. Finally, we compute the out-of-time-order correlator for the torus topology with superconformal primary insertions as matter using the tools of super-Virasoro TQFT and investigate its early-time behaviour., Comment: 48 pages, 4 figures, 1 table
Published: 2024

40. Robust Implementation of Discrete-time Quantum Walks in Any Finite-dimensional Quantum System

Author: Nandi, Biswayan, Singha, Sandipan, Datta, Ankan, Saha, Amit, and Chakrabarti, Amlan
Subjects: Quantum Physics, Computer Science - Emerging Technologies
Abstract: Research has shown that quantum walks can accelerate certain quantum algorithms and act as a universal paradigm for quantum processing. The discrete-time quantum walk (DTQW) model, owing to its discrete nature, stands out as one of the most suitable choices for circuit implementation. Nevertheless, most current implementations are characterized by extensive, multi-layered quantum circuits, leading to higher computational expenses and a notable decrease in the number of confidently executable time steps on current quantum computers. Since quantum computers are not scalable enough in this NISQ era, we also must confine ourselves to the ancilla-free frontier zone. Therefore, in this paper, we have successfully cut down the circuit cost concerning gate count and circuit depth by half through our proposed methodology in qubit systems as compared to the state-of-the-art increment-decrement approach. Furthermore, for the engineering excellence of our proposed approach, we implement DTQW in any finite-dimensional quantum system with akin efficiency. To ensure an efficient implementation of quantum walks without requiring ancilla, we have incorporated an intermediate qudit technique for decomposing multi-qubit gates. Experimental outcomes hold significance far beyond the realm of just a few time steps, laying the groundwork for dependable implementation and utilization on quantum computers., Comment: 13 pages, 21 figures
Published: 2024

41. $\Delta$-Machine Learning to Elevate DFT-based Potentials and a Force Field to the CCSD(T) Level Illustrated for Ethanol

Author: Nandi, Apurba, Pandey, Priyanka, Houston, Paul L., Qu, Chen, Yu, Qi, Conte, Riccardo, Tkatchenko, Alexandre, and Bowman, Joel M.
Subjects: Physics - Chemical Physics
Abstract: Progress in machine learning has facilitated the development of potentials that offer both the accuracy of first-principles techniques and vast increases in the speed of evaluation. Recently,"$\Delta$-machine learning" has been used to elevate the quality of a potential energy surface (PES) based on low-level, e.g., density functional theory (DFT) energies and gradients to close to the gold-standard coupled cluster level of accuracy. We have demonstrated the success of this approach for molecules, ranging in size from H$_3$O$^+$ to 15-atom acetyl-acetone and tropolone. These were all done using the B3LYP functional. Here we investigate the generality of this approach for the PBE, M06, M06-2X, and PBE0+MBD functionals, using ethanol as the example molecule. Linear regression with permutationally invariant polynomials is used to fit both low-level and correction PESs. These PESs are employed for standard RMSE analysis for training and test datasets, and then general fidelity tests such as energetics of stationary points, normal mode frequencies, and torsional potentials are examined. We achieve similar improvements in all cases. Interestingly, we obtained significant improvement over DFT gradients where coupled cluster gradients were not used to correct the low-level PES. Finally, we present some results for correcting a recent molecular mechanics force field for ethanol and comment on the possible generality of this approach.
Published: 2024

42. When Life Gives You Lemons, Squeeze Your Way Through: Understanding Citrus Avoidance Behaviour by Free-Ranging Dogs in India

Author: Pal, Tuhin Subhra, Nandi, Srijaya, Sarkar, Rohan, and Bhadra, Anindita
Subjects: Quantitative Biology - Other Quantitative Biology
Abstract: Palatability of food is driven by multiple factors like taste, smell, texture, freshness, etc. and can be very variable across species. There are classic examples of local adaptations leading to speciation, driven by food availability. Urbanization across the world is causing rapid decline of biodiversity, while also driving local adaptations in some species. Free-ranging dogs are an interesting example of adaptation to a human-dominated environment across varied habitats. They have co-existed with humans for centuries and are a perfect model system for studying local adaptations. We attempted to understand a specific aspect of their scavenging behaviour in India: citrus aversion. Pet dogs are known to avoid citrus fruits and food contaminated by them. In India, lemons are used widely in the cuisine, and discarded in the garbage. Hence, free-ranging dogs, that typically are scavengers of human leftovers, are likely to encounter lemons and lemon-contaminated food on a regular basis. We carried out a population level experiment to test response of free-ranging dogs to chicken contaminated with various parts of lemon. The dogs avoided chicken contaminated with lemon juice the most. Further, when provided with chicken dipped in three different concentrations of lemon juice, the lowest concentration was most preferred. A survey confirmed that the local people use lemon in their diet extensively and also discard these with the leftovers. People avoided giving citrus contaminated food to their pets but did not follow the same caution for free-ranging dogs. This study revealed that free-ranging dogs in West Bengal, India, are well adapted to scavenging among citrus-contaminated garbage and have their own strategies to avoid the contamination as far as possible, while maximizing their preferred food intake., Comment: Includes supplementary information
Published: 2024

43. Angular momentum dependence in multiphoton ionization and attosecond time delays

Author: Benda, Jakub, Mašín, Zdeněk, Palakkal, Sreelakshmi, Lépine, Franck, Nandi, Saikat, and Loriot, Vincent
Subjects: Physics - Atomic Physics
Abstract: Attosecond ionization time-delays at photoelectron energies above typically 10 eV are usually interpreted using the so called asymptotic approximation as a sum of the atomic or molecular delays with a universal laser-induced contribution. Here, we employ a two-harmonic RABITT (Reconstruction of Attosecond Beating by Interference of Two-photon Transitions) configuration to isolate the multiphoton pathways and measure the ionization time delays as a function of the dressing field intensity. We show that the validity of the asymptotic theory can be extended to the threshold or to higher-order contributions by rigorously treating the angular-momentum dependence of the continuum-continuum transitions into universal and easily computable partial-wave-specific correction factors. Our asymptotic treatment is also valid for higher-order interfering amplitudes while significantly simplifying their evaluation and providing a transparent physical interpretation. The validity of the method for atomic and molecular targets in the vicinity of resonances, ionization thresholds, and for both the emission-integrated and angularly resolved signal is confirmed by comparison to ab initio calculations over a wide energy range.
Published: 2024

44. Long term wide-band spectro-temporal studies of outbursting black hole candidate sources GX 339-4 and H 1743-322: AstroSat and NuSTAR results

Author: Aneesha, U., Das, Santabrata, Katoch, Tilak B., and Nandi, Anuj
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present a comprehensive spectro-temporal analyses of recurrent outbursting black hole sources GX 339$-$4 and H 1743$-$322 using available AstroSat and NuSTAR archival observations during 2016-2024. The nature of the outburst profiles of both sources are examined using long-term MAXI/GSC and Swift/BAT lightcurves, and failed as well as successful outbursts are classified. Wide-band (0.5-60 keV) spectral modelling with disc (diskbb) and Comptonized (Nthcomp) components indicates that GX 339-4 transits from hard ($kT_{bb}=0.12-0.77$ keV, $\Gamma_{nth}=1.54-1.74$ and $L_{bol}=0.91-11.56$\% $L_{Edd}$) to soft state ($kT_{in}~[\approx{kT}_{bb}]=0.82-0.88$ keV, $\Gamma_{nth}=1.46-3.26$, $L_{bol}=19.59-30.06\%L_{Edd}$) via intermediate state ($kT_{in}~[\approx{kT}_{bb}]=0.56-0.88$ keV, $\Gamma_{nth}=1.76-2.66$, $L_{bol}=2.90-16.09\%L_{Edd}$), whereas H 1743-322 transits from quiescent to hard state ($\Gamma_{nth}=1.57-1.71$, $L_{bol}=2.08-3.48\%L_{Edd}$). We observe type-B and type-C Quasi-periodic Oscillations (QPOs) in GX 339-4 with increasing frequencies ($0.10-5.37$ Hz) along with harmonics. For H 1743-322, prominent type-C QPOs are observed in frequency range 0.22-1.01 Hz along with distinct harmonics. Energy-dependent power spectral studies reveal that fundamental QPO and harmonics disappear beyond 20 keV in GX 339-4, whereas fundamental QPO in H 1743-322 persists up to 40 keV. We also observe that type-C $QPO_{rms}\%$ decreases with energy for both sources although such variations appear marginal for type-B QPOs. Additionally, we report non-monotonic behavior of photon index with plasma temperature and detection of annihilation line. Finally, we discuss the relevance of the observational findings in the context of accretion dynamics around black hole binaries., Comment: 20 pages, 9 figures, 5 tables. Accepted for publication in MNRAS
Published: 2024

45. Anomalous resistivity upturn in Co intercalated TaS$_2$

Author: Nandi, Moumita, Dutta, Surajit, Thamizhavel, A., and Dhar, S. K.
Subjects: Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science
Abstract: Intercalation of magnetic atoms into the van der Waals gaps of layered transition metal dichalcogenides offers an excellent platform to produce exotic physical properties. Here, we report a detailed study of magnetic and electrical transport properties of Co$_{0.28}$TaS$_2$. The temperature dependent resistivity measurements display anomalous upturn below 11 K, which persists in presence of magnetic field even up to 14 T. In the low temperature region, the resistivity upturn exhibits a unique $T^{1/2}$ scaling behavior, which remains unchanged when an external magnetic field is applied. The $T^{1/2}$ dependence of resistivity upturn is the hallmark of non-Fermi liquid state in orbital two-channel Kondo effect(2CK). This anomalous resistivity upturn in Co$_{0.28}$TaS$_2$ can be attributed to the orbital two-channel Kondo mechanism., Comment: 7 pages, 5 figures
Published: 2024

46. Swift-BAT GUANO follow-up of gravitational-wave triggers in the third LIGO-Virgo-KAGRA observing run

Author: Raman, Gayathri, Ronchini, Samuele, Delaunay, James, Tohuvavohu, Aaron, Kennea, Jamie A., Parsotan, Tyler, Ambrosi, Elena, Bernardini, Maria Grazia, Campana, Sergio, Cusumano, Giancarlo, D'Ai, Antonino, D'Avanzo, Paolo, D'Elia, Valerio, De Pasquale, Massimiliano, Dichiara, Simone, Evans, Phil, Hartmann, Dieter, Kuin, Paul, Melandri, Andrea, O'Brien, Paul, Osborne, Julian P., Page, Kim, Palmer, David M., Sbarufatti, Boris, Tagliaferri, Gianpiero, Troja, Eleonora, Abac, A. G., Abbott, R., Abe, H., Abouelfettouh, I., Acernese, F., Ackley, K., Adamcewicz, C., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boumerdassi, A., Bozzi, A., Bradaschia, C., Brady, P. 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Chalathadka, Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, R. -J., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, K. H., Chen, X., Chen, Yi-Ru, Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Chia, H. Y., Chiadini, F., Chiang, C., Chiarini, G., Chiba, A., Chiba, R., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Croquette, M., Crouch, R., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Daw, E. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhani, A., Dhurandhar, S., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Emma, M., Engelby, E., Engl, A. J., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Ferrante, I., Ferreira, T. A., Fidecaro, F., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fukunaga, I., Fulda, P., Fyffe, M., Gabella, W. 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M., Mchedlidze, M., McIsaac, C., McIver, J., McKinney, K., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehta, A. K., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Modafferi, L. M., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Morales, M., Moraru, D., Morawski, F., More, A., More, S., Moreno, C., Moreno, G., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mungioli, C. L., Munn, M., Oberg, W. R. Munn, Murakoshi, M., Murray, P. G., Muusse, S., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narola, H., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Nguyen, C., Nguyen, P., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nurbek, G., Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Ohta, H., Oliveira, A. S., Oliveri, R., Oloworaran, V., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pai, S. A., Pal, A., Pal, S., Palaia, M. A., Palashov, O., Pálfi, M., Palma, P. P., Palomba, C., Pan, K. C., Panda, P. K., Panebianco, L., Pang, P. T. H., Pannarale, F., Pant, B. C., Panther, F. H., Panzer, C. D., Paoletti, F., Paoli, A., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Parisi, A., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patane, O., Patel, M., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, A., Perez, J. J., Périgois, C., Perkins, C. C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pineda-Bosque, C., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Portell, J., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Pullin, J., Punturo, M., Puosi, F., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, D. S., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Randel, E., Ranjan, S., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Revenu, B., Reza, A., Rezac, M., Rezaei, A. S., Ricci, F., Ricci, M., Richards, D., Richardson, C. J., Richardson, J. W., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Rittmeyer, J., Robertson, C., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romanelli, M., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S. K., Roy, S., Rozza, D., Ruggi, P., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Sah, M. R., Saha, S. S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sako, T., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Saravanan, T. R., Sarin, N., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, S., Sato, Y., Sauter, O., Savage, R. L., Sawada, T., Sawant, H. L., Sayah, S., Schaetzl, D., Scheel, M., Scheuer, J., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schouteden, K., Schuler, H., Schulte, B. W., Schutz, B. F., Schwartz, E., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Sergeev, A., Serra, M., Servignat, G., Setyawati, Y., Shaffer, T., Shah, U. S., Shahriar, M. S., Shaikh, M. A., Shams, B., Shao, L., Sharma, A. K., Sharma, P., Sharma-Chaudhary, S., Shawhan, P., Shcheblanov, N. S., Shen, B., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Smith, W. J., Soldateschi, J., Somala, S. N., Somiya, K., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Southgate, A., Sowell, E., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Strang, L. C., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Sullivan, A. G., Sullivan, K. D., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takatani, K., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tanasijczuk, A. J., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trani, A. A., Trapananti, A., Travasso, F., Traylor, G., Trenado, J., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Ubhi, A. S., Uchikata, N., Uchiyama, T., Udall, R. P., Uehara, T., Ueno, K., Unnikrishnan, C. S., Ushiba, T., Utina, A., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, D., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, L. -C., Yang, Y., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhong, S., Zhou, R., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables
Published: 2024

47. A Practical Guide to Transcranial Ultrasonic Stimulation from the IFCN-endorsed ITRUSST Consortium

Author: Murphy, Keith R, Nandi, Tulika, Kop, Benjamin, Osada, Takahiro, N'Djin, W Apoutou, Lueckel, Maximilian, Caulfield, Kevin A, Fomenko, Anton, Siebner, Hartwig R, Ugawa, Yoshikazu, Verhagen, Lennart, Bestmann, Sven, Martin, Eleanor, Pauly, Kim Butts, Fouragnan, Elsa, and Bergmann, Til Ole
Subjects: Physics - Medical Physics, Physics - Biological Physics
Abstract: Low-intensity Transcranial Ultrasonic Stimulation (TUS) is a non-invasive brain stimulation technique enabling cortical and deep brain targeting with unprecedented spatial accuracy. Given the high rate of adoption by new users with varying levels of expertise and interdisciplinary backgrounds, practical guidelines are needed to ensure state-of-the-art TUS application and reproducible outcomes. Therefore, the International Transcranial Ultrasonic Stimulation Safety and Standards (ITRUSST) consortium has formed a subcommittee, endorsed by the International Federation of Clinical Neurophysiology (IFCN), to develop recommendations for best practice in TUS applications in humans. The practical guide presented here provides a brief introduction into ultrasound physics and sonication parameters. It explains the requirements of TUS lab equipment and transducer selection and discusses experimental design and procedures alongside potential confounds and control conditions. Finally, the guide elaborates on essential steps of application planning for stimulation safety and efficacy, as well as considerations when combining TUS with neuroimaging, electrophysiology, or other brain stimulation techniques. We hope that this practical guide to TUS will assist both novice and experienced users in planning and conducting high-quality studies and provide a solid foundation for further advancements in this promising field., Comment: 66 pages, 23 Figures, 2 Tables, 5 Supplementary Tables
Published: 2024

48. Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge

Author: Yenamandra, Sriram, Ramachandran, Arun, Khanna, Mukul, Yadav, Karmesh, Vakil, Jay, Melnik, Andrew, Büttner, Michael, Harz, Leon, Brown, Lyon, Nandi, Gora Chand, PS, Arjun, Yadav, Gaurav Kumar, Kala, Rahul, Haschke, Robert, Luo, Yang, Zhu, Jinxin, Han, Yansen, Lu, Bingyi, Gu, Xuan, Liu, Qinyuan, Zhao, Yaping, Ye, Qiting, Dou, Chenxiao, Chua, Yansong, Kuzma, Volodymyr, Humennyy, Vladyslav, Partsey, Ruslan, Francis, Jonathan, Chaplot, Devendra Singh, Chhablani, Gunjan, Clegg, Alexander, Gervet, Theophile, Jain, Vidhi, Ramrakhya, Ram, Szot, Andrew, Wang, Austin, Yang, Tsung-Yen, Edsinger, Aaron, Kemp, Charlie, Shah, Binit, Kira, Zsolt, Batra, Dhruv, Mottaghi, Roozbeh, Bisk, Yonatan, and Paxton, Chris
Subjects: Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract: In order to develop robots that can effectively serve as versatile and capable home assistants, it is crucial for them to reliably perceive and interact with a wide variety of objects across diverse environments. To this end, we proposed Open Vocabulary Mobile Manipulation as a key benchmark task for robotics: finding any object in a novel environment and placing it on any receptacle surface within that environment. We organized a NeurIPS 2023 competition featuring both simulation and real-world components to evaluate solutions to this task. Our baselines on the most challenging version of this task, using real perception in simulation, achieved only an 0.8% success rate; by the end of the competition, the best participants achieved an 10.8\% success rate, a 13x improvement. We observed that the most successful teams employed a variety of methods, yet two common threads emerged among the best solutions: enhancing error detection and recovery, and improving the integration of perception with decision-making processes. In this paper, we detail the results and methodologies used, both in simulation and real-world settings. We discuss the lessons learned and their implications for future research. Additionally, we compare performance in real and simulated environments, emphasizing the necessity for robust generalization to novel settings.
Published: 2024

49. Using Photoplethysmography to Detect Real-time Blood Pressure Changes with a Calibration-free Deep Learning Model

Author: Hong, Jingyuan, Nandi, Manasi, Jin, Weiwei, and Alastruey, Jordi
Subjects: Electrical Engineering and Systems Science - Signal Processing
Abstract: Blood pressure (BP) changes are linked to individual health status in both clinical and non-clinical settings. This study developed a deep learning model to classify systolic (SBP), diastolic (DBP), and mean (MBP) BP changes using photoplethysmography (PPG) waveforms. Data from the Vital Signs Database (VitalDB) comprising 1,005 ICU patients with synchronized PPG and BP recordings was used. BP changes were categorized into three labels: Spike (increase above a threshold), Stable (change within a plus or minus threshold), and Dip (decrease below a threshold). Four time-series classification models were studied: multi-layer perceptron, convolutional neural network, residual network, and Encoder. A subset of 500 patients was randomly selected for training and validation, ensuring a uniform distribution across BP change labels. Two test datasets were compiled: Test-I (n=500) with a uniform distribution selection process, and Test-II (n=5) without. The study also explored the impact of including second-deviation PPG (sdPPG) waveforms as additional input information. The Encoder model with a Softmax weighting process using both PPG and sdPPG waveforms achieved the highest detection accuracy--exceeding 71.3% and 85.4% in Test-I and Test-II, respectively, with thresholds of 30 mmHg for SBP, 15 mmHg for DBP, and 20 mmHg for MBP. Corresponding F1-scores were over 71.8% and 88.5%. These findings confirm that PPG waveforms are effective for real-time monitoring of BP changes in ICU settings and suggest potential for broader applications., Comment: 8 pages, 5 figures, 7 tables, 1 supplementary material
Published: 2024

50. Simple Augmentations of Logical Rules for Neuro-Symbolic Knowledge Graph Completion

Author: Nandi, Ananjan, Kaur, Navdeep, Singla, Parag, and Mausam
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Information Retrieval
Abstract: High-quality and high-coverage rule sets are imperative to the success of Neuro-Symbolic Knowledge Graph Completion (NS-KGC) models, because they form the basis of all symbolic inferences. Recent literature builds neural models for generating rule sets, however, preliminary experiments show that they struggle with maintaining high coverage. In this work, we suggest three simple augmentations to existing rule sets: (1) transforming rules to their abductive forms, (2) generating equivalent rules that use inverse forms of constituent relations and (3) random walks that propose new rules. Finally, we prune potentially low quality rules. Experiments over four datasets and five ruleset-baseline settings suggest that these simple augmentations consistently improve results, and obtain up to 7.1 pt MRR and 8.5 pt Hits@1 gains over using rules without augmentations., Comment: 12 pages, 15 tables Published in ACL 2023
Published: 2024
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