Výsledky vyhledávání - "Doogesh Kodi Ramanah"

Dynamical mass inference of galaxy clusters with neural flows

Autor: Jens Hjorth, Zoe Ansari, Christa Gall, Doogesh Kodi Ramanah, Radosław Wojtak

Publikováno v: Ramanah, D K, Wojtak, R, Ansari, Z, Gall, C & Hjorth, J 2020, ' Dynamical mass inference of galaxy clusters with neural flows ', Monthly Notices of the Royal Astronomical Society, vol. 499, no. 2, pp. 1985-1997 . https://doi.org/10.1093/mnras/staa2886

We present an algorithm for inferring the dynamical mass of galaxy clusters directly from their respective phase-space distributions, i.e. the observed line-of-sight velocities and projected distances of galaxies from the cluster centre. Our method e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::287438bbb3d266d20ee50fee8da12a58
https://doi.org/10.1093/mnras/staa2886

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Simulation-based inference of dynamical galaxy cluster masses with 3D convolutional neural networks

Autor: Doogesh Kodi Ramanah, Radosław Wojtak, Nikki Arendse

Publikováno v: Ramanah, D K, Wojtak, R & Arendse, N 2021, ' Simulation-based inference of dynamical galaxy cluster masses with 3D convolutional neural networks ', Monthly Notices of the Royal Astronomical Society, vol. 501, no. 3, pp. 4080-4091 . https://doi.org/10.1093/mnras/staa3922

We present a simulation-based inference framework using a convolutional neural network to infer dynamical masses of galaxy clusters from their observed 3D projected phase-space distribution, which consists of the projected galaxy positions in the sky

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c5df9cc57c2934558ceeedd26fb0977
http://arxiv.org/abs/2009.03340

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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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Optimal and fast $\mathcal {E}/\mathcal {B}$ separation with a dual messenger field

Autor: Benjamin D. Wandelt, Doogesh Kodi Ramanah, Guilhem Lavaux

Publikováno v: Monthly Notices of the Royal Astronomical Society
Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP): Policy P-Oxford Open Option A, 2018, 476 (2), pp.2825-2834. ⟨10.1093/mnras/sty341⟩
Mon.Not.Roy.Astron.Soc.
Mon.Not.Roy.Astron.Soc., 2018, 476 (2), pp.2825-2834. ⟨10.1093/mnras/sty341⟩

International audience; We adapt our recently proposed dual messenger algorithm for spin field reconstruction and showcase its efficiency and effectiveness in Wiener filtering polarized cosmic microwave background (CMB) maps. Unlike conventional prec

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93b0c268aec2d57b0ccb8ae50539b964
https://doi.org/10.1093/mnras/sty341

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Explicit Bayesian treatment of unknown foreground contaminations in galaxy surveys

Autor: Natalia Porqueres, Guilhem Lavaux, Jens Jasche, Doogesh Kodi Ramanah

Publikováno v: Astronomy and Astrophysics-A&A
Astronomy and Astrophysics-A&A, EDP Sciences, 2019, 624, pp.A115. ⟨10.1051/0004-6361/201834844⟩
Astronomy and Astrophysics-A&A, 2019, 624, pp.A115. ⟨10.1051/0004-6361/201834844⟩
Astron.Astrophys.
Astron.Astrophys., 2019, 624, pp.A115. ⟨10.1051/0004-6361/201834844⟩

International audience; The treatment of unknown foreground contaminations will be one of the major challenges for galaxy clustering analyses of coming decadal surveys. These data contaminations introduce erroneous large-scale effects in recovered po

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58a49e811aec5c20a22c624848c7049a
https://mediatum.ub.tum.de/doc/1537981/document.pdf

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Wiener filtering and pure $\mathcal {E}/\mathcal {B}$ decomposition of CMB maps with anisotropic correlated noise

Autor: Guilhem Lavaux, Doogesh Kodi Ramanah, Benjamin D. Wandelt

Publikováno v: Mon.Not.Roy.Astron.Soc.
Mon.Not.Roy.Astron.Soc., 2019, 490 (1), pp.947-961. ⟨10.1093/mnras/stz2608⟩

We present an augmented version of our dual messenger algorithm for spin field reconstruction on the sphere, while accounting for highly non-trivial and realistic noise models such as modulated correlated noise. We also describe an optimization metho

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf0c97715589d6c91723b1d801594e87
https://hal.archives-ouvertes.fr/hal-02193940

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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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The Quijote Simulations

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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Wiener filter reloaded: fast signal reconstruction without preconditioning

Autor: Doogesh Kodi Ramanah, Benjamin D. Wandelt, Guilhem Lavaux

Publikováno v: Mon.Not.Roy.Astron.Soc.
Mon.Not.Roy.Astron.Soc., 2017, 468 (2), pp.1782-1793. ⟨10.1093/mnras/stx527⟩
Mon.Not.Roy.Astron.Soc., 2017, 468 (2), pp.1782-1793. 〈10.1093/mnras/stx527〉
Monthly Notices of the Royal Astronomical Society
Monthly Notices of the Royal Astronomical Society, Oxford University Press (OUP): Policy P-Oxford Open Option A, 2017, 468 (2), pp.1782-1793. ⟨10.1093/mnras/stx527⟩

We present a high performance solution to the Wiener filtering problem via a formulation that is dual to the recently developed messenger technique. This new dual messenger algorithm, like its predecessor, efficiently calculates the Wiener filter sol

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bbb9a3b3805a4cb4db1ae57389f3077
https://hal.archives-ouvertes.fr/hal-01554850

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