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arXiv 2020年

作者： Naess, Sigurd Aiola, Simone Austermann, Jason E. Battaglia, Nick Beall, James A. Becker, Daniel T. Bond, Richard J. Calabrese, Erminia Choi, Steve K. Cothard, Nicholas F. Crowley, Kevin T. Darwish, Omar Datta, Rahul Denison, Edward V. Devlin, Mark Duell, Cody J. Duff, Shannon M. Duivenvoorden, Adriaan J. Dunkley, Jo Dünner, Rolando Fox, Anna E. Gallardo, Patricio A. Halpern, Mark Han, Dongwon Hasselfield, Matthew Hill, J. Colin Hilton, Gene C. Hilton, Matt Hincks, Adam D. Hložek, Renée Ho, Shuay-Pwu Patty Hubmayr, Johannes Huffenberger, Kevin Hughes, John P. Kosowsky, Arthur B. Louis, Thibaut Madhavacheril, Mathew S. McMahon, Jeff Moodley, Kavilan Nati, Federico Nibarger, John P. Niemack, Michael D. Page, Lyman Partridge, Bruce Salatino, Maria Schaan, Emmanuel Schillaci, Alessandro Schmitt, Benjamin Sherwin, Blake D. Sehgal, Neelima Sifón, Cristóbal Spergel, David Staggs, Suzanne Stevens, Jason Storer, Emilie Ullom, Joel N. Vale, Leila R. van Engelen, Alexander van Lanen, Jeff Vavagiakis, Eve M. Wollack, Edward J. Xu, Zhilei Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Astrophysical Sciences Peyton Hall Princeton University PrincetonNJ08544 United States Joseph Henry Laboratories of Physics Jadwin Hall Princeton University PrincetonNJ08544 United States Department of Physics and Astronomy Haverford College HaverfordPA19041 United States Laboratoire de l’Accélérateur Linéaire Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France NASA/Goddard Space Flight Center GreenbeltMD20771 United States Physics and Astronomy Department Stony Brook University Stony BrookNY11794 United States Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa Department of Physics California Institute of Technology PasadenaCA91125 United States Instituto de Física Pontificia Universidad Católica de Valparaíso Chile Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States School of Physics and Astronomy Cardiff University The Parade Cardiff WalesCF24 3AA United Kingdom Department of Physics University of Milano-Bicocca Piazza della Scienza 3 MilanoMI20126 Italy Astrophysics Research Centre School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban4041 South Africa Department of Physics and Astronomy Rutgers State University of New Jersey PiscatawayNJ08854-8019 United States StanfordCA United States Instituto de Astrofísica and Centro de Astro-Ingeniería Facultad de Física Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Department of Physics Cornell University IthacaNY14853 United States Department of Astronomy Cornell University IthacaNY14853 United States Dept. of Physics and Astronomy Johns Hopkins University 3400 N. Charles St. BaltimoreMD21218 United States NIST Q

This paper presents a maximum-likelihood algorithm for combining sky maps with disparate sky coverage, angular resolution and spatially varying anisotropic noise into a single map of the sky. We use this to merge hundreds of individual maps covering the 2008–2018 ACT observing seasons, resulting in by far the deepest ACT maps released so far. We also combine the maps with the full Planck maps, resulting in maps that have the best features of both Planck and ACT: Planck’s nearly white noise on intermediate and large angular scales and ACT’s high-resolution and sensitivity on small angular scales. The maps cover over 18 000 square degrees, nearly half the full sky, at 100, 150 and 220 GHz. They reveal 4 000 optically-confirmed clusters through the Sunyaev Zel’dovich effect (SZ) and 18 500 point source candidates at > 5σ, the largest single collection of SZ clusters and millimeter wave sources to date. The multi-frequency maps provide millimeter images of nearby galaxies and individual Milky Way nebulae, and even clear detections of several nearby stars. Other anticipated uses of these maps include, for example, thermal SZ and kinematic SZ cluster stacking, CMB cluster lensing and galactic dust science. The method itself has negligible bias. However, due to the preliminary nature of some of the component data sets, we caution that these maps should not be used for precision cosmological analysis. The maps are part of ACT DR5, and are available on LAMBDA at https://***/product/act/actpol_prod_***. There is also a web atlas at https://***/public/snaess/actpol/dr5/atlas. © 2020, CC0.

关键词： Galaxies

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A Geometric Approach for the Upper Bound Theorem for Minkowski Sums of Convex Polytopes 31

A Geometric Approach for the Upper Bound Theorem for Minkows...

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31st International Symposium on computational Geometry, SoCG 2015

作者： Karavelas, Menelaos I. Tzanaki, Eleni Department of Mathematics and Applied Mathematics University of Crete Heraklion Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas Heraklion Greece

ISBN: (纸本)9783939897835

We derive tight expressions for the maximum number of κ-faces, 0 ≤ κ ≤ d - 1, of the Minkowski sum, P1++Pr, of r convex d-polytopes P1, . . . ,Pr in d, where d ≥ 2 and r 1 + + Pr as a section of the Cayley polytope C of the summands;bounding the κ-faces of P1 + + Pr reduces to bounding the subset of the (k + r - 1)-faces of C that contain vertices from each of the r polytopes. We end our paper with a sketch of an explicit construction that establishes the tightness of the upper bounds.

关键词： Algebra

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Time reversal in elastodynamics and applications to structural health monitoring 5

Time reversal in elastodynamics and applications to structur...

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5th ECCOMAS Thematic Conference on computational Methods in Structural Dynamics and Earthquake Engineering, COMPDYN 2015

作者： Panagiotopoulos, Christos G. Petromichelakis, Yiannis Tsogka, Chrysoula Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas Heraklion Greece Department of Mathematics and Applied Mathematics University of Crete Heraklion Greece

In structural health monitoring, detection of localized damage can be achieved by exploiting recorded signals at a limited number of sensors within the structure. Here we propose the localization of damage using an array of sensors as a computational time-reversal mirror (TRM). Time reversal (TR) is a physical process that exploits the time reversibility of wave equations and achieves re-focusing of the wave on the source of its origin by sending back, reversed in time, the signals recorded on an array of transducers. TR was originally introduced by Mathias Fink and his group and has several applications ranging from medical imaging to telecommunications [14]. In the present work, we perform time reversal numerically in order to effectively detect and localize defects in a bounded two-dimensional elastic domain. This is a generalization of a respective time-reversal implementation in an acoustic medium [12]. The solid contains a number of Nr sensors which can act as sources as well. Our data is the response matrix of the scattered field, that is, the difference between the total field obtained in the damaged structure and the incident field corresponding to the response in the healthy structure. Numerical solution of the wave propagation problem is performed using a mixed finite element formulation in terms of the velocity and stress fields [6]. In order to dissociate the response caused by Nd different defects, we apply the singular value decomposition (SVD) of the response matrix, while back-propagation of the projection of each singular vector corresponding to a non-zero singular value is performed in order to highlight each defect separately.

关键词： Damage detection

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Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017)

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NATURE GENETICS 2018年第5期50卷 765-766页

作者： Turcot, Valerie Lu, Yingchang Highland, Heather M. Schurmann, Claudia Justice, Anne E. Fine, Rebecca S. Bradfield, Jonathan P. Esko, Tonu Giri, Ayush Graff, Mariaelisa Guo, Xiuqing Hendricks, Audrey E. Karaderi, Tugce Lempradl, Adelheid Locke, Adam E. Mahajan, Anubha Marouli, Eirini Sivapalaratnam, Suthesh Young, Kristin L. Alfred, Tamuno Feitosa, Mary F. Masca, Nicholas G. D. Manning, Alisa K. Medina-Gomez, Carolina Mudgal, Poorva Ng, Maggie C. Y. Reiner, Alex P. Vedantam, Sailaja Willems, Sara M. Winkler, Thomas W. Abecasis, Goncalo Aben, Katja K. Alam, Dewan S. Alharthi, Sameer E. Allison, Matthew Amouyel, Philippe Asselbergs, Folkert W. Auer, Paul L. Balkau, Beverley Bang, Lia E. Barroso, Ines Bastarache, Lisa Benn, Marianne Bergmann, Sven Bielak, Lawrence F. Bluher, Matthias Boehnke, Michael Boeing, Heiner Boerwinkle, Eric Boger, Carsten A. Bork-Jensen, Jette Bots, Michiel L. Bottinger, Erwin P. Bowden, Donald W. Brandslund, Ivan Breen, Gerome Brilliant, Murray H. Broer, Linda Brumat, Marco Burt, Amber A. Butterworth, Adam S. Campbell, Peter T. Cappellani, Stefania Carey, David J. Catamo, Eulalia Caulfield, Mark J. Chambers, John C. Chasman, Daniel I. Chen, Yii-Der I. Chowdhury, Rajiv Christensen, Cramer Chu, Audrey Y. Cocca, Massimiliano Collins, Francis S. Cook, James P. Corley, Janie Galbany, Jordi Corominas Cox, Amanda J. Crosslin, David S. Cuellar-Partida, Gabriel D'Eustacchio, Angela Danesh, John Davies, Gail Bakker, Paul I. W. Groot, Mark C. H. Mutsert, Renee Deary, Ian J. Dedoussis, George Demerath, Ellen W. Heijer, Martin Hollander, Anneke I. Ruijter, Hester M. Dennis, Joe G. Denny, Josh C. Angelantonio, Emanuele Drenos, Fotios Du, Mengmeng Dube, Marie-Pierre Dunning, Alison M. Easton, Douglas F. Edwards, Todd L. Ellinghaus, David Ellinor, Patrick T. Elliott, Paul Evangelou, Evangelos Farmaki, Aliki-Eleni Farooqi, I. Sadaf Faul, Jessica D. Fauser, Sascha Feng, Shuang Ferrannini, Ele Ferrieres, Jean Florez, Jose C. Ford, Ian Fornage, Myriam Franco, Oscar H. Franke, Andre Franks, Paul W. Friedrich, Ne Montreal Heart Institute Université de Montréal Montreal Quebec Canada Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA Department of Epidemiology University of North Carolina Chapel Hill NC USA Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Genetics Harvard Medical School Boston MA USA Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children’s Hospital Boston MA USA Center for Applied Genomics Division of Human Genetics Children’s Hospital of Philadelphia Philadelphia PA USA Quantinuum Research LLC San Diego CA USA Estonian Genome Center University of Tartu Tartu Estonia Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA Wellcome Trust Sanger Institute Hinxton UK Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (***35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

关键词： Genome-wide association studies Obesity

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Fixed point and periodic point results for α-type F-contractions in modular metric spaces

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Fixed Point Theory and Applications 2016年第1期2016卷 1-12页

作者： Padcharoen, Anantachai Gopal, Dhananjay Chaipunya, Parin Kumam, Poom Theoretical and Computational Science Center (TaCS-Center) Department of Mathematics King Mongkut’s University of Technology Thonburi (KMUTT) 126 Pracha-Uthit Road Bang Mod Thung Khru Bangkok 10140 Thailand Department of Applied Mathematics and Humanities S.V. National Institute of Technology Surat 395007 Gujarat India Department of Medical Research China Medical University Hospital China Medical University Taichung 40402 Taiwan

Motivated by Gopal et al. (Acta Math. Sci. 36B(3):1-14, 2016). We introduce the notion of α-type F-contraction in the setting of modular metric spaces which is independent from one given in (Hussain et al. in Fixed Point Theory Appl. 2015:158, 2015). Further, we establish some fixed point and periodic point results for such contraction. The obtained results encompass various generalizations of the Banach contraction principle and others. © 2016, Padcharoen et al.

关键词： fixed point modular metric space α-type F-contraction

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Erratum to: Insight into particle production mechanisms via angular correlations of identified particles in pp collisions at s=7 TeV

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The European Physical Journal C 2019年第12期79卷 1-9页

作者： Adam, J. Adamová, D. Aggarwal, M. M. Rinella, G. Aglieri Agnello, M. Agrawal, N. Ahammed, Z. Ahmad, S. Ahn, S. U. Aiola, S. Akindinov, A. Alam, S. N. Albuquerque, D. S. D. Aleksandrov, D. Alessandro, B. Alexandre, D. Molina, R. Alfaro Alici, A. Alkin, A. Alme, J. Alt, T. Altinpinar, S. Altsybeev, I. Prado, C. Alves Garcia An, M. Andrei, C. Andrews, H. A. Andronic, A. Anguelov, V. Anson, C. Antičić, T. Antinori, F. Antonioli, P. Anwar, R. Aphecetche, L. Appelshäuser, H. Arcelli, S. Arnaldi, R. Arnold, O. W. Arsene, I. C. Arslandok, M. Audurier, B. Augustinus, A. Averbeck, R. Azmi, M. D. Badalà, A. Baek, Y. W. Bagnasco, S. Bailhache, R. Bala, R. Baldisseri, A. Baral, R. C. Barbano, A. M. Barbera, R. Barile, F. Barioglio, L. Barnaföldi, G. G. Barnby, L. S. Barret, V. Bartalini, P. Barth, K. Bartke, J. Bartsch, E. Basile, M. Bastid, N. Basu, S. Bathen, B. Batigne, G. Camejo, A. Batista Batyunya, B. Batzing, P. C. Bearden, I. G. Beck, H. Bedda, C. Behera, N. K. Belikov, I. Bellini, F. Martinez, H. Bello Bellwied, R. Beltran, L. G. E. Belyaev, V. Bencedi, G. Beole, S. Bercuci, A. Berdnikov, Y. Berenyi, D. Bertens, R. A. Berzano, D. Betev, L. Bhasin, A. Bhat, I. R. Bhati, A. K. Bhattacharjee, B. Bhom, J. Bianchi, L. Bianchi, N. Bianchin, C. Bielčík, J. Bielčíková, J. Bilandzic, A. Biro, G. Biswas, R. Biswas, S. Blair, J. T. Blau, D. Blume, C. Bock, F. Bogdanov, A. Boldizsár, L. Bombara, M. Bonora, M. Book, J. Borel, H. Borissov, A. Borri, M. Botta, E. Bourjau, C. Braun-Munzinger, P. Bregant, M. Broker, T. A. Browning, T. A. Broz, M. Brucken, E. J. Bruna, E. Bruno, G. E. Budnikov, D. Buesching, H. Bufalino, S. Buhler, P. Buitron, S. A. I. Buncic, P. Busch, O. Buthelezi, Z. Butt, J. B. Buxton, J. T. Cabala, J. Caffarri, D. Caines, H. Caliva, A. Villar, E. Calvo Camerini, P. Capon, A. A. Carena, F. Carena, W. Carnesecchi, F. Castellanos, J. Castillo Castro, A. J. Casula, E. A. R. Sanchez, C. Ceballos Cerello, P. Cerkala, J. Chang, B. Chapeland, S. Chartier, M. Charvet, J. L. Chattopadhyay, S. Chauvin, A. Cherney, M. Cheshk Faculty of Nuclear Sciences and Physical Engineering Czech Technical University in Prague Prague Czech Republic Nuclear Physics Institute Academy of Sciences of the Czech Republic Řež u Prahy Czech Republic Physics Department Panjab University Chandigarh India European Organization for Nuclear Research (CERN) Geneva Switzerland Dipartimento DISAT del Politecnico and Sezione INFN Turin Italy Sezione INFN Turin Italy Indian Institute of Technology Bombay (IIT) Mumbai India Variable Energy Cyclotron Centre Kolkata India Department of Physics Aligarh Muslim University Aligarh India Korea Institute of Science and Technology Information Daejeon South Korea Yale University New Haven United States Institute for Theoretical and Experimental Physics Moscow Russia Universidade Estadual de Campinas (UNICAMP) Campinas Brazil National Research Centre Kurchatov Institute Moscow Russia School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Instituto de Física Universidad Nacional Autónoma de México Mexico City Mexico Centro Fermi-Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi’ Rome Italy Sezione INFN Bologna Italy Bogolyubov Institute for Theoretical Physics Kiev Ukraine Department of Physics and Technology University of Bergen Bergen Norway Faculty of Engineering Bergen University College Bergen Norway Frankfurt Institute for Advanced Studies Johann Wolfgang Goethe-Universität Frankfurt Frankfurt Germany V. Fock Institute for Physics St. Petersburg State University St. Petersburg Russia Universidade de São Paulo (USP) São Paulo Brazil Central China Normal University Wuhan China National Institute for Physics and Nuclear Engineering Bucharest Romania Research Division and ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Physics Department Creighton University Omaha United States Rudj

This document corrects two errors in Eur. Phys. J. C77 (2017) no. 8, 56: the incorrect referencing of Fig. 1 labels in three paragraphs in the results section and a missing acknowledgements section.

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meson production at forward rapidity in Pb–Pb collisions at √sNN=2.76 TeV

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European Physical Journal C 2018年第7期78卷 1-18页

作者： Acharya, S. Acosta, F.-T. Adamová, D. Adolfsson, J. Aggarwal, M.M. Aglieri Rinella, G. Agnello, M. Agrawal, N. Ahammed, Z. Ahn, S.U. Aiola, S. Akindinov, A. Al-Turany, M. Alam, S.N. Albuquerque, D.S.D. Aleksandrov, D. Alessandro, B. Alfaro Molina, R. Ali, Y. Alici, A. Alkin, A. Alme, J. Alt, T. Altenkamper, L. Altsybeev, I. Andrei, C. Andreou, D. Andrews, H.A. Andronic, A. Angeletti, M. Anguelov, V. Anson, C. Antičić, T. Antinori, F. Antonioli, P. Apadula, N. Aphecetche, L. Appelshäuser, H. Arcelli, S. Arnaldi, R. Arnold, O.W. Arsene, I.C. Arslandok, M. Audurier, B. Augustinus, A. Averbeck, R. Azmi, M.D. Badalà, A. Baek, Y.W. Bagnasco, S. Bailhache, R. Bala, R. Baldisseri, A. Ball, M. Baral, R.C. Barbano, A.M. Barbera, R. Barile, F. Barioglio, L. Barnaföldi, G.G. Barnby, L.S. Barret, V. Bartalini, P. Barth, K. Bartsch, E. Bastid, N. Basu, S. Batigne, G. Batyunya, B. Batzing, P.C. Bazo Alba, J.L. Bearden, I.G. Beck, H. Bedda, C. Behera, N.K. Belikov, I. Bellini, F. Bello Martinez, H. Bellwied, R. Beltran, L.G.E. Belyaev, V. Bencedi, G. Beole, S. Bercuci, A. Berdnikov, Y. Berenyi, D. Bertens, R.A. Berzano, D. Betev, L. Bhaduri, P.P. Bhasin, A. Bhat, I.R. Bhattacharjee, B. Bhom, J. Bianchi, A. Bianchi, L. Bianchi, N. Bianchin, C. Bielčík, J. Bielčíková, J. Bilandzic, A. Biro, G. Biswas, R. Biswas, S. Blair, J.T. Blau, D. Blume, C. Boca, G. Bock, F. Bogdanov, A. Boldizsár, L. Bombara, M. Bonomi, G. Bonora, M. Borel, H. Borissov, A. Borri, M. Botta, E. Bourjau, C. Bratrud, L. Braun-Munzinger, P. Bregant, M. Broker, T.A. Broz, M. Brucken, E.J. Bruna, E. Bruno, G.E. Budnikov, D. Buesching, H. Bufalino, S. Buhler, P. Buncic, P. Busch, O. Buthelezi, Z. Butt, J.B. Buxton, J.T. Cabala, J. Caffarri, D. Caines, H. Caliva, A. Calvo Villar, E. Camacho, R.S. Camerini, P. Capon, A.A. Carena, F. Carena, W. Carnesecchi, F. Castillo Castellanos, J. Castro, A.J. Casula, E.A.R. Ceballos Sanchez, C. Chandra, S. Chang, B. Foundation Yerevan Armenia Benemérita Universidad Autónoma de Puebla Puebla Mexico Bogolyubov Institute for Theoretical Physics National Academy of Sciences of Ukraine Kiev Ukraine Bose Institute Kolkata India Budker Institute for Nuclear Physics Novosibirsk Russia California Polytechnic State University San Luis ObispoCA United States Central China Normal University Wuhan China Centre de Calcul de l’IN2P3 Villeurbanne Lyon France Havana Cuba Mexico City and Mérida Mexico Centro Fermi-Museo Storico della Fisica e Centro Studi e Ricerche "Enrico Fermi’ Rome Italy Chicago State University ChicagoIL United States China Institute of Atomic Energy Beijing China Chonbuk National University Jeonju Korea Republic of Faculty of Mathematics Physics and Informatics Comenius University Bratislava Bratislava Slovakia Islamabad Pakistan Creighton University OmahaNE United States Department of Physics Aligarh Muslim University Aligarh India Department of Physics Ohio State University ColumbusOH United States Department of Physics Pusan National University Pusan Korea Republic of Department of Physics Sejong University Seoul Korea Republic of Department of Physics University of California BerkeleyCA United States Department of Physics University of Oslo Oslo Norway Department of Physics and Technology University of Bergen Bergen Norway Dipartimento di Fisica dell’Università ’La Sapienza’ and Sezione INFN Rome Italy Dipartimento di Fisica dell’Università and Sezione INFN Cagliari Italy Dipartimento di Fisica dell’Università and Sezione INFN Trieste Italy Dipartimento di Fisica dell’Università and Sezione INFN Turin Italy Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN Bologna Italy Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN Catania Italy Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN Padua Italy Dipartimento di Fisica ‘E.R. Caianiello’ dell’Università and Gruppo Collegato INFN

meson measurements provide insight into strangeness production, which is one of the key observables for the hot medium formed in high-energy heavy-ion collisions. ALICE measured production through its decay in muon pairs in Pb–Pb collisions at sNN=2.76 TeV in the intermediate transverse momentum range 2 TT range at midrapidity. The values of the nuclear modification factor in the two rapidity regions are in agreement within uncertainties. © 2018, CERN for the benefit of the ALICE collaboration.

关键词： Bosons

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Crossing fitness canyons by a finite population

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Physical Review E 2017年第6期95卷 062405-062405页

作者： David B. Saakian Alexander S. Bratus Chin-Kun Hu Theoretical Physics Research Group Ton Duc Thang University Ho Chi Minh City Vietnam Faculty of Applied Sciences Ton Duc Thang University Ho Chi Minh City Vietnam Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow 119992 Russia National Center for Theoretical Sciences National Tsing Hua University Hsinchu 30013 Taiwan Business School University of Shanghai for Science and Technology Shanghai 200093 China

We consider the Wright-Fisher model of the finite population evolution on a fitness landscape defined in the sequence space by a path of nearly neutral mutations. We study a specific structure of the fitness landscape: One of the intermediate mutations on the mutation path results in either a large fitness value (climbing up a fitness hill) or a low fitness value (crossing a fitness canyon), the rest of the mutations besides the last one are neutral, and the last sequence has much higher fitness than any intermediate sequence. We derive analytical formulas for the first arrival time of the mutant with two point mutations. For the first arrival problem for the further mutants in the case of canyon crossing, we analytically deduce how the mean first arrival time scales with the population size and fitness difference. The location of the canyon on the path of sequences has a crucial role. If the canyon is at the beginning of the path, then it significantly prolongs the first arrival time; otherwise it just slightly changes it. Furthermore, the fitness hill at the beginning of the path strongly prolongs the arrival time period; however, the hill located near the end of the path shortens it. We optimize the first arrival time by applying a nonzero selection to the intermediate sequences. We extend our results and provide a scaling for the valley crossing time via the depth of the canyon and population size in the case of a fitness canyon at the first position. Our approach is useful for understanding some complex evolution systems, e.g., the evolution of cancer.

关键词： Evolutionary dynamics

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SciPy 1.0—Fundamental algorithms for scientific computing in python

arXiv

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arXiv 2019年

作者： Virtanen, Pauli Gommers, Ralf Oliphant, Travis E. Haberland, Matt Reddy, Tyler Cournapeau, David Burovski, Evgeni Peterson, Pearu Weckesser, Warren Bright, Jonathan van der Walt, Stéfan J. Brett, Matthew Wilson, Joshua Millman, K. Jarrod Mayorov, Nikolay Nelson, Andrew R.J. Jones, Eric Kern, Robert Larson, Eric Carey, C.J. Polat, Ilhan Feng, Yu Moore, Eric W. VanderPlas, Jake Laxalde, Denis Perktold, Josef Cimrman, Robert Henriksen, Ian Quintero, E.A. Harris, Charles R. Archibald, Anne M. Ribeiro, Antônio H. Pedregosa, Fabian van Mulbregt, Paul University of Jyväskylä University of Jyväskylä FI-40014 Finland Quansight LLC AustinTX United States Ultrasound Imaging Mayo Clinic RochesterMN55902 United States Electrical Engineering Brigham Young University ProvoUT84604 United States Enthought Inc. AustinTX78701 United States Anaconda Inc AustinTX78701 United States BioResource and Agricultural Engineering Department California Polytechnic State University San Luis ObispoCA93407 United States Department of Mathematics University of California Los AngelesCA90025 United States Los Alamos National Laboratory Los AlamosNM87544 United States Independent Researcher Higher School of Economics Myasnitskaya 20 Moscow101000 Russia Independent Researcher Saue Estonia Department of Mechanics and Applied Mathematics Institute of Cybernetics Tallinn Technical University Akadeemia Rd 21 Tallinn Estonia Independent Researcher NY United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States School of Psychology University of Birmingham Edgbaston BirmighamB15 2TT United Kingdom Division of Biostatistics University of California BerkeleyCA94720 United States WayRay LLC Skolkovo Innovation Center Moscow143026 Russia Australian Nuclear Science and Technology Organisation Locked Bag 2001 Kirrawee DCNSW2232 Australia Institute for Learning and Brain Sciences University of Washington SeattleWA98195 United States College of Information and Computing Sciences University of Massachusetts Amherst AmherstMA01002 United States Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States Bruker Biospin Corp. 15 Fortune Drive BillericaMA01821 United States University of Washington SeattleWA98195 United States New Technologies - Research Centre University of West Bohemia Univerzitní 8 Plzeň306 14 Czech Republic Oden Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX7

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments. Copyright © 2019, The Authors. All rights reserved.

关键词： Open source software

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GW190521: A Binary Black Hole Merger with a Total Mass of 150 M⊙

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Physical Review Letters 2020年第10期125卷 101102-101102页

作者： R. Abbott T. D. Abbott S. Abraham F. Acernese K. Ackley C. Adams R. X. Adhikari V. B. Adya C. Affeldt M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar A. Aich L. Aiello A. Ain P. Ajith S. Akcay G. Allen A. Allocca P. A. Altin A. Amato S. Anand A. Ananyeva S. B. Anderson W. G. Anderson S. V. Angelova S. Ansoldi S. Antier S. Appert K. Arai M. C. Araya J. S. Areeda M. Arène N. Arnaud S. M. Aronson K. G. Arun Y. Asali S. Ascenzi G. Ashton S. M. Aston P. Astone F. Aubin P. Aufmuth K. AultONeal C. Austin V. Avendano S. Babak P. Bacon F. Badaracco M. K. M. Bader S. Bae A. M. Baer J. Baird F. Baldaccini G. Ballardin S. W. Ballmer A. Bals A. Balsamo G. Baltus S. Banagiri D. Bankar R. S. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker K. Barkett P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley M. Bazzan B. Bécsy M. Bejger I. Belahcene A. S. Bell D. Beniwal M. G. Benjamin J. D. Bentley F. Bergamin B. K. Berger G. Bergmann S. Bernuzzi C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser R. Bhandare A. V. Bhandari J. Bidler E. Biggs I. A. Bilenko G. Billingsley R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht G. Bissenbayeva M. Bitossi M. A. Bizouard J. K. Blackburn J. Blackman C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer Y. Boetzel G. Bogaert F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi S. Bose V. Bossilkov J. Bosveld Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley M. Branchesi J. E. Brau M. Breschi T. Briant J. H. Briggs F. Brighenti A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz A. Buikema T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic R. L. Byer M. Cabero L. Cadonati G. Cagnoli C. Cahillane J. Calderón Bustillo J. D. Callaghan T. A. Callister E. Calloni J. B. Camp M. Canepa K. C. Cannon H. Cao J. Cao G. Carapella F. Carbognani S. Caride M. F. Carney G. Carullo J. Casanueva Diaz C. Casentini J. Castañ LIGO California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Inter-University Centre for Astronomy and Astrophysics Pune 411007 India Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S.Angelo I-80126 Napoli Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Cambridge Cambridge CB2 1TN United Kingdom University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil The University of Texas Rio Grande Valley Brownsville Texas 78520 USA Gran Sasso Science Institute (GSSI) I-67100 L’Aquila Italy INFN Laboratori Nazionali del Gran Sasso I-67100 Assergi Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India NCSA University of Illinois at Urbana-Champaign Urbana Illinois 61801 USA INFN Sezione di Pisa I-56127 Pisa Italy Laboratoire des Matériaux Avancés (LMA) IP2I—UMR 5822 CNRS Université de Lyon F-69622 Villeurbanne France University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA SUPA University of Strathclyde Glasgow G1 1XQ United Kingdom Dipartimento di Matematica e Informatica Università di Udine I-33100 Udine Italy INFN Sezione di Trieste I-34127 Trieste Italy APC AstroP

On May 21, 2019 at 03:02:29 UTC Advanced LIGO and Advanced Virgo observed a short duration gravitational-wave signal, GW190521, with a three-detector network signal-to-noise ratio of 14.7, and an estimated false-alarm rate of 1 in 4900 yr using a search sensitive to generic transients. If GW190521 is from a quasicircular binary inspiral, then the detected signal is consistent with the merger of two black holes with masses of 85−14+21 M⊙ and 66−18+17 M⊙ (90% credible intervals). We infer that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, with only a 0.32% probability of being below 65 M⊙. We calculate the mass of the remnant to be 142−16+28 M⊙, which can be considered an intermediate mass black hole (IMBH). The luminosity distance of the source is 5.3−2.6+2.4 Gpc, corresponding to a redshift of 0.82−0.34+0.28. The inferred rate of mergers similar to GW190521 is 0.13−0.11+0.30 Gpc−3 yr−1.

关键词： Experimental studies of gravity General relativity Gravitational waves

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