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SSRN 2023年

作者： Makra, László Matyasovszky, István Tusnády, Gábor Ziska, Lewis H. Hess, Jeremy J. Nyúl, László G. Chapman, Daniel S. Coviello, Luca Gobbi, Andrea Jurman, Giuseppe Furlanello, Cesare brunato, Mauro Damialis, Athanasios Charalampopoulos, Athanasios Müller-Schärer, Heinz Schneider, Norbert Szabó, bence Sümeghy, Zoltán Páldy, Anna Magyar, Donát bergmann, Karl-Christian Deák, Áron József Mikó, edit Thibaudon, Michel Oliver, Gilles Albertini, Roberto bonini, Maira Šikoparija, branko Radišić, Predrag Mitrović Josipović, Mirjana Gehrig, Regula Severova, elena Rodinkova, Victoria Palamarchuk, Olena Stjepanović, barbara Ianovici, Nicoleta berger, Uwe Kofol Seliger, Andreja Rybníček, Ondřej Myszkowska, Dorota Dąbrowska-Zapart, Katarzyna Majkowska-Wojciechowska, barbara Weryszko-Chmielewska, elzb.eta Grewling, Lukasz Rapiejko, Piotr Malkiewicz, Malgorzata Šaulienė, Ingrida Shalaboda, Valentina Prykhodo, Olexander Maleeva, Anna Ščevková, Jana bullock, James M. Institute of Economics and Rural Development Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Department of Meteorology Eötvös Loránd University P.O.B. 32 Budapest1518 Hungary Alfréd Rényi Institute of Mathematics P.O.B 127 Budapest1364 Hungary Mailman School of Public Health Columbia University New YorkNY10032 United States Department of Global Health University of Washington SeattleWA98105 United States Department of Image Processing and Computer Graphics University of Szeged P.O.B. 652 Szeged6701 Hungary Biological and Environmental Sciences Faculty of Natural Sciences University of Stirling Scotland StirlingFK9 4LA United Kingdom University of Trento Enogis s.r.l. Trento Italy Bruno Kessler Foundation Trento Italy HK3 Lab Orobix Life Srl Rovereto Bergamo Italy Department of Information Engineering and Computer Science University of Trento Trento Italy Terrestrial Ecology and Climate Change Department of Ecology School of Biology Aristotle University of Thessaloniki ThessalonikiGR-54124 Greece Departement of Biology Unit of Ecology and Evolution University of Fribourg FribourgCH-1700 Switzerland National Institute of Environmental Health Albert Flórián út 2-6 Budapest1097 Hungary Institute of Allergology Charité Hindenburgdamm 30 Berlin12203 Germany Institute of Animal Science and Wildlife Management Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Réseau National de Surveillance Aérobiologique 11 chemin de la Creuzille Le Plat du Pin Brussieu696905 France Laboratory of Hygiene and Aerobiology Department of Medicine and Surgery University of Parma U.O. Medicina Interna di Continuità Azienda Ospedaliero-Universitaria di Parma Via Gramsci 14 Parma43126 Italy Hygiene and Public Health Service via Spagliardi 19 Parabiago Milan20015 Italy BioSensе Institute Research Institute for Information Technologies in Biosystems University of Novi Sad Dr

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health prob.em across europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant’s reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating annual total pollen concentrations than those of the GM approach. These are the first published modeled maps using altitude correction and phenology to recover missing pollen information. We created a web page (http://***/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions. © 2023, The Authors. All rights reserved.

关键词： Climate change

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A universal equation to predict Ωmfrom halo and galaxy catalogues

arXiv

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arXiv 2023年

作者： Shao, Helen De Santi, Natalí S.M. Villaescusa-Navarro, Francisco Teyssier, Romain Ni, Yueying Anglés-Alcázar, Daniel Genel, Shy Steinwandel, Ulrich P. Hernández-Martínez, elena Dolag, Klaus Lovell, Christopher C. Garrison, Lehman H. Visbal, eli Kulkarni, Mihir Hernquist, Lars Castro, Tiago Vogelsberger, Mark Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08544 United States Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Instituto de Física Universidade de São Paulo R. do Matão 1371 São Paulo05508-900 Brazil Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA02138 United States McWilliams Center for Cosmology Department of Physics Carnegie Mellon University PittsburghPA15213 United States Department of Physics University of Connecticut 196 Auditorium Road U-3046 StorrsCT06269 United States Columbia Astrophysics Laboratory Columbia University New YorkNY10027 United States Universitäts-Sternwarte Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstr. 1 München81679 Germany Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Straße 1 Garching85741 Germany Institute of Cosmology and Gravitation University of Portsmouth Burnaby Road PortsmouthPO1 3FX United Kingdom Centre for Astrophysics Research School of Physics Engineering & Computer Science University of Hertfordshire HatfieldAL10 9AB United Kingdom Department of Physics and Astronomy Ritter Astrophysical Research Center University of Toledo 2801 W Bancroft Street ToledoOH43606 United States Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA02138 United States INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI-34143 Italy INFN Sezione di Trieste Via Valerio 2 TS TriesteI-34127 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy Kavli Institute for Astrophysics and Space Research Department of Physics Mit CambridgeMA02139 United States The Nsf Ai Institute for Artificial Intelligence and Fundamental Interactions Massachusetts Institute of Technology CambridgeMA02139 United States

We discover analytic equations that can infer the value of Ωmfrom the positions and velocity moduli of halo and galaxy catalogues. The equations are derived by combining a tailored graph neural network (GNN) architecture with symbolic regression. We first train the GNN on dark matter halos from Gadget N-body simulations to perform field-level likelihood-free inference, and show that our model can infer Ωmwith ∼ 6% accuracy from halo catalogues of thousands of N-body simulations run with six different codes: Abacus, CUbeP3M, Gadget, enzo, PKDGrav3, and Ramses. by applying symbolic regression to the different parts comprising the GNN, we derive equations that can predict Ωmfrom halo catalogues of simulations run with all of the above codes with accuracies similar to those of the GNN. We show that by tuning a single free parameter, our equations can also infer the value of Ωmfrom galaxy catalogues of thousands of state-of-the-art hydrodynamic simulations of the CAMeLS project, each with a different astrophysics model, run with five distinct codes that employ different subgrid physics: IllustrisTNG, SIMbA, Astrid, Magneticum, SWIFT-eAGLe. Furthermore, the equations also perform well when tested on galaxy catalogues from simulations covering a vast region in parameter space that samples variations in 5 cosmological and 23 astrophysical parameters. We speculate that the equations may reflect the existence of a fundamental physics relation between the phase-space distribution of generic tracers and Ωm, one that is not affected by galaxy formation physics down to scales as small as 10 h-1kpc. © 2023, CC bY.

关键词： Galaxies

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Hybrid Attitude and Gyro-bias Ob.erver Design on $sO(3)$

Hybrid Attitude and Gyro-Bias Observer Design on $sO(3)$

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作者： berkane, Soulaimane Ab.essameud, Ab.elkader Tayebi, Ab.elhamid Department of Electrical and Computer Engineering University of Western Ontario LondonONN6A5B9 Canada School of Science Engineering and Technology Pennsylvania State University MiddletownPA17057 United States Department of Electrical Engineering Lakehead University Thunder BayONP7B5E1 Canada

This paper presents an approach for the design of globally exponentially stab.e hybrid attitude and gyro-bias ob.ervers on SO(3)×R3. First, we propose a hybrid ob.erver developed in a generic manner involving a generic family of potential functions with specific properties. Thereafter, we present a design method for such potential functions via an appropriate angular warping transformation applied to a new potential function on SO(3). This results in a hybrid ob.erver that uses directly body-frame measurements of known inertial vectors. © 2012 Ieee.

关键词： Hybrid systems

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Contributions of KM3NeT to ICRC2023

arXiv

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arXiv 2023年

作者： Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, e. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. bailly-Salins, L. bardačová, Z. baret, b. bariego-Quintana, A. basegmez du Pree, S. becherini, Y. bendahman, M. benfenati, F. benhassi, M. benoit, D.M. berb.e, e. bertin, V. biagi, S. b.ettcher, M. bonanno, D. boumaaza, J. bouta, M. bouwhuis, M. bozza, C. bozza, R.M. brânzaş, H. b.etaudeau, F. bruijn, R. brunner, J. bruno, R. buis, e. buompane, R. busto, J. Caiffi, b. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.b. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De benedittis, A. De Martino, b. De Wasseige, G. Decoene, V. Del burgo, R. Di Cerbo, U.M. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diaz, C. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, e. Drouhin, D. Dvornický, R. eberl, T. eckerová, e. eddymaoui, A. van eeden, T. eff, M. van eijk, D. el bojaddaini, I. el Hedri, S. enzenhöfer, A. de Favereau, J. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelb.echt, N. Ghaddari, H. Gialanella, L. Gibson, b.K. Giorgio, e. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, b. Gutiérrez, M. van Haren, H. Heijb.er, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, b.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Lamoureux, M. Larosa, G. Lastoria, C. Lazo, A. Le Guirriec, e. Le Stum, S. INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France c/Catedrático José Beltrán 2 Valencia Paterna46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d'Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece University of Granada Dept. of Computer Architecture and Technology CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP 20722 Nantes44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1009 DB Netherlands INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Picha

This document collects the contributions of the KM3NeT collaboration to the ICRC2023 conference, held from July 26 to August 3, 2023, in Nagoya, Japan. KM3NeT submitted 38 contributions to ICRC2023, on neutrino- and multimessenger astronomy, neutrino oscillation physics, cosmic ray physics, searches for dark matter and exotics, calibration, technical detector descriptions, and art. Proceedings are published in Proceedings of science. © 2023, CC bY-NC-ND.

关键词： Cosmology

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Harmonized-Multinational qeeG norms (HarMNqeeG)

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NeUROIMAGe 2022年 256卷 119190-119190页

作者： Li, Min Wang, Ying Lopez-Naranjo, Carlos Hu, Shiang Reyes, Ronaldo Cesar Garcia Paz-Linares, Deirel Areces-Gonzalez, Ariosky Hamid, Aini Ismafairus Abd evans, Alan C. Savostyanov, Alexander N. Calzada-Reyes, Ana Villringer, Arno Tobon-Quintero, Carlos A. Garcia-Agustin, Daysi Yao, Dezhong Dong, Li Aubert-Vazquez, eduardo Reza, Faruque Razzaq, Fuleah Abdul Omar, Hazim Abdullah, Jafri Malin Galler, Janina R. Ochoa-Gomez, John F. Prichep, Leslie S. Galan-Garcia, Lidice Morales-Chacon, Lilia Valdes-Sosa, Mitchell J. Trondle, Marius Zulkifly, Mohd Faizal Mohd Rahman, Muhammad Riddha bin Abdul Milakhina, Natalya S. Langer, Nicolas Rudych, Pavel Koenig, Thomas Virues-Alba, Trinidad A. Lei, Xu bringas-Vega, Maria L. bosch-bayard, Jorge F. Valdes-Sosa, Pedro Antonio [a]The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China [b]Cuban Center for Neurocience La Habana Cuba [c]McGill Centre for Integrative Neuroscience Ludmer Centre for Neuroinformatics and Mental Health Montreal Neurological Institute Canada [d]Department of Neurosciences School of Medical Sciences Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [e]Brain and Behaviour Cluster School of Medical Sciences Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [f]Hospital Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [g]Humanitarian Institute Novosibirsk State University Novosibirsk 630090 Russia [h]Laboratory of Psychophysiology of Individual Differences Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine Novosibirsk 630117 Russia [i]Laboratory of Psychological Genetics at the Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences Novosibirsk 630090 Russia [j]University of Pinar del Río “Hermanos Saiz Montes de Oca” Pinar del Río Cuba [k]Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany [l]Department of Cognitive Neurology University Hospital Leipzig Leipzig Germany [m]Center for Stroke Research Charité-Universitätsmedizin Berlin Berlin Germany [n]Grupo Neuropsicología y Conducta - GRUNECO Faculty of Medicine Universidad de Antioquia Colombia [o]Research Department Institución Prestadora de Servicios de Salud IPS Universitaria Colombia [p]The Cuban center aging longevity and health Havana Cuba [q]Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu 2019RU035 China [r]School of Electrical Engineering Zhengzhou University Zhengzhou 4500

This paper extends frequency domain quantitative electroencephalography (qeeG) methods pursuing higher sensitivity to detect brain Developmental Disorders. Prior qeeG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qeeG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qeeG norms for cross-spectral tensors. These norms result from the HarMNqeeG project fostered by the Global brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 sub.ects. Instead of raw data, only anonymized metadata and eeG cross spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qeeG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qeeG "batch effects " and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqeeG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicab.e in various health settings.

关键词： Quantitative eeG eeG cross-spectrum Riemannian geometry batch effects Z-score Harmonization Malnutrition Covid induced brain dysfunction Developmental brain Chart

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Gaia Data Release 3: Apsis. III. Non-stellar content and source classification

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Astronomy and Astrophysics 2023年 674卷

作者： Delchamb.e, L. bailer-Jones, C.A.L. bellas-Velidis, I. Drimmel, R. Garabato, D. Carballo, R. Hatzidimitriou, D. Marshall, D.J. Andrae, R. Dafonte, C. Livanou, e. Fouesneau, M. Licata, e.L. Lindstrøm, H.e.P. Manteiga, M. Robin, C. Silvelo, A. Ab.eu Aramburu, A. Álvarez, M.A. bakker, J. bijaoui, A. brouillet, N. brugaletta, e. burlacu, A. Casamiquela, L. Chaoul, L. Chiavassa, A. Contursi, G. Cooper, W.J. Creevey, O.L. Dapergolas, A. De Laverny, P. Demouchy, C. Dharmawardena, T.e. edvardsson, b. Frémat, Y. García-Lario, P. García-Torres, M. Gavel, A. Gomez, A. González-Santamaría, I. Heiter, U. Jean-Antoine Piccolo, A. Kontizas, M. Kordopatis, G. Korn, A.J. Lanzafame, A.C. Leb.eton, Y. Lobel, A. Lorca, A. Magdaleno Romeo, A. Marocco, F. Mary, N. Nicolas, C. Ordenovic, C. Pailler, F. Palicio, P.A. Pallas-Quintela, L. Panem, C. Pichon, b. Poggio, e. Recio-blanco, A. Riclet, F. Rybizki, J. Santoveña, R. Sarro, L.M. Schultheis, M.S. Segol, M. Slezak, I. Smart, R.L. Sordo, R. Soubiran, C. Süveges, M. Thévenin, F. Torralba elipe, G. Ulla, A. Utrilla, e. Vallenari, A. Van Dillen, e. Zhao, H. Zorec, J. Institut D Astrophysique et de Géophysique Université de Liège 19c Allée du 6 Août Liège4000 Belgium Max Planck Institute for Astronomy Königstuhl 17 Heidelberg69117 Germany National Observatory of Athens I. Metaxa and Vas. Pavlou Palaia Penteli Athens15236 Greece INAF Osservatorio Astrofisico di Torino Via Osservatorio 20 TO Pino Torinese10025 Italy CIGUS CITIC Department of Computer Science and Information Technologies University of A Coruña Campus de Elviña s/n A Coruña15071 Spain Dpto. de Matemática Aplicada y Ciencias de la Computación Univ. de Cantabria ETS Ingenieros de Caminos Canales y Puertos Avda. de los Castros s/n Santander39005 Spain Department of Astrophysics Astronomy and Mechanics National and Kapodistrian University of Athens Panepistimiopolis Zografos Athens15783 Greece IRAP Université de Toulouse CNRS UPS CNES 9 Av. colonel Roche BP 44346 ToulouseCedex 4 31028 France Niels Bohr Institute University of Copenhagen Juliane Maries Vej 30 Copenhagen2100 Denmark DXC Technology Retortvej 8 Valby2500 Denmark CIGUS CITIC Department of Nautical Sciences and Marine Engineering University of A Coruña Paseo de Ronda 51 A Coruña15071 Spain Thales Services for CNES Centre Spatial de Toulouse 18 avenue Edouard Belin ToulouseCedex 9 31401 France Camino bajo del Castillo s/n Urbanizacion Villafranca del Castillo Villanueva de la Cañada Madrid28692 Spain Université Côte D Azur Observatoire de la Côte D Azur CNRS Laboratoire Lagrange Bd de l Observatoire CS 34229 NiceCedex 4 06304 France Laboratoire D Astrophysique de Bordeaux Univ. Bordeaux CNRS B18N allée Geoffroy Saint-Hilaire Pessac33615 France INAF Osservatorio Astrofisico di Catania Via S. Sofia 78 Catania95123 Italy Telespazio for CNES Centre Spatial de Toulouse 18 avenue Edouard Belin ToulouseCedex 9 31401 France GEPI Observatoire de Paris Université PSL CNRS 5 place Jules Janssen Meudon92190 France CNES Centre Spatial de Toulouse 18 avenue Edouard B

Context. As part of the third Gaia Data Release, we present the contributions of the non-stellar and classification modules from the eighth coordination unit (CU8) of the Data Processing and Analysis Consortium, which is responsib.e for the determination of source astrophysical parameters using Gaia data. This is the third in a series of three papers describing the work done within CU8 for this release. Aims. For each of the five relevant modules from CU8, we summarise their ob.ectives, the methods they employ, their performance, and the results they produce for Gaia DR3. We further advise how to use these data products and highlight some limitations. Methods. The Discrete Source Classifier (DSC) module provides classification probabilities associated with five types of sources: quasars, galaxies, stars, white dwarfs, and physical binary stars. A sub.et of these sources are processed by the Outlier Analysis (OA) module, which performs an unsupervised clustering analysis, and then associates labels with the clusters to complement the DSC classification. The Quasi Stellar Ob.ect Classifier (QSOC) and the Unresolved Galaxy Classifier (UGC) determine the redshifts of the sources classified as quasar and galaxy by the DSC module. Finally, the Total Galactic extinction (TGe) module uses the extinctions of individual stars determined by another CU8 module to determine the asymptotic extinction along all lines of sight for Galactic latitudes |b|& 5. *** DR3 includes 1591 million sources with DSC classifications;56 million sources to which the OA clustering is applied;1.4 million sources with redshift estimates from UGC;6.4 million sources with QSOC redshift;and 3.1 million level 9 HeALPixes of size 0.013 deg2where the extinction is evaluated by TGe. Conclusions. Validation shows that results are in good agreement with values from external catalogues;for example 90% of the QSOC redshifts have absolute error lower than 0.1 for sources with empty warning flags, while

关键词： Galaxies

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Prospects for combined analyses of hadronic emission from γ-ray sources in the Milky Way with CTA and KM3NeT

arXiv

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arXiv 2023年

作者： Unbehaun, T. Mohrmann, L. Funk, S. Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, e. Anghinolfi, M. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. bagatelas, C. bailly-Salins, L. bardačová, Z. baret, b. basegmez du Pree, S. becherini, Y. bendahman, M. benfenati, F. benhassi, M. benoit, D.M. berb.e, e. bertin, V. biagi, S. b.ettcher, M. bou Cabo, M. boumaaza, J. bouta, M. bouwhuis, M. bozza, C. bozza, R.M. brânzaş, H. b.etaudeau, F. bruijn, R. brunner, J. bruno, R. buis, e. buompane, R. busto, J. Caiffi, b. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.b. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De benedittis, A. De Martino, b. Decoene, V. Del burgo, R. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, e. Drouhin, D. Dvornický, R. eberl, T. eckerová, e. eddymaoui, A. van eeden, T. eff, M. van eijk, D. el bojaddaini, I. el Hedri, S. enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Fusco, L.A. Gabriel, J. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelb.echt, N. Ghaddari, H. Gialanella, L. Gibson, b.K. Giorgio, e. Girardi, A. Goos, I. Gozzini, S.R. Gracia, R. Graf, K. Guderian, D. Guidi, C. Guillon, b. Gutiérrez, M. van Haren, H. Heijb.er, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, b.J. Kalaczynski, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. van der Knaap, F. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. Lastoria, C. Lazo, A. Le Stum, S. Lehaut, G. Leonora, e. Lessing, N. Erlangen Centre for Astroparticle Physics University of Erlangen-Nuremberg Nikolaus-Fiebiger-Str. 2 Erlangen91058 Germany Max-Planck-Institut für Kernphysik Saupfercheckweg 1 Heidelberg69117 Germany INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d'Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece INFN Sezione di Genova Via Dodecaneso 33 Genova16146 Italy University of Granada Dept. of Computer Architecture and Technology CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP 20722 Nantes44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 R.P. Rabat10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1009 DB Netherlands INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università di Bologna Dipartimento di Fisica e Astronomia v.l

The Cherenkov Telescope Array and the KM3NeT neutrino telescopes are major upcoming facilities in the fields of γ-ray and neutrino astronomy, respectively. Possib.e simultaneous production of γ rays and neutrinos in astrophysical accelerators of cosmic-ray nuclei motivates a combination of their data. We assess the potential of a combined analysis of CTA and KM3NeT data to determine the contribution of hadronic emission processes in known Galactic γ-ray emitters, comparing this result to the cases of two separate analyses. In doing so, we demonstrate the capability of GAMMAPY, an open-source software package for the analysis of γ-ray data, to also process data from neutrino telescopes. For a selection of prototypical γ-ray sources within our Galaxy, we obtain models for primary proton and electron spectra in the hadronic and leptonic emission scenario, respectively, by fitting published γ-ray spectra. Using these models and instrument response functions for both detectors, we employ the GAMMAPY package to generate pseudo data sets, where we assume 200 hours of CTA ob.ervations and 10 years of KM3NeT detector operation. We then apply a three-dimensional binned likelihood analysis to these data sets, separately for each instrument and jointly for both. We find that the largest benefit of the combined analysis lies in the possibility of a consistent modelling of the γ-ray and neutrino emission. Assuming a purely leptonic scenario as input, we obtain, for the most favourab.e source, an average expected 68% credib.e interval that constrains the contribution of hadronic processes to the ob.erved γ-ray emission to below 15%. © 2023, CC bY.

关键词： Gamma rays

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emulating the impact of additional proton–proton interactions in the ATLAS simulation by presampling sets of inelastic Monte Carlo events

引用

Computing and Software for big science 2022年第1期6卷 1-35页

作者： Aad, G. Abbott, b. Abbott, D.C. Abud, A. Abed Abeling, K. Abhayasinghe, D.K. Abidi, S.H. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Ab.eu, H. Abulaiti, Y. Hoffman, A. C. Abusleme Acharya, b.S. Achkar, b. Adam, L. bourdarios, C. Adam Adamczyk, L. Adamek, L. Adelman, J. Adiguzel, A. Adorni, S. Adye, T. Affolder, A.A. Afik, Y. Agapopoulou, C. Agaras, M.N. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ai, X. Aielli, G. Akatsuka, S. Akbiyik, M. Åkesson, T.P.A. Akilli, e. Akimov, A.V. Khoury, K. Al Alberghi, G.L. Albert, J. Verzini, M. J. Alconada Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, A. Alfonsi, F. Alhroob, M. Ali, b. Ali, S. Aliev, M. Alimonti, G. Allaire, C. Allbrooke, b.M.M. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Camelia, e. Alunno estevez, M. Alvarez Alviggi, M.G. Coutinho, Y. Amaral Amb.er, A. Ambroz, L. Amelung, C. Amidei, D. Santos, S. P. Amor Dos Amoroso, S. Amrouche, C.S. Anastopoulos, C. Andari, N. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Andrei, V. Anelli, C.R. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, e. Antonelli, M. Antrim, D.J.A. Anulli, F. Aoki, M. Pozo, J. A. Aparisi Aparo, M.A. bella, L. Aperio Aranzabal, N. Ferraz, V. Araujo Arcangeletti, C. Arce, A.T.H. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Armbruster, A.J. Armstrong, A. Arnaez, O. Arnold, H. Tame, Z. P. Arrubarrena Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Asimakopoulou, e.M. Asquith, L. Assahsah, J. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.b. Atmani, H. Atmasiddha, P.A. Augsten, K. Austrup, V.A. Avolio, G. Ayoub, M.K. Azuelos, G. babal, D. bachacou, H. bachas, K. backman, F. bagnaia, P. bahrasemani, H. bailey, A.J. bailey, V.R. baines, J.T. bakalis, C. baker, O.K. bakker, P.J. bakos, e. Gupta, D. bakshi balaji, S. balasubramanian, R. baldin, e.M. balek, P. balli, F. balunas, W.K. balz, J. banas, e. bandieramonte, M. bandyopadhyay, A. barak, L. barbe, W.M. ba Department of Physics University of Adelaide Adelaide Australia Physics Department SUNY Albany Albany NY United States Department of Physics University of Alberta Edmonton AB Canada Department of Physics Ankara University Ankara Turkey Istanbul Aydin University Application and Research Center for Advanced Studies Istanbul Turkey Division of Physics TOBB University of Economics and Technology Ankara Turkey LAPP Univ. Savoie Mont Blanc CNRS/IN2P3 Annecy France High Energy Physics Division Argonne National Laboratory Argonne IL United States Department of Physics University of Arizona Tucson AZ United States Department of Physics University of Texas at Arlington Arlington TX United States Physics Department National and Kapodistrian University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics University of Texas at Austin Austin TX United States Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Istanbul Bilgi University Faculty of Engineering and Natural Sciences Istanbul Turkey Department of Physics Bogazici University Istanbul Turkey Department of Physics Engineering Gaziantep University Gaziantep Turkey Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain Institute of High Energy Physics Chinese Academy of Sciences Beijing China Physics Department Tsinghua University Beijing China Department of Physics Nanjing University Nanjing China University of Chinese Academy of Science (UCAS) Beijing China Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory and University of California Berkeley CA United States Institut für Physik Humboldt Universität zu Berlin Berlin Germany Albert Ei

The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy. © 2022, The Author(s).

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StaNdaRT: A repository of standardised test models and outputs for supernova radiative transfer

arXiv

引用

arXiv 2022年

作者： blondin, Stéphane blinnikov, Sergei Callan, Fionntan P. Collins, Christine e. Dessart, Luc even, Wesley Flörs, Andreas Fullard, Andrew G. Hillier, D. John Jerkstrand, Anders Kasen, Daniel Katz, boaz Kerzendorf, Wolfgang Kozyreva, Alexandra O’brien, Jack Pássaro, ezequiel A. Roth, Nathaniel Shen, Ken J. Shingles, Luke Sim, Stuart A. Singhal, Jaladh Smith, Isaac G. Sorokina, elena Utrobin, Victor P. Vogl, Christian Williamson, Marc Wollaeger, Ryan Woosley, Stan e. Wygoda, Nahliel Aix Marseille Univ CNRS CNES LAM Marseille France Unidad Mixta Internacional Franco-Chilena de Astronomía CNRS INSU UMI 3386 Instituto de Astrofísica Pontificia Universidad Católica de Chile Santiago Chile Moscow117218 Russia Sternberg Astronomical Institute Moscow State University Moscow119234 Russia The University of Tokyo Institutes for Advanced Study The University of Tokyo 5-1-5 Kashiwanoha Chiba Kashiwa277-8583 Japan Astrophysics Research Centre School of Mathematics and Physics Queen’s University Belfast Northern Ireland BelfastBT7 1NN United Kingdom GSI Helmholtzzentrum für Schwerionenforschung Planckstraße 1 Darmstadt64291 Germany Institut d’Astrophysique de Paris CNRS Sorbonne Université 98 bis boulevard Arago Paris75014 France Center for Theoretical Astrophysics Los Alamos National Laboratory Los AlamosNM87545 United States Theoretical Division Los Alamos National Laboratory Los AlamosNM87545 United States Department of Physics and Astronomy Michigan State University East LansingMI48823 United States University of Pittsburgh 3941 O’Hara Street PittsburghPA15260 United States The Oskar Klein Centre Department of Astronomy Stockholm University AlbaNova StockholmSE-10691 Sweden Departments of Physics and Astronomy University of California Berkeley Lawrence Berkeley National Laboratory United States Dept. of Particle Phys. & Astrophys. Weizmann Institute of Science Rehovot76100 Israel Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Straße 1 Garching bei München85748 Germany Facultad de Ciencias Astronómicas y Geofísicas Universidad Nacional de La Plata La PlataB1900 Argentina Department of Astronomy Theoretical Astrophysics Center University of California BerkeleyCA94720 United States Institute of Astronomy Russian Academy of Sciences Pyatnitskaya St. 48 Moscow119017 Russia D

We present the first results of a comprehensive supernova (SN) radiative-transfer (RT) code-comparison initiative (StaNdaRT), where the emission from the same set of standardised test models is simulated by currently used RT codes. We ran a total of ten codes on a set of four benchmark ejecta models of Type Ia SNe. We consider two sub-Chandrasekhar-mass (Mtot = 1.0 Mo) toy models with analytic density and composition profiles and two Chandrasekhar-mass delayed-detonation models that are outcomes of hydrodynamical simulations. We adopt spherical symmetry for all four models. The results of the different codes, including the light curves, spectra, and the evolution of several physical properties as a function of radius and time are provided in electronic form in a standard format via a public repository. We also include the detailed test model profiles and several Python scripts for accessing and presenting the input and output files. We also provide the code used to generate the toy models studied here. In this paper, we describe the test models, radiative-transfer codes, and output formats in detail, and provide access to the repository. We present example results of several key diagnostic features. © 2022, CC bY.

关键词： Radiative transfer

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evidence for the Higgs boson Decay to a Z boson and a Photon at the LHC

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Physical Review Letters 2024年第2期132卷 021803-021803页

作者： G. Aad b. Abbott K. Abeling N. J. Abicht S. H. Abidi A. Aboulhorma H. Abramowicz H. Ab.eu Y. Abulaiti b. S. Acharya C. Adam bourdarios L. Adamczyk L. Adamek S. V. Addepalli M. J. Addison J. Adelman A. Adiguzel T. Adye A. A. Affolder Y. Afik M. N. Agaras J. Agarwala A. Aggarwal C. Agheorghiesei A. Ahmad F. Ahmadov W. S. Ahmed S. Ahuja X. Ai G. Aielli A. Aikot M. Ait Tamlihat b. Aitbenchikh I. Aizenberg M. Akbiyik T. P. A. Åkesson A. V. Akimov D. Akiyama N. N. Akolkar K. Al Khoury G. L. Alberghi J. Albert P. Albicocco G. L. Albouy S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos F. Alfonsi M. Algren M. Alhroob b. Ali H. M. J. Ali S. Ali S. W. Alibocus M. Aliev G. Alimonti W. Alkakhi C. Allaire b. M. M. Allbrooke J. F. Allen C. A. Allendes Flores P. P. Allport A. Aloisio F. Alonso C. Alpigiani M. Alvarez estevez A. Alvarez Fernandez M. Alves Cardoso M. G. Alviggi M. Aly Y. Amaral Coutinho A. Amb.er C. Amelung M. Amerl C. G. Ames D. Amidei S. P. Amor Dos Santos K. R. Amos V. Ananiev C. Anastopoulos T. Andeen J. K. Anders S. Y. Andrean A. Andreazza S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony e. Antipov M. Antonelli F. Anulli M. Aoki T. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio bella C. Appelt A. Apyan N. Aranzabal C. Arcangeletti A. T. H. Arce e. Arena J-F. Arguin S. Argyropoulos J.-H. Arling O. Arnaez H. Arnold G. Artoni H. Asada K. Asai S. Asai N. A. Asbah J. Assahsah K. Assamagan R. Astalos S. Atashi R. J. Atkin M. Atkinson H. Atmani P. A. Atmasiddha K. Augsten S. Auricchio A. D. Auriol V. A. Austrup G. Avolio K. Axiotis G. Azuelos D. babal H. bachacou K. bachas A. bachiu F. backman A. badea P. bagnaia M. bahmani A. J. bailey V. R. bailey J. T. baines L. baines C. bakalis O. K. baker e. bakos D. bakshi Gupta V. balakrishnan R. balasubramanian e. M. baldin P. balek e. ballabene F. balli L. M. baltes W. K. balunas J. balz e. banas M. bandieramonte A. bandyopadhyay S. bansal L. barak M. barakat e. L. barberio D. barberis M. barbero M. Z. barel K. N. barends T. ba Benemerita Universidad Autonoma de Puebla Puebla Mexico ETH Zurich—Institute for Particle Physics and Astrophysics (IPA) Zurich Switzerland Institute of Nuclear Research ATOMKI Debrecen Hungary National and Kapodistrian University of Athens Athens Greece Escuela Politecnica Nacional Quito Ecuador Faculté des sciences Université Mohammed V Rabat Morocco University of Florida Gainesville Florida USA Fermi National Accelerator Laboratory Batavia Illinois USA University of Ruhuna Department of Physics Matara Sri Lanka INFN Sezione di Bologna Bologna Italy Università di Bologna Bologna Italy Vrije Universiteit Brussel Brussel Belgium AGH University of Krakow Faculty of Physics and Applied Computer Science Krakow Poland The University of Iowa Iowa City Iowa USA Institute Rudjer Boskovic Zagreb Croatia Universidad Iberoamericana Mexico City Mexico Instituto de Física de Cantabria (IFCA) CSIC-Universidad de Cantabria Santander Spain Department of Physics Istanbul University Istanbul Türkiye Imperial College London United Kingdom Baylor University Waco Texas USA Lappeenranta-Lahti University of Technology Lappeenranta Finland Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile INFN Sezione di Genova Genova Italy Università di Genova Genova Italy Centro de Investigacion y de Estudios Avanzados del IPN Mexico City Mexico Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania National Centre for Physics Quaid-I-Azam University Islamabad Pakistan Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France University of Canterbury Christchurch New Zealand Riga Technical University Riga Latvia Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei China INFN Sezione di Padova Padova Italy Università di Padova Padova Italy University of Mississippi Oxford Mississi

The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CeRN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140 fb−1 for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.

关键词： Rare decays Higgs bosons W & Z bosons Hadron colliders

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