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BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2023年第9期104卷 S322-S365页

作者： Clem, Kyle R. Raphael, Marilyn N. School of Geography Environment and Earth Sciences Victoria University of Wellington Wellington New Zealand Scripps Institution of Oceanography University of California San Diego La Jolla California Department of Atmospheric and Oceanic Sciences University of Colorado Boulder Boulder Colorado Earth Science Observation Center Cooperative Institute for Research in Environmental Sciences (ESOC/CIRES) University of Colorado Boulder Boulder Colorado Argentine Naval Hydrographic Service Buenos Aires Argentina Department of Earth and Environmental Science Temple University Philadelphia Pennsylvania Department of Meteorology University of Valparaíso Valparaíso Chile Center for Climate and Resilience Research (CR)2 Santiago Chile British Antarctic Survey Cambridge United Kingdom Science Systems and Applications Inc. Lanham Maryland NASA Goddard Space Flight Center Greenbelt Maryland Royal Netherlands Meteorological Institute (KNMI) DeBilt The Netherlands Department of Marine Sciences University of Gothenburg Gothenburg Sweden Department of Geography Ohio University Athens Ohio NASA Jet Propulsion Laboratory Pasadena California NOAA/OAR Earth System Research Laboratory Global Monitoring Division Boulder Colorado University of Colorado Boulder Boulder Colorado National Oceanography Centre Southampton United Kingdom. Antarctic Meteorological Research and Data Center Space Science and Engineering Center University of Wisconsin-Madison Madison Wisconsin Department of Physical Sciences School of Arts and Sciences Madison Area Technical College Madison Wisconsin Australian Bureau of Meteorology and Institute for Marine and Antarctic Studies (IMAS) University of Tasmania Hobart Australia Earth Science and Observation Center CIRES University of Colorado Boulder Colorado University of St. Andrews St Andrews United Kingdom Princeton University Princeton New Jersey Australian Antarctic Division Australian Antarctic Program Partnership (AAPP) and Australian Centre fo

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Direct observational evidence of multi-epoch massive star formation in G24.47+0.49

arXiv

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arXiv 2024年

作者： Saha, Anindya Tej, Anandmayee Liu, Hong-Li Liu, Tie Garay, Guido Goldsmith, Paul F. Lee, Chang Won He, Jinhua Juvela, Mika Bronfman, Leonardo Baug, Tapas Vázquez-Semadeni, Enrique Sanhueza, Patricio Li, Shanghuo Chibueze, James O. Bhadari, N.K. Dewangan, Lokesh K. Das, Swagat Ranjan Xu, Feng-Wei Issac, Namitha Hwang, Jihye Tóth, L. Viktor Indian Institute of Space Science and Technology Kerala Thiruvananthapuram695 547 India Department of Astronomy Yunnan University Kunming650091 China Shanghai Astronomical Observatory Chinese Academy of Sciences 80 Nandan Road Shanghai200030 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences 80 Nandan Road Shanghai200030 China Departamento de Astronomía Universidad de Chile Las Condes Santiago7550000 Chile Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States 217 Gajeong-ro Yuseong-gu Daejeon34113 Korea Republic of Korea Astronomy and Space Science Institute 776 Daedeokdae-ro Yuseong-gu Daejeon34055 Korea Republic of Yunnan Observatories Chinese Academy of Sciences Phoenix Mountain East Suburb of Kunming Yunnan650216 China at Cerro Calán Camino El Observatorio #1515 Las Condes Santiago Chile Department of Physics University of Helsinki P.O. box 64 FI- 00014 Finland Satyendra Nath Bose National Centre for Basic Sciences Block-JD Sector-III Kolkata Salt Lake700 106 India Instituto de Radioastronomía y Astrofísica Universidad Nacional Autónoma de México Antigua Carretera a Pátzcuaro 8701 Ex-Hda. San José de la Huerta Michoacán Morelia58089 Mexico National Astronomical Observatory of Japan National Institutes of Natural Sciences 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Astronomical Science Program The Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Max Planck Institute for Astronomy Königstuhl 17 HeidelbergD-69117 Germany Department of Mathematical Sciences University of South Africa Cnr Christian de Wet Rd and Pioneer Avenue Florida Park Roodepoort1709 South Africa Department of Physics and Astronomy Faculty of Physical Sciences University of Nigeria Carver Building 1 University Road Nsukka410001 Nigeria Physical Research Laboratory Navrangpura Ahm

Using new continuum and molecular line data from the ALMA Three-millimeter Observations of Massive Star-forming Regions (ATOMS) survey and archival VLA, 4.86 GHz data, we present direct observational evidence of hierarchical triggering relating three epochs of massive star formation in a ring-like H II region, G24.47+0.49. We find from radio flux analysis that it is excited by a massive star(s) of spectral type O8.5V–O8V from the first epoch of star formation. The swept-up ionized ring structure shows evidence of secondary collapse, and within this ring a burst of massive star formation is observed in different evolutionary phases, which constitutes the second epoch. ATOMS spectral line (e.g., HCO+(1–0)) observations reveal an outer concentric molecular gas ring expanding at a velocity of ~ 9 km s−1, constituting the direct and unambiguous detection of an expanding molecular ring. It harbors twelve dense molecular cores with surface mass density greater than 0.05 g cm−2, a threshold typical of massive star formation. Half of them are found to be subvirial, and thus in gravitational collapse, making them third epoch of potential massive star-forming sites. Copyright © 2024, The Authors. All rights reserved.

关键词： Stars

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Resource-optimized fermionic local-hamiltonian simulation on a quantum computer for quantum chemistry

arXiv

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arXiv 2020年

作者： Wang, Qingfeng Li, Ming Monroe, Christopher Nam, Yunseong Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States IonQ College ParkMD20740 United States Joint Quantum Institute Department of Physics Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States Department of Physics University of Maryland College ParkMD20742 United States

The ability to simulate a fermionic system on a quantum computer is expected to revolutionize chemical engineering, materials design, nuclear physics, to name a few. Thus, optimizing the simulation circuits is of significance in harnessing the power of quantum computers. Here, we address this problem in two aspects. In the fault-tolerant regime, we optimize the rz and t gate counts along with the ancilla qubit counts required, assuming the use of a product-formula algorithm for implementation. We obtain a savings ratio of two in the gate counts and a savings ratio of eleven in the number of ancilla qubits required over the state of the art. In the pre-fault tolerant regime, we optimize the two-qubit gate counts, assuming the use of the variational quantum eigensolver (VQE) approach. Specific to the latter, we present a framework that enables bootstrapping the VQE progression towards the convergence of the ground-state energy of the fermionic system. This framework, based on perturbation theory, is capable of improving the energy estimate at each cycle of the VQE progression, by about a factor of three closer to the known ground-state energy compared to the standard VQE approach in the test-bed, classically-accessible system of the water molecule. The improved energy estimate in turn results in a commensurate level of savings of quantum resources, such as the number of qubits and quantum gates, required to be within a pre-specified tolerance from the known ground-state energy. We also explore a suite of generalized transformations of fermion to qubit operators and show that resource-requirement savings of up to more than 20%, in small instances, is possible. © 2020, CC BY.

关键词： Fault tolerance

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EMPRESS. X. Spatially resolved mass-metallicity relation in extremely metal-poor galaxies: Evidence of episodic star-formation fueled by a metal-poor gas infall

arXiv

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arXiv 2024年

作者： Nakajima, Kimihiko Ouchi, Masami Isobe, Yuki Xu, Yi Ozaki, Shinobu Nagao, Tohru Inoue, Akio K. Rauch, Michael Kusakabe, Haruka Onodera, Masato Nishigaki, Moka Ono, Yoshiaki Sugahara, Yuma Hattori, Takashi Hirai, Yutaka Hashimoto, Takuya Kim, Ji Hoon Moriya, Takashi J. Yanagisawa, Hiroto Aoyama, Shohei Fujimoto, Seiji Fukushima, Hajime Fukushima, Keita Harikane, Yuichi Hatano, Shun Hayashi, Kohei Ishigaki, Tsuyoshi Kawasaki, Masahiro Kojima, Takashi Komiyama, Yutaka Koyama, Shuhei Koyama, Yusei Lee, Chien-Hsiu Matsumoto, Akinori Mawatari, Ken Motohara, Kentaro Murai, Kai Nagamine, Kentaro Nakane, Minami Saito, Tomoki Sasaki, Rin Shibuya, Takatoshi Suzuki, Akihiro Takeuchi, Tsutomu T. Umeda, Hiroya Umemura, Masayuki Watanabe, Kuria Yabe, Kiyoto Yajima, Hidenobu Zhang, Yechi National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwanoha Chiba Kashiwa277-8582 Japan Osawa 2-21-1 Mitaka Tokyo181-8588 Japan University of Tokyo Chiba Kashiwa277-8583 Japan Kavli Institute for Cosmology University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom Cavendish Laboratory University of Cambridge 19 JJ Thomson Avenue CambridgeCB3 0HE United Kingdom Waseda Research Institute for Science and Engineering Faculty of Science and Engineering Waseda University 3-4-1 Okubo Shinjuku Tokyo169-8555 Japan Department of Physics Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Research Center for Space and Cosmic Evolution Ehime University Bunkyo-cho 2-5 Ehime Matsuyama790-8577 Japan Department of Physics School of Advanced Science and Engineering Faculty of Science and Engineering Waseda University 3-4-1 Okubo Shinjuku Tokyo169-8555 Japan Observatories of the Carnegie Institution for Science 813 Santa Barbara St. PasadenaCA91101 United States Observatoire de Genève Université de Genève 51 Chemin de Pégase Versoix1290 Switzerland 650 North Aohoku Place HiloHI96720 United States Department of Physics and Astronomy University of Notre Dame 225 Nieuwland Science Hall Notre DameIN46556 United States Astronomical Institute Tohoku University 6-3 Aoba Aramaki Aoba-ku Miyagi Sendai980-8578 Japan Division of Physics Faculty of Pure and Applied Sciences University of Tsukuba Ibaraki Tsukuba305-8571 Japan Faculty of Pure and Applied Sciences University of Tsukuba Ibaraki Tsukuba305-8571 Japan Astronomy Program Department of Physics and Astronomy Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of SNU Astronomy Research Cent

Using the Subaru/FOCAS IFU capability, we examine the spatially resolved relationships between gas-phase metallicity, stellar mass, and star-formation rate surface densities (Σ★ and ΣSFR, respectively) in extremely metal-poor galaxies (EMPGs) in the local universe. Our analysis includes 24 EMPGs, comprising 9,177 spaxels, which span a unique parameter space of local metallicity (12 + log(O/H) 6.9 to 7.9) and stellar mass surface density (Σ★ ∼ 105 to 107 Mo kpc−2), extending beyond the range of existing large integral-field spectroscopic surveys. Through spatially resolved emission line diagnostics based on the [N ii] BPT-diagram, we verify the absence of evolved active galactic nuclei in these EMPGs. Our findings reveal that, while the resolved mass-metallicity relation exhibits significant scatter in the low-mass regime, this scatter is closely correlated with local star-formation surface density. Specifically, metallicity decreases as ΣSFR increases for a given Σ★. Notably, half of the EMPGs show a distinct metal-poor horizontal branch on the resolved mass-metallicity relation. This feature typically appears at the peak clump with the highest Σ★ and ΣSFR and is surrounded by a relatively metal-enriched ambient region. These findings support a scenario in which metal-poor gas infall fuels episodic star formation in EMPGs, consistent with the kinematic properties observed in these systems. In addition, we identify four EMPGs with exceptionally low central metallicities (12 + log(O/H) 7.2), which display only a metal-poor clump without a surrounding metal-rich region. This suggests that such ultra-low metallicity EMPGs, at less than a few percent of the solar metallicity, may serve as valuable analogs for galaxies in the early stages of galaxy evolution. Copyright © 2024, The Authors. All rights reserved.

关键词： Spectroscopic analysis

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Consensus Statement on Brillouin Light Scattering Microscopy of Biological Materials

arXiv

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arXiv 2024年

作者： Bouvet, Pierre Bevilacqua, Carlo Ambekar, Yogeshwari Antonacci, Giuseppe Au, Joshua Caponi, Silvia Chagnon-Lessard, Sophie Czarske, Juergen Dehoux, Thomas Fioretto, Daniele Fu, Yujian Guck, Jochen Hamann, Thorsten Heinemann, Dag Jähnke, Torsten Jean-Ruel, Hubert Kabakova, Irina Koski, Kristie Koukourakis, Nektarios Krause, David La Cavera, Salvatore Landes, Timm Li, Jinhao Margueritat, Jeremie Mattarelli, Maurizio Monaghan, Michael Overby, Darryl R. Perez-Cota, Fernando Pontecorvo, Emanuele Prevedel, Robert Ruocco, Giancarlo Sandercock, John Scarcelli, Giuliano Scarponi, Filippo Testi, Claudia Török, Peter Vovard, Lucie Weninger, Wolfgang Yakovlev, Vladislav Yun, Seok-Hyun Zhang, Jitao Palombo, Francesca Bilenca, Alberto Elsayad, Kareem Center for Anatomy and Cell Biology Medical University of Vienna Austria Cell Biology and Biophysics Unit European Molecular Biology Laboratory Germany Fischell Department of Bioengineering University of Maryland United States Specto Srl. Milan Italy Unità di Perugia Italy LightMachinery Inc. Canada Departement of Electronics Carleton University Canada TU Dresden Germany Cluster of Excellence Physics of Life TU Dresden Germany Competence Center for Biomedical Computational Laser Systems TU Dresden Germany Institut Lumière Matière UMR5306 Université Lyon 1 CNRS Université de Lyon France Dipartimento di Fisica e Geologia Università di Perugia Italy Max Planck Institute for the Science of Light Erlangen Germany Department of Biology Norwegian University of Science and Technology Trondheim Norway Hannover Centre for Optical Technologies Leibniz University Hannover Germany CellSense Technologies GmbH Berlin Germany School of Mathematical and Physical Sciences University of Technology Sydney Australia Department of Chemistry University of California Davis United States Optics & Photonics Group Faculty of Engineering University of Nottingham United Kingdom Discipline of Mechanical Manufacturing & Biomedical Engineering Trinity College Dublin Ireland Department of Bioengineering Imperial College London United Kingdom CREST Optics S.p.A. Rome Italy Heidelberg Germany Center for Life Nano- & Neuro-Science Istituto Italiano di Tecnologia Rome Italy The Table Stable Ltd. Mettmenstetten Switzerland School of Physical & Mathematical Sciences Nanyang Technological University Singapore Nanyang Technological University Singapore Institute for Digital Molecular Analytics & Sciences Nanyang Technological University Singapore Department of Biomedical Engineering Texas A&M University United States Department of Electrical and Computer Engineering Texas A&M University United States Department of Physics and Astronomy Texas A&M University United States Harvard Me

Brillouin Light Scattering (BLS) spectroscopy is a non-invasive, non-contact, label-free optical technique that can provide information on the mechanical properties of a material on the sub-micron scale. Over the last decade it has seen increased applications in the life sciences, driven by the observed significance of mechanical properties in biological processes, the realization of more sensitive BLS spectrometers and its extension to an imaging modality. As with other spectroscopic techniques, BLS measurements not only detect signals characteristic of the investigated sample, but also of the experimental apparatus, and can be significantly affected by measurement conditions. The aim of this consensus statement is to improve the comparability of BLS studies by providing reporting recommendations for the measured parameters and detailing common artifacts. Given that most BLS studies of biological matter are still at proof-of-concept stages and use different-often self-built-spectrometers, a consensus statement is particularly timely to assure unified advancement. © 2024, CC BY.

关键词： Brillouin scattering

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GLOBAL OCEANS

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BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2023年第9期104卷 S146-S206页

作者： Johnson, G. C. Lumpkin, R. Met Office Hadley Center Exeter United Kingdom NOAA/OAR Atlantic Oceanographic and Meteorological Laboratory Miami Florida Cooperative Institute for Marine and Atmospheric Studies University of Miami Miami Florida NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland Cooperative Institute for Climate Ocean and Ecosystem Studies University of Washington Seattle Washington NOAA/OAR Pacific Marine Environmental Laboratory Seattle Washington NASA Goddard Space Flight Center Greenbelt Maryland Morgan State University Baltimore Maryland College of Marine Science University of South Florida St. Petersburg Florida Woods Hole Oceanographic Institution Woods Hole Massachusetts International Center for Climate and Environment Sciences Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China Cooperative Institute for Marine and Atmospheric Studies University of Miami Rosenstiel School of Marine Atmospheric and Earth Science University of Miami Miami Florida Science Systems and Applications Inc. Lanham Maryland Science Systems and Applications Inc. Hampton Virginia Scripps Institution of Oceanography University of California San Diego La Jolla California Center for Coastal Physical Oceanography Old Dominion University Norfolk Virginia Australian Antarctic Program Partnership Institute for Marine and Antarctic Studies Australian Research Council Centre of Excellence for Climate Extremes University of Tasmania Hobart Tasmania NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Department of Atmosphere Ocean and Earth System Modeling Research Meteorological Research Institute Japan Meteorological Agency Tsukuba Japan National Oceanography Centre Liverpool United Kingdom Flanders Marine Institute InnovOcean Campus Ostend Belgium NOAA/NWS NCWCP Laboratory for Satellite Altimetry College Par

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Effects of 4-week moderate-intensity aerobic exercise on stress reactivity, decision-making, and prefrontal brain activity under acute stress in emerging adults

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Journal of science and Medicine in Sport 2025年

作者： Baihui Luo Lu Leng Min Hu Yuehua He Hui Zheng Junhao Huang Guangdong Provincial Key Laboratory of Physical Activity and Health Promotion Scientific Research Center Guangzhou Sport University Guangzhou 510500 Guangdong China School of Physical Education and Health Guangzhou City Construction College Guangzhou Guangdong 510925 China College of Foreign Languages Jinan University Guangzhou 510632 Guangdong China Guangdong Engineering Polytechnic Guangzhou 511510 Guangdong China Shanghai Key Laboratory of Psychotic Disorders Brain Health Institute National Center for Mental Disorders Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine Shanghai 200032 China Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery State Key Laboratory of Quality Research in Chinese Medicine Macau University of Science and Technology Macau 999078 China

Objectives The present study aimed to investigate whether 4-week moderate-intensity aerobic training (MIAT) has beneficial effects on stress reactivity, decision-making, and associated prefrontal brain activity in presence of acute stress in emerging adults. Design A randomized controlled trial. Methods Forty-one emerging adults (age range: 18–26 years) were randomly assigned to MIAT group (n = 21, 22.76 ± 2.51 years) or control group (n = 20, 22.05 ± 1.36 years). The MIAT group underwent supervised cycling for 4 weeks, while the control group did not receive any intervention. All participants completed a challenging mental work task (operation span task) as an acute stress manipulation, followed by a two-step decision-making task with functional near-infrared spectroscopy to measure prefrontal cortex activation before and after the intervention. We also assessed state anxiety (STAI-S), visual analogue scales, and heart rate variability as indicators of stress level. Results Operation span task was effective at inducing psychological stress. After the intervention, the MIAT group exhibited lower STAI-S than the control group. The MIAT group showed higher orbitofrontal activation and significantly greater post-test reward-option selection improvement compared to the control group ( t  = 3.492, p  = 0.001, d  = 1.106), indicating enhanced reward sensitivity. Conclusions These findings indicated that 4 weeks of MIAT intervention enhanced cognitive function, particularly reward-based decision-making, while reducing psychological stress. The increased activation in the orbitofrontal cortex was likely involved in the improvements of STAI-S and decision-making under acute stress elicited by 4-week MIAT intervention.

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Cover Image, Volume 5, Number 3, March 2023

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Carbon Energy 2023年第3期5卷

作者： Jun Yang Xing Li Ke Qu Yixian Wang Kangqi Shen Changhuan Jiang Bo Yu Pan Luo Zhuangzhi Li Mingyang Chen Bingshu Guo Mingshan Wang Junchen Chen Zhiyuan Ma Yun Huang Zhenzhong Yang Pengcheng Liu Rong Huang Xiaodi Ren David Mitlin School of New Energy and Materials Southwest Petroleum University Chengdu China Energy Storage Research Institute Southwest Petroleum University Chengdu China Ke Qu Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. China Key Laboratory of Polar Materials and Devices (MOE) and Department of Electronics East China Normal University Shanghai 200062 China. Mingyang Chen Beijing Computational Science Research Center Beijing 100193 China. Center for Green Innovation School of Materials Science and Engineering University of Science and Technology Beijing Beijing 100083 China. Rong Huang China Key Laboratory of Polar Materials and Devices (MOE) and Department of Electronics East China Normal University Shanghai 200062 China. Xiaodi Ren Hefei National Research Center for Physical Sciences at the Microscale Department of Materials Science and Engineering University of Science and Technology of China Hefei Anhui 230026 China. David Mitlin Materials Science Program and Texas Materials Institute The University of Texas at Austin Austin Texas 78712-1591 USA. Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China China Key Laboratory of Polar Materials and Devices (MOE) Department of Electronics East China Normal University Shanghai China Xing Li School of New Energy and Materials Southwest Petroleum University Chengdu China. Materials Science Program and Texas Materials Institute The University of Texas at Austin Austin Texas USA Beijing Computational Science Research Center Beijing China School of Materials Science and Engineering Center for Green Innovation University of Science and Technology Beijing Beijing China Department of Materials Science and Engineering Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of China Hefei Anhui China

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Comparative cellular analysis of motor cortex in human, marmoset and mouse (vol 598, pg 111, 2021)

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NATURE 2022年第7904期604卷 E8-E8页

作者： Bakken, Trygve E. Jorstad, Nikolas L. Hu, Qiwen Lake, Blue B. Tian, Wei Kalmbach, Brian E. Crow, Megan Hodge, Rebecca D. Krienen, Fenna M. Sorensen, Staci A. Eggermont, Jeroen Yao, Zizhen Aevermann, Brian D. Aldridge, Andrew I. Bartlett, Anna Bertagnolli, Darren Casper, Tamara Castanon, Rosa G. Crichton, Kirsten Daigle, Tanya L. Dalley, Rachel Dee, Nick Dembrow, Nikolai Diep, Dinh Ding, Song-Lin Dong, Weixiu Fang, Rongxin Fischer, Stephan Goldman, Melissa Goldy, Jeff Graybuck, Lucas T. Herb, Brian R. Hou, Xiaomeng Kancherla, Jayaram Kroll, Matthew Lathia, Kanan van Lew, Baldur Li, Yang Eric Liu, Christine S. Liu, Hanqing Lucero, Jacinta D. Mahurkar, Anup McMillen, Delissa Miller, Jeremy A. Moussa, Marmar Nery, Joseph R. Nicovich, Philip R. Niu, Sheng-Yong Orvis, Joshua Osteen, Julia K. Owen, Scott Palmer, Carter R. Pham, Thanh Plongthongkum, Nongluk Poirion, Olivier Reed, Nora M. Rimorin, Christine Rivkin, Angeline Romanow, William J. Sedeno-Cortes, Adriana E. Siletti, Kimberly Somasundaram, Saroja Sulc, Josef Tieu, Michael Torkelson, Amy Tung, Herman Wang, Xinxin Xie, Fangming Yanny, Anna Marie Zhang, Renee Ament, Seth A. Behrens, M. Margarita Bravo, Hector Corrada Chun, Jerold Dobin, Alexander Gillis, Jesse Hertzano, Ronna Hof, Patrick R. Hollt, Thomas Horwitz, Gregory D. Keene, C. Dirk Kharchenko, Peter V. Ko, Andrew L. Lelieveldt, Boudewijn P. Luo, Chongyuan Mukamel, Eran A. Pinto-Duarte, Antonio Preiss, Sebastian Regev, Aviv Ren, Bing Scheuermann, Richard H. Smith, Kimberly Spain, William J. White, Owen R. Koch, Christof Hawrylycz, Michael Tasic, Bosiljka Macosko, Evan Z. McCarroll, Steven A. Ting, Jonathan T. Zeng, Hongkui Zhang, Kun Feng, Guoping Ecker, Joseph R. Linnarsson, Sten Lein, Ed S. Allen Institute for Brain Science Seattle WA USA Department of Physiology and Biophysics University of Washington Seattle WA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Bioengineering University of California San Diego La Jolla CA USA The Salk Institute for Biological Studies La Jolla CA USA Epilepsy Center of Excellence Department of Veterans Affairs Medical Center Seattle WA USA Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory Cold Spring Harbor NY USA Department of Genetics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA LKEB Department of Radiology Leiden University Medical Center Leiden The Netherlands Pattern Recognition and Bioinformatics group Delft University of Technology Delft The Netherlands J. Craig Venter Institute La Jolla CA USA Department of Pathology University of California San Diego CA USA Division of Vaccine Discovery La Jolla Institute for Immunology La Jolla CA USA Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA Computer Science and Engineering Program University of California San Diego La Jolla CA USA Howard Hughes Medical Institute The Salk Institute for Biological Studies La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Institute for Genomes Sciences University of Maryland School of Medicine Baltimore MD USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA Ludwig Institute for Cancer Research La Jolla CA USA Department of Computer Science University of Maryland College Park College Park MD USA Sanford Burnham Prebys Medical Discovery Institute La Jolla CA USA Biomedical Sciences Program School of Medicine University of California San Diego La Jolla CA USA University of Connecticut Storrs CT USA Department

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Deep-learning-driven event reconstruction applied to simulated data from a single Large-Sized Telescope of CTA 37

Deep-learning-driven event reconstruction applied to simulat...

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37th International Cosmic Ray Conference, ICRC 2021

作者： Abe, H. Aguasca, A. Agudo, I. Antonelli, L.A. Aramo, C. Armstrong, T. Artero, M. Asano, K. Ashkar, H. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Becerra González, J. Bernardos, M.I. Berti, A. Biederbeck, N. Bigongiari, C. Blanch, O. Bonnoli, G. Bordas, P. Bose, D. Bulgarelli, A. Burelli, I. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Cassol, F. Cerruti, M. Chai, Y. Cheng, K. Chikawa, M. Chytka, L. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. De Angelis, A. de Bony de Lavergne, M. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Depaoli, D. Di Pierro, F. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsässer, D. Emery, G. Escudero, J. Fiasson, A. Foffano, L. Fonseca, M.V. Freixas Coromina, L. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Green, D. Grespan, P. Gunji, S. Hackfeld, J. Hadasch, D. Hahn, A. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Herrera Llorente, J. Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Inada, T. Inome, Y. Iori, M. Ishio, K. Iwamura, Y. Jacquemont, M. Jimenez Martinez, I. Jouvin, L. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kong, A. Kubo, H. Kushida, J. Lamanna, G. Lamastra, A. Le Flour, T. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Luque-Escamilla, P.L. Majumdar, P. Makariev, M. Mandat, D. Manganaro, M. Mannheim, K. Mariotti, M. Marquez, P. Marsella, G. Martí, J. Martinez, O. Martínez, G. Martínez, M. Marusevec, P. Mas, A. Maurin, G. Mazin, D. Mestre Guillen, E. Micanovic, S. Miceli, D. Miener, T. Miranda, J.M. Miranda, L.D.M. Mirzoyan, R. Mizuno, T. Molina, E. Montaruli, T. Monteiro, I. Moralejo, A. Morcuende, D. Moretti, E. Morselli, A. Mrakovcic, K. Murase, K. Nagai, A. Nakamori, T. Nickel, L. LISTIC Université Savoie Mont-Blanc Polytech Annecy-Chambéry 5 chemin de bellevue Annecy74940 France Institute for Cosmic Ray Research University of Tokyo Japan Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain Instituto de Astrofísica de Andalucía-CSIC Italy INAF Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy Aix Marseille Univ CNRS IN2P3 CPPM France The Barcelona Institute of Science and Technology Spain IRFU CEA Université Paris-Saclay France Laboratoire d'Annecy de Physique des Particules Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS LAPP 9 chemin de bellevue Annecy74940 France Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Instituto de Física de Partículas y del Cosmos Departamento de EMFTEL Universidad Complutense de Madrid Madrid Spain INAF Osservatorio di Astrofisica e Scienza Spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil INFN Istituto Nazionale di Fisica Nucleare Sezione di Padova PadovaI-35131 Italy Università degli Studi di Padova Italy Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain Max-Planck-Institut für Physik Germany Department of Physics TU Dortmund University Germany Saha Institute of Nuclear Physics INFN Sezione di Trieste Università degli Studi di Udine Italy INFN Sezione di Catania Italy Italy University of Geneva Département de Physique Nucléaire et Corpusculaire Switzerland Palacky University Olomouc Faculty of Science Czech Republic CIEMAT Port d'Informació Científica INFN Sezione di Torino Italy Dipartimento di Fisica Universitá degli Studi di Torino Italy INFN Sezione di Bari Università di Bari Italy University of Rijeka Department of Physics Croatia Institute for Theoretical Physics and Astrophysics Universität Würzburg Germany Physics Program Graduate School of Advanced Science and Engin

When very-high-energy gamma rays interact high in the Earth's atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into shower images that can be analyzed to extract the properties of the primary gamma ray. The dominant background for IACTs is comprised of air shower images produced by cosmic hadrons, with typical noise-to-signal ratios of several orders of magnitude. The standard technique adopted to differentiate between images initiated by gamma rays and those initiated by hadrons is based on classical machine learning algorithms, such as Random Forests, that operate on a set of handcrafted parameters extracted from the images. Likewise, the inference of the energy and the arrival direction of the primary gamma ray is performed using those parameters. State-of-the-art deep learning techniques based on convolutional neural networks (CNNs) have the potential to enhance the event reconstruction performance, since they are able to autonomously extract features from raw images, exploiting the pixel-wise information washed out during the parametrization process. Here we present the results obtained by applying deep learning techniques to the reconstruction of Monte Carlo simulated events from a single, next-generation IACT, the Large-Sized Telescope (LST) of the Cherenkov Telescope Array (CTA). We use CNNs to separate the gamma-ray-induced events from hadronic events and to reconstruct the properties of the former, comparing their performance to the standard reconstruction technique. Three independent implementations of CNN-based event reconstruction models have been utilized in this work, producing consistent results. © 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： Hadrons

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