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4,902 results on '"More P"'

61. Ensemble approach for fake news classification using machine learning

Author

Pogul Gopi, Rohokhale Sankei, More Priya, and Chavan Pallavi

Subjects
Information technology, T58.5-58.64
Abstract

During the covid 19 outbreak, fake news has grown highly, affecting people’s mental and physical health. There is a wide range of solutions for fake news classification which are machine learning-based proposed models. Research shows that the existing proposed models have less accuracy, and they are only text-based models. In our research paper, we are focused on different algorithms, and we are comparing these algorithms in our proposed model in this research paper. We are considering the title author and text in the proposed model. Based on our experiments, Logistic Regression has high accuracy, recall, and precision score values. This research paper suggests using a logistic regression model to classify fake news.

Published
2022
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63. Upgrading the GRAVITY fringe tracker for GRAVITY+: Tracking the white light fringe in the non-observable Optical Path Length state-space

Author

Nowak, M., Lacour, S., Abuter, R., Woillez, J., Dembet, R., Bordoni, M. S., Bourdarot, G., Courtney-Barrer, B., Defrère, D., Drescher, A., Eisenhauer, F., Fabricius, M., Feuchtgruber, H., Frahm, R., Garcia, P., Gillessen, S., Gopinath, V., Graf, J., Hoenig, S., Kreidberg, L., Laugier, R., Bouquin, J. B. Le, Lutz, D., Mang, F., Millour, F., More, N., Morujão, N., Ott, T., Paumard, T., Perrin, G., Rau, C., Ribeiro, D. C., Shangguan, J., Shimizu, T., Soulez, F., Straubmeier, C., Widmann, F., and Wolff, B.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Aims. As part of the ongoing GRAVITY+ upgrade of the Very Large Telescope Interferometer infrastructure, we aim to improve the performance of the GRAVITY Fringe-Tracker, and to enable its use by other instruments. Methods. We modify the group delay controller to consistently maintain tracking in the white light fringe, characterised by a minimum group delay. Additionally, we introduce a novel approach in which fringe-tracking is performed in the non-observable Optical Path Length state-space, using a covariance-weighted Kalman filter and an auto-regressive model of the disturbance. We outline this new state-space representation, and the formalism we use to propagate the state-vector and generate the control signal. While our approach is presented specifically in the context of GRAVITY/GRAVITY+, it can easily be adapted to other instruments or interferometric facilities. Results. We successfully demonstrate phase delay tracking within a single fringe, with any spurious phase jumps detected and corrected in less than 100 ms. We also report a significant performance improvement, as evidenced by a reduction of about 30 to 40% in phase residuals, and a much better behaviour under sub-optimal atmospheric conditions. Compared to what was observed in 2019, the median residuals have decreased from 150 nm to 100 nm on the Auxiliary Telescopes and from 250 nm to 150 nm on the Unit Telescopes. Conclusions. The improved phase-delay tracking combined with whit light fringe tracking means that from now-on, the GRAVITY Fringe-Tracker can be used by other instruments operating in different wavebands. The only limitation remains the need for an optical path dispersion adjustment., Comment: 16 pages, 8 figures. Accepted for publication in A&A

Published
2024

64. Efficient Causal Graph Discovery Using Large Language Models

Author

Jiralerspong, Thomas, Chen, Xiaoyin, More, Yash, Shah, Vedant, and Bengio, Yoshua

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Methodology
Abstract

We propose a novel framework that leverages LLMs for full causal graph discovery. While previous LLM-based methods have used a pairwise query approach, this requires a quadratic number of queries which quickly becomes impractical for larger causal graphs. In contrast, the proposed framework uses a breadth-first search (BFS) approach which allows it to use only a linear number of queries. We also show that the proposed method can easily incorporate observational data when available, to improve performance. In addition to being more time and data-efficient, the proposed framework achieves state-of-the-art results on real-world causal graphs of varying sizes. The results demonstrate the effectiveness and efficiency of the proposed method in discovering causal relationships, showcasing its potential for broad applicability in causal graph discovery tasks across different domains.

Published
2024

65. Identifying noise transients in gravitational-wave data arising from nonlinear couplings

Author

Hall, Bernard, Suyamprakasam, Sudhagar, Mazumder, Nairwita, More, Anupreeta, and Bose, Sukanta

Subjects
General Relativity and Quantum Cosmology, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Data Analysis, Statistics and Probability
Abstract

Noise in various interferometer systems can sometimes couple non-linearly to create excess noise in the gravitational wave (GW) strain data. Third-order statistics, such as bicoherence and biphase, can identify these couplings and help discriminate those occurrences from astrophysical GW signals. However, the conventional analysis can yield large bicoherence values even when no phase-coupling is present, thereby, resulting in false identifications. Introducing artificial phase randomization in computing the bicoherence reduces such occurrences with negligible impact on its effectiveness for detecting true phase-coupled disturbances. We demonstrate this property with simulated disturbances in this work. Statistical hypothesis testing is used for distinguishing phase-coupled disturbances from non-phase coupled ones when employing the phase-randomized bicoherence. We also obtain an expression for the bicoherence value that minimizes the sum of the probabilities of false positives and false negatives. This can be chosen as a threshold for shortlisting bicoherence triggers for further scrutiny for the presence of non-linear coupling. Finally, the utility of the phase-randomized bicoherence analysis in GW time-series data is demonstrated for the following three scenarios: (1) Finding third-order statistical similarities within categories of noise transients, such as blips and koi fish. If these non-Gaussian noise transients, or glitches, have a common source, their bicoherence maps can have similarities arising from common bifrequencies related to that source. (2) Differentiating linear or non-linear phase-coupled glitches from compact binary coalescence signals through their bicoherence maps. This is explained with a simulated signal. (3) Identifying repeated bifrequencies in the second and third observation runs (i.e., O2 and O3) of LIGO and Virgo., Comment: 25 Pages, 10 figures. Reviewed by LIGO Scientific Collaboration (LSC) with LIGO Document Number P2200344

Published
2024

66. A dynamical measure of the black hole mass in a quasar 11 billion years ago

Author

Abuter, R., Allouche, F., Amorim, A., Bailet, C., Berdeu, A., Berger, J. -P., Berio, P., Bigioli, A., Boebion, O., Bolzer, M. -L., Bonnet, H., Bourdarot, G., Bourget, P., Brandner, W., Cao, Y., Conzelmann, R., Comin, M., Clénet, Y., Courtney-Barrer, B., Davies, R., Defrère, D., Delboulbé, A., Delplancke-Ströbele, F., Dembet, R., Dexter, J., de Zeeuw, P. T., Drescher, A., Eckart, A., Édouard, C., Eisenhauer, F., Fabricius, M., Feuchtgruber, H., Finger, G., Schreiber, N. M. Förster, Garcia, P., Lopez, R. Garcia, Gao, F., Gendron, E., Genzel, R., Gil, J. P., Gillessen, S., Gomes, T., Gonté, F., Gouvret, C., Guajardo, P., Guieu, S., Hackenberg, W., Haddad, N., Hartl, M., Haubois, X., Haußmann, F., Heißel, G., Henning, Th., Hippler, S., Hönig, S. F., Horrobin, M., Hubin, N., Jacqmart, E., Jocou, L., Kaufer, A., Kervella, P., Kolb, J., Korhonen, H., Lacour, S., Lagarde, S., Lai, O., Lapeyrère, V., Laugier, R., Bouquin, J. -B. Le, Leftley, J., Léna, P., Lewis, S., Liu, D., Lopez, B., Lutz, D., Magnard, Y., Mang, F., Marcotto, A., Maurel, D., Mérand, A., Millour, F., More, N., Netzer, H., Nowacki, H., Nowak, M., Oberti, S., Ott, T., Pallanca, L., Paumard, T., Perraut, K., Perrin, G., Petrov, R., Pfuhl, O., Pourré, N., Rabien, S., Rau, C., Riquelme, M., Robbe-Dubois, S., Rochat, S., Salman, M., Sanchez-Bermudez, J., Santos, D. J. D., Scheithauer, S., Schöller, M., Schubert, J., Schuhler, N., Shangguan, J., Shchekaturov, P., Shimizu, T. T., Sevin, A., Soulez, F., Spang, A., Stadler, E., Sternberg, A., Straubmeier, C., Sturm, E., Sykes, C., Tacconi, L. J., Tristram, K. R. W., Vincent, F., von Fellenberg, S., Uysal, S., Widmann, F., Wieprecht, E., Wiezorrek, E., Woillez, J., and Zins, G.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Tight relationships exist in the local universe between the central stellar properties of galaxies and the mass of their supermassive black hole. These suggest galaxies and black holes co-evolve, with the main regulation mechanism being energetic feedback from accretion onto the black hole during its quasar phase. A crucial question is how the relationship between black holes and galaxies evolves with time; a key epoch to probe this relationship is at the peaks of star formation and black hole growth 8-12 billion years ago (redshifts 1-3). Here we report a dynamical measurement of the mass of the black hole in a luminous quasar at a redshift of 2, with a look back time of 11 billion years, by spatially resolving the broad line region. We detect a 40 micro-arcsecond (0.31 pc) spatial offset between the red and blue photocenters of the H$\alpha$ line that traces the velocity gradient of a rotating broad line region. The flux and differential phase spectra are well reproduced by a thick, moderately inclined disk of gas clouds within the sphere of influence of a central black hole with a mass of 3.2x10$^{8}$ solar masses. Molecular gas data reveal a dynamical mass for the host galaxy of 6x10$^{11}$ solar masses, which indicates an under-massive black hole accreting at a super-Eddington rate. This suggests a host galaxy that grew faster than the supermassive black hole, indicating a delay between galaxy and black hole formation for some systems., Comment: 5 pages Main text, 8 figures, 2 tables, to be published in Nature, under embargo until 29 January 2024 16:00 (London)

Published
2024
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67. A Double-Humanized Mouse Model for Studying Host Gut Microbiome-Immune Interactions in Gulf War Illness.

Author

Bose, Dipro, Saha, Punnag, Roy, Subhajit, Trivedi, Ayushi, More, Madhura, Klimas, Nancy, Tuteja, Ashok, and Chatterjee, Saurabh

Subjects
IL-6, NSG, TNF R-1, bacteriome, gut–immune axis, humanized mice, Animals, Gastrointestinal Microbiome, Persian Gulf Syndrome, Humans, Mice, Disease Models, Animal, Cytokines, Fecal Microbiota Transplantation
Abstract

Unraveling the multisymptomatic Gulf War Illness (GWI) pathology and finding an effective cure have eluded researchers for decades. The chronic symptom persistence and limitations for studying the etiologies in mouse models that differ significantly from those in humans pose challenges for drug discovery and finding effective therapeutic regimens. The GWI exposome differs significantly in the study cohorts, and the above makes it difficult to recreate a model closely resembling the GWI symptom pathology. We have used a double engraftment strategy for reconstituting a human immune system coupled with human microbiome transfer to create a humanized-mouse model for GWI. Using whole-genome shotgun sequencing and blood immune cytokine enzyme linked immunosorbent assay (ELISA), we show that our double humanized mice treated with Gulf War (GW) chemicals show significantly altered gut microbiomes, similar to those reported in a Veteran cohort of GWI. The results also showed similar cytokine profiles, such as increased levels of IL-1β, IL-6, and TNF R-1, in the double humanized model, as found previously in a human cohort. Further, a novel GWI Veteran fecal microbiota transfer was used to create a second alternative model that closely resembled the microbiome and immune-system-associated pathology of a GWI Veteran. A GWI Veteran microbiota transplant in humanized mice showed a human microbiome reconstitution and a systemic inflammatory pathology, as reflected by increases in interleukins 1β, 6, 8 (IL-1β, IL-6, IL-8), tumor necrosis factor receptor 1 (TNF R-1), and endotoxemia. In conclusion, though preliminary, we report a novel in vivo model with a human microbiome reconstitution and an engrafted human immune phenotype that may help to better understand gut-immune interactions in GWI.

Published
2024

68. Periodic heat waves-induced neuronal etiology in the elderly is mediated by gut-liver-brain axis: a transcriptome profiling approach.

Author

Roy, Subhajit, Bose, Dipro, Trivedi, Ayushi, More, Madhura, Lin, Christina, Wu, Jie, Oakes, Melanie, Chatterjee, Saurabh, and Saha, Punnag

Subjects
Climate change, Gut-liver-brain axis, Human health, Hyperthermia, ORM2, RANTES, Animals, Mice, Liver, Brain, Gene Expression Profiling, Male, Transcriptome, Brain-Gut Axis, Heat-Shock Response, Mice, Inbred C57BL, Signal Transduction, Aging
Abstract

Heat stress exposure in intermittent heat waves and subsequent exposure during war theaters pose a clinical challenge that can lead to multi-organ dysfunction and long-term complications in the elderly. Using an aged mouse model and high-throughput sequencing, this study investigated the molecular dynamics of the liver-brain connection during heat stress exposure. Distinctive gene expression patterns induced by periodic heat stress emerged in both brain and liver tissues. An altered transcriptome profile showed heat stress-induced altered acute phase response pathways, causing neural, hepatic, and systemic inflammation and impaired synaptic plasticity. Results also demonstrated that proinflammatory molecules such as S100B, IL-17, IL-33, and neurological disease signaling pathways were upregulated, while protective pathways like aryl hydrocarbon receptor signaling were downregulated. In parallel, Rantes, IRF7, NOD1/2, TREM1, and hepatic injury signaling pathways were upregulated. Furthermore, current research identified Orosomucoid 2 (ORM2) in the liver as one of the mediators of the liver-brain axis due to heat exposure. In conclusion, the transcriptome profiling in elderly heat-stressed mice revealed a coordinated network of liver-brain axis pathways with increased hepatic ORM2 secretion, possibly due to gut inflammation and dysbiosis. The above secretion of ORM2 may impact the brain through a leaky blood-brain barrier, thus emphasizing intricate multi-organ crosstalk.

Published
2024

69. Bayesian framework to infer the Hubble constant from cross-correlation of individual gravitational wave events with galaxies

Author

Ghosh, Tathagata, More, Surhud, Bera, Sayantani, and Bose, Sukanta

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract

Gravitational waves (GW) from the inspiral of binary compact objects offers a one-step measurement of the luminosity distance to the event, which is essential for the measurement of the Hubble constant, $H_0$, that characterizes the expansion rate of the Universe. However, unlike binary neutron stars, the inspiral of binary black holes is not expected to be accompanied by electromagnetic radiation and a subsequent determination of its redshift. Consequently, independent redshift measurements of such GW events are necessary to measure $H_0$. In this study, we present a novel Bayesian approach to infer $H_0$ from the cross-correlation between galaxies with known redshifts and individual binary black hole merger events. We demonstrate the efficacy of our method with $250$ simulated GW events distributed within $1$ Gpc in colored Gaussian noise of Advanced LIGO and Advanced Virgo detectors operating at O4 sensitivity. We show that such measurements can constrain the Hubble constant with a precision of $\lesssim 15 \%$ ($90\%$ highest density interval). We highlight the potential improvements that need to be accounted for in further studies before the method can be applied to real data., Comment: 12 pages, 5 figures, 1 table

Published
2023

70. Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI) $-$ X. Strong Lens Finding in The HSC-SSP using Convolutional Neural Networks

Author

Jaelani, Anton T., More, Anupreeta, Wong, Kenneth C., Inoue, Kaiki T., Chao, Dani C. -Y., Premadi, Premana W., and Cañameras, Raoul

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

We apply a novel model based on convolutional neural networks (CNNs) to identify gravitationally-lensed galaxies in multi-band imaging of the Hyper Suprime Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2 350 061 galaxies selected from the $\sim$ 800 deg$^2$ Wide area of the HSC-SSP Public Data Release 2. The galaxies in HSC Wide are selected based on stringent pre-selection criteria, such as multiband magnitudes, stellar mass, star formation rate, extendedness limit, photometric redshift range, etc. Initially, the CNNs provide a total of 20 241 cutouts with a score greater than 0.9, but this number is subsequently reduced to 1 522 cutouts by removing definite non-lenses for further inspection by human eyes. We discover 43 definite and 269 probable lenses, of which 97 are completely new. In addition, out of 880 potential lenses, we recovered 289 known systems in the literature. We identify 143 candidates from the known systems that had higher confidence in previous searches. Our model can also recover 285 candidate galaxy-scale lenses from the Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI), where a single foreground galaxy acts as the deflector. Even though group-scale and cluster-scale lens systems were not included in the training, a sample of 32 SuGOHI-c (i.e., group/cluster-scale systems) lens candidates was retrieved. Our discoveries will be useful for ongoing and planned spectroscopic surveys, such as the Subaru Prime Focus Spectrograph project, to measure lens and source redshifts in order to enable detailed lens modelling., Comment: Submitted to MNRAS, 16 pages, 13 figures. Comments welcome

Published
2023

71. Over-abundance of orphan galaxies in the UniverseMachine

Author

Kumar, Amit, More, Surhud, and Sunayama, Tomomi

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Orphan galaxies that have lost a large fraction of the dark matter subhaloes have often been invoked in semi-analytical as well as empirical models of galaxy formation. We run a mock cluster finder that mimics the optical cluster finding technique of the redMaPPer algorithm on a catalogue of galaxies with quenched star formation from one such empirical model, the UniverseMachine, and obtain the prevalence of orphan galaxies in these clusters as a function of their cluster-centric distance. We compare the fraction of orphan galaxies with the upper limits derived based on our prior observations of the weak lensing signals around satellite galaxies from SDSS redMaPPer clusters. Although the orphan fraction from the UniverseMachine is marginally consistent with the upper limits in the innermost regions of galaxy clusters spanning [0.1, 0.3] $h^{-1}$ Mpc, we observe that the orphan fractions substantially violate the upper limits in the outer regions of galaxy clusters beyond 0.3 $h^{-1}$ Mpc. We discuss the reasons, plausible improvements to the model and how observations can be used to constrain such models further., Comment: 6 pages, 5 figures

Published
2023

72. Synergistic locoregional chemoradiotherapy using a composite liposome-in-gel system as an injectable drug depot

Author

GuhaSarkar S, Pathak K, Sudhalkar N, More P, Goda JS, Gota V, and Banerjee R

Subjects
Liposome, radiosensitizer, chemoradiotherapy, hydrogel, regional drug delivery, Medicine (General), R5-920
Abstract

Shruti GuhaSarkar,1 Kamal Pathak,2 Niyati Sudhalkar,3 Prachi More,1 Jayant Sastri Goda,3 Vikram Gota,2 Rinti Banerjee1 1Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, 2Department of Clinical Pharmacology, 3Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer, Navi Mumbai, Maharashtra, India Abstract: The use of radiosensitizers in clinical radiotherapy is limited by systemic toxicity. The biopolymeric, biodegradable, injectable liposome-in-gel-paclitaxel (LG-PTX) system was developed for regional delivery of the radiosensitizer paclitaxel (PTX), and its efficacy was evaluated with concurrent fractionated radiation. LG-PTX is composed of nano-sized drug-loaded fluidizing liposomes, which are incorporated into a porous biodegradable gellan hydrogel. This allows enhanced drug permeation while maintaining a localization of the drug depot. LG-PTX had an IC50 of 325±117 nM in B16F10 melanoma cells, and cytotoxicity with concurrent doses of fractionated radiation showed significant increase in apoptotic cells (75%) compared to radiation (39%) or LG-PTX (43%) alone. Peri-tumoral injection in tumor-bearing mice showed PTX localization in the tumor 2 hours after administration, with no drug detected in plasma or other organs. LG-PTX administration with doses of focal radiation (5×3 Gy) significantly reduced tumor volumes compared to control (6.4 times) and radiation alone (1.6 times) and improved animal survival. LG-PTX thus efficiently localizes the drug at the tumor site and synergistically enhances the effect of concurrent radiotherapy. This novel liposome-in-gel system can potentially be used as a platform technology for the delivery of radiosensitizing drugs to enhance the efficacy of chemoradiotherapy. Keywords: radiosensitizer, hydrogel, regional drug delivery, concurrent radiotherapy, lipid nanocarrier

Published
2016

73. Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Author

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abe, H., 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., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Almualla, M., Altin, P. A., Álvarez-López, S., Amato, A., Amez-Droz, L., Amorosi, A., Anand, S., Ananyeva, A., Andersen, R., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Apostolatos, T., 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., Arun, K. G., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badalyan, A., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barber, J., 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., 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., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boër, M., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonnand, R., Booker, P., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., 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., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Cain III, H. W., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chalathadka-Subrahmanya, S., Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, I. P., Chang, R. -J., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chastain, L., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, X., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., 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., 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., Cowburn, B. D., Coyne, D. C., Coyne, R., Craig, K., Creighton, J. D. E., Creighton, T. D., 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., Curyło, M., 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., Darsow-Fromm, C., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Dave, I., Davenport, A., Davier, M., Davis, D., Davis, M. C., Daw, E. J., Dax, M., 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., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhurandhar, S., Diab, R., Diamond, P. Z., Díaz, M. C., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Lieto, A., 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. 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J., Scheuer, J., Schiworski, M. G., Schmidt, P., Schmidt, S., Schmitz, S. J., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schönbeck, A., 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., Servignat, G., Setyawati, Y., Shaffer, T., Shahriar, M. S., Shaikh, M. A., Shams, B., Shao, L., Sharma, P., Sharma-Chaudhary, S., Shawhan, P., Shcheblanov, N. S., Sheela, A., Shen, B., Shepard, K. G., 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., Soldateschi, J., Somala, S. N., Somiya, K., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Sowell, E., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Srivastava, A. K., Srivastava, V., Stachie, C., 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., Suh, H. G., Sullivan, A. G., Summerscales, T. Z., 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., Tanioka, S., Tanner, D. B., Tao, D., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Terkowski, L., Themann, H., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toivonen, A. M., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tonelli, M., Toriyama, A., 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., Tse, M., 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., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., 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., 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., Venneberg, J., Verdier, P., Verkindt, D., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Veutro, A., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, 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., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watada, K., 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., Williamson, A. R., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wong, D., Wong, H. T., Wong, I. C. F., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yang, F. W., Yang, K. Z., Yang, L. -C., Yang, Y. -C., Yang, Yang, Yang, Yi, Yap, M. J., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yeung, T. Y., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Yanqi, Zhang, Ya, Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level., Comment: 24 pages, 5 figures

Published
2023

89. A Bayesian Approach to Strong Lens Finding in the Era of Wide-area Surveys

Author

Holloway, Philip, Marshall, Philip J., Verma, Aprajita, More, Anupreeta, Cañameras, Raoul, Jaelani, Anton T., Ishida, Yuichiro, and Wong, Kenneth C.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The arrival of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), Euclid-Wide and Roman wide area sensitive surveys will herald a new era in strong lens science in which the number of strong lenses known is expected to rise from $\mathcal{O}(10^3)$ to $\mathcal{O}(10^5)$. However, current lens-finding methods still require time-consuming follow-up visual inspection by strong-lens experts to remove false positives which is only set to increase with these surveys. In this work we demonstrate a range of methods to produce calibrated probabilities to help determine the veracity of any given lens candidate. To do this we use the classifications from citizen science and multiple neural networks for galaxies selected from the Hyper Suprime-Cam (HSC) survey. Our methodology is not restricted to particular classifier types and could be applied to any strong lens classifier which produces quantitative scores. Using these calibrated probabilities, we generate an ensemble classifier, combining citizen science and neural network lens finders. We find such an ensemble can provide improved classification over the individual classifiers. We find a false positive rate of $10^{-3}$ can be achieved with a completeness of $46\%$, compared to $34\%$ for the best individual classifier. Given the large number of galaxy-galaxy strong lenses anticipated in LSST, such improvement would still produce significant numbers of false positives, in which case using calibrated probabilities will be essential for population analysis of large populations of lenses., Comment: 14 pages, 9 figures. Accepted for publication in MNRAS

Published
2023
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90. 4x2 Hot electron bolometer mixer arrays for detection at 1.46, 1.9 and 4.7 THz for a balloon borne terahertz observatory

Author

Silva, José R. G., Laauwen, Wouter M., Mirzaei, Behnam, Vercruyssen, Nathan, Finkel, Matvey, Westerveld, Menno, More, Nikhil, Silva, Vitor, Young, Abram, Kulesa, Craig, Walker, Christopher, van der Tak, Floris, and Gao, Jian Rong

Subjects
Physics - Instrumentation and Detectors
Abstract

We have demonstrated three 4x2 hot electron bolometer (HEB) mixer arrays for operation at local oscillator (LO) frequencies of 1.46, 1.9 and 4.7 THz, respectively. They consist of spiral antenna coupled NbN HEB mixers combined with elliptical lenses. These are to date the highest pixel count arrays using a quasi-optical coupling scheme at supra-THz frequencies. At 1.4 THz, we measured an average double sideband mixer noise temperature of 330 K, a mixer conversion loss of 5.7 dB, and an optimum LO power of 210 nW. The array at 1.9 THz has an average mixer noise temperature of 420K, a conversion loss of 6.9 dB, and an optimum LO power of 190 nW. For the array at 4.7 THz, we obtained an average mixer noise temperature of 700 K, a conversion loss of 9.7 dB, and an optimum LO power of 240 nW. We found the arrays to be uniform regarding the mixer noise temperature with a standard deviation of 3-4%, the conversion loss with a standard deviation of 7-10%, and optimum LO power with a standard deviation of 5-6%. The noise bandwidth was also measured, being 3.5 GHz for the three arrays. These performances are comparable to previously reported values in the literature for single pixels and also other detector arrays. Our arrays meet the requirements of the Galactic/Extra-Galactic ULDB Spectroscopic Terahertz Observatory (GUSTO), a NASA balloon borne observatory, and are therefore scheduled to fly as part of the payload, which is expected to be launched in December 2023.

Published
2023

91. Performance Prediction of Data-Driven Knowledge summarization of High Entropy Alloys (HEAs) literature implementing Natural Language Processing algorithms

Author

Mishra, Akshansh, Jatti, Vijaykumar S, More, Vaishnavi, Dasgupta, Anish, Dixit, Devarrishi, and Sefene, Eyob Messele

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Information Retrieval, Computer Science - Information Theory, Computer Science - Machine Learning
Abstract

The ability to interpret spoken language is connected to natural language processing. It involves teaching the AI how words relate to one another, how they are meant to be used, and in what settings. The goal of natural language processing (NLP) is to get a machine intelligence to process words the same way a human brain does. This enables machine intelligence to interpret, arrange, and comprehend textual data by processing the natural language. The technology can comprehend what is communicated, whether it be through speech or writing because AI pro-cesses language more quickly than humans can. In the present study, five NLP algorithms, namely, Geneism, Sumy, Luhn, Latent Semantic Analysis (LSA), and Kull-back-Liebler (KL) al-gorithm, are implemented for the first time for the knowledge summarization purpose of the High Entropy Alloys (HEAs). The performance prediction of these algorithms is made by using the BLEU score and ROUGE score. The results showed that the Luhn algorithm has the highest accuracy score for the knowledge summarization tasks compared to the other used algorithms.

Published
2023

92. Polarization analysis of the VLTI and GRAVITY

Author

GRAVITY Collaboration, Widmann, F., Schuhler, X. Haubois N., Pfuhl, O., Eisenhauer, F., Gillessen, S., Aimar, N., Amorim, A., Bauböck, M., Berger, J. B., Bonnet, H., Bourdarot, G., Brandner, W., Clénet, Y., Davies, R., de Zeeuw, P. T., Dexter, J., Drescher, A., Eckart, A., Feuchtgruber, H., Schreiber, N. M. Förster, Garcia, P., Gendron, E., Genzel, R., Hartl, M., Haußmann, F., Heißel, G., Henning, T., Hippler, S., Horrobin, M., Jiménez-Rosales, A., Jocou, L., Kaufer, A., Kervella, P., Lacour, S., Lapeyrère, V., Bouquin, J. -B. Le, Léna, P., Lutz, D., Mang, F., More, N., Nowak, M., Ott, T., Paumard, T., Perraut, K., Perrin, G., Rabien, S., Ribeiro, D., Bordoni, M. Sadun, Scheithauer, S., Shangguan, J., Shimizu, T., Stadler, J., Straub, O., Straubmeier, C., Sturm, E., Tacconi, L. J., Vincent, F., von Fellenberg, S. D., Wieprecht, E., Wiezorrek, E., and Woillez, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The goal of this work is to characterize the polarization effects of the VLTI and GRAVITY. This is needed to calibrate polarimetric observations with GRAVITY for instrumental effects and to understand the systematic error introduced to the astrometry due to birefringence when observing targets with a significant intrinsic polarization. By combining a model of the VLTI light path and its mirrors and dedicated experimental data, we construct a full polarization model of the VLTI UTs and the GRAVITY instrument. We first characterize all telescopes together to construct a UT calibration model for polarized targets. We then expand the model to include the differential birefringence. With this, we can constrain the systematic errors for highly polarized targets. Together with this paper, we publish a standalone Python package to calibrate the instrumental effects on polarimetric observations. This enables the community to use GRAVITY to observe targets in a polarimetric observing mode. We demonstrate the calibration model with the galactic center star IRS 16C. For this source, we can constrain the polarization degree to within 0.4 % and the polarization angle within 5 deg while being consistent with the literature. Furthermore, we show that there is no significant contrast loss, even if the science and fringe-tracker targets have significantly different polarization, and we determine that the phase error in such an observation is smaller than 1 deg, corresponding to an astrometric error of 10 {\mu}as. With this work, we enable the use of the polarimetric mode with GRAVITY/UTs and outline the steps necessary to observe and calibrate polarized targets. We demonstrate that it is possible to measure the intrinsic polarization of astrophysical sources with high precision and that polarization effects do not limit astrometric observations of polarized targets., Comment: Accepted by A&A

Published
2023

93. Searching for strong gravitational lenses

Author

Lemon, Cameron, Courbin, Frédéric, More, Anupreeta, Schechter, Paul, Cañameras, Raoul, Delchambre, Ludovic, Leung, Calvin, Shu, Yiping, Spiniello, Chiara, Hezaveh, Yashar, Klüter, Jonas, and McMahon, Richard

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Strong gravitational lenses provide unique laboratories for cosmological and astrophysical investigations, but they must first be discovered - a task that can be met with significant contamination by other astrophysical objects and asterisms. Here we review strong lens searches, covering various sources (quasars, galaxies, supernovae, FRBs, GRBs, and GWs), lenses (early- and late-type galaxies, groups, and clusters), datasets (imaging, spectra, and lightcurves), and wavelengths. We first present the physical characteristics of the lens and source populations, highlighting relevant details for constructing targeted searches. Search techniques are described based on the main lensing feature that is required for the technique to work, namely one of: (i) an associated magnification, (ii) multiple spatially-resolved images, (iii) multiple redshifts, or (iv) a non-zero time delay between images. To use the current lens samples for science, and for the design of future searches, we list several selection biases that exist due to these discovery techniques. We conclude by discussing the future of lens searches in upcoming surveys and the new population of lenses that will be discovered., Comment: 54 pages, 15 figures, submitted to Space Science Reviews, Topical Collection "Strong Gravitational Lensing", eds. J. Wambsganss et al

Published
2023

94. Julearn: an easy-to-use library for leakage-free evaluation and inspection of ML models

Author

Hamdan, Sami, More, Shammi, Sasse, Leonard, Komeyer, Vera, Patil, Kaustubh R., and Raimondo, Federico

Subjects
Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

The fast-paced development of machine learning (ML) methods coupled with its increasing adoption in research poses challenges for researchers without extensive training in ML. In neuroscience, for example, ML can help understand brain-behavior relationships, diagnose diseases, and develop biomarkers using various data sources like magnetic resonance imaging and electroencephalography. The primary objective of ML is to build models that can make accurate predictions on unseen data. Researchers aim to prove the existence of such generalizable models by evaluating performance using techniques such as cross-validation (CV), which uses systematic subsampling to estimate the generalization performance. Choosing a CV scheme and evaluating an ML pipeline can be challenging and, if used improperly, can lead to overestimated results and incorrect interpretations. We created julearn, an open-source Python library, that allow researchers to design and evaluate complex ML pipelines without encountering in common pitfalls. In this manuscript, we present the rationale behind julearn's design, its core features, and showcase three examples of previously-published research projects that can be easily implemented using this novel library. Julearn aims to simplify the entry into the ML world by providing an easy-to-use environment with built in guards against some of the most common ML pitfalls. With its design, unique features and simple interface, it poses as a useful Python-based library for research projects., Comment: 13 pages, 5 figures

Published
2023

95. Elasto-Inertial Instability in Torsional Flows of Shear-Thinning Viscoelastic Fluids

Author

More, Rishabh V., Pashkovski, Eugene, Patterson, Reid, and McKinley, Gareth H.

Subjects
Physics - Fluid Dynamics, Physics - Applied Physics
Abstract

It is well known that inertia-free shearing flows of a viscoelastic fluid with curved streamlines, such as the torsional flow between a rotating cone and plate, or the flow in a Taylor-Couette geometry, can become unstable to a three-dimensional time-dependent instability at conditions exceeding a critical Weissenberg (Wi) number. However, the combined effects of fluid elasticity, shear thinning, and finite inertia (as quantified by the Reynolds number Re) on the onset of elasto-inertial instabilities are not fully understood. Using a set of cone-plate geometries, we experimentally explore the entire Wi - Re phase space for a series of rate-dependent viscoelastic fluids (quantified using a shear thinning parameter $\beta_P$). We tune $\beta_P$ by varying the polymer concentration in solutions. This progressively reduces shear-thinning but leads to finite inertial effects before the onset of elastic instability, thus naturally resulting in elasto-inertial coupling. Transient rheometric measurements and flow visualization experiments allow us to investigate the effects of flow geometry and document the combined effects of varying Wi, Re, and $\beta_P$ on the emergence of secondary motions at the onset of instability. The resulting critical state diagram quantitatively depicts the competition between the stabilizing effects of shear thinning and the destabilizing effects of inertia. We extend the curved streamline instability criterion of Pakdel and McKinley 1996 for the onset of purely elastic instability in curvilinear geometries by using scaling arguments to incorporate shear thinning and finite inertial effects. The augmented condition facilitates predictions of the onset of instability over a broader range of flow conditions, thus bridging the gap between purely elastic and elasto-inertial curved streamline instabilities.

Published
2023

96. Microscaling Data Formats for Deep Learning

Author

Rouhani, Bita Darvish, Zhao, Ritchie, More, Ankit, Hall, Mathew, Khodamoradi, Alireza, Deng, Summer, Choudhary, Dhruv, Cornea, Marius, Dellinger, Eric, Denolf, Kristof, Dusan, Stosic, Elango, Venmugil, Golub, Maximilian, Heinecke, Alexander, James-Roxby, Phil, Jani, Dharmesh, Kolhe, Gaurav, Langhammer, Martin, Li, Ada, Melnick, Levi, Mesmakhosroshahi, Maral, Rodriguez, Andres, Schulte, Michael, Shafipour, Rasoul, Shao, Lei, Siu, Michael, Dubey, Pradeep, Micikevicius, Paulius, Naumov, Maxim, Verrilli, Colin, Wittig, Ralph, Burger, Doug, and Chung, Eric

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Narrow bit-width data formats are key to reducing the computational and storage costs of modern deep learning applications. This paper evaluates Microscaling (MX) data formats that combine a per-block scaling factor with narrow floating-point and integer types for individual elements. MX formats balance the competing needs of hardware efficiency, model accuracy, and user friction. Empirical results on over two dozen benchmarks demonstrate practicality of MX data formats as a drop-in replacement for baseline FP32 for AI inference and training with low user friction. We also show the first instance of training generative language models at sub-8-bit weights, activations, and gradients with minimal accuracy loss and no modifications to the training recipe.

Published
2023

97. Dynamics of heavy quarks in the Fock space

Author

Serafin, Kamil, Gómez-Rocha, María, More, Jai, and Głazek, S. D.

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

This paper concerns a method of describing hadrons that starts with the canonical front form Hamiltonian of QCD. The method is developed in the relatively simple context of QCD with only heavy quarks. We regulate its canonical Hamiltonian by introducing a vanishingly small gluon mass $m_g$. For positive $m_g$, the small-$x$ gluon divergences become ultraviolet and hence they are renormalized in the same way the ultraviolet transverse divergences are. This is done using the renormalization group procedure for effective particles. Up to the second order of expansion of the renormalized Hamiltonian in powers of the quark-gluon coupling constant $g$, only the quark mass-squared and gluon-exchange divergences require counter terms. In these circumstances, we calculate an effective potential between quarks in heavy quarkonia in an elementary way, replacing all the quarkonium-state components with gluons of mass $m_g$ by only one component with just one gluon that is assigned a mass $m_G$, comparable to or exceeding the scale of typical relative momenta of bound quarks. In the limit of $m_g \to 0$ and large $m_G$ two results are obtained. (1) While the color-singlet quarkonium mass eigenvalue stays finite and physically reasonable in that limit, the eigenvalues for single quarks and octet quarkonia are infinite. (2) The effective quark-antiquark potential is quadratic as a function of the distance and spherically symmetric for typical separations between quarks but becomes logarithmic and no longer spherically symmetric for large separations. Our conclusion indicates how to systematically improve upon the approximations made in this paper., Comment: 31 pages, 4 figures

Published
2023

98. Optical Cluster Cosmology with SDSS redMaPPer clusters and HSC-Y3 lensing measurements

Author

Sunayama, Tomomi, Miyatake, Hironao, Sugiyama, Sunao, More, Surhud, Li, Xiangchong, Dalal, Roohi, Rau, Markus Michael, Shi, Jingjing, Chiu, I-Non, Shirasaki, Masato, Zhang, Tianqing, and Nishizawa, Atsushi J.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We present cosmology results obtained from a blind joint analysis of the abundance, projected clustering, and weak lensing of galaxy clusters measured from the Sloan Digital Sky Survey (SDSS) redMaPPer cluster catalog and the Hyper-Suprime Cam (HSC) Year3 shape catalog. We present a full-forward model for the cluster observables, which includes empirical modeling for the anisotropic boosts on the lensing and clustering signals of optical clusters. We validate our analysis via mock cluster catalogs which include observational systematics, such as the projection effect and the effect of baryonic feedback, and find that our analysis can robustly constrain cosmological parameters in an unbiased manner without any informative priors on our model parameters. The joint analysis of our observables in the context of the flat $\Lambda$CDM model results in cosmological constraints for $S_8\equiv \sigma_8 \sqrt{\Omega_{\rm m} / 0.3}=0.816^{+0.041}_{-0.039}$. Our result is consistent with the $S_8$ inference from other cosmic microwave background- and large scale structure-based cosmology analyses, including the result from the \emph{Planck} 2018 primary CMB analysis., Comment: v1: 22 pages, 15 figures, Comments welcome

Published
2023

99. Domain Adaptive Few-Shot Open-Set Learning

Author

Pal, Debabrata, More, Deeptej, Bhargav, Sai, Tamboli, Dipesh, Aggarwal, Vaneet, and Banerjee, Biplab

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Few-shot learning has made impressive strides in addressing the crucial challenges of recognizing unknown samples from novel classes in target query sets and managing visual shifts between domains. However, existing techniques fall short when it comes to identifying target outliers under domain shifts by learning to reject pseudo-outliers from the source domain, resulting in an incomplete solution to both problems. To address these challenges comprehensively, we propose a novel approach called Domain Adaptive Few-Shot Open Set Recognition (DA-FSOS) and introduce a meta-learning-based architecture named DAFOSNET. During training, our model learns a shared and discriminative embedding space while creating a pseudo open-space decision boundary, given a fully-supervised source domain and a label-disjoint few-shot target domain. To enhance data density, we use a pair of conditional adversarial networks with tunable noise variances to augment both domains closed and pseudo-open spaces. Furthermore, we propose a domain-specific batch-normalized class prototypes alignment strategy to align both domains globally while ensuring class-discriminativeness through novel metric objectives. Our training approach ensures that DAFOS-NET can generalize well to new scenarios in the target domain. We present three benchmarks for DA-FSOS based on the Office-Home, mini-ImageNet/CUB, and DomainNet datasets and demonstrate the efficacy of DAFOS-NET through extensive experimentation

Published
2023

100. Identification of Superclusters and their Properties in the Sloan Digital Sky Survey Using WHL Cluster Catalog

Author

Sankhyayan, Shishir, Bagchi, Joydeep, Tempel, Elmo, More, Surhud, Einasto, Maret, Dabhade, Pratik, Raychaudhury, Somak, Athreya, Ramana, and Heinämäki, Pekka

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Superclusters are the largest massive structures in the cosmic web on tens to hundreds of megaparsecs (Mpc) scales. They are the largest assembly of galaxy clusters in the Universe. Apart from a few detailed studies of such structures, their evolutionary mechanism is still an open question. In order to address and answer the relevant questions, a statistically significant, large catalog of superclusters covering a wide range of redshifts and sky areas is essential. Here, we present a large catalog of 662 superclusters identified using a modified $\textit{ Friends of Friends}$ algorithm applied on the WHL (Wen-Han-Liu) cluster catalog within a redshift range of $0.05 \le z \le 0.42$. We name the most massive supercluster at $z \sim 0.25$ as $\textit{Einasto Supercluster}$. We find that the median mass of superclusters is $\sim 5.8 \times 10^{15}$ M$_{\odot}$ and median size $\sim 65$ Mpc. We find that the supercluster environment slightly affects the growth of clusters. We compare the properties of the observed superclusters with the mock superclusters extracted from the Horizon Run 4 cosmological simulation. The properties of superclusters in mocks and observations are in broad agreement. We find that the density contrast of a supercluster is correlated with its maximum extent with a power law index, $\alpha \sim -2$. The phase-space distribution of mock superclusters shows that, on average, $\sim 90\%$ part of a supercluster has a gravitational influence on its constituents. We also show mock halos' average number density and peculiar velocity profiles in and around the superclusters., Comment: 23 pages, 16 figures, and 2 tables. Accepted for publication in ApJ

Published
2023

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