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Evaluating Large Language Models for Enhancing Radiology Specialty Examination: A Comparative Study with Human Performance

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Academic Radiology 2025年

作者： Liu, Hao-Yun Chen, Shyh-Jye Wang, Weichung Lee, Chung-Hsi Hsu, Hsian-He Shen, Shu-Huei Chiou, Hong-Jen Lee, Wen-Jeng Department of Medical Imaging National Taiwan University Hospital Hsin-Chu Branch Br. No.25 Lane 442 Sec.1 Jingguo Rd Hsinchu City 300 Taiwan National Taiwan University College of Medicine No.1 Jen Ai Road Section 1 Taipei 100 Taiwan Department of Medical Imaging National Taiwan University Hospital No. 7 Zhongshan S. Rd. Zhongzheng Dist. Taipei City 100229 Taiwan Institute of Applied Mathematical Sciences Department of Mathematics and Data Science Degree Program National Taiwan University No. 1 Sec. 4 Roosevelt Rd. Taipei 106319 Taiwan Graduate Institute of Health and Biotechnology Law Taipei Medical University 250 Wuxing Street Taipei City Taiwan Department of Radiology Tri-Service General Hospital National Defense Medical Center No.325 Sec.2 Chenggong Rd. Neihu District Taipei City Taiwan Department of Radiology Taipei Veterans General Hospital No.201 Sec. 2 Shipai Rd. Beitou District Taipei City Taiwan National Yang Ming Chiao Tung University School of Medicine No. 118 Sec. 1 Zhongxiao West Road Taipei City 100 Taiwan

Rationale and Objectives: The radiology specialty examination assesses clinical decision-making, image interpretation, and diagnostic reasoning. With the expansion of medical knowledge, traditional test design faces challenges in maintaining accuracy and relevance. Large language models (LLMs) demonstrate potential in medical education. This study evaluates LLM performance in radiology specialty exams, explores their role in assessing question difficulty, and investigates their reasoning processes, aiming to develop a more objective and efficient framework for exam design. Materials and Methods: This study compared the performance of LLMs and human examinees in a radiology specialty examination. Three LLMs (GPT-4o, o1-preview, and GPT-3.5-turbo-1106) were evaluated under zero-shot conditions. Exam accuracy, examinee accuracy, discrimination index, and point-biserial correlation were used to assess LLMs’ ability to predict question difficulty and reasoning processes. The data provided by the Taiwan Radiological Society ensures comparability between AI and human performance. Results: As for accuracy, GPT-4o (88.0%) and o1-preview (90.9%) outperformed human examinees (76.3%), whereas GPT-3.5-turbo-1106 showed significantly lower accuracy (50.2%). Question difficulty analysis revealed that newer LLMs excel in solving complex questions, while GPT-3.5-turbo-1106 exhibited greater performance variability. Discrimination index and point-biserial Correlation analyses demonstrated that GPT-4o and o1-preview accurately identified key differentiating questions, closely mirroring human reasoning patterns. These findings suggest that advanced LLMs can assess medical examination difficulty, offering potential applications in exam standardization and question evaluation. Conclusion: This study evaluated the problem-solving capabilities of GPT-3.5-turbo-1106, GPT-4o, and o1-preview in a radiology specialty examination. LLMs should be utilized as tools for assessing exam question dif

关键词： Accuracy Evaluation GPT LLMs Radiology specialty examination

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Erratum for Wang et al., "Clinically Applicable System for Rapidly Predicting Enterococcus faecium Susceptibility to Vancomycin"

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Microbiology spectrum 2022年第1期10卷 e0261021页

作者： Hsin-Yao Wang Chia-Ru Chung Chao-Jung Chen Ko-Pei Lu Yi-Ju Tseng Tzu-Hao Chang Min-Hsien Wu Wan-Ting Huang Ting-Wei Lin Tsui-Ping Liu Tzong-Yi Lee Jorng-Tzong Horng Jang-Jih Lu Department of Laboratory Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Ph.D. Program in Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Computer Science and Information Engineering National Central Universitygrid.37589.30 Taoyuan City Taiwan. Graduate Institute of Integrated Medicine China Medical Universitygrid.254145.3 Taichung Taiwan. Proteomics Core Laboratory China Medical Universitygrid.254145.3 Hospital Taichung Taiwan. Graduate Program in Biomedical Information Yuan-Ze University Taoyuan City Taiwan. Department of Information Management Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City Taiwan. Clinical Big Data Research Center Taipei Medical University Hospital Taipei City Taiwan. Graduate Institute of Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Division of Haematology/Oncology Department of Internal Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Biosensor Group Biomedical Engineering Research Center Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Pathology Kaohsiung Chang Gung Memorial Hospitalgrid.413801.f and Chang Gung University College of Medicine Kaohsiung Taiwan. School of Life and Health Sciences The Chinese University of Hong Kong Shenzhen China. Warshel Institute for Computational Biology The Chinese University of Hong Kong Shenzhen China. Department of Bioinformatics and Medical Engineering Asia University Taichung City Taiwan. School of Medicine Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Medical Biotechnology and Laboratory Science Chang Gung Universitygrid.145695.a Taoyuan City Taiwan.

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What is a data science/analytics degree?

What is a data science/analytics degree?

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America"s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017

作者： Saltz, Jeffrey Armour, Frank Sharda, Ramesh Applied Data Science Master of Science Program Syracuse University United States American University United States Graduate Programs ConocoPhillips Chairs of Mgmt. Sc. and Info Systems Oklahoma State University United States

ISBN: (纸本)9780996683142

data science, and the related field of analytics, is an emerging discipline that integrates concepts across a range of domains, including computer science, information systems, software engineering and statistics. While the number of data science / analytics programs continues to increase, there has been little discussion on how we should define this emerging educational field. This panel will foster a debate with respect to what are the key learning objectives within these programs and should there be different types of data science related programs (such as an applied data science program or a business analytics program in addition to data science programs). Via a debate, this panel, along with the audience, will explore the field of data science and these emerging questions regarding data science and analytics education. © 2017 AIS/ICIS Administrative Office. All Rights Reserved.

关键词： data Analytics

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Hybrid support vector regression in electric load during national holiday season

Hybrid support vector regression in electric load during nat...

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2017 International Conference on Innovative and Creative Information Technology: Computational Intelligence and IoT, ICITech 2017

作者： Caraka, Rezzy Eko Bakar, Sakhinah Abu Pardamean, Bens Budiarto, Arif School of Mathematical Sciences Faculty of Science and Technology National University of Malaysia Malaysia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538640456

This paper studies non-parametric time-series approach to electric load in national holiday seasons based on historical hourly data in state electric company of Indonesia consisting of historical data of the Northern Sumatera also South and Central Sumatra electricity load. Given a baseline for forecasting performance, we apply our hybrid models and computation platform with combining parameter of the kernel. To facilitate comparison to results of our analysis, we highlighted the results around MAPE-based and R2-based techniques. In order to get more accurate results, we need to improve, investigate, also develop the appropriate statistical tools. Electric load forecasting is a fundamental aspect of infrastructure development decisions and can reduce the energy usage of the nation. © 2017 IEEE.

关键词： Time series

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Information to the Eye of the Beholder: data Visualization for Many-Objective Optimization

Information to the Eye of the Beholder: Data Visualization f...

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Congress on Evolutionary Computation

作者： Ivan Reinaldo Meneghini Roozbeh H. Koochaksaraei Frederico G. Guimarães Antonio Gaspar-Cunha Graduate Program in Eletrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Machine Intelligence and Data Science (MINDS) Laboratory Universidade Federal de Minas Gerais Belo Horizonte Brazil Institute for Polymers and Composites University of Minho Guimaraes Portugal

The visualization gap is one of the important challenges posed by many-objective optimization problems (MaOPs). In this paper, we present an integrated data visualization method for MaOPs, called CAP-vis plot, combining the Chord diagram, the Angular mapping and the Parallel coordinates in the same visualization. The method follows the circular design layout, showing different levels of information. This new approach allows the spatial location of points in high dimensional spaces, the visualization of harmony and conflict between objectives, as well as the comparison of the approximation sets provided by different algorithms. With this work, we try to fill the visualization gap and bring information to the eye of the decision-maker and the optimizer, with an intuitive overview of the obtained results. Some experiments were performed using the Benchmark Functions proposed for the IEEE-CEC 2018 Competition on Many-Objective Optimization. We used the tool to visualize the results obtained by NSGA-III, HypE, RVEA, MOEA/DD, PICEA-g, using the PlatEMO MATLAB platform, with the same parameter settings of the competition. The results on the Benchmark Problems show the importance of the qualitative analysis of the data. The experiments show how visualization can help interpretation of the results and identification of strengths and drawbacks of MOEA.

关键词： data visualization Tools Optimization Layout Approximation algorithms Benchmark testing Linear programming

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Serum Arachidonic Acid Oxylipins Indicate Small Vessel Injury And the Related Executive Function Decline In Stroke Patients

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Alzheimer's & Dementia 2023年第S15期19卷

作者： Di Yu Nuanyi Liang Lisa Y. Xiong Qing Shen William Z. Lin Miracle Ozzoude Maged Goubran Jennifer S. Rabin Joel Ramirez Sean Symons Seyyed MH Haddad Brian Tan Nuwan D. Nanayakkara Allison Ann Dilliott Malcolm Binns Derek Beaton Stephen R. Arnott Jane M Lawrenece-Dewar Demetrios J. Sahlas Leanne Casaubon Yurika Otoki Krista L. Lanctôt Mario Masellis Richard H. Swartz Ameer Y. Taha Walter Swardfager The ONDRI Investigators Department of Pharmacology and Toxicology University of Toronto Toronto ON Canada Sandra Black Centre for Brain Resilience and Recovery Sunnybrook Research Institute Toronto ON Canada Correspondece University of California Davis Davis CA USA Physical Sciences Platform Sunnybrook Research Institute University of Toronto Toronto ON Canada Department of Medical Biophysics University of Toronto Toronto ON Canada Harquail Centre for Neuromodulation Sunnybrook Research Institute Toronto ON Canada Division of Neurology Department of Medicine University of Toronto Toronto ON Canada Rehabilitation Sciences Institute University of Toronto Toronto ON Canada Physical Sciences Sunnybrook Research Institute Toronto ON Canada Hurvitz Brain Sciences Program Sunnybrook Research Institute Toronto ON Canada University of Toronto Toronto ON Canada Robarts Research Institute London ON Canada Rotman Research Institute Toronto ON Canada University of Western Ontario London ON Canada Western University London ON Canada Data Science & Advanced Analytics St. Michael’s Hospital Unity Health Toronto Toronto ON Canada Baycrest Hospital Toronto ON Canada Thunder Bay Regional Health Research Institute Northern Ontario School of Medicine University Thunder Bay ON Canada Department of Medicine McMaster University Hamilton ON Canada Division of Agricultural Chemistry Graduate School of Agricultural Science Tohoku University Sendai Tohoku Japan Department of Psychiatry Temerty Faculty of Medicine University of Toronto Toronto ON Canada Toronto Rehabilitation Institute Toronto ON Canada

Background Cerebral small vessel disease (SVD) frequently co-occurs with other neurodegenerative pathologies and collectively lead to cognitive deficits. Previously, we found that the ratios of soluble epoxide hydrolase (sEH)- derived diols to the parent epoxides (generated by CYP2J/2Cs) linoleic acids were associated with greater white matter hyperintensities (WMH) and poorer executive function in patients with transient ischemic attack. However, the associations with the diol and epoxide species derived from arachidonic acid (AA) have not been explored. Methods The study cohort is comprised of 159 stroke patients (mean age = 69.2, 32.1% female) from the Ontario Neurodegenerative Degenerative Research Initiative. EpETrEs (AA epoxides) and DiHETrEs (AA diols) were quantified by a targeted ultrahigh pressure liquid chromatography mass spectrometry (UPLC-MS/MS). Executive function was assessed using a composite score that included Digit Symbol Substitution Test (DSST), Trial-Making Test Part B, Stroop Color-Word Interference Test, and FAS Verbal Fluency Test. WMHs were quantified from T2-Fluid-Attenuated-Inversion-Recovery MRI through Lesion Explorer (https://***/***).In linear models controlling for age, sex, education or age, sex, glucose, cholesterol, and waist circumferences were used for cognitive and imaging out comes, respectively. Results 11(12)-EpETrE was found to be associated with less WHM (ρ = -0.175, p = 0.040) and better executive function (ρ = 0.166, p = 0.039). In a sub-cohort of patients with small vessel stroke (n = 50), the relationship between WMH and 11(12)-EpETrE became stronger (ρ = -0.390, p = 0.014). 14(15)-EpETrE was also associated with less WMH (ρ = -0.416, p = 0.009). Similar relationships were not seen with the diols or diol to epoxide ratios. Conclusions Oxylipins derived from sEH activity may be potential biomarkers of vascular cognitive impairment and small vessel disease in stroke patients.

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MAGIC and H.E.S.S. detect VHE gamma rays from the blazar OT 081 for the first time: a deep multiwavelength study 37

MAGIC and H.E.S.S. detect VHE gamma rays from the blazar OT ...

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37th International Cosmic Ray Conference, ICRC 2021

作者： Seglar-Arroyo, M. Sanchez, D. Esteban Gutierrez, A. Agudo, I. Ciprini, S. Filippenko, A.V. Hovatta, T. Jermak, H. Kopatskaya, E.N. Lähteenmäki, A. Larionov, V.M. Larionova, L.V. Morozova, D.A. Pahljina, M. Tornikoski, M. Troitsky, I. Verrecchia, F. Xiao, H.B. Zheng, W. Acciari, V.A. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Becerra González, J. Bednarek, W. Bellizzi, L. Bernardini, E. Bernardos, M. Berti, A. Besenrieder, J. Bhattacharyya, W. Bigongiari, C. Biland, A. Blanch, O. Bökenkamp, H. Bonnoli, G. Bošnjak, Ž. Busetto, G. Carosi, R. Ceribella, G. Cerruti, M. Chai, Y. Chilingarian, A. Cikota, S. Colak, S.M. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D'Amico, G. D'Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Do Souto Espiñeira, E. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Fallah Ramazani, V. Fattorini, A. Fonseca, M.V. Font, L. Fruck, C. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Green, J.G. Green, D. Hadasch, D. Hahn, A. Heckmann, L. Herrera, J. Hoang, J. Hrupec, D. Hütten, M. Inada, T. Ishio, K. Iwamura, Y. Jiménez Martínez, I. Jormanainen, J. Jouvin, L. Karjalainen, M. Kerszberg, D. Kobayashi, Y. Kubo, H. Kushida, J. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Machado de Oliveira Fraga, B. Maggio, C. Majumdar, P. Makariev, M. Mallamaci, M. Maneva, G. Manganaro, M. Mannheim, K. Maraschi, L. Mariotti, M. Martínez, M. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molina, E. Moralejo, A. Morcuende, D. Moreno, V. Moretti, E. Nakamori, T. Nava, L. Neustroev, V. University of Rijeka Department of Physics Radmile Matejčić 2 Rijeka Croatia IRFU CEA Université Paris-Saclay Gif-sur-YvetteF-91191 France CNRS LAPP France CSIC Granada Spain Roma Tor Vergata Section RomeI-00133 Italy ASI Space Science Data Center RomeI-00133 Italy Department of Astronomy University of California BerkeleyCA94720-3411 United States Miller Institute for Basic Research in Science University of California BerkeleyCA94720 United States Aalto University Tuorla observatory Finland Liverpool John Moores University United Kingdom St. Petersburg State University Russia Aalto University Finland INAF Osservatorio Astronomico di Roma via Frascati 33 Monte Porzio CatoneI-00078 Italy Guangzhou University China Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Università di Udine INFN Trieste UdineI-33100 Italy RomeI-00136 Italy ETH Zürich ZürichCH-8093 Switzerland E-08193 Spain The University of Tokyo Chiba Kashiwa277-8582 Japan Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil Università di Padova INFN PadovaI-35131 Italy University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Università di Siena INFN Pisa SienaI-53100 Italy ZeuthenD-15738 Germany Max-Planck-Institut für Physik MünchenD-80805 Germany Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain INFN MAGIC Group INFN Sezione di Torino Università d

OT 081 is a luminous blazar well known for its variability in many energy bands. The very-high-energy (VHE;E > 100 GeV) gamma-ray emission from the source was discovered by MAGIC and H.E.S.S. during flaring activity in July 2016, after a trigger from the Large Area Telescope (LAT) onboard the Fermi satellite. By analysing the multiwavelength light curves and the broadband spectral energy distribution (SED), we study the activity of the source and investigate four individual states of activity in the window from MJD 57575 to 57602. The intrinsic gamma-ray spectrum can be described by a power law with spectral indices of 3.27 ± 0.44 (MAGIC) and 3.39 ± 0.58 (H.E.S.S.) over energy ranges 60-300 GeV and 120-500 GeV, respectively. The combined contemporaneous high-energy (HE;E > 100 MeV) through VHE SED shows curvature and can be described by a log-parabola shape. A simple one-zone synchrotron self-Compton (SSC) model is not sufficient to describe the broadband SED. The presence of broad emission lines in the optical spectrum of the source challenges the categorisation of OT 081 as a BL Lac and, together with the emission scenarios tested, points to the possibility that the source is transitional in nature between a BL Lac and a flat-spectrum radio quasar. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Germanium alloys

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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Follow-up observations of GW170817 with the MAGIC telescopes 37

Follow-up observations of GW170817 with the MAGIC telescopes

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37th International Cosmic Ray Conference, ICRC 2021

作者： Stamerra, A. Salafia, O.S. Berti, A. Covino, S. D'Elia, V. Miceli, D. Nava, L. Patricelli, B. Righi, C. Inoue, S. Antonelli, L.A. Ansoldi, S. De Lotto, B. Longo, F. Tavecchio, F. Acciari, V.A. Arbet Engels, A. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Becerra González, J. Bednarek, W. Bellizzi, L. Bernardini, E. Bernardos, M. Besenrieder, J. Bhattacharyya, W. Bigongiari, C. Biland, A. Blanch, O. Bökenkamp, H. Bonnoli, G. Bošnjak, Ž. Busetto, G. Carosi, R. Ceribella, G. Cerruti, M. Chai, Y. Chilingarian, A. Cikota, S. Colak, S.M. Colombo, E. Contreras, J.L. Cortina, J. D'Amico, G. Da Vela, P. Dazzi, F. De Angelis, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Do Souto Espiñeira, E. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Fallah Ramazani, V. Fattorini, A. Fonseca, M.V. Font, L. Fruck, C. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Green, J.G. Green, D. Hadasch, D. Hahn, A. Heckmann, L. Herrera, J. Hoang, J. Hrupec, D. Hütten, M. Inada, T. Ishio, K. Iwamura, Y. Jiménez Martínez, I. Jormanainen, J. Jouvin, L. Karjalainen, M. Kerszberg, D. Kobayashi, Y. Kubo, H. Kushida, J. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Machado de Oliveira Fraga, B. Maggio, C. Majumdar, P. Makariev, M. Mallamaci, M. Maneva, G. Manganaro, M. Mannheim, K. Maraschi, L. Mariotti, M. Martínez, M. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miener, T. Miranda, J.M. Mirzoyan, R. Molina, E. Moralejo, A. Morcuende, D. Moreno, V. Moretti, E. Nakamori, T. Neustroev, V. Nigro, C. Nilsson, K. Nishijima, K. Noda, K. Nozaki, S. Ohtani, Y. Oka, T. Otero-Santos, J. Paiano, S. Palatiello, M. Paneque, D. Paoletti, R. Paredes, J.M. INAF - Osservatorio Astronomico di Roma Rome Italy INAF - Osservatorio Astronomico di Brera Merate Italy Rome Italy Max-Planck-Institut für Physik München Germany Space Science Data Center - Agenzia Spaziale Italiana Rome Italy European Gravitational Observatory Pisa Italy RIKEN Saitama Wako Japan Università di Udine INFN Trieste Udine Italy Dipartimento di Fisica Università di Trieste Trieste Italy Scuola Normale Superiore Pisa Italy Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Università di Udine INFN Trieste UdineI-33100 Italy RomeI-00136 Italy ETH Zürich ZürichCH-8093 Switzerland E-08193 Spain The University of Tokyo Chiba Kashiwa277-8582 Japan Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil Università di Padova INFN PadovaI-35131 Italy University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Università di Siena INFN Pisa SienaI-53100 Italy ZeuthenD-15738 Germany Max-Planck-Institut für Physik MünchenD-80805 Germany Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Department of Physics Rijeka51000 Croatia Universität Würzburg WürzburgD-

The discovery of the electromagnetic counterpart AT2017gfo and the GRB 170817A, associated to the binary neutron star merger GW170817, was one of the major advances in the study of gamma-ray bursts (GRBs) and the hallmark of the multi-messenger astronomy with gravitational waves. Another breakthrough in GRB physics is represented by the discovery of the highly energetic, teraelectronvolt (TeV) component in the GRB 190114C, possibly an universal component in all GRBs. This conclusion is also suggested by the hint of TeV emission in the short GRB 160821B and a few more events reported in the literature. The missing observational piece is the joint detection of TeV emission and gravitational waves from a short GRB and its progenitor. MAGIC observed the counterpart AT2017gfo as soon as the visibility conditions allowed it, namely from January to June 2018. These observations correspond to the maximum flux level observed in the radio and X-ray bands. The upper limits derived from TeV observations are compared with the modelling of the late non-thermal emission using the multi-frequency SED. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)

关键词： Gravity waves

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