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authFullName_s : Francisco Villaescusa-Navarro

The Quijote simulations

Francisco Villaescusa-Navarro , Changhoon Hahn , Elena Massara , Arka Banerjee , Ana Maria Delgado , et al.
Astrophys.J.Suppl., 2020, 250 (1), pp.2. ⟨10.3847/1538-4365/ab9d82⟩
Journal articles hal-02362603v1

Cosmic voids: a novel probe to shed light on our Universe

Alice Pisani , Elena Massara , David N. Spergel , David Alonso , Tessa Baker , et al.
2019
Preprints, Working Papers, ... hal-02080702v1

Statistical properties of paired fixed fields

Francisco Villaescusa-Navarro , Sigurd Naess , Shy Genel , Andrew Pontzen , Benjamin Wandelt , et al.
Astrophys.J., 2018, 867 (2), pp.137. ⟨10.3847/1538-4357/aae52b⟩
Journal articles hal-01823203v1

Quijote-PNG: Simulations of primordial non-Gaussianity and the information content of the matter field power spectrum and bispectrum

William R. Coulton , Francisco Villaescusa-Navarro , Drew Jamieson , Marco Baldi , Gabriel Jung , et al.
Astrophys.J., 2023, 943 (1), pp.64. ⟨10.3847/1538-4357/aca8a7⟩
Journal articles hal-03699874v1

Fisher for complements: Extracting cosmology and neutrino mass from the counts-in-cells PDF

Cora Uhlemann , Oliver Friedrich , Francisco Villaescusa-Navarro , Arka Banerjee , Sandrine Codis
Monthly Notices of the Royal Astronomical Society, 2020, 495 (4), pp.4006-4027. ⟨10.1093/mnras/staa1155⟩
Journal articles hal-02423738v1

Quijote PNG: The information content of the halo power spectrum and bispectrum

William R. Coulton , Francisco Villaescusa-Navarro , Drew Jamieson , Marco Baldi , Gabriel Jung , et al.
Astrophys.J., 2023, 943 (2), pp.178. ⟨10.3847/1538-4357/aca7c1⟩
Journal articles hal-03726336v1

Quijote-PNG: Quasi-maximum likelihood estimation of Primordial Non-Gaussianity in the non-linear halo density field

Gabriel Jung , Dionysios Karagiannis , Michele Liguori , Marco Baldi , William R. Coulton , et al.
Astrophys.J., 2023, 948 (2), pp.2. ⟨10.3847/1538-4357/acc4bd⟩
Journal articles hal-03879314v1
Image document

Neural Networks as Optimal Estimators to Marginalize Over Baryonic Effects

Francisco Villaescusa-Navarro , Benjamin D. Wandelt , Daniel Angles-Alcazar , Shy Genel , Jose Manuel Zorrilla Mantilla , et al.
Astrophys.J., 2022, 928 (1), pp.44. ⟨10.3847/1538-4357/ac54a5⟩
Journal articles hal-03047629v1

The CAMELS project: public data release

Francisco Villaescusa-Navarro , Shy Genel , Daniel Anglés-Alcázar , Lucia A. Perez , Pablo Villanueva-Domingo , et al.
Astrophys.J.Suppl., 2023, 265 (2), pp.54. ⟨10.3847/1538-4365/acbf47⟩
Journal articles hal-03538658v1

Super-resolution emulator of cosmological simulations using deep physical models

Doogesh Kodi Ramanah , Tom Charnock , Francisco Villaescusa-Navarro , Benjamin D. Wandelt
Monthly Notices of the Royal Astronomical Society, 2020, 495, pp.4227. ⟨10.1093/mnras/staa1428⟩
Journal articles hal-02475275v1
Image document

Quijote-PNG: Quasi-maximum likelihood estimation of Primordial Non-Gaussianity in the non-linear dark matter density field

Gabriel Jung , Dionysios Karagiannis , Michele Liguori , Marco Baldi , William R. Coulton , et al.
Astrophys.J., 2022, 940 (1), pp.71. ⟨10.3847/1538-4357/ac9837⟩
Journal articles hal-03699873v1
Image document

The CAMELS Multifield Data Set: Learning the Universe’s Fundamental Parameters with Artificial Intelligence

Francisco Villaescusa-Navarro , Shy Genel , Daniel Angles-Alcazar , Leander Thiele , Romeel Dave , et al.
Astrophys.J.Supp., 2022, 259 (2), pp.61. ⟨10.3847/1538-4365/ac5ab0⟩
Journal articles hal-03373429v1

deep21: a deep learning method for 21 cm foreground removal

T. Lucas Makinen , Lachlan Lancaster , Francisco Villaescusa-Navarro , Peter Melchior , Shirley Ho , et al.
JCAP, 2021, 04, pp.081. ⟨10.1088/1475-7516/2021/04/081⟩
Journal articles hal-03011003v1
Image document

The Circumgalactic Medium from the CAMELS Simulations: Forecasting Constraints on Feedback Processes from Future Sunyaev-Zeldovich Observations

Emily Moser , Nicholas Battaglia , Daisuke Nagai , Erwin Lau , Luis Fernando Machado Poletti Valle , et al.
The Astrophysical Journal, 2022, 933, ⟨10.3847/1538-4357/ac70c6⟩
Journal articles insu-03764662v1

Quijote-PNG: The Information Content of the Halo Mass Function

Gabriel Jung , Andrea Ravenni , Marco Baldi , William R Coulton , Drew Jamieson , et al.
2023
Preprints, Working Papers, ... hal-04117533v1

Breaking baryon-cosmology degeneracy with the electron density power spectrum

Andrina Nicola , Francisco Villaescusa-Navarro , David N. Spergel , Jo Dunkley , Daniel Anglés-Alcázar , et al.
JCAP, 2022, 04 (04), pp.046. ⟨10.1088/1475-7516/2022/04/046⟩
Journal articles hal-03549741v1

Detecting Neutrino Mass by Combining Matter Clustering, Halos, and Voids

Adrian E. Bayer , Francisco Villaescusa-Navarro , Elena Massara , Jia Liu , David N. Spergel , et al.
Astrophys.J., 2021, 919 (1), pp.24. ⟨10.3847/1538-4357/ac0e91⟩
Journal articles hal-03157122v1

Extreme Spheres: Counts-in-cells for 21cm intensity mapping

Oliver Leicht , Cora Uhlemann , Francisco Villaescusa-Navarro , Sandrine Codis , Lars Hernquist , et al.
Monthly Notices of the Royal Astronomical Society, 2019, 484 (1), pp.269-281. ⟨10.1093/mnras/sty3469⟩
Journal articles hal-01871802v1
Image document

HIFLOW: Generating Diverse HI Maps and Inferring Cosmology while Marginalizing over Astrophysics Using Normalizing Flows

Sultan Hassan , Francisco Villaescusa-Navarro , Benjamin Wandelt , David N. Spergel , Daniel Anglés-Alcázar , et al.
The Astrophysical Journal, 2022, 937, ⟨10.3847/1538-4357/ac8b09⟩
Journal articles insu-03839638v1
Image document

The GIGANTES Data Set: Precision Cosmology from Voids in the Machine-learning Era

Christina D. Kreisch , Alice Pisani , Francisco Villaescusa-Navarro , David N. Spergel , Benjamin D. Wandelt , et al.
The Astrophysical Journal, 2022, 935, ⟨10.3847/1538-4357/ac7d4b⟩
Journal articles insu-03839656v1

Robust marginalization of baryonic effects for cosmological inference at the field level

Francisco Villaescusa-Navarro , Shy Genel , Daniel Angles-Alcazar , David N. Spergel , Yin Li , et al.
2021
Preprints, Working Papers, ... hal-03373428v1
Image document

CARPool: fast, accurate computation of large-scale structure statistics by pairing costly and cheap cosmological simulations

Nicolas Chartier , Benjamin Wandelt , Yashar Akrami , Francisco Villaescusa-Navarro
Monthly Notices of the Royal Astronomical Society, 2021, 503 (2), pp.1897-1914. ⟨10.1093/mnras/stab430⟩
Journal articles hal-02959517v1
Image document

Line-Intensity Mapping: 2017 Status Report

Ely D. Kovetz , Marco P. Viero , Adam Lidz , Laura Newburgh , Mubdi Rahman , et al.
2017
Preprints, Working Papers, ... hal-02176413v1