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arXiv 2022年

作者： Jones, Michael G. Sand, David J. Bellazzini, Michele Spekkens, Kristine Karunakaran, Ananthan Adams, Elizabeth A.K. Battaglia, Giuseppina Beccari, Giacomo Bennet, Paul Cannon, John M. Cresci, Giovanni Crnojević, Denija Caldwell, Nelson Fuson, Jackson Guhathakurta, Puragra Haynes, Martha P. Inoue, John L. Magrini, Laura Muñoz, Ricardo R. Mutlu-Pakdil, Burçin Seth, Anil Strader, Jay Toloba, Elisa Zaritsky, Dennis Steward Observatory University of Arizona 933 North Cherry Avenue Rm. N204 TucsonAZ85721-0065 United States INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Gobetti 93/3 Bologna40129 Italy Department of Physics and Space Science Royal Military College of Canada P.O. Box 17000 Station Forces Kingston ONK7K 7B4 Canada Department of Physics Engineering Physics and Astronomy Queen's University KingstonONK7L 3N6 Canada Glorieta de la Astronomía Granada18008 Spain ASTRON The Netherlands Institute for Radio Astronomy Oude Hoogeveesedijk 4 Dwingeloo 7991 PD Netherlands Kapteyn Astronomical Institute PO Box 800 Groningen9700 AV Netherlands Instituto de Astrofísica de Canarias Vía Láctea s/n La Laguna 38205 Spain Universidad de La Laguna Avda. Astrofísico Fco. Sánchez Tenerife La LagunaE-38205 Spain European Southern Observatory Karl-Schwarzschild-Strasse 2 Garching bei München D-85748 Germany Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Department of Physics & Astronomy Macalester College 1600 Grand Avenue Saint PaulMN55105 United States INAF - Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 Firenze50125 Italy University of Tampa 401 West Kennedy Boulevard TampaFL33606 United States Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States UCO/Lick Observatory University of California Santa Cruz 1156 High Street Santa CruzCA95064 United States Cornell Center for Astrophysics and Planetary Science Space Sciences Building Cornell University IthacaNY14853 United States Departamento de Astronomía Universidad de Chile Camino El Observatorio 1515 Las Condes Santiago Chile Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Department of Astronomy and Astrophysics University of Chicago ChicagoIL60637 United States Department of Physics & Astronomy University of Utah Salt Lake City

We discuss five blue stellar systems in the direction of the Virgo cluster, analogous to the enigmatic object SECCO 1 (AGC 226067). These objects were identified based on their optical and UV morpholog☉y and followed up with H i observations with the VLA (and GBT), MUSE/VLT optical spectroscopy, and HST imaging. These new data indicate that one system is a distant group of galaxies. The remaining four are extremely low mass (M∗ ∼ 105 M☉), are dominated by young, blue stars, have highly irregular and clumpy morphologies, are only a few kpc across, yet host an abundance of metal-rich, 12 + log(O/H) > 8.2, H ii regions. These high metallicities indicate that these stellar systems formed from gas stripped from much more massive galaxies. Despite the young age of their stellar populations, only one system is detected in H i, while the remaining three have minimal (if any) gas reservoirs. Furthermore, two systems are surprisingly isolated and have no plausible parent galaxy within ∼30' (∼140 kpc). Although tidal stripping cannot be conclusively excluded as the formation mechanism of these objects, ram pressure stripping more naturally explains their properties, in particular their isolation, owing to the higher velocities, relative to the parent system, that can be achieved. Therefore, we posit that most of these systems formed from ram pressure stripped gas removed from new infalling cluster members, and survived in the intracluster medium long enough to become separated from their parent galaxies by hundreds of kiloparsecs, and that they thus represent a new type of stellar system. © 2022, CC BY.

关键词： Galaxies

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Constraining the Progenitor System of the Type Ia Supernova 2021aefx

arXiv

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arXiv 2022年

作者： Hosseinzadeh, Griffin Sand, David J. Lundqvist, Peter Andrews, Jennifer E. Bostroem, K. Azalee Dong, Yize Janzen, Daryl Jencson, Jacob E. Lundquist, Michael Retamal, Nicolas E. Meza Pearson, Jeniveve Valenti, Stefano Wyatt, Samuel Burke, Jamison Howell, D. Andrew McCully, Curtis Newsome, Megan Gonzalez, Estefania Padilla Pellegrino, Craig Terreran, Giacomo Kwok, Lindsey A. Jha, Saurabh W. Strader, Jay Kundu, Esha Ryder, Stuart D. Haislip, Joshua Kouprianov, Vladimir Reichart, Daniel E. Steward Observatory University of Arizona 933 North Cherry Avenue TucsonAZ85721-0065 United States Oskar Klein Centre Department of Astronomy Stockholm University Albanova University Centre StockholmSE-106 91 Sweden Gemini Observatory 670 North A'ohoku Place HiloHI96720-2700 United States Department of Astronomy University of Washington 3910 15th Avenue NE SeattleWA98195-0002 United States Department of Physics and Astronomy University of California Davis 1 Shields Avenue DavisCA95616-5270 United States Department of Physics & Engineering Physics University of Saskatchewan 116 Science Place SaskatoonSKS7N 5E2 Canada W. M. Keck Observatory 65-1120 Mamalahoa Highway KamuelaHI96743-8431 United States Las Cumbres Observatory 6740 Cortona Drive GoletaCA93117-5575 United States Department of Physics University of California Santa BarbaraCA93106-9530 United States Department of Physics and Astronomy Rutgers the State University of New Jersey 136 Frelinghuysen Road PiscatawayNJ08854-8019 United States Center for Data Intensive and Time Domain Astronomy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia Astronomy Astrophysics and Astrophotonics Research Centre Macquarie University SydneyNSW2109 Australia Department of Physics and Astronomy University of North Carolina 120 East Cameron Avenue Chapel HillNC27599 United States

We present high-cadence optical and ultraviolet light curves of the normal Type Ia supernova (SN) 2021aefx, which shows an early bump during the first two days of observation. This bump may be a signature of interaction between the exploding white dwarf and a nondegenerate binary companion, or it may be intrinsic to the white dwarf explosion mechanism. In the case of the former, the short duration of the bump implies a relatively compact main-sequence companion star, although this conclusion is viewing-angle dependent. Our best-fit companion-shocking and double-detonation models both overpredict the UV luminosity during the bump, and existing nickel-shell models do not match the strength and timescale of the bump. We also present nebular spectra of SN 2021aefx, which do not show the hydrogen or helium emission expected from a nondegenerate companion, as well as a radio nondetection that rules out all symbiotic progenitor systems and most accretion disk winds. Our analysis places strong but conflicting constraints on the progenitor of SN 2021aefx;no current model can explain all of our observations. Copyright © 2022, The Authors. All rights reserved.

关键词： Supernovae

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Peter H. Rose - Father of Ion Implantation: The Early Years

Peter H. Rose - Father of Ion Implantation: The Early Years

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International Conference on Ion Implantation Technology (IIT)

作者： Andrew Wittkower Geoffrey Ryding ESAT/STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In 1996, President Clinton presented Peter Rose with the National Medal of Technology and Innovation. This paper describes his innovations in ion implantation technology which led to the award presented twenty years l... 详细信息

ISBN: (纸本)9781538668306

关键词： Ion implantation Ion sources Business Technological innovation Acceleration Particle beams

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Publisher Correction: Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

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Nature genetics 2023年第1期55卷 166页

作者： Huipeng Li Elise T Courtois Debarka Sengupta Yuliana Tan Kok Hao Chen Jolene Jie Lin Goh Say Li Kong Clarinda Chua Lim Kiat Hon Wah Siew Tan Mark Wong Paul Jongjoon Choi Lawrence J K Wee Axel M Hillmer Iain Beehuat Tan Paul Robson Shyam Prabhakar Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India. Synthetic Biology Genome Institute of Singapore Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. Department of Pathology Singapore General Hospital Singapore Singapore. Department of Colorectal Surgery Singapore General Hospital Singapore Singapore. Data Analytics Department Institute for Infocomm Research Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. paul.robson@***. The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA. paul.robson@***. Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA. paul.robson@***. Department of Biological Sciences National University of Singapore Singapore Singapore. paul.robson@***. Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. prabhakars@gis.a-star.edu.sg.

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Making the most of data: Quantum monte carlo post-analysis revisited

arXiv

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arXiv 2019年

作者： Ichibha, Tom Hongo, Kenta Maezono, Ryo Thom, Alex J.W. School of Information Science JAIST 1-1 Asahidai Nomi Ishikawa923-1292 Japan Research Center for Advanced Computing Infrastructure JAIST 1-1 Asahidai Nomi Ishikawa923-1292 Japan Center for Materials Research by Information Integration Research and Services Division of Materials Data and Integrated System National Institute for Materials Science 1-2-1 Sengen Tsukuba305-0047 Japan PRESTO Japan Science and Technology Agency 4-1-8 Honcho Kawaguchi-shi Saitama322-0012 Japan Computational Engineering Applications Unit RIKEN 2-1 Hirosawa Wako Saitama351-0198 Japan Department of Chemistry University of Cambridge Lensfield Road CambridgeCB2 1EW United Kingdom

In quantum Monte Carlo (QMC) methods, energy estimators are calculated as the statistical average of the Markov chain sampling of energy estimator along with an associated statistical error. This error estimation is not straightforward and there are several choices of the error estimation methods. We evaluate the performance of three methods, Straatsma, an autoregressive model, and a blocking analysis based on von Neumann's ratio test for randomness, for the energy time-series given by Diffusion Monte Carlo, Full Configuration Interaction Quantum Monte Carlo and Coupled Cluster Monte Carlo methods. From these analyses we describe a hybrid analysis method which provides reliable error estimates for series of all lengths. Equally important is the estimation of the appropriate start point of the equilibrated phase, and two heuristic schemes are tested, establishing that MSER (mean squared error rule) gives reasonable and constant estimations independent of the length of time-series. Copyright © 2019, The Authors. All rights reserved.

关键词： Time series

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Corrigendum to “Single-walled carbon nanotube membranes for optical applications in the extreme ultraviolet rang” [155, (2019) 734–739]

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Carbon 2020年 156卷 576-576页

作者： V.M. Gubarev V.Y. Yakovlev M.G. Sertsu O.F. Yakushev V.M. Krivtsun Yu G. Gladush I.A. Ostanin A. Sokolov F. Schäfers V.V. Medvedev A.G. Nasibulin Moscow Institute of Physics and Technology (State University) Institutskiy pereulok str. 9 Dolgoprudny Moscow Region 141701 Russia Skolkovo Institute of Science and Technology Nobel str. 3 Moscow 121205 Russia Helmholtz Zentrum Berlin (BESSY-II) Albert-Einstein-Strasse 15 D-12489 Berlin Germany P. N. Lebedev Physical Institute of the Russian Academy of Science Moscow Russia Institute for Spectroscopy of the Russian Academy of Science Moscow Troitsk Russia Faculty of Physics Higher School of Economics Old Basmannya 21/4 Moscow Russia Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russia Multi-Scale Mechanics (MSM) Faculty of Engineering Technology MESA+ University of Twente Enschede the Netherlands Department of Applied Physics Aalto University 15100 FI-00076 Aalto Finland

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A decoupling two-grid method for the time-dependent poisson-nernst-planck equations

arXiv

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arXiv 2018年

作者： Shen, Ruigang Shu, Shi Yang, Ying Lu, Benzhuo School of Mathematics and Computational Science Xiangtan University Xiangtan Hunan411105 China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan411105 China School of Mathematics and Computational Science Guangxi Colleges Universities Key Laboratory of Data Analysis and Computation Guangxi Key Laboratory of Cryptography and information Security Guilin University of Electronic Technology Guilin Guangxi541004 China Institute of Computational Mathematics and Scientific/Engineering Computing National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

We study a two-grid strategy for decoupling the time-dependent Poisson-Nernst-Planck equations describing the mass concentration of ions and the electrostatic potential. The computational system is decoupled to smaller systems by using coarse space solutions at each time level, which can speed up the solution process compared with the finite element method combined with the Gummel iteration. We derive the optimal error estimates in L2 norm for both semi- and fully discrete finite element approximations. Based on the a priori error estimates, the error estimates in H1 norm are presented for the two-grid algorithm. The theoretical results indicate this decoupling method can retain the same accuracy as the finite element method. Numerical experiments including the Poisson-Nernst-Planck equations for an ion channel show the efficiency and effectiveness of the decoupling two-grid method. Copyright © 2018, The Authors. All rights reserved.

关键词： Finite element method

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End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems 18

End-to-end symmetry preserving inter-atomic potential energy...

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Proceedings of the 32nd International Conference on Neural Information Processing Systems

作者： Linfeng Zhang Jiequn Han Han Wang Wissam A. Saidi Roberto Car E. Weinan Program in Applied and Computational Mathematics Princeton University Institute of Applied Physics and Computational Mathematics China and CAEP Software Center for High Performance Numerical Simulation China Department of Mechanical Engineering and Materials Science University of Pittsburgh Program in Applied and Computational Mathematics Princeton University and Department of Chemistry and Department of Physics Princeton University and Princeton Institute for the Science and Technology of Materials Princeton University Program in Applied and Computational Mathematics Princeton University and Department of Mathematics Princeton University and Beijing Institute of Big Data Research China

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular interest is the inter-atomic potential energy surface (PES). Here we develop Deep Potential - Smooth Edition (DeepPot-SE), an end-to-end machine learning-based PES model, which is able to efficiently represent the PES of a wide variety of systems with the accuracy of ab initio quantum mechanics models. By construction, DeepPot-SE is extensive and continuously differentiable, scales linearly with system size, and preserves all the natural symmetries of the system. Further, we show that DeepPot-SE describes finite and extended systems including organic molecules, metals, semiconductors, and insulators with high fidelity.

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The GAPS Programme at TNG L TOI-4515 b: An eccentric warm Jupiter orbiting a 1.2 Gyr-old G-star

arXiv

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arXiv 2023年

作者： Carleo, I. Malavolta, L. Desidera, S. Nardiello, D. Wang, S. Turrini, D. Lanza, A.F. Baratella, M. Marzari, F. Benatti, S. Biazzo, K. Bieryla, A. Brahm, R. Bonavita, M. Collins, K.A. Hellier, C. Locci, D. Hobson, M.J. Maggio, A. Mantovan, G. Pinamonti, S. Messina, M. Rodriguez, J.E. Sozzetti, A. Stassun, K. Wang, X.Y. Ziegler, C. Damasso, M. Giacobbe, P. Murgas, F. Parviainen, H. Andreuzzi, G. Barkaoui, K. Berlind, P. Bignamini, A. Borsa, F. Briceno, C. Brogi, M. Cabona, L. Calkins, M.L. Capuzzo-Dolcetta, R. Cecconi, M. Colon, K.D. Cosentino, R. Dragomir, D. Esquerdo, G.A. Henning, T. Ghedina, A. Goeke, R.F. Gratton, R. Grau Horta, F. Gupta, A.F. Jenkins, J.M. Jordan, A. Knapic, C. Latham, D.W. Mireles, I. Law, N. Lorenzi, V. Lund, M.B. Maldonado, J. Mann, A.W. Molinari, E. Palle, E. Paegert, M. Pedani, M. Quinn, S.N. Scandariato, G. Seager, S. Winn, J.N. Wohler, B. Zingales, T. Calle Via Lactea s/n Tenerife La Laguna38200 Spain Tenerife La Laguna38206 Spain INAF - Osservatorio Astrofisico di Torino Via Osservatorio 20 Pino TorineseI-10025 Italy Dipartimento di Fisica e Astronomia "Galileo Galilei" Universita di Padova Vicolo dellOsservatorio 3 PadovaI-35122 Italy INAF - Osservatorio Astronomico di Padova Vicolo dell'Osservatorio 5 PadovaI-35122 Italy Astronomy Department Indiana University BloomingtonIN47405-7105 United States INAF - Osservatorio Astrofisico di Catania Via S. Sofia 78 CataniaI-95123 Italy An der Sternwarte 16 PotsdamD-14482 Germany INAF - Osservatorio Astronomico di Palermo Piazza del Parlamento1 PalermoI-90134 Italy Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Facultad de Ingeniera y Ciencias Universidad Adolfo Ibanez Av. Diagonal las Torres 2640 Penalolen Santiago Chile Millennium Institute for Astrophysics Chile Data Observatory Foundation Chile SUPA Institute for Astronomy University of Edinburgh Blackford Hill EdinburghEH9 3HJ United Kingdom Astrophysics Group Keele University Staffs ST5 5BG United Kingdom Max-Planck-Institut fur Astronomie Konigstuhl 17 Heidelberg69117 Germany Center for Data Intensive and Time Domain Astronomy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Department of Physics & Astronomy Vanderbilt University NashvilleTN United States Department of Physics Engineering and Astronomy Stephen F. Austin State University 1936 North St. NacogdochesTX75962 United States Fundacion Galileo Galilei-INAF Rambla Jose Ana Fernandez Perez 7 TF Brena Baja38712 Spain INAF - Osservatorio Astronomico di Roma Via Frascati 33 Monte Porzio Catone00078 Italy Astrobiology Research Unit Universite de Liege 19C Allee du 6 Aout Liege4000 Belgium Department of Earth Atmospheric and Planetary Science Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge

Context. Different theories have been developed to explain the origins and properties of close-in giant planets, but none of them alone can explain all of the properties of the warm Jupiters (WJs, Porb = 10 - 200 days). One of the most intriguing characteristics of WJs is that they have a wide range of orbital eccentricities, challenging our understanding of their formation and evolution. Aims. The investigation of these systems is crucial in order to put constraints on formation and evolution theories. TESS is providing a significant sample of transiting WJs around stars bright enough to allow spectroscopic follow-up studies. Methods. We carried out a radial velocity (RV) follow-up study of the TESS candidate TOI-4515 b with the high-resolution spectrograph HARPSN in the context of the GAPS project, the aim of which is to characterize young giant planets, and the TRES and FEROS spectrographs. We then performed a joint analysis of the HARPS-N, TRES, FEROS, and TESS data in order to fully characterize this planetary system. Results. We find that TOI-4515 b orbits a 1.2 Gyr-old G-star, has an orbital period of Pb = 15.266446 ± 0.000013 days, a mass of Mb = 2.01 ± 0.05 MJ, and a radius of Rb = 1.09 ± 0.04 RJ. We also find an eccentricity of e = 0.46 ± 0.01, placing this planet among the WJs with highly eccentric orbits. As no additional companion has been detected, this high eccentricity might be the consequence of past violent scattering events. Copyright © 2023, The Authors. All rights reserved.

关键词： Stars

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Unsupervised extraction of phenotypes from cancer clinical notes for association studies

arXiv

引用

arXiv 2019年

作者： Stark, Stefan G. Hyland, Stephanie L. Pradier, Melanie F. Lehmann, Kjong-Van Wicki, Andreas Perez-Cruz, Fernando Vogt, Julia E. Rätsch, Gunnar Computational Biology Program Memorial Sloan Kettering Cancer Center New York United States Tri-Institutional Ph.D. Program in Computational Biology and Medicine Weill Cornell Medicine New York United States Department of Computer Science ETH Zürich Zürich Switzerland Medical Informatics Group University Hospital Zürich Zürich Switzerland Swiss Institute for Bioinformatics Zurich Switzerland Department of Biology ETH Zürich Zürich Switzerland Department of Signal Processing and Information Theory University Carlos III in Madrid Leganés Spain School of Engineering and Applied Sciences Harvard University CambridgeMA United States Department of Biomedicine University of Basel Basel Switzerland Tumorzentrum University Hospital Basel Basel Switzerland Swiss Data Science Center ETH Zürich and EPFL Lausanne Switzerland Department of Mathematics and Computer Science University of Basel Basel Switzerland

The recent adoption of Electronic Health Records (EHRs) by healthcare providers has introduced an important source of data that provides detailed and highly specific insights into patient phenotypes over large cohorts. These datasets, in combination with machine learning and statistical approaches, generate new opportunities for research and clinical care. However, many methods require the patient representations to be in structured formats, while the information in the EHR is often locked in unstructured text designed for human readability. In this work, we develop the methodology to automatically extract clinical features from clinical narratives from large EHR corpora without the need for prior knowledge. We consider medical terms and sentences appearing in clinical narratives as atomic information units. We propose an efficient clustering strategy suitable for the analysis of large text corpora and utilize the clusters to represent information about the patient compactly. Additionally, we define the sentences on ontologic and natural language vocabularies to automatically detect pertinent combinations of concepts present in the corpus, even when an ontology is not available. To demonstrate the utility of our approach, we perform an association study of clinical features with somatic mutation profiles from 4,007 cancer patients and their tumors. We apply the proposed algorithm to a dataset consisting of .65 thousand documents with a total of .3.2 million sentences. After correcting for cancer type and other confounding factors, we identify a total of 340 significant statistical associations between the presence of somatic mutations and clinical features. We annotated these associations according to their novelty and we report several known associations. We also propose 37 plausible, testable hypothesis for associations where the underlying biological mechanism does not appear to be known. These results illustrate that the automated discovery of clinical features

关键词： Diseases

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