Zobrazeno 1 - 10 of 18 pro vyhledávání: '"Tom Charnock"'
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Akademický článek
The Cosmic Graph: Optimal Information Extraction from Large-Scale Structure using Catalogues
Autor: T. Lucas Makinen, Tom Charnock, Pablo Lemos, Natalia Porqueres, Alan Heavens, Benjamin D. Wandelt
Publikováno v: The Open Journal of Astrophysics, Vol 5 (2022)
We present an implicit likelihood approach to quantifying cosmological information over discrete catalogue data, assembled as graphs. To do so, we explore cosmological parameter constraints using mock dark matter halo catalogues. We employ Informatio
Externí odkaz: https://doaj.org/article/a66d17905c864b70a6c044d17c7ccb4c
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2
The cosmic graph: optimal information extraction from large-scale structure using catalogues
Autor: T Lucas Makinen, Tom Charnock, Pablo Lemos, Natalie Porqueres, Alan F Heavens, Benjamin D Wandelt
We present an implicit likelihood approach to quantifying cosmological information over discrete catalogue data, assembled as graphs. To do so, we explore cosmological parameter constraints using mock dark matter halo catalogues. We employ Informatio
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fa0799a372e52e78e889ca2e6ee0d95
http://hdl.handle.net/10044/1/101619
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5
Lossless, Scalable Implicit Likelihood Inference for Cosmological Fields
Autor: Justin Alsing, T. Lucas Makinen, Benjamin D. Wandelt, Tom Charnock
Publikováno v: JCAP
JCAP, 2021, 11 (11), pp.049. ⟨10.1088/1475-7516/2021/11/049⟩
We present a comparison of simulation-based inference to full, field-based analytical inference in cosmological data analysis. To do so, we explore parameter inference for two cases where the information content is calculable analytically: Gaussian r
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4201a73a421f801a376e2f75f0f7d2ce
http://arxiv.org/abs/2107.07405
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6
Super-resolution emulator of cosmological simulations using deep physical models
Autor: Tom Charnock, Francisco Villaescusa-Navarro, Doogesh Kodi Ramanah, Benjamin D. Wandelt
Publikováno v: Ramanah, D K, Charnock, T, Villaescusa-Navarro, F & Wandelt, B D 2020, ' Super-resolution emulator of cosmological simulations using deep physical models ', Monthly Notices of the Royal Astronomical Society, vol. 495, no. 4, pp. 4227-4236 . https://doi.org/10.1093/mnras/staa1428
Monthly Notices of the Royal Astronomical Society
Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP): Policy P-Oxford Open Option A, 2020, 495, pp.4227. ⟨10.1093/mnras/staa1428⟩
We present an extension of our recently developed Wasserstein optimized model to emulate accurate high-resolution features from computationally cheaper low-resolution cosmological simulations. Our deep physical modelling technique relies on restricte
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::221c4524a38d15b9683308d906f42064
http://arxiv.org/abs/2001.05519
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7
Fast likelihood-free cosmology with neural density estimators and active learning
Autor: Tom Charnock, Stephen M. Feeney, Justin Alsing, Benjamin D. Wandelt
Publikováno v: Mon.Not.Roy.Astron.Soc.
Mon.Not.Roy.Astron.Soc., 2019, 488 (3), pp.4440-4458. ⟨10.1093/mnras/stz1960⟩
Monthly Notices of the Royal Astronomical Society
Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP): Policy P-Oxford Open Option A, 2019, 488 (3), pp.4440-4458. ⟨10.1093/mnras/stz1960⟩
Likelihood-free inference provides a framework for performing rigorous Bayesian inference using only forward simulations, properly accounting for all physical and observational effects that can be successfully included in the simulations. The key cha
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9903f83b4723d86c469bdb071efa64c1
http://arxiv.org/abs/1903.00007
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8
Painting halos from cosmic density fields of dark matter with physically motivated neural networks
Autor: Guilhem Lavaux, Tom Charnock, Doogesh Kodi ramanah
Publikováno v: Phys.Rev.D
Phys.Rev.D, 2019, 100 (4), pp.043515. ⟨10.1103/PhysRevD.100.043515⟩
Physical Review D
Physical Review D, American Physical Society, 2019, 100 (4), pp.043515. ⟨10.1103/PhysRevD.100.043515⟩
We present a novel halo painting network that learns to map approximate 3D dark matter fields to realistic halo distributions. This map is provided via a physically motivated network with which we can learn the non-trivial local relation between dark
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b381d9dfb052273e780f3b17f57d1f91
https://hal.archives-ouvertes.fr/hal-02101666
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9
Inter-comparison of transboundary atmospheric dispersion calculations: A summary of outputs from the ASEAN NPSR benchmark exercise
Autor: Somboon Rassame, Tang Jia Hao, Kampanart Silva, Hoang Sy Than, Nguyen Hao Quang, Chung Keng Yeow, Tom Charnock, Pham Kim Long, Wasin Vechgama, Piyawan Krisanungkura, Vitesh Krishnan, Narakhan Khunsrimek, Tay Bee Kiat, Pham Duy Hien
Publikováno v: Progress in Nuclear Energy. 135:103718
Previous nuclear power plant (NPP) severe accidents have raised great concern in Southeast Asia on the issue of transboundary atmospheric dispersion of an accidental release from an external NPP. This study presents the inter-comparison of atmospheri
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6eceb6f900004f73579e5c23832756f6
https://doi.org/10.1016/j.pnucene.2021.103718
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10
The Quijote Simulations
Autor: Licia Verde, Stéphane Mallat, Siyu He, Francisco Villaescusa-Navarro, Andrej Obuljen, Yin Li, Elena Giusarma, Justin Alsing, Chi-Ting Chiang, Benjamin D. Wandelt, Emanuele Castorina, Shirley Ho, Roman Scoccimarro, Gabriella Contardo, Doogesh Kodi Ramanah, Tom Charnock, Elena Massara, David N. Spergel, Antoine Brochard, Yu Feng, Alice Pisani, Arka Banerjee, Christina D. Kreisch, Ana Maria Delgado, Andrina Nicola, Matteo Viel, Cora Uhlemann, ChangHoon Hahn, Erwan Allys
Publikováno v: Astrophys.J.Suppl.
Astrophys.J.Suppl., 2020, 250 (1), pp.2. ⟨10.3847/1538-4365/ab9d82⟩
The Astrophysical Journal Supplement Series
The Astrophysical Journal Supplement Series, 2020, 250 (1), pp.2. ⟨10.3847/1538-4365/ab9d82⟩
The Quijote simulations are a set of 44,100 full N-body simulations spanning more than 7,000 cosmological models in the $\{\Omega_{\rm m}, \Omega_{\rm b}, h, n_s, \sigma_8, M_\nu, w \}$ hyperplane. At a single redshift the simulations contain more th
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19940f7265979c7f25bec7ad41fe1623
https://doi.org/10.3847/1538-4365/ab9d82
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