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arXiv 2024年

作者： Joshi, Abhishek V. Prather, Ben S. Chan, Chi-Kwan Wielgus, Maciek Gammie, Charles F. Department of Physics University of Illinois 1110 West Green Street UrbanaIL61801 United States Illinois Center for Advanced Study of the Universe 1110 West Green Street UrbanaIL61801 United States Los Alamos National Lab Los AlamosNM87545 United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Department of Astronomy University of Illinois 1002 West Green Street UrbanaIL61801 United States National Center for Supercomputing Applications 605 East Springfield Avenue ChampaignIL61820 United States

Models of the resolved Event Horizon Telescope (EHT) sources Sgr A* and M87* are constrained by observations at multiple wavelengths, resolutions, polarizations, and time cadences. In this paper we compare unresolved circular polarization (CP) measurements to a library of models, where each model is characterized by a distribution of CP over time. In the library we vary the spin of the black hole, the magnetic field strength at the horizon (i.e. both SANE and MAD models), the observer inclination, a parameter for the maximum ion-electron temperature ratio assuming a thermal plasma, and the direction of the magnetic field dipole moment. We find that ALMA observations of Sgr A* are inconsistent with all edge-on (i = 90◦) models. Restricting attention to the magnetically arrested disk (MAD) models favored by earlier EHT studies of Sgr A*, we find that only models with magnetic dipole moment pointing away from the observer are consistent with ALMA data. We also note that in 26 of the 27 passing MAD models the accretion flow rotates clockwise on the sky. We provide a table of the mean and standard deviation of the CP distributions for all model parameters along with their trends. © 2024, CC BY.

关键词： Stars

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*** - A plug-and-play solution for online systems medicine and network-based drug repurposing

arXiv

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arXiv 2023年

作者： Maier, Andreas Hartung, Michael Abovsky, Mark Adamowicz, Klaudia Bader, Gary D. Baier, Sylvie Blumenthal, David B. Chen, Jing Elkjaer, Maria L. Garcia-Hernandez, Carlos Helmy, Mohamed Hoffmann, Markus Jurisica, Igor Kotlyar, Max Lazareva, Olga Levi, Hagai List, Markus Lobentanzer, Sebastian Loscalzo, Joseph Malod-Dognin, Noel Manz, Quirin Matschinske, Julian Mee, Miles Oubounyt, Mhaned Pico, Alexander R. Pillich, Rudolf T. Poschenrieder, Julian M. Pratt, Dexter Pržulj, Nataša Sadegh, Sepideh Saez-Rodriguez, Julio Sarkar, Suryadipto Shaked, Gideon Shamir, Ron Trummer, Nico Turhan, Ugur Wang, Ruisheng Zolotareva, Olga Baumbach, Jan Institute for Computational Systems Biology University of Hamburg Hamburg Germany Division of Orthopaedic Surgery Schroeder Arthritis Institute Data Science Discovery Centre Osteoarthritis Research Program Krembil Research Institute UHN Toronto Canada Data Science Discovery Centre for Chronic Diseases Krembil Research Institute University Health Network 60 Leonard Avenue 5KD-407 TorontoONM5T 0S8 Canada Department of Molecular Genetics University of Toronto TorontoON Canada The Donnelly Centre University of Toronto TorontoON Canada Department of Computer Science University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada The Lunenfeld-Tanenbaum Research Institute Mount Sinai Hospital TorontoON Canada TUM School of Life Sciences Technical University of Munich Munich Germany Erlangen91052 Germany Department of Medicine University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Neurology Odense University Hospital Odense Denmark Institute of Clinical Research University of Southern Denmark Odense Denmark Institute of Molecular Medicine University of Southern Denmark Odense Denmark Barcelona08034 Spain Institute for Advanced Study Lichtenbergstrasse 2a GarchingD-85748 Germany Technical University of Munich Germany National Institute of Diabetes Digestive and Kidney Diseases BethesdaMD20892 United States Departments of Medical Biophysics and Computer Science University of Toronto Toronto Canada Institute of Neuroimmunology Slovak Academy of Sciences Bratislava Slovakia Heidelberg69120 Germany Heidelberg Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg69117 Germany Blavatnik School of Computer Science Tel-Aviv University Tel-Aviv Israel Heidelberg University Faculty of Medicine Heidelberg University Hospital Institute for Computational Biomedicine Bioquant Heidelberg Germany Department of Medicine Bri

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce ***, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, *** turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, *** has been successfully integrated with 21 computational systems medicine tools. Available at https://***, *** has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research. © 2023, CC BY.

关键词： data visualization

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Search for Majorana Neutrinos with the Complete KamLAND-Zen dataset

arXiv

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arXiv 2024年

作者： Abe, S. Araki, T. Chiba, K. Eda, T. Eizuka, M. Funahashi, Y. Furuto, A. Gando, A. Gando, Y. Goto, S. Hachiya, T. Hata, K. Ichimura, K. Ieki, S. Ikeda, H. Inoue, K. Ishidoshiro, K. Kamei, Y. Kawada, N. Kishimoto, Y. Koga, M. Marthe, A. Matsumoto, Y. Mitsui, T. Miyake, Haruhiko Morita, D. Nakamura, K. Nakamura, R. Nakamura, R. Nakane, J. Ono, T. Ozaki, H. Saito, K. Sakai, T. Shimizu, I. Shirai, J. Shiraishi, K. Suzuki, A. Tachibana, K. Tamae, K. Watanabe, H. Watanabe, K. Yoshida, S. Umehara, S. Fushimi, K. Kotera, K. Urano, Y. Berger, B.E. Fujikawa, B.K. Learned, J.G. Maricic, J. Fu, Z. Ghosh, S. Smolsky, J. Winslow, L.A. Efremenko, Y. Karwowski, H.J. Markoff, D.M. Tornow, W. Dell'Oro, S. Donnell, T.O. Detwiler, J.A. Enomoto, S. Decowski, M.P. Weerman, K.M. Grant, C. Penek, O. Song, H. Li, A. Axani, S.N. Garcia, M. Sarfraz, M. Research Center for Neutrino Science Tohoku University Sendai980-8578 Japan Department of Human Science Obihiro University of Agriculture and Veterinary Medicine Hokkaido Obihiro080-8555 Japan The University of Tokyo Institutes for Advanced Study The University of Tokyo Chiba Kashiwa277-8583 Japan Graduate Program on Physics for the Universe Tohoku University Sendai980-8578 Japan Graduate School of Science Osaka University Toyonaka Osaka560-0043 Japan Research Center for Nuclear Physics Osaka University Osaka Ibaraki567-0047 Japan Department of Physics Tokushima University Tokushima770-8506 Japan Graduate School of Integrated Arts and Sciences Tokushima University Tokushima770-8502 Japan Nuclear Science Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Physics and Astronomy University of Hawaii at Manoa HonoluluHI96822 United States Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics and Astronomy University of Tennessee KnoxvilleTN37996 United States Triangle Universities Nuclear Laboratory DurhamNC27708 United States Physics Departments Duke University DurhamNC27708 United States North Carolina Central University DurhamNC27707 United States The University of North Carolina at Chapel Hill Chapel HillNC27599 United States Center for Neutrino Physics Virginia Polytechnic Institute State University BlacksburgVA24061 United States Center for Experimental Nuclear Physics and Astrophysics University of Washington SeattleWA98195 United States Nikhef The University of Amsterdam Science Park Amsterdam Netherlands Boston University BostonMA02215 United States Halıcıoglu Data Science Institute Department of Physics University of California San Diego La Jolla CA92093 United States Department of Physics and Astronomy University of Delaware NewarkDE19716 United States

We present a search for neutrinoless double-beta (0νββ) decay of 136Xe using the full KamLAND-Zen 800 dataset with 745 kg of enriched xenon, corresponding to an exposure of 2.097 ton yr of 136Xe. This updated search benefits from a more than twofold increase in exposure, recovery of photo-sensor gain, and reduced background from muon-induced spallation of xenon. Combining with the search in the previous KamLAND-Zen phase, we obtain a lower limit for the 0νββ decay half-life of T1/20ν > 3.8 × 1026 yr at 90% C.L., a factor of 1.7 improvement over the previous limit. The corresponding upper limits on the effective Majorana neutrino mass are in the range 28–122 meV using phenomenological nuclear matrix element calculations. © 2024, CC BY.

关键词： Xenon

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Sustainable improvement of food SMEs through halal certification: A meta-analysis

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AIP Conference Proceedings 2024年第1期2957卷

作者： Rizal Bahara Muhammad N. Aidi Khaswar Syamsu Euis Sunarti Anuraga Jayanegara Natural Resources and Environmental Management Science Study Program Graduate School IPB University Jl Pajajaran No 1 Kampus IPB Baranangsiang Bogor West Java 1614 Indonesia Statistics and Data Science Department Mathematics and Natural Science Faculty IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16680 Indonesia Halal Science Center LPPM IPB. Gedung Pascasarjana Gedung Kimia IPB University Jl Pajajaran No 1 Kampus IPB Baranangsiang Bogor West Java 1644 Indonesia Department of Family and Consumer Sciences Faculty of Human Ecology IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16610 Indonesia Department of Nutrition and Feed Technology Faculty of Animal Science IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16680 Indonesia

Small and medium enterprises (SMEs) are one of the important economic drivers in Indonesia, including during the Covid-19 pandemic. Indonesia as the country with the largest Muslim population requires halal certificates for all food products sold in Indonesia. Obstacles to the implementation and certification of halal in the food SME sector are still encountered due to, among others, the cost of certification, knowledge from human resources, ease of access and information. The purpose of this study was to evaluate the role of halal certification on financial performance in Food SMEs by employing the meta-analysis method. A number of six articles out of 55 articles were selected and integrated into a database. The data were analyzed based on the Hedges’ d (standardized mean difference/SMD) effect size values and confidence interval (CI) values by using the Open MEE software. The results showed that halal-certified food SMEs significantly increased sales (SMD: 3.182; 95% CI:1.228 to 5.136; p<0.001) as compared to those of food SMEs that were not halal-certified. In the location in the Indonesia subgroup, halal certification at Food SMEs in Bogor city had a higher sale (SMD: 12.105; 95% CI: 10.289 to 13.922; p<0.001) compared to other cities. The conclusion of this study is that halal certification enhances sales and thus contributes to the sustainability of food SMEs.

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A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Taufik Budhi Pramono R Ardharyan Islamy Saprudin Joni Johanda Putra Teddy Suparyanto Kartika Purwandari Tjeng Wawan Cenggoro Bens Pardamean Aquaculture Study Program Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Aquatic Resources Management Brawijaya University Malang East Java Indonesia Graduate Program Aquatic Resources Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

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Brightness asymmetry of black hole images as a probe of observer inclination

arXiv

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arXiv 2021年

作者： Medeiros, Lia Chan, Chi-Kwan Narayan, Ramesh Özel, Feryal Psaltis, Dimitrios School of Natural Sciences Institute for Advanced Study 1 Einstein Drive PrincetonNJ08540 United States Steward Observatory and Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States

The Event Horizon Telescope recently captured images of the supermassive black hole in the center of the M87 galaxy, which show a ring-like emission structure with the South side only slightly brighter than the North side. This relatively weak asymmetry in the brightness profile along the ring has been interpreted as a consequence of the low inclination of the observer (around 17◦ for M87), which suppresses the Doppler beaming and boosting effects that might otherwise be expected due to the nearly relativistic velocities of the orbiting plasma. In this work, we use a large suite of general relativistic magnetohydrodynamic simulations to reassess the validity of this argument. By constructing explicit counter examples, we show that low-inclination is a sufficient but not necessary condition for images to have low brightness asymmetry. Accretion flow models with high accumulated magnetic flux close to the black hole horizon (the so-called magnetically arrested disks) and low black-hole spins have angular velocities that are substantially smaller than the orbital velocities of test particles at the same location. As a result, such models can produce images with low brightness asymmetry even when viewed edge on. Copyright © 2021, The Authors. All rights reserved.

关键词： Luminance

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Bioinformatics Pathway Analysis Pipeline for NGS Transcriptome Profile data on Nasopharyngeal Carcinoma

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Digdo Sudigyo Gisti Rahmawati Dicka W. Setiasari Risky H. Poluan Tjeng Wawan Cenggoro Arif Budiarto Alam Ahmad Hidayat Sri R. Indrasari Afiahayati Sofia M. Haryana Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Study Program of Biotechnology Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Faculty of Medicine Public Health and Nursing Gadjah Mada University Yogyakarta Indonesia 55281 Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Next-Generation Sequencing (NGS)-based genomics data have a huge potential to be used in transcriptomic profiling of Nasopharyngeal Carcinoma (NPC) to study the biosynthesis mechanism behind it. The high dimensionality of NGS data is the main challenge in performing the data analysis to extract useful information. In this workflow pipeline, memory-efficient Linux-based software such as HISAT2 and HTSeq are utilized to process the raw NGS data. Furthermore, Differential Expression Gene (DEG) list can be obtained by performing advanced analysis to the aligned Ribonucleic Acid (RNA) sequence using the edgeR protocol. This DEG list is one of the main inputs of biological pathway analysis that can be done in DAVID and PANTHER web-based software. Both tools generate a different pathway result related to inflammation.

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The 230 GHz Variability of Numerical Models of Sagittarius A* I. Parameter Surveys on Varying Ion-electron Temperature Ratios Under Strongly Magnetized Conditions

arXiv

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arXiv 2023年

作者： Chan, Ho-Sang Chan, Chi-Kwan Prather, Ben S. Wong, George N. Gammie, Charles Department of Physics Institute of Theoretical Physics The Chinese University of Hong Kong N.T. Shatin Hong Kong JILA University of Colorado National Institute of Standards and Technology 440 UCB BoulderCO80309-0440 United States Department of Astrophysical and Planetary Sciences University of Colorado 391 UCB BoulderCO80309 United States Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Avenue TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 North Santa Rita TucsonAZ85721 United States Los Alamos National Lab Los AlamosNM87545 United States School of Natural Sciences Institute for Advanced Study 1 Einstein Drive PrincetonNJ08540 United States Princeton Gravity Initiative Princeton University PrincetonNJ08544 United States Department of Physics University of Illinois at Urbana-Champaign 1110 West Green Street UrbanaIL61801 United States Department of Astronomy University of Illinois at Urbana-Champaign 1002 West Green Street UrbanaIL61801 United States NCSA University of Illinois at Urbana-Champaign 1205 W. Clark St. UrbanaIL61801 United States Illinois Center for the Advanced Study of the Universe University of Illinois at Urbana-Champaign 1110 West Green St. UrbanaIL61801 United States

The 230 GHz lightcurves of Sagittarius A* (Sgr A*) predicted by general relativistic magnetohydrodynamics (GRMHD) and ray-tracing (GRRT) models in Event Horizon Telescope Collaboration et al. (2022) have higher variability M∆T compared to observations. In this series of papers, we explore the origin of such large brightness variability. In this first paper, we performed large GRRT parameter surveys that span from the optically thin to the optically thick regimes, covering the ion-electron temperature ratio under strongly magnetized conditions, RLow, from 1 to 60. We find that increasing RLow can lead to either an increase or a reduction in M∆T depending on other model parameters, making it consistent with the observed variability of Sgr A* in some cases. Our analysis of GRRT image snapshots finds that the major contribution to the large M∆T for the RLow = 1 models comes from the photon rings. However, secondary contributions from the accretion flow are also visible depending on the spin parameter. Our work demonstrates the importance of the electron temperature used for modelling radiatively inefficient accretion flows and places new constraints on the ion-electron temperature ratio. A more in-depth analysis for understanding the dependencies of M∆T on RLow will be performed in subsequent papers. © 2023, CC BY.

关键词： Black holes

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Rotation in Event Horizon Telescope Movies

arXiv

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arXiv 2023年

作者： Conroy, Nicholas S. Bauböck, Michi Dhruv, Vedant Lee, Daeyoung Broderick, Avery E. Chan, Chi-Kwan Georgiev, Boris Joshi, Abhishek V. Prather, Ben Gammie, Charles F. Department of Astronomy University of Illinois at Urbana-Champaign 1002 West Green Street UrbanaIL61801 United States Department of Physics University of Illinois at Urbana-Champaign 1110 West Green Street UrbanaIL61801 United States Illinois Center for the Advanced Study of the Universe University of Illinois at Urbana-Champaign 1110 West Green St. UrbanaIL61801 United States Perimeter Institute for Theoretical Physics 31 Caroline Street North WaterlooONN2L 2Y5 Canada Department of Physics and Astronomy University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada Waterloo Centre for Astrophysics University of Waterloo WaterlooONN2L 3G1 Canada Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Los Alamos National Lab Los AlamosNM87545 United States NCSA University of Illinois at Urbana-Champaign 1205 W. Clark St. UrbanaIL61801 United States

The Event Horizon Telescope (EHT) has produced images of M87* and Sagittarius A*, and will soon produce time sequences of images, or movies. In anticipation of this, we describe a technique to measure the rotation rate, or pattern speed Ωp, from movies using an autocorrelation technique. We validate the technique on Gaussian random field models with a known rotation rate and apply it to a library of synthetic images of Sgr A* based on general relativistic magnetohydrodynamics simulations. We predict that EHT movies will have Ωp ≈ 1◦ per GMc−3, which is of order 15% of the Keplerian orbital frequency in the emitting region. We can plausibly attribute the slow rotation seen in our models to the pattern speed of inward-propagating spiral shocks. We also find that Ωp depends strongly on inclination. Application of this technique will enable us to compare future EHT movies with the clockwise rotation of Sgr A* seen in near-infrared flares by GRAVITY. Pattern speed analysis of future EHT observations of M87* and Sgr A* may also provide novel constraints on black hole inclination and spin, as well as an independent measurement of black hole mass. © 2023, CC BY.

关键词： Black holes

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