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DATA-DRIVEN MORI-ZWANZIG: REDUCED ORDER MODELING OF SPARSE SENSORS MEASUREMENTS FOR BOUNDARY LAYER TRANSITION

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arXiv 2023年

作者： Woodward, Michael Tian, Yifeng Mohan, Arvind Lin, Yen Ting Hader, Christoph Fasel, Hermann Chertkov, Michael Livescu, Daniel Computer Computational and Statistical Sciences Division Los Alamos National Laboratory Los AlamosNM87544 United States Graduate Interdisciplinary Program in Applied Mathematics Department of Mathematics University of Arizona TucsonAZ85721 United States Department of Aerospace and Mechanical Engineering University of Arizona TucsonAZ85721 United States

Understanding, predicting and controlling laminar-turbulent boundary-layer transition is crucial for the next generation aircraft design. However, in real flight experiments, or wind tunnel tests, often only sparse sensor measurements can be collected at fixed locations. Thus, in developing reduced models for predicting and controlling the flow at the sensor locations, the main challenge is in accounting for how the surrounding field of unobserved (or unresolved) variables interacts with the observed (or resolved) variables at the fixed sensor locations. This makes the Mori-Zwanzig (MZ) formalism a natural choice, as it results in the Generalized Langevin Equations which provides a mathematically sound framework for constructing non-Markovian reduced-order models that include the effects the unresolved variables have on the resolved variables. These effects are captured in the so called memory kernel and orthogonal dynamics, which, when using Mori's linear projection, provides a higher order approximation to the traditional approximate Koopman learning methods. In this work, we explore recently developed data-driven methods for extracting the MZ operators to two boundary-layer flows obtained from high resolution data;a low speed incompressible flow over a flat plate exhibiting bypass transition;and a high speed compressible flow over a flared cone at Mach 6 and zero angle of attack where transition was initiated using a broadband forcing approach ("natural" transition). In each case, an array of "sensors" are placed near the surface of the solid boundary, and the MZ operators are learned and the predictions are compared to the Extended Dynamic Mode Decomposition (EDMD), both using delay embedded coordinates. Further comparisons are made with Long Short-Term Memory (LSTM) and a regression based projection framework using neural networks for the MZ operators. First, we compare the effects of including delay embedded coordinates with EDMD and Mori based MZ and provide

关键词： Dynamic mode decomposition

Data-Driven Mori-Zwanzig: Approaching a Reduced Order Model for Hypersonic Boundary Layer Transition

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arXiv 2023年

作者： Woodward, Michael Tian, Yifeng Mohan, Arvind Lin, Yen Ting Hader, Christoph Fasel, Hermann Chertkov, Misha Livescu, Daniel Graduate Interdisciplinary Program in Applied Mathematics Department of Mathematics University of Arizona TucsonAZ85721 United States Computer Computational and Statistical Sciences Division Los Alamos National Laboratory Los AlamosNM87544 United States Department of Aerospace and Mechanical Engineering University of Arizona TucsonAZ85721 United States

In this work, we apply, for the first time to spatially inhomogeneous flows, a recently developed data-driven learning algorithm of Mori-Zwanzig (MZ) operators, which is based on a generalized Koopman’s description of dynamical systems. The MZ formalism provides a mathematically exact procedure for constructing non-Markovian reduced-order models of resolved variables from high-dimensional dynamical systems, where the effects due to the unresolved dynamics are captured in the memory kernel and orthogonal dynamics. The algorithm developed in this work applies Mori’s linear projection operator and an SVD based compression to the selection of the resolved variables (equivalently, a low rank approximation of the two time covariance matrices). We show that this MZ decomposition not only identifies the same spatio-temporal structures found by DMD, but it can also be used to extract spatio-temporal structures of the hysteresis effects present in the memory kernels. We perform an analysis of these structures in the context of a laminar-turbulent boundary-layer transition flow over a flared cone at Mach 6, and show the dynamical relevance of the memory kernels. Additionally, by including these memory terms learned in our data-driven MZ approach, we show improvement in prediction accuracy over DMD at the same level of truncation and at a similar computational cost. Furthermore, an analysis of the spatio-temporal structures of the MZ operators shows identifiable structures associated with the nonlinear generation of the so-called "hot" streaks on the surface of the flared cone, which have previously been observed in experiments and direct numerical simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamic mode decomposition

On hom-yetter-drinfeld category 1

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International Conference on Stochastic Processes and Algebraic Structures, SPAS 2017

作者： Ma, Tianshui Silvestrov, Sergei Zheng, Huihui Henan Engineering Laboratory for Big Data Statistical Analysis and Optimal Control Henan Normal University Xinxiang453007 China Division of Applied Mathematics School of Education Culture and Communication Mälardalen University Box 883 Västerås72123 Sweden

ISBN: (数字)9783030418502

ISBN: (纸本)9783030418496

Let (H, β) be a Hom-Hopf algebra. Recently we introduced the Hom-Yetter-Drinfeld category HHYD via Radford biproduct Hom-Hopf algebra, and proved that HHYD is a braided tensor category. Let (H, β, R (or~σ)) be a quasitriangular (or cobraided) Hom-Hopf algebra. In this paper, we prove that the category HM (or HM) of left (H, β)-Hom-modules comodules) is a braided tensor subcategory of HHYD. As a generalization of Radford biproduct Hom-Hopf algebra, we derive necessary and sufficient conditions for R-smash product Hom-algebra (Formula Presented) and T-smash coproduct Hom-coalgebra (Formula Presented) to be a Hom-Hopf algebra. At last, two nontrivial examples are given. © Springer Nature Switzerland AG 2020.

关键词： Tensors

Energy-positive soaring using transient turbulent fluctuations

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arXiv 2023年

作者： He, Danyun Reddy, Gautam Rycroft, Chris H. John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Mathematics University of Wisconsin–Madison MadisonWI53706 United States Physics & Informatics Laboratories NTT Research Inc. SunnyvaleCA94085 United States Center for Brain Science Harvard University CambridgeMA02138 United States NSF-Simons Center for Mathematical & Statistical Analysis of Biology Harvard University CambridgeMA02138 United States Computational Research Division Lawrence Berkeley Laboratory BerkeleyCA94720 United States

Soaring birds gain energy from stable ascending currents or shear. However, it remains unclear whether energy loss due to drag can be overcome by extracting work from transient turbulent fluctuations. We designed numerical simulations of gliders navigating in a kinematic model that captures the spatio-temporal correlations of atmospheric turbulence. Energy extraction is enabled by an adaptive algorithm based on Monte Carlo tree search that dynamically filters acquired information about the flow to plan future paths. We show that net energy gain is feasible under realistic constraints. Glider paths reflect patterns of foraging, where exploration of the flow is interspersed with bouts of energy extraction through localized spirals. © 2023, CC BY-NC-ND.

关键词： Shear flow

Polygenic risk score and lung adenocarcinoma risk among never-smokers by EGFR mutation status-a brief report

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Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 2024年第4期20卷 521-530页

作者： Batel Blechter Chao Agnes Hsiung Xiaoyu Wang Haoyu Zhang Wei Jie Seow Jianxin Shi Nilanjan Chatterjee Hee Nam Kim Maria Pik Wong Yun-Chul Hong Jason Yy Wong Juncheng Dai H Dean Hosgood Zhaoming Wang I-Shou Chang Jiyeon Choi Jiucun Wang Minsun Song Wei Hu Wei Zheng Jin Hee Kim Baosen Zhou Demetrius Albanes Min-Ho Shin Lap Ping Chung She-Juan An Hong Zheng Yasushi Yatabe Xu-Chao Zhang Young Tae Kim Xiao-Ou Shu Young-Chul Kim Roel C H Vermeulen Bryan A Bassig Jiang Chang James Chung Man Ho Bu-Tian Ji Michiaki Kubo Yataro Daigo Yukihide Momozawa Yoichiro Kamatani Takayuki Honda Hideo Kunitoh Shun-Ichi Watanabe Yohei Miyagi Haruhiko Nakayama Shingo Matsumoto Masahiro Tsuboi Koichi Goto Zhihua Yin Atsushi Takahashi Akiteru Goto Yoshihiro Minamiya Kimihiro Shimizu Kazumi Tanaka Tangchun Wu Fusheng Wei Jian Su Yeul Hong Kim In-Jae Oh Victor Ho Fun Lee Wu-Chou Su Yuh-Min Chen Gee-Chen Chang Kuan-Yu Chen Ming-Shyan Huang Hsien-Chih Lin Adeline Seow Jae Yong Park Sun-Seog Kweon Chien-Jen Chen Yu-Tang Gao Chen Wu Biyun Qian Daru Lu Jianjun Liu Hyo-Sung Jeon Chin-Fu Hsiao Jae Sook Sung Ying-Huang Tsai Yoo Jin Jung Huan Guo Zhibin Hu Tzu-Yu Chen Laurie Burdett Meredith Yeager Amy Hutchinson Sonja I Berndt Wei Wu Junwen Wang Jin Eun Choi Kyong Hwa Park Sook Whan Sung Li Liu Chang Hyun Kang Chung-Hsing Chen Jun Xu Peng Guan Wen Tan Chih-Liang Wang Alan Dart Loon Sihoe Ying Chen Yi Young Choi Jun Suk Kim Ho-Il Yoon Qiuyin Cai In Kyu Park Ping Xu Qincheng He Chih-Yi Chen Junjie Wu Wei-Yen Lim Kun-Chieh Chen John K C Chan Jihua Li Hongyan Chen Chong-Jen Yu Li Jin Joseph F Fraumeni Jie Liu Maria Teresa Landi Taiki Yamaji Yang Yang Belynda Hicks Kathleen Wyatt Shengchao A Li Hongxia Ma Bao Song Zhehai Wang Sensen Cheng Xuelian Li Yangwu Ren Motoki Iwasaki Junjie Zhu Gening Jiang Ke Fei Guoping Wu Li-Hsin Chien Fang-Yu Tsai Jinming Yu Victoria L Stevens Pan-Chyr Yang Dongxin Lin Kexin Chen Yi-Long Wu Keitaro Matsuo Nathaniel Rothman Kouya Shiraishi Hongbing Shen Stephen J Chanock Takashi Kohno Qing Lan Division of Cancer Epidemiology and Genetics National Cancer Institute Rockville MD USA. Institute of Population Health Sciences National Health Research Institutes Zhunan Taiwan. Division of Cancer Epidemiology and Genetics National Cancer Institute Rockville MD USA Saw Swee Hock School of Public Health National University of Singapore and National University Health System Singapore Singapore Department of Medicine Yong Loo Lin School of Medicine National University of Singapore and National University Health System Singapore Singapore. Department of Oncology School of Medicine Johns Hopkins University Baltimore MD USA Department of Biostatistics Johns Hopkins Bloomberg School of Public Health Baltimore MD USA. Department of Preventive Medicine Chonnam National University Medical School Gwangju Republic of Korea. Department of Pathology Queen Mary Hospital Hong Kong Hong Kong. Department of Preventive Medicine Seoul National University College of Medicine Seoul Republic of Korea. Epidemiology and Community Health Branch National Heart Lung and Blood Institute Bethesda MD USA. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Epidemiology and Population Health Albert Einstein College of Medicine New York USA. Department of Computational Biology St. Jude Children's Research Hospital Memphis TN USA. National Institute of Cancer Research National Health Research Institutes Zhunan Taiwan. Ministry of Education Key Laboratory of Contemporary Anthropology School of Life Sciences Fudan University Shanghai China State Key Laboratory of Genetic Engineering School of Life Sciences Fudan University Shanghai China. Department of Statistics & Research Institute of Natural Sciences Sookmyung Women's University Seoul 04310 Korea. Division of Epidemiology Department of Medicine Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center Nashville TN USA. Department of Environmental Health

We assessed the association between a genome-wide polygenic risk score (PRS) developed for lung adenocarcinoma (LUAD) risk and mutation on the epidermal growth factor receptor (EGFR) gene in 998 East Asian never-smoking female LUAD cases (518 EGFR-positive; 480 EGFR-negative) and 4,544 never-smoking controls using case-case and multinomial regression analyses. We found that the PRS was more strongly associated with EGFR-positive LUAD compared to EGFR-negative LUAD, where the association between the fourth quartile of the PRS and EGFR-positive LUAD (OR=8.63, 95% CI:5.67, 13.14) was significantly higher than the association between the fourth quartile of the PRS with EGFR-negative LUAD (OR=3.50, 95% CI: 2.44, 5.00) (p-heterogeneity=3.66x10). Our findings suggest that germline genetic susceptibility may be differentially associated with LUAD in never-smoking female East Asian patients depending on the cancer's mutation status, which may have important public health and clinical implications.

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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

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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

Lattice QCD and Particle Physics

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arXiv 2022年

作者： Kronfeld, Andreas S. Bhattacharya, Tanmoy Blum, Thomas Christ, Norman H. DeTar, Carleton Detmold, William Edwards, Robert Hasenfratz, Anna Lin, Huey-Wen Mukherjee, Swagato Orginos, Konstantinos Brower, Richard Cirigliano, Vincenzo Davoudi, Zohreh Jóo, Bálint Jung, Chulwoo Lehner, Christoph Meinel, Stefan Neil, Ethan T. Petreczky, Peter Richards, David G. Bazavov, Alexei Catterall, Simon Dudek, Jozef J. El-Khadra, Aida X. Engelhardt, Michael Fleming, George T. Giedt, Joel Gupta, Rajan Hansen, Maxwell T. Izubuchi, Taku Karsch, Frithjof Laiho, Jack Liu, Keh-Fei Meyer, Aaron S. Rinaldi, Enrico Savage, Martin Schaich, David Shanahan, Phiala E. Sharpe, Stephen R. Sufian, Raza Syritsyn, Sergey Van de Water, Ruth S. Wagman, Michael L. Weinberg, Evan Witzel, Oliver Aubin, Christopher Boyle, Peter Chandrasekharan, Shailesh Cloët, Ian C. Constantinou, Martha Cushman, Kimmy DeGrand, Thomas Fodor, Zoltan Foreman, Sam Gottlieb, Steven Hoying, Daniel Jang, Yong-Chull Jay, William I. Jin, Xiao-Yong Kelly, Christopher Kuti, Julius Lamm, Henry Lin, Meifeng Lin, Yin Lytle, Andrew T. Mackenzie, Paul Mandula, Jeffrey Meurice, Yannick Monahan, Christopher Morningstar, Colin Osborn, James C. Park, Sungwoo Simone, James N. Strelchenko, Alexei Tomii, Masaaki Vaquero, Alejandro Vranas, Pavlos Wang, Bigeng Wilcox, Walter Yoon, Boram Zhao, Yong Theory Division Fermi National Accelerator Laboratory BataviaIL60510 United States Group T-2 Los Alamos National Laboratory Los AlamosNM87545 United States Department of Physics University of Connecticut StorrsCT06269 United States RIKEN BNL Research Center Brookhaven National Laboratory UptonNY11973 United States Department of Physics Columbia University New YorkNY10027 United States Department of Physics and Astronomy University of Utah Salt Lake CityUT84112 United States Center for Theoretical Physics Massachusetts Institute of Technology CambridgeMA02139 United States The NSF Institute for Artificial Intelligence and Fundamental Interactions Theory Center Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States Department of Physics University of Colorado BoulderCO80309 United States Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Physics Department Brookhaven National Laboratory UptonNY11973 United States Department of Physics College of William & Mary WilliamsburgVA23187 United States Department of Physics Center for Computational Science Boston University BostonMA02215 United States Institute of Nuclear Theory University of Washington SeattleWA98195 United States Department of Physics Maryland Center for Fundamental Physics University of Maryland College ParkMD20742 United States Oak Ridge Leadership Computing Facility Oak Ridge National Laboratory Oak RidgeTN37831 United States Fakultät für Physik Universität Regensburg RegensburgD-93040 Germany Department of Physics University of Arizona TucsonAZ85721 United States Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Physics Syracuse University SyracuseNY13244 United States Department of Physics University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Physics New Mexic

Lattice field theory provides a mathematically rigorous definition of quantum field theory, including gauge theories. The rigor provides a platform for computation of strongly-coupled gauge theories, not only quantum chromodynamics (QCD) at long-distances but also strongly-coupled sectors that might lie beyond the Standard Model (BSM) of particle physics. Indeed, the interpretation of many experiments in particle physics, nuclear physics, and astrophysics relies, often crucially, on results from lattice QCD or BSM. In quark-flavor physics, lattice QCD is essential for grounding theoretical predictions. Together with experimental measurements, lattice QCD is used to determine many of the fundamental parameters of the Standard Model's flavor sector: five out of six quark masses and the three mixing angles and CP-violating phase of the Cabibbo-Kobayashi-Maskawa (CKM) matrix. Further Standard-Model predictions requiring lattice QCD are for processes that could reveal signatures of new physics. This area of lattice QCD has become a precision science, as has the determination of the strong coupling, αs, which is key in many areas, for example for understanding Higgs-boson decay to gluons. Lattice-QCD calculations of the hadronic contributions to the anomalous magnetic moment of the muon are another area for which precision is both mandatory and achievable. While these contributions can be estimated via a combination of certain measurements and general theoretical concepts, a direct ab initio calculation from QCD is desirable to confirm robustly the tantalizingly large discrepancy between experiment and the Standard Model. Other indirect searches for new physics are complementary to quark-flavor physics and the muon anomalous magnetic moment. Lattice QCD is an essential tool for understanding newly discovered hadrons with quark content different from the usual baryons and mesons. Lattice-QCD calculations are needed to interpret bounds on electric dipole moments, proton dec

关键词： Calculations

Horizons: Nuclear Astrophysics in the 2020s and Beyond

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arXiv 2022年

作者： Schatz, Hendrik Becerril Reyes, A.D. Best, A. Brown, E.F. Chatziioannou, K. Chipps, K.A. Deibel, C.M. Ezzeddine, R. Galloway, D.K. Hansen, C.J. Herwig, F. Ji, A.P. Lugaro, M. Meisel, Z. Norman, D. Read, J.S. Roberts, L.F. Spyrou, A. Tews, I. Timmes, F.X. Travaglio, C. Vassh, N. Abia, C. Adsley, P. Agarwal, S. Aliotta, M. Aoki, W. Arcones, A. Aryan, A. Bandyopadhyay, A. Banu, A. Bardayan, D.W. Barnes, J. Bauswein, A. Beers, T.C. Bishop, J. Boztepe, T. Côté, B. Caplan, M.E. Champagne, A.E. Clark, J.A. Couder, M. Couture, A. de Mink, S.E. Debnath, S. deBoer, R.J. den Hartogh, J. Denissenkov, P. Dexheimer, V. Dillmann, I. Escher, J.E. Famiano, M.A. Farmer, R. Fisher, R. Fröhlich, C. Frebel, A. Fryer, C. Fuller, G. Ganguly, A.K. Ghosh, S. Gibson, B.K. Gorda, T. Gourgouliatos, K.N. Graber, V. Gupta, M. Haxton, W. Heger, A. Hix, W.R. Ho, W.C.G. Holmbeck, E.M. Hood, A.A. Huth, S. Imbriani, G. Izzard, R.G. Jain, R. Jayatissa, H. Johnston, Z. Kajino, T. Kankainen, A. Kiss, G.G. Kwiatkowski, A. La Cognata, M. Laird, A.M. Lamia, L. Landry, P. Laplace, E. Launey, K.D. Leahy, D. Leckenby, G. Lennarz, A. Longfellow, B. Lovell, A.E. Lynch, W.G. Lyons, S.M. Maeda, K. Masha, E. Matei, C. Merc, J. Messer, B. Montes, F. Mukherjee, A. Mumpower, M. Neto, D. Nevins, B. Newton, W.G. Nguyen, L.Q. Nishikawa, K. Nishimura, N. Nunes, F.M. O’Connor, E. O’Shea, B.W. Ong, W.-J. Pain, S.D. Pajkos, M.A. Pignatari, M. Pizzone, R.G. Placco, V.M. Plewa, T. Pritychenko, B. Psaltis, A. Puentes, D. Qian, Y.-Z. Radice, D. Rapagnani, D. Rebeiro, B.M. Reifarth, R. Richard, A.L. Rijal, N. Roederer, I.U. Rojo, J.S. Sk, J. Saito, Y. Schwenk, A. Sergi, M.L. Sidhu, R.S. Simon, A. Sivarani, T. Skúladóttir, Á. Smith, M.S. Spiridon, A. Sprouse, T.M. Starrfield, S. Steiner, A.W. Strieder, F. Sultana, I. Surman, R. Szücs, T. Tawfik, A. Thielemann, F. Trache, L. Trappitsch, R. Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Facility for Rare Isotope Beams Michigan State University East LansingMI48824 United States United States Department of Physics University of Naples"Federico II" Napoli80126 Italy INFN - Sezione di Napoli Napoli80126 Italy Department of Computational Mathematics Science and Engineering MichiganState University East LansingMI48824 United States Department of Physics California Institute of Technology PasadenaCA91125 United States LIGO Laboratory California Institute of Technology PasadenaCA91125 United States Physics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics and Astronomy University of Tennessee Knoxville KnoxvilleTN37996 United States Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States Department of Astronomy University of Florida GainesvilleFL32601 United States School of Physics and Astronomy Monash University VIC3800 Australia OzGRav-Monash School of Physics & Astronomy Monash University VIC3800 Australia Goethe University Frankfurt Institute for Applied Physics Max-von-Laue-Str. 12 Frankfurt am Main60438 Germany Technical University of Darmstadt Institute for Nuclear Physics Germany Max Planck Institute for Astronomy Heidelberg Germany Department of Physics and Astronomy University of Victoria VictoriaBCV8P 5C2 Canada Department of Astronomy & Astrophysics University of Chicago 5640 S Ellis Avenue ChicagoIL60637 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Excellence Centre of the Hungarian Academy of Sciences Konkoly-Thege Miklós út 15-17 BudapestH-1121 Hungary ELTE Eötvös Loránd University Institute of Physics Pázmány Péter sétány 1/A Budapest1117 Hungary Institute of Nuclear & Particle Physics Department of Physics & Astronomy Ohio University AthensOH45701

Nuclear Astrophysics is a field at the intersection of nuclear physics and astrophysics, which seeks to understand the nuclear engines of astronomical objects and the origin of the chemical elements. This white paper summarizes progress and status of the field, the new open questions that have emerged, and the tremendous scientific opportunities that have opened up with major advances in capabilities across an ever growing number of disciplines and subfields that need to be integrated. We take a holistic view of the field discussing the unique challenges and opportunities in nuclear astrophysics in regards to science, diversity, education, and the interdisciplinarity and breadth of the field. Clearly nuclear astrophysics is a dynamic field with a bright future that is entering a new era of discovery opportunities. © 2022, CC BY-NC-SA.

关键词： Astrophysics

Author Correction: Community-wide hackathons to identify central themes in single-cell multi-omics

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Genome biology 2021年第1期22卷 246页

作者： Kim-Anh Lê Cao Al J Abadi Emily F Davis-Marcisak Lauren Hsu Arshi Arora Alexis Coullomb Atul Deshpande Yuzhou Feng Pratheepa Jeganathan Melanie Loth Chen Meng Wancen Mu Vera Pancaldi Kris Sankaran Dario Righelli Amrit Singh Joshua S Sodicoff Genevieve L Stein-O'Brien Ayshwarya Subramanian Joshua D Welch Yue You Ricard Argelaguet Vincent J Carey Ruben Dries Casey S Greene Susan Holmes Michael I Love Matthew E Ritchie Guo-Cheng Yuan Aedin C Culhane Elana Fertig Melbourne Integrative Genomics School of Mathematics and Statistics University of Melbourne Melbourne Australia. kimanh.lecao@nimelb.edu.au. Melbourne Integrative Genomics School of Mathematics and Statistics University of Melbourne Melbourne Australia. McKusick-Nathans Institute of the Department of Genetic Medicine Johns Hopkins School of Medicine Baltimore MD USA. Data Science Dana-Farber Cancer Institute Boston MA USA. Biostatistics Harvard TH Chan School of Public Health Boston MA USA. Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA. Centre de Recherches en Cancérologie de Toulouse (INSERM) Université Paul Sabatier III Toulouse France. Cancer Convergence Institute and Division of Quantitative Sciences Department of Oncology Sidney Kimmel Comprehensive Cancer Center Johns Hopkins University School of Medicine Baltimore MD USA. Department of Mathematics and Statistics McMaster University Hamilton Canada. Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS) School of Life Sciences Technical University of Munich Munich Germany. Department of Biostatistics UNC Chapel Hill NC USA. Barcelona Supercomputing Center Barcelona Spain. Department of Statistics University of Wisconsin Madison WI USA. Department of Statistical Sciences University of Padova Padova PD Italy. Department of Pathology and Laboratory Medicine University of British Columbia Vancouver BC Canada. PROOF Centre of Excellence Vancouver BC Canada. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. Department of Biomedical Engineering University of Michigan Ann Arbor MI USA. Department of Neuroscience Johns Hopkins University Baltimore MD USA. Kavli Neuroscience Discovery Institute Johns Hopkins University Baltimore MD USA. Klarman Cell Observatory Broad Institute of MIT and Harvard Cambridge MA USA. Department of Computer Science and Engineering University of Michiga