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TensorFlow quantum: A software framework for quantum machine learning

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arXiv 2020年

作者： Broughton, Michael Verdon, Guillaume McCourt, Trevor Martinez, Antonio J. Yoo, Jae Hyeon Isakov, Sergei V. Massey, Philip Halavati, Ramin Niu, Murphy Yuezhen Zlokapa, Alexander Peters, Evan Lockwood, Owen Skolik, Andrea Jerbi, Sofiene Dunjko, Vedran Leib, Martin Streif, Michael Von Dollen, David Chen, Hongxiang Cao, Shuxiang Wiersema, Roeland Huang, Hsin-Yuan McClean, Jarrod R. Babbush, Ryan Boixo, Sergio Bacon, Dave Ho, Alan K. Neven, Hartmut Mohseni, Masoud Google Quantum Ai Mountain ViewCA United States Sandbox Alphabet Mountain ViewCA United States Google Mountain ViewCA United States Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada School of Computer Science University of Waterloo WaterlooONN2L 3G1 Canada Department of Applied Mathematics University of Waterloo WaterlooONN2L 3G1 Canada Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Division of Physics Mathematics and Astronomy Caltech PasadenaCA91125 United States Fermi National Accelerator Laboratory P.O. Box 500 BataviaIL605010 United States Department of Computer Science Rensselaer Polytechnic Institute TroyNY12180 United States Data:Lab Volkswagen Group Ungererstr. 69 München80805 Germany Leiden University Niels Bohrweg 1 Leiden2333 CA Netherlands Institute for Theoretical Physics University of Innsbruck Technikerstr. 21a InnsbruckA-6020 Austria Institute of Theoretical Physics Staudtstr. 7 Erlangen91058 Germany Volkswagen Group Advanced Technologies San FranciscoCA94108 United States Rahko Ltd. Finsbury Park LondonN4 3JP United Kingdom Department of Computer Science University College London WC1E 6BT United Kingdom Clarendon Laboratory Department of Physics University of Oxford OxfordOX1 3PU United Kingdom Vector Institute MaRS Centre TorontoONM5G 1M1 Canada Department of Physics and Astronomy University of Waterloo ONN2L 3G1 Canada Institute for Quantum Information and Matter Caltech PasadenaCA United States Department of Computing and Mathematical Sciences Caltech PasadenaCA United States

We introduce TensorFlow quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high-level abstractions for the design and training of both discriminative and generative quantum models under TensorFlow and supports high-performance quantum circuit simulators. We provide an overview of the software architecture and building blocks through several examples and review the theory of hybrid quantum-classical neural networks. We illustrate TFQ functionalities via several basic applications including supervised learning for quantum classification, quantum control, simulating noisy quantum circuits, and quantum approximate optimization. Moreover, we demonstrate how one can apply TFQ to tackle advanced quantum learning tasks including meta-learning, layerwise learning, Hamiltonian learning, sampling thermal states, variational quantum eigensolvers, classification of quantum phase transitions, generative adversarial networks, and reinforcement learning. We hope this framework provides the necessary tools for the quantum computing and machine learning research communities to explore models of both natural and artificial quantum systems, and ultimately discover new quantum algorithms which could potentially yield a quantum advantage. Copyright © 2020, The Authors. All rights reserved.

关键词： Open source software

Machine learning and the physical sciences

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arXiv 2019年

作者： Carleo, Giuseppe Cirac, Ignacio Cranmer, Kyle Daudet, Laurent Schuld, Maria Tishby, Naftali Vogt-Maranto, Leslie Zdeborová, Lenka Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Max-Planck-Institut fur Quantenoptik Hans-Kopfermann-Straße 1 GarchingD-85748 Germany Center for Cosmology and Particle Physics Center of Data Science New York University 726 Broadway New YorkNY10003 United States LightOn 2 rue de la Bourse ParisF-75002 France University of KwaZulu-Natal Durban4000 South Africa Xanadu Quantum Computing 777 Bay Street TorontoM5B 2H7 Canada Hebrew University of Jerusalem Edmond Safra Campus Jerusalem91904 Israel Department of Chemistry New York University New YorkNY10003 United States Institut de physique théorique Université Paris Saclay CNRS CEA Gif-sur-YvetteF-91191 France

Machine learning encompasses a broad range of algorithms and modeling tools used for a vast array of data processing tasks, which has entered most scientific disciplines in recent years. We review in a selective way the recent research on the interface between machine learning and physical sciences. This includes conceptual developments in machine learning (ML) motivated by physical insights, applications of machine learning techniques to several domains in physics, and cross-fertilization between the two fields. After giving basic notion of machine learning methods and principles, we describe examples of how statistical physics is used to understand methods in ML. We then move to describe applications of ML methods in particle physics and cosmology, quantum many body physics, quantum computing, and chemical and material physics. We also highlight research and development into novel computing architectures aimed at accelerating ML. In each of the sections we describe recent successes as well as domain-specific methodology and challenges. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Output statistics of quantum annealers with disorder

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arXiv 2018年

作者： Brugger, Jonathan Seidel, Christian Streif, Michael Wudarski, Filip A. Dittel, Christoph Buchleitner, Andreas Physikalisches Institut Albert-Ludwigs-Universität Freiburg Herrmann-Herder-Straße 3 FreiburgD-79104 Germany Data:Lab Volkswagen Group Ungererstr. 69 München80805 Germany Institute of Physics Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Grudziądzka 5/7 Toruń87–100 Poland EUCOR Centre for Quantum Science and Quantum Computing Albert-Ludwigs-Universität Freiburg Herrmann-Herder-Straße 3 FreiburgD-79104 Germany

We demonstrate that the output statistics of a standard quantum annealing protocol run on D-Wave 2000Q can be mimicked by static disorder garnishing an otherwise ideal device hardware – for a 10-qubit toy Hamiltonian as well as for problem instances with thousands of qubits. A Boltzmann-like distribution over distinct output states is shown to emerge with increasing disorder strength. Copyright © 2018, The Authors. All rights reserved.

关键词： Toys

Stable quantum memories with limited measurement

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Physical Review A 2018年第3期98卷 032322-032322页

作者： C. Daniel Freeman Mohan Sarovar C. M. Herdman K. B. Whaley Berkeley Quantum Information & Computation Center University of California Berkeley California 94720 USA Department of Physics University of California Berkeley California 94720 USA Extreme-scale Data Science and Analytics Sandia National Laboratories Livermore California 94550 USA Institute for Quantum Computing University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Chemistry University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Physics & Astronomy University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Chemistry University of California Berkeley California 94720 USA

We demonstrate the existence of a finite temperature threshold for a one-dimensional stabilizer code under an error correcting protocol that requires only a fraction of the syndrome measurements. Below the threshold temperature, encoded states have exponentially long lifetimes, as demonstrated by numerical and analytical arguments. We sketch how this algorithm generalizes to higher-dimensional stabilizer codes with stringlike excitations, such as the toric code.

关键词： quantum error correction quantum memories

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

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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

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

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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

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

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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

Euclid preparation TBD. Galaxy power spectrum modelling in real space

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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

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