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Comparing approximate methods for mock catalogues and covariance matrices I: correlation function

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Comparing approximate methods for mock catalogues and covariance matrices I : correlation function. / Lippich, Martha; Sánchez, Ariel G.; Colavincenzo, Manuel; Sefusatti, Emiliano; Monaco, Pierluigi; Blot, Linda; Crocce, Martin; Alvarez, Marcelo A.; Agrawal, Aniket; Avila, Santiago; Balaguera-Antolínez, Andrés; Bond, Richard; Codis, Sandrine; Vecchia, Claudio Dalla; Dorta, Antonio; Fosalba, Pablo; Izard, Albert; Kitaura, Francisco-Shu; Pellejero-Ibanez, Marcos; Stein, George; Vakili, Mohammadjavad; Yepes, Gustavo.

In: Monthly Notices of the Royal Astronomical Society, Vol. 482, No. 2, 11.01.2019, p. 1786-1806.

Research output: Contribution to journalArticlepeer-review

Harvard

Lippich, M, Sánchez, AG, Colavincenzo, M, Sefusatti, E, Monaco, P, Blot, L, Crocce, M, Alvarez, MA, Agrawal, A, Avila, S, Balaguera-Antolínez, A, Bond, R, Codis, S, Vecchia, CD, Dorta, A, Fosalba, P, Izard, A, Kitaura, F-S, Pellejero-Ibanez, M, Stein, G, Vakili, M & Yepes, G 2019, 'Comparing approximate methods for mock catalogues and covariance matrices I: correlation function', Monthly Notices of the Royal Astronomical Society, vol. 482, no. 2, pp. 1786-1806. https://doi.org/10.1093/mnras/sty2757

APA

Lippich, M., Sánchez, A. G., Colavincenzo, M., Sefusatti, E., Monaco, P., Blot, L., Crocce, M., Alvarez, M. A., Agrawal, A., Avila, S., Balaguera-Antolínez, A., Bond, R., Codis, S., Vecchia, C. D., Dorta, A., Fosalba, P., Izard, A., Kitaura, F-S., Pellejero-Ibanez, M., ... Yepes, G. (2019). Comparing approximate methods for mock catalogues and covariance matrices I: correlation function. Monthly Notices of the Royal Astronomical Society, 482(2), 1786-1806. https://doi.org/10.1093/mnras/sty2757

Vancouver

Lippich M, Sánchez AG, Colavincenzo M, Sefusatti E, Monaco P, Blot L et al. Comparing approximate methods for mock catalogues and covariance matrices I: correlation function. Monthly Notices of the Royal Astronomical Society. 2019 Jan 11;482(2):1786-1806. https://doi.org/10.1093/mnras/sty2757

Author

Lippich, Martha ; Sánchez, Ariel G. ; Colavincenzo, Manuel ; Sefusatti, Emiliano ; Monaco, Pierluigi ; Blot, Linda ; Crocce, Martin ; Alvarez, Marcelo A. ; Agrawal, Aniket ; Avila, Santiago ; Balaguera-Antolínez, Andrés ; Bond, Richard ; Codis, Sandrine ; Vecchia, Claudio Dalla ; Dorta, Antonio ; Fosalba, Pablo ; Izard, Albert ; Kitaura, Francisco-Shu ; Pellejero-Ibanez, Marcos ; Stein, George ; Vakili, Mohammadjavad ; Yepes, Gustavo. / Comparing approximate methods for mock catalogues and covariance matrices I : correlation function. In: Monthly Notices of the Royal Astronomical Society. 2019 ; Vol. 482, No. 2. pp. 1786-1806.

Bibtex

@article{21c92acbbc1f468bbf73e474cde4762f,
title = "Comparing approximate methods for mock catalogues and covariance matrices I: correlation function",
abstract = "This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic two-point correlation function measurements. Our comparison includes seven approximate methods, which can be divided into three categories: predictive methods that follow the evolution of the linear density field deterministically (ICE-COLA, PEAK PATCH, and PINOCCHIO), methods that require a calibration with N-body simulations (PATCHY and HALOGEN), and simpler recipes based on assumptions regarding the shape of the probability distribution function (PDF) of density fluctuations (lognormal and Gaussian density fields). We analyse the impact of using covariance estimates obtained from these approximate methods on cosmological analyses of galaxy clustering measurements, using as a reference the covariances inferred from a set of full N-body simulations. We find that all approximate methods can accurately recover the mean parameter values inferred using the N-body covariances. The obtained parameter uncertainties typically agree with the corresponding N-body results within 5 per cent for our lower mass threshold and 10 per cent for our higher mass threshold. Furthermore, we find that the constraints for some methods can differ by up to 20 per cent depending on whether the halo samples used to define the covariance matrices are defined by matching the mass, number density, or clustering amplitude of the parent N-body samples. The results of our configuration-space analysis indicate that most approximate methods provide similar results, with no single method clearly outperforming the others.",
keywords = "astro-ph.CO, RCUK, STFC, ST/K00283X/1",
author = "Martha Lippich and S{\'a}nchez, {Ariel G.} and Manuel Colavincenzo and Emiliano Sefusatti and Pierluigi Monaco and Linda Blot and Martin Crocce and Alvarez, {Marcelo A.} and Aniket Agrawal and Santiago Avila and Andr{\'e}s Balaguera-Antol{\'i}nez and Richard Bond and Sandrine Codis and Vecchia, {Claudio Dalla} and Antonio Dorta and Pablo Fosalba and Albert Izard and Francisco-Shu Kitaura and Marcos Pellejero-Ibanez and George Stein and Mohammadjavad Vakili and Gustavo Yepes",
note = "23 pages, 11 figures, MNRAS submitted",
year = "2019",
month = jan,
day = "11",
doi = "10.1093/mnras/sty2757",
language = "English",
volume = "482",
pages = "1786--1806",
journal = "MNRAS",
issn = "0035-8711",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - Comparing approximate methods for mock catalogues and covariance matrices I

T2 - correlation function

AU - Lippich, Martha

AU - Sánchez, Ariel G.

AU - Colavincenzo, Manuel

AU - Sefusatti, Emiliano

AU - Monaco, Pierluigi

AU - Blot, Linda

AU - Crocce, Martin

AU - Alvarez, Marcelo A.

AU - Agrawal, Aniket

AU - Avila, Santiago

AU - Balaguera-Antolínez, Andrés

AU - Bond, Richard

AU - Codis, Sandrine

AU - Vecchia, Claudio Dalla

AU - Dorta, Antonio

AU - Fosalba, Pablo

AU - Izard, Albert

AU - Kitaura, Francisco-Shu

AU - Pellejero-Ibanez, Marcos

AU - Stein, George

AU - Vakili, Mohammadjavad

AU - Yepes, Gustavo

N1 - 23 pages, 11 figures, MNRAS submitted

PY - 2019/1/11

Y1 - 2019/1/11

N2 - This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic two-point correlation function measurements. Our comparison includes seven approximate methods, which can be divided into three categories: predictive methods that follow the evolution of the linear density field deterministically (ICE-COLA, PEAK PATCH, and PINOCCHIO), methods that require a calibration with N-body simulations (PATCHY and HALOGEN), and simpler recipes based on assumptions regarding the shape of the probability distribution function (PDF) of density fluctuations (lognormal and Gaussian density fields). We analyse the impact of using covariance estimates obtained from these approximate methods on cosmological analyses of galaxy clustering measurements, using as a reference the covariances inferred from a set of full N-body simulations. We find that all approximate methods can accurately recover the mean parameter values inferred using the N-body covariances. The obtained parameter uncertainties typically agree with the corresponding N-body results within 5 per cent for our lower mass threshold and 10 per cent for our higher mass threshold. Furthermore, we find that the constraints for some methods can differ by up to 20 per cent depending on whether the halo samples used to define the covariance matrices are defined by matching the mass, number density, or clustering amplitude of the parent N-body samples. The results of our configuration-space analysis indicate that most approximate methods provide similar results, with no single method clearly outperforming the others.

AB - This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic two-point correlation function measurements. Our comparison includes seven approximate methods, which can be divided into three categories: predictive methods that follow the evolution of the linear density field deterministically (ICE-COLA, PEAK PATCH, and PINOCCHIO), methods that require a calibration with N-body simulations (PATCHY and HALOGEN), and simpler recipes based on assumptions regarding the shape of the probability distribution function (PDF) of density fluctuations (lognormal and Gaussian density fields). We analyse the impact of using covariance estimates obtained from these approximate methods on cosmological analyses of galaxy clustering measurements, using as a reference the covariances inferred from a set of full N-body simulations. We find that all approximate methods can accurately recover the mean parameter values inferred using the N-body covariances. The obtained parameter uncertainties typically agree with the corresponding N-body results within 5 per cent for our lower mass threshold and 10 per cent for our higher mass threshold. Furthermore, we find that the constraints for some methods can differ by up to 20 per cent depending on whether the halo samples used to define the covariance matrices are defined by matching the mass, number density, or clustering amplitude of the parent N-body samples. The results of our configuration-space analysis indicate that most approximate methods provide similar results, with no single method clearly outperforming the others.

KW - astro-ph.CO

KW - RCUK

KW - STFC

KW - ST/K00283X/1

UR - http://www.scopus.com/inward/record.url?scp=85057192783&partnerID=8YFLogxK

UR - https://arxiv.org/abs/1806.09477

U2 - 10.1093/mnras/sty2757

DO - 10.1093/mnras/sty2757

M3 - Article

VL - 482

SP - 1786

EP - 1806

JO - MNRAS

JF - MNRAS

SN - 0035-8711

IS - 2

ER -

ID: 10769090