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27th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2017

作者： Zhang, Jiaming Zhou, Yipeng Wu, Di Yang, Chunfeng School of Data and Computer Science Sun Yat-sen University Guangzhou Guangdong China Institute for Telecommunications Research University of South Australia Australia Guangdong Province Key Laboratory of Big Data Analysis and Processing Sun Yat-sen University Guangzhou Guangdong China Collaborative Innovation Center of High Performance Computing National University of Defense Technology China Tencent Inc. China

ISBN: (纸本)9781450350037

With the astronomical growth of online video population, the video recommendation system is crucial for users to locate videos fitting their interests. The collaborative filtering (CF) realizing personalized recommendation by analyzing users' historical view records is currently the most prevalent algorithm adopted by existing systems. Nevertheless, video recommendation performance can be improved for most cases, particularly the one with cold-start problem, if additional information is involved. In this article, we propose an AP-based Context-Aware (APCA) recommendation scheme on top of the traditional factor-based CF algorithm by utilizing the information of access points which has not been explored yet by existing works. The underlying principle is that users' view preferences are expected to be different with different contexts, e.g., hotel, home, public areas, which can be inferred by mining the information of access points via which users launch video requests. With the data collected from Tencent Video, a leading online video provider in China, we present a measurement study to show user view preferences in different contexts before our APCA algorithm is introduced. Experiments are executed driven by the trace data collected from Tencent Video to validate the effectiveness of our scheme in improving recommendation performance. © 2017 ACM.

关键词： Collaborative filtering

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SPT clusters with DES and HST weak lensing. I. Cluster lensing and Bayesian population modeling of multiwavelength cluster datasets

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Physical Review D 2024年第8期110卷 083509页

作者： S. Bocquet S. Grandis L. E. Bleem M. Klein J. J. Mohr M. Aguena A. Alarcon S. Allam S. W. Allen O. Alves A. Amon B. Ansarinejad D. Bacon M. Bayliss K. Bechtol M. R. Becker B. A. Benson G. M. Bernstein M. Brodwin D. Brooks A. Campos R. E. A. Canning J. E. Carlstrom A. Carnero Rosell M. Carrasco Kind J. Carretero R. Cawthon C. Chang R. Chen A. Choi J. Cordero M. Costanzi L. N. da Costa M. E. S. Pereira C. Davis J. DeRose S. Desai T. de Haan J. De Vicente H. T. Diehl S. Dodelson P. Doel C. Doux A. Drlica-Wagner K. Eckert J. Elvin-Poole S. Everett I. Ferrero A. Ferté A. M. Flores J. Frieman J. García-Bellido M. Gatti G. Giannini M. D. Gladders D. Gruen R. A. Gruendl I. Harrison W. G. Hartley K. Herner S. R. Hinton D. L. Hollowood W. L. Holzapfel K. Honscheid N. Huang E. M. Huff D. J. James M. Jarvis G. Khullar K. Kim R. Kraft K. Kuehn N. Kuropatkin F. Kéruzoré S. Lee P.-F. Leget N. MacCrann G. Mahler A. Mantz J. L. Marshall J. McCullough M. McDonald J. Mena-Fernández R. Miquel J. Myles A. Navarro-Alsina R. L. C. Ogando A. Palmese S. Pandey A. Pieres A. A. Plazas Malagón J. Prat M. Raveri C. L. Reichardt J. Roberson R. P. Rollins A. K. Romer C. Romero A. Roodman A. J. Ross E. S. Rykoff L. Salvati C. Sánchez E. Sanchez D. Sanchez Cid A. Saro T. Schrabback M. Schubnell L. F. Secco I. Sevilla-Noarbe K. Sharon E. Sheldon T. Shin M. Smith T. Somboonpanyakul B. Stalder A. A. Stark V. Strazzullo E. Suchyta M. E. C. Swanson G. Tarle C. To M. A. Troxel I. Tutusaus T. N. Varga A. von der Linden N. Weaverdyck J. Weller P. Wiseman B. Yanny B. Yin M. Young Y. Zhang J. Zuntz University Observatory Faculty of Physics Universität Innsbruck Institut für Astro- und Teilchenphysik Technikerstr. 25/8 6020 Innsbruck Austria Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Kavli Institute for Cosmological Physics University of Chicago Chicago Illinois 60637 USA Max Planck Institute for Extraterrestrial Physics Gießenbachstr. 1 85748 Garching Germany Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 Rio de Janeiro RJ-20921-400 Brazil Fermi National Accelerator Laboratory P. O. Box 500 Batavia Illinois 60510 USA Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall Stanford California 94305 USA Department of Physics Stanford University 382 Via Pueblo Mall Stanford California 94305 USA SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park California 94025 USA Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Institute of Astronomy University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom School of Physics University of Melbourne Parkville Victoria 3010 Australia Institute of Cosmology and Gravitation University of Portsmouth Portsmouth PO1 3FX United Kingdom Department of Physics University of Cincinnati Cincinnati Ohio 45221 USA Physics Department 2320 Chamberlin Hall University of Wisconsin-Madison 1150 University Avenue Madison Wisconsin 53706-1390 USA Department of Astronomy and Astrophysics University of Chicago Chicago Illinois 60637 USA Fermi National Accelerator Laboratory Batavia Illinois 60510-0500 USA Department of Physics and Astronomy University of Pennsylvania Philadelphia Pennsylvania 19104 USA Department of Physics and Astronomy University of Missouri 5110 Rockhill Road Kansas City Missouri 64110 USA Department of Physics and Astronomy University Coll

We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1% at z=0.25 to 10% at z=0.95, to which we add 2% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multiobservable likelihood for the Sunyaev-Zel’dovich effect, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol ECS, and SPTpol 500d surveys and the DES Year 3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset.

关键词： Cosmological parameters Gravitational lenses Large scale structure of the Universe

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SPT clusters with DES and HST weak lensing. II. Cosmological constraints from the abundance of massive halos

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Physical Review D 2024年第8期110卷 083510页

作者： S. Bocquet S. Grandis L. E. Bleem M. Klein J. J. Mohr T. Schrabback T. M. C. Abbott P. A. R. Ade M. Aguena A. Alarcon S. Allam S. W. Allen O. Alves A. Amon A. J. Anderson J. Annis B. Ansarinejad J. E. Austermann S. Avila D. Bacon M. Bayliss J. A. Beall K. Bechtol M. R. Becker A. N. Bender B. A. Benson G. M. Bernstein S. Bhargava F. Bianchini M. Brodwin D. Brooks L. Bryant A. Campos R. E. A. Canning J. E. Carlstrom A. Carnero Rosell M. Carrasco Kind J. Carretero F. J. Castander R. Cawthon C. L. Chang C. Chang P. Chaubal R. Chen H. C. Chiang A. Choi T-L. Chou R. Citron C. Corbett Moran J. Cordero M. Costanzi T. M. Crawford A. T. Crites L. N. da Costa M. E. S. Pereira C. Davis T. M. Davis J. DeRose S. Desai T. de Haan H. T. Diehl M. A. Dobbs S. Dodelson C. Doux A. Drlica-Wagner K. Eckert J. Elvin-Poole S. Everett W. Everett I. Ferrero A. Ferté A. M. Flores J. Frieman J. Gallicchio J. García-Bellido M. Gatti E. M. George G. Giannini M. D. Gladders D. Gruen R. A. Gruendl N. Gupta G. Gutierrez N. W. Halverson I. Harrison W. G. Hartley K. Herner S. R. Hinton G. P. Holder D. L. Hollowood W. L. Holzapfel K. Honscheid J. D. Hrubes N. Huang J. Hubmayr E. M. Huff D. Huterer K. D. Irwin D. J. James M. Jarvis G. Khullar K. Kim L. Knox R. Kraft E. Krause K. Kuehn N. Kuropatkin F. Kéruzoré O. Lahav A. T. Lee P.-F. Leget D. Li H. Lin A. Lowitz N. MacCrann G. Mahler A. Mantz J. L. Marshall J. McCullough M. McDonald J. J. McMahon J. Mena-Fernández F. Menanteau S. S. Meyer R. Miquel J. Montgomery J. Myles T. Natoli A. Navarro-Alsina J. P. Nibarger G. I. Noble V. Novosad R. L. C. Ogando Y. Omori S. Padin S. Pandey P. Paschos S. Patil A. Pieres A. A. Plazas Malagón A. Porredon J. Prat C. Pryke M. Raveri C. L. Reichardt J. Roberson R. P. Rollins C. Romero A. Roodman J. E. Ruhl E. S. Rykoff B. R. Saliwanchik L. Salvati C. Sánchez E. Sanchez D. Sanchez Cid A. Saro K. K. Schaffer L. F. Secco I. Sevilla-Noarbe K. Sharon E. Sheldon T. Shin C. Sievers G. Smecher M. Smith T. Somboonpanyakul M. Sommer B. Stalder A. A. Stark J. Stephen V. Straz University Observatory Faculty of Physics Universität Innsbruck Institut für Astro- und Teilchenphysik Technikerstraße 25/8 6020 Innsbruck Austria High-Energy Physics Division Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Max Planck Institute for Extraterrestrial Physics Gießenbachstraße 1 85748 Garching Germany Argelander-Institut für Astronomie Auf dem Hügel 71 53121 Bonn Germany Cerro Tololo Inter-American Observatory NSF’s National Optical-Infrared Astronomy Research Laboratory Casilla 603 La Serena Chile School of Physics and Astronomy Cardiff University Cardiff CF24 3YB United Kingdom Laboratório Interinstitucional de e-Astronomia—LIneA Rua Gal. José Cristino 77 Rio de Janeiro Rio de Janeiro—20921-400 Brazil Fermi National Accelerator Laboratory P. O. Box 500 Batavia Illinois 60510 USA Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall Stanford California 94305 USA Department of Physics Stanford University 382 Via Pueblo Mall Stanford California 94305 USA SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park California 94025 USA Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Institute of Astronomy University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom School of Physics University of Melbourne Parkville Victoria 3010 Australia NIST Quantum Devices Group 325 Broadway Mailcode 817.03 Boulder Colorado 80305 USA Department of Physics University of Colorado Boulder Colorado 80309 USA Institut de Física d’Altes Energies (IFAE) The Barcelona Institute of Science and Technology Campus UAB 08193 Bellaterra (Barcelona) Spain Institute of Cosmology and Gravitation University of Portsmouth Portsmouth

We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range 0.25–1.78 over a total sky area of 5200 deg2. We use DES Year 3 weak-lensing data for 688 clusters with redshifts z<0.95 and HST weak-lensing data for 39 clusters with 0.6dataset, we place a 95% upper limit on the sum of neutrino masses ∑mν<0.18 eV. When additionally allowing the dark energy equation of state parameter w to vary, we obtain w=−1.45±0.31 from our cluster-based analysis. In combination with Planck data, we measure w=−1.34−0.15+0.22, or a 2.2σ difference with a cosmological constant. We use the cluster abundance to measure σ8 in five redshift bins between 0.25 and 1.8, and we find the results to be consistent with structure growth as predicted by the ΛCDM model fit to Planck primary CMB data.

关键词： Cosmological parameters Dark energy Large scale structure of the Universe Galaxy clusters

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Fast 3D Map Reconstruction Using Dense Visual Simultaneous Localization and Mapping Based on Unmanned Aerial Vehicle

Fast 3D Map Reconstruction Using Dense Visual Simultaneous L...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Siyuan Peng Fang Huang Jian Tao Bo Tie Jun Lu Xiaodong Zhang School of Resources & Environment University of Electronic Science and Technology of China Chengdu P.R. China Institute of Remote Sensing Big Data University of Electronic Science and Technology of China Chengdu P.R. China Texas A&M Engineering Experiment Station and High Performance Research Computing Texas A&M University College Station TX USA

Traditional 3D map reconstruction methods based on unmanned aerial (UA) always relies on multi-camera optical equipment or additional space positioning equipment. All of these restrict the UA's application scenarios to some extent. Visual simultaneous localization and mapping (VSLAM), using the camera as the only external sensor, can construct a 3D map of its spatial environment while recording its own localization. This paper proposes a technique of fast 3D map reconstruction based on UAs by using VSLAM, with parallel computing based on CUDA, to achieve fast dense reconstruction based on a UA platform. This research belongs to one of the emerging but very exciting application areas using UAs. It helps to expand the application scope of UAs to some extent. From the experiments, it is demonstrated that the methodology presented in this paper works well, and could be applied to real world applications.

关键词： Unmanned aerial Visual SLAM 3D map high performance computing Dense reconstruction

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Enabling QoE-aware Mobile Cloud Video Recording over Roadside Vehicular Networks

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China Communications 2016年第8期13卷 63-73页

作者： Tongtong Jiang Zhaobin Deng Weiwei Huang Guoqing Zhang Department of Computer Science Sun Yat-sen University Guangdong Province Key Laboratory of Big Data Analysis and Processing Sun Yat-sen University Collaborative Innovation Center of High Performance Computing National University of Defense Technology Institute of Computing Technology Chinese Academy of Sciences

Most of previous video recording devices in mobile vehicles commonly store captured video contents locally. With the rapid development of 4G/Wi Fi networks, there emerges a new trend to equip video recording devices with wireless interfaces to enable video uploading to the cloud for video playback in a later time point. In this paper, we propose a QoE-aware mobile cloud video recording scheme in the roadside vehicular networks, which can adaptively select the proper wireless interface and video bitrate for video uploading to the cloud. To maximize the total utility, we need to design a control strategy to carefully balance the transmission cost and the achieved QoE for users. To this purpose, we investigate the tradeoff between cost incurred by uploading through cellular networks and the achieved QoE of users. We apply the optimization framework to solve the formulated problem and design an online scheduling algorithm. We also conduct extensive trace-driven simulations and our results show that our algorithm achieves a good balance between the transmission cost and user QoE.

关键词： mobile cloud video vehicular networks quality-of-experience

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Euclid preparation. Simulations and nonlinearities beyond ΛCDM. 2. Results from non-standard simulations

arXiv

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arXiv 2024年

作者： Rácz, G. Breton, M.-A. Fiorini, B. Le Brun, A.M.C. Winther, H.-A. Sakr, Z. Pizzuti, L. Ragagnin, A. Gayoux, T. Altamura, E. Carella, E. Pardede, K. Verza, G. Koyama, K. Baldi, M. Pourtsidou, A. Vernizzi, F. Adame, A.G. Adamek, J. Avila, S. Carbone, C. Despali, G. Giocoli, C. Hernández-Aguayo, C. Hassani, F. Kunz, M. Li, B. Rasera, Y. Yepes, G. Gonzalez-Perez, V. Corasaniti, P.-S. García-Bellido, J. Hamaus, N. Kiessling, A. Marinucci, M. Moretti, C. Mota, D.F. Piga, L. Pisani, A. Szapudi, I. Tallada-Crespí, P. Aghanim, N. Andreon, S. Baccigalupi, C. Bardelli, S. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Camera, S. Capobianco, V. Cardone, V.F. Carretero, J. Casas, S. Castellano, M. Castignani, G. Cavuoti, S. Cimatti, A. Colodro-Conde, C. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Courbin, F. Courtois, H.M. Da Silva, A. Degaudenzi, H. De Lucia, G. Douspis, M. Dubath, F. Duncan, C.A.J. Dupac, X. Dusini, S. Ealet, A. Farina, M. Farrens, S. Ferriol, S. Fosalba, P. Frailis, M. Franceschi, E. Fumana, M. Galeotta, S. Gillis, B. Gómez-Alvarez, P. Grazian, A. Grupp, F. Haugan, S.V.H. Holmes, W. Hormuth, F. Hornstrup, A. Ilić, S. Jahnke, K. Jhabvala, M. Joachimi, B. Keihänen, E. Kermiche, S. Kilbinger, M. Kitching, T. Kubik, B. Kurki-Suonio, H. Lilje, P.B. Lindholm, V. Lloro, I. Mainetti, G. Maiorano, E. Mansutti, O. Marggraf, O. Markovic, K. Martinelli, M. Martinet, N. Marulli, F. Massey, R. Medinaceli, E. Mei, S. Mellier, Y. Meneghetti, M. Meylan, G. Moresco, M. Moscardini, L. Niemi, S.-M. Padilla, C. Paltani, S. Pasian, F. Pedersen, K. Percival, W.J. Pettorino, V. Pires, S. Polenta, G. Poncet, M. Popa, L.A. Raison, F. Rebolo, R. Renzi, A. Rhodes, J. Riccio, G. Romelli, E. Roncarelli, M. Saglia, R. Salvignol, J.-C. Sánchez, A.G. Sapone, D. Sartoris, B. Schirmer, M. Schrabback, T. Secroun, A. Seidel, G. Serrano, S. Sirignano, C. Sirri, G. Stanco, L. Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Department of Physics University of Helsinki P.O. Box 64 00014 Finland Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain Campus UAB Carrer de Can Magrans s/n Cerdanyola del Vallés Barcelona08193 Spain Laboratoire Univers et Théorie Observatoire de Paris Université PSL Université Paris Cité CNRS Meudon92190 France Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom School of Physics and Astronomy Queen Mary University of London Mile End Road LondonE1 4NS United Kingdom Institut d’Astrophysique de Paris UMR 7095 CNRS Sorbonne Université 98 bis boulevard Arago Paris75014 France Institute of Theoretical Astrophysics University of Oslo P.O. Box 1029 Blindern Oslo0315 Norway Institut für Theoretische Physik University of Heidelberg Philosophenweg 16 Heidelberg69120 Germany Université de Toulouse CNRS UPS CNES 14 Av. Edouard Belin Toulouse31400 France Université St Joseph Faculty of Sciences Beirut Lebanon Dipartimento di Fisica "G. Occhialini" Università degli Studi di Milano Bicocca Piazza della Scienza 3 Milano20126 Italy INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy Dipartimento di Fisica e Astronomia "Augusto Righi" Alma Mater Studiorum Università di Bologna via Piero Gobetti 93/2 Bologna40129 Italy ICSC - Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy University of Manchester Oxford Road ManchesterM13 9PL United Kingdom INAF-IASF Milano Via Alfonso Corti 12 Milano20133 Italy Dipartimento di Fisica "Aldo Pontremoli" Università degli Studi di Milano Via Celoria 16

The Euclid mission will measure cosmological parameters with unprecedented precision. To distinguish between cosmological models, it is essential to generate realistic mock observables from cosmological simulations that were run in both the standard Λ-cold-dark-matter (ΛCDM) paradigm and in many non-standard models beyond ΛCDM. We present the scientific results from a suite of cosmological N-body simulations using non-standard models including dynamical dark energy, k-essence, interacting dark energy, modified gravity, massive neutrinos, and primordial non-Gaussianities. We investigate how these models affect the large-scale-structure formation and evolution in addition to providing synthetic observables that can be used to test and constrain these models with Euclid data. We developed a custom pipeline based on the Rockstar halo finder and the nbodykit large-scale structure toolkit to analyse the particle output of non-standard simulations and generate mock observables such as halo and void catalogues, mass density fields, and power spectra in a consistent way. We compare these observables with those from the standard ΛCDM model and quantify the deviations. We find that non-standard cosmological models can leave significant imprints on the synthetic observables that we have generated. Our results demonstrate that non-standard cosmological N-body simulations provide valuable insights into the physics of dark energy and dark matter, which is essential to maximising the scientific return of Euclid. © 2024, CC BY.

关键词： Dark energy

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Euclid preparation. 3-dimensional galaxy clustering in configuration space Part I: 2-point correlation function estimation

arXiv

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arXiv 2025年

作者： de la Torre, S. Marulli, F. Keihänen, E. Viitanen, A. Viel, M. Veropalumbo, A. Branchini, E. Tavagnacco, D. Rizzo, F. Valiviita, J. Lindholm, V. Allevato, V. Parimbelli, G. Sarpa, E. Z., Ghaffari A., Amara S., Andreon N., Auricchio C., Baccigalupi M., Baldi S., Bardelli A., Basset D., Bonino M., Brescia J., Brinchmann A., Caillat S., Camera V., Capobianco C., Carbone J., Carretero S., Casas F.J., Castander M., Castellano G., Castignani S., Cavuoti A., Cimatti C., Colodro-Conde G., Congedo C.J., Conselice L., Conversi Y., Copin F., Courbin H.M., Courtois M., Crocce A., Da Silva H., Degaudenzi G., De Lucia A.M., Di Giorgio J., Dinis F., Dubath C.A.J., Duncan X., Dupac S., Dusini M., Farina S., Farrens F., Faustini S., Ferriol N., Fourmanoit M., Frailis E., Franceschi P., Franzetti M., Fumana S., Galeotta K., George W., Gillard B., Gillis C., Giocoli P., Gómez-Alvarez B.R., Granett A., Grazian F., Grupp L., Guzzo S.V.H., Haugan W., Holmes F., Hormuth A., Hornstrup S., Ilić K., Jahnke M., Jhabvala B., Joachimi S., Kermiche A., Kiessling M., Kilbinger B., Kubik M., Kunz H., Kurki-Suonio S., Ligori P.B., Lilje I., Lloro G., Mainetti D., Maino E., Maiorano O., Mansutti O., Marggraf K., Markovic M., Martinelli N., Martinet R., Massey S., Maurogordato E., Medinaceli S., Mei M., MELMhior Y., Mellier M., Meneghetti E., Merlin G., Meylan M., Moresco B., Morin L., Moscardini E., Munari C., Neissner S.-M., Niemi C., Padilla S., Paltani F., Pasian K., Pedersen W.J., Percival V., Pettorino S., Pires G., Polenta M., Poncet L., Pozzetti F., Raison A., Renzi J., Rhodes G., Riccio E., Romelli M., Roncarelli E., Rossetti R., Saglia Z., Sakr A.G., Sánchez D., Sapone B., Sartoris P., Schneider T., Schrabback M., Scodeggio A., Secroun E., Sefusatti G., Seidel M., Seiffert S., Serrano C., Sirignano G., Sirri L., Stanco J., Steinwagner C., Surace P., Tallada-Crespí A.N., Taylor I., Tereno R., Toledo-Moreo Aix-Marseille Université CNRS CNES LAM Marseille France Dipartimento di Fisica e Astronomia Augusto Righi Alma Mater Studiorum Università di Bologna via Piero Gobetti 93/2 Bologna40129 Italy INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy INFN-Sezione di Bologna Viale Berti Pichat 6/2 Bologna40127 Italy Department of Physics Helsinki Institute of Physics University of Helsinki Gustaf Hällströmin katu 2 00014 Finland INAF-Osservatorio Astronomico di Roma Via Frascati 33 Monteporzio Catone00078 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 Trieste34143 Italy SISSA International School for Advanced Studies Via Bonomea 265 TS Trieste34136 Italy INFN Sezione di Trieste Via Valerio 2 TS Trieste34127 Italy ICSC - Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy INAF-Osservatorio Astronomico di Brera Via Brera 28 Milano20122 Italy INFN-Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Dipartimento di Fisica Università degli studi di Genova INFN-Sezione di Genova via Dodecaneso 33 Genova16146 Italy Dipartimento di Fisica Università di Genova Via Dodecaneso 33 Genova16146 Italy Department of Physics University of Helsinki P.O. Box 64 00014 Finland Helsinki Institute of Physics University of Helsinki Gustaf Hällströmin katu 2 Helsinki Finland INAF-Osservatorio Astronomico di Capodimonte Via Moiariello 16 Napoli80131 Italy Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain School of Mathematics and Physics University of Surrey Guild-ford SurreyGU2 7XH United Kingdom Dipartimento di Fisica e Astronomia Università di Bologna Via Gobetti 93/2 Bologna40129 Italy Centre National d’Etudes Spatiales Centre spatial de Toulouse 18 avenue Edouard Belin Toulouse31401Cedex 9 France Pino

The 2-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission aims at performing an extensive spectroscopic survey of approximately 20–30 million Hα-emitting galaxies up to about redshift two. This ambitious project seeks to elucidate the nature of dark energy by mapping the 3-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the 3-dimensional 2-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid data set, which involves millions of galaxies. Key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including kd-tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. These methods are crucial for handling the massive volume of data efficiently. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. Those have been performed by using various mock galaxy catalogues to ensure that it meets the stringent accuracy requirement of the Euclid mission. The results indicate that the software is robust and can reliably estimate the 2-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of the Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission’s t

关键词： Dark energy

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Euclid preparation. XXXIX. The effect of baryons on the Halo Mass Function

arXiv

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arXiv 2023年

作者： Castro, T. Borgani, S. Costanzi, M. Dakin, J. Dolag, K. Fumagalli, A. Ragagnin, A. Saro, A. Le Brun, A.M.C. Aghanim, N. Amara, A. Andreon, S. Auricchio, N. Baldi, M. Bardelli, S. Bodendorf, C. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Camera, S. Capobianco, V. Carbone, C. Carretero, J. Casas, S. Castellano, M. Cavuoti, S. Cimatti, A. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Corcione, L. Courbin, F. Courtois, H.M. Cropper, M. Da Silva, A. Degaudenzi, H. Di Giorgio, A.M. Dinis, J. Dubath, F. Duncan, C.A.J. Dupac, X. Farina, M. Farrens, S. Ferriol, S. Frailis, M. Franceschi, E. Fumana, M. Galeotta, S. Gillis, B. Giocoli, C. Grazian, A. Grupp, F. Haugan, S.V.H. Holmes, W. Hormuth, F. Hornstrup, A. Jahnke, K. Keihänen, E. Kermiche, S. Kiessling, A. Kilbinger, M. Kubik, B. Kunz, M. Kurki-Suonio, H. Ligori, S. Lilje, P.B. Lindholm, V. Lloro, I. Maiorano, E. Mansutti, O. Marggraf, O. Markovic, K. Martinet, N. Marulli, F. Massey, R. Maurogordato, S. Medinaceli, E. Meneghetti, M. Merlin, E. Meylan, G. Moresco, M. Moscardini, L. Munari, E. Niemi, S.-M. Padilla, C. Paltani, S. Pasian, F. Pettorino, V. Pires, S. Polenta, G. Poncet, M. Popa, L.A. Pozzetti, L. Raison, F. Rebolo, R. Renzi, A. Rhodes, J. Riccio, G. Romelli, E. Roncarelli, M. Saglia, R. Sapone, D. Sartoris, B. Schneider, P. Schrabback, T. Secroun, A. Seidel, G. Serrano, S. Sirignano, C. Sirri, G. Stanco, L. Starck, J.-L. Tallada-Crespí, P. Taylor, A.N. Tereno, I. Toledo-Moreo, R. Torradeflot, F. Tutusaus, I. Valentijn, E.A. Valenziano, L. Vassallo, T. Veropalumbo, A. Wang, Y. Weller, J. Zacchei, A. Zamorani, G. Zoubian, J. Zucca, E. Biviano, A. Bozzo, E. Cerna, C. Colodro-Conde, C. Di Ferdinando, D. Mauri, N. Neissner, C. Sakr, Z. Scottez, V. Tenti, M. Viel, M. Wiesmann, M. Akrami, Y. Anselmi, S. Baccigalupi, C. Ballardini, M. Borlaff, A.S. Bruton, S. Burigana, C. Cabanac, R. Cappi, A. Carvalho, C.S. INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 Trieste34143 Italy INFN Sezione di Trieste Via Valerio 2 TS Trieste34127 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy ICSC - Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Dipartimento di Fisica - Sezione di Astronomia Università di Trieste Via Tiepolo 11 Trieste34131 Italy Institute for Computational Science University of Zurich Winterthurerstrasse 190 Zurich8057 Switzerland Universitäts-Sternwarte München Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstrasse 1 München81679 Germany INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy Dipartimento di Fisica e Astronomia "Augusto Righi" Alma Mater Studiorum Università di Bologna via Piero Gobetti 93/2 Bologna40129 Italy Laboratoire Univers et Théorie Observatoire de Paris Université PSL Université Paris Cité CNRS Meudon92190 France Université Paris-Saclay CNRS Institut d'astrophysique spatiale Orsay91405 France Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom INAF-Osservatorio Astronomico di Brera Via Brera 28 Milano20122 Italy Dipartimento di Fisica e Astronomia Università di Bologna Via Gobetti 93/2 Bologna40129 Italy INFN-Sezione di Bologna Viale Berti Pichat 6/2 Bologna40127 Italy Max Planck Institute for Extraterrestrial Physics Giessenbachstr. 1 Garching85748 Germany Pino Torinese10025 Italy Dipartimento di Fisica Università di Genova Via Dodecaneso 33 Genova16146 Italy INFN-Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Department of Physics "E. Pancini" University Federico II Via Cinthia 6 Napoli80126 Italy INAF-Osservatorio Astronomico di Capodimonte Via Moiariello 16 Napoli80131 Italy INFN section of Naples Via Cinthia 6 Napoli80126 Italy Instit

The Euclid photometric survey of galaxy clusters stands as a powerful cosmological tool, with the capacity to significantly propel our understanding of the Universe. Despite being subdominant to dark matter and dark energy, the baryonic component of our Universe holds substantial influence over the structure and mass of galaxy clusters. This paper presents a novel model that can be used to precisely quantify the impact of baryons on the virial halo masses of galaxy clusters using the baryon fraction within a cluster as a proxy for their effect. Constructed on the premise of quasi-adiabaticity, the model includes two parameters, which are calibrated using non-radiative cosmological hydrodynamical simulations, and a single large-scale simulation from the Magneticum set, which includes the physical processes driving galaxy formation. As a main result of our analysis, we demonstrate that this model delivers a remarkable 1% relative accuracy in determining the virial dark matter-only equivalent mass of galaxy clusters starting from the corresponding total cluster mass and baryon fraction measured in hydrodynamical simulations. Furthermore, we demonstrate that this result is robust against changes in cosmological parameters and against variation of the numerical implementation of the subresolution physical processes included in the simulations. Our work substantiates previous claims regarding the impact of baryons on cluster cosmology studies. In particular, we show how neglecting these effects would lead to biased cosmological constraints for a Euclid-like cluster abundance analysis. Importantly, we demonstrate that uncertainties associated with our model arising from baryonic corrections to cluster masses are subdominant when compared to the precision with which mass-observable (i.e. richness) relations will be calibrated using Euclid and to our current understanding of the baryon fraction within galaxy clusters. Copyright © 2023, The Authors. All rights reserved.

关键词： Galaxies

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Euclid preparation TBD. Galaxy power spectrum modelling in real space

arXiv

引用

arXiv 2023年

作者： Pezzotta, A. Moretti, C. Zennaro, M. Dizgah, A. Moradinezhad Crocce, M. Sefusatti, E. Ferrero, I. Pardede, K. Eggemeier, A. Barreira, A. Angulo, R.E. Marinucci, M. Quevedo, B. Camacho de la Torre, S. Alkhanishvili, D. Biagetti, M. Breton, M.-A. Castorina, E. D’Amico, G. Desjacques, V. Guidi, M. Kärcher, M. Oddo, A. Ibanez, M. Pellejero Porciani, C. Pugno, A. Salvalaggio, J. Sarpa, E. Veropalumbo, A. Vlah, Z. Amara, A. Andreon, S. Auricchio, N. Baldi, M. Bardelli, S. Bender, R. Bodendorf, C. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Camera, S. Capobianco, V. Carbone, C. Cardone, V.F. Carretero, J. Casas, S. Castander, F.J. Castellano, M. Cavuoti, S. Cimatti, A. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Corcione, L. Courbin, F. Courtois, H.M. Da Silva, A. Degaudenzi, H. Di Giorgio, A.M. Dinis, J. Dupac, X. Dusini, S. Ealet, A. Farina, M. Farrens, S. Fosalba, P. Frailis, M. Franceschi, E. Galeotta, S. Gillis, B. Giocoli, C. Granett, B.R. Grazian, A. Grupp, F. Guzzo, L. Haugan, S.V.H. Hormuth, F. Hornstrup, A. Jahnke, K. Joachimi, B. Keihänen, E. Kermiche, S. Kiessling, A. Kilbinger, M. Kitching, T. Kubik, B. Kunz, M. Kurki-Suonio, H. Ligori, S. Lilje, P.B. Lindholm, V. Lloro, I. Maiorano, E. Mansutti, O. Marggraf, O. Markovic, K. Martinet, N. Marulli, F. Massey, R. Medinaceli, E. Mellier, Y. Meneghetti, M. Merlin, E. Meylan, G. Moresco, M. Moscardini, L. Munari, E. Niemi, S.-M. Padilla, C. Paltani, S. Pasian, F. Pedersen, K. Percival, W.J. Pettorino, V. Pires, S. Polenta, G. Pollack, J.E. Poncet, M. Popa, L.A. Pozzetti, L. Raison, F. Renzi, A. Rhodes, J. Riccio, G. Romelli, E. Roncarelli, M. Rossetti, E. Saglia, R. Sapone, D. Sartoris, B. Schneider, P. Schrabback, T. Secroun, A. Seidel, G. Seiffert, M. Serrano, S. Sirignano, C. Sirri, G. Stanco, L. Surace, C. Tallada-Crespí, P. Taylor, A.N. Tereno, I. Toledo-Moreo, R. Torradeflot, F. Tutusaus, I. Valentijn, E.A. Max Planck Institute for Extraterrestrial Physics Giessenbachstr. 1 Garching85748 Germany SISSA International School for Advanced Studies Via Bonomea 265 TS Trieste34136 Italy ICSC - Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Institute for Astronomy University of Edinburgh Royal Observatory Blackford Hill EdinburghEH9 3HJ United Kingdom INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 Trieste34143 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy Department of Physics Oxford University Keble Road OxfordOX1 3RH United Kingdom Université de Genève Département de Physique Théorique Centre for Astroparticle Physics 24 quai Ernest-Ansermet Genève 4CH-1211 Switzerland Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain Campus UAB Carrer de Can Magrans s/n Cerdanyola del Vallés Barcelona08193 Spain INFN Sezione di Trieste Via Valerio 2 TS Trieste34127 Italy Institute of Theoretical Astrophysics University of Oslo P.O. Box 1029 Blindern Oslo0315 Norway Strada Costiera 11 Trieste34151 Italy Universität Bonn Argelander-Institut für Astronomie Auf dem Hügel 71 Bonn53121 Germany Excellence Cluster ORIGINS Boltzmannstrasse e 2 Garching85748 Germany Ludwig-Maximilians-University Schellingstrasse 4 Munich80799 Germany Paseo Manuel de Lardizabal 4 Donostia-San Sebastián Guipuzkoa20018 Spain IKERBASQUE Basque Foundation for Science Bilbao48013 Spain Dipartimento di Scienze Matematiche Fisiche e Informatiche Università di Parma Viale delle Scienze 7/A Parma43124 Italy Technion Israel Institute of Technology Israel Carrer Gran Capitá 2-4 Barcelona08034 Spain Aix-Marseille Université CNRS CNES LAM Marseille France Area Science Park Località Padriciano 99 Trieste34149 Italy Laboratoire Univers et Théorie Observatoire de Paris Université PSL Université Paris Cité CNRS Meudon92190

We investigate the accuracy of the perturbative galaxy bias expansion in view of the forthcoming analysis of the Euclid spectroscopic galaxy samples. We compare the performance of an Eulerian galaxy bias expansion, using state-of-art prescriptions from the effective field theory of large-scale structure (EFTofLSS), against a hybrid approach based on Lagrangian perturbation theory and high-resolution simulations. These models are benchmarked against comoving snapshots of the Flagship I N-body simulation at z = (0.9, 1.2, 1.5, 1.8), which have been populated with Hα galaxies leading to catalogues of millions of objects within a volume of about 58 h−3 Gpc3. Our analysis suggests that both models can be used to provide a robust inference of the parameters (h, ωc) in the redshift range under consideration, with comparable constraining power. We additionally determine the range of validity of the EFTofLSS model in terms of scale cuts and model degrees of freedom. From these tests, it emerges that the standard third-order Eulerian bias expansion can accurately describe the full shape of the real-space galaxy power spectrum up to the maximum wavenumber kmax = 0.45 hMpc−1, even with a measurement precision well below the percent level. In particular, this is true for a configuration with six free nuisance parameters, including local and non-local bias parameters, a matter counterterm, and a correction to the shot-noise contribution. Fixing either tidal bias parameters to physically-motivated relations still leads to unbiased cosmological constraints. We finally repeat our analysis assuming a volume that matches the expected footprint of Euclid, but without considering observational effects, as purity and completeness, showing that we can get consistent cosmological constraints over this range of scales and redshifts. © 2023, CC BY.

关键词： Galaxies

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Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification

arXiv

引用

arXiv 2017年

作者： Yu, Hong-Xing Wu, Ancong Zheng, Wei-Shi School of Data and Computer Science Sun Yat-sen University China School of Electronics and Information Technology Sun Yat-sen University China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Collaborative Innovation Center of High Performance Computing NUDT China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China

While metric learning is important for Person reidentification (RE-ID), a significant problem in visual surveillance for cross-view pedestrian matching, existing metric models for RE-ID are mostly based on supervised learning that requires quantities of labeled samples in all pairs of camera views for training. However, this limits their scalabilities to realistic applications, in which a large amount of data over multiple disjoint camera views is available but not labelled. To overcome the problem, we propose unsupervised asymmetric metric learning for unsupervised RE-ID. Our model aims to learn an asymmetric metric, i.e., specific projection for each view, based on asymmetric clustering on cross-view person images. Our model finds a shared space where view-specific bias is alleviated and thus better matching performance can be achieved. Extensive experiments have been conducted on a baseline and five large-scale RE-ID datasets to demonstrate the effectiveness of the proposed model. Through the comparison, we show that our model works much more suitable for unsupervised RE-ID compared to classical unsupervised metric learning models. We also compare with existing unsupervised REID methods, and our model outperforms them with notable margins. Specifically, we report the results on large-scale unlabelled RE-ID dataset, which is important but unfortunately less concerned in literatures. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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