Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond

S. Ramirez-Solano; M. Icaza-Lizaola; H. E. Noriega; M. Vargas-Magaña; S. Fromenteau; A. Aviles; F. Rodriguez-Martinez; J. Aguilar; S. Ahlen; O. Alves; S. Brieden; D. Brooks; T. Claybaugh; S. Cole; A. de la Macorra; Arjun Dey; B. Dey; P. Doel; K. Fanning; J. E. Forero-Romero; E. Gaztañaga; H. Gil-Marín; S. Gontcho A Gontcho; K. Honscheid; C. Howlett; S. Juneau; M. Landriau; M. Manera; M. Maus; R. Miquel; E. Mueller; A. Muñoz-Gutiérrez; A. D. Myers; S. Nadathur; J. Nie; W. J. Percival; C. Poppett; M. Rezaie; G. Rossi; E. Sanchez; D. Schlegel; M. Schubnell; H. Seo; D. Sprayberry; G. Tarlé; L. Verde; B. A. Weaver; R. H. Wechsler; S. Yuan; P. Zarrouk; H. Zou

doi:10.1088/1475-7516/2025/01/129

Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond

S. Ramirez-Solano, M. Icaza-Lizaola, H. E. Noriega, M. Vargas-Magaña, S. Fromenteau, A. Aviles, F. Rodriguez-Martinez, J. Aguilar, S. Ahlen, O. Alves, S. Brieden, D. Brooks, T. Claybaugh, S. Cole, A. de la Macorra, Arjun Dey, B. Dey, P. Doel, K. Fanning, J. E. Forero-RomeroE. Gaztañaga, H. Gil-Marín, S. Gontcho A Gontcho, K. Honscheid, C. Howlett, S. Juneau, M. Landriau, M. Manera, M. Maus, R. Miquel, E. Mueller, A. Muñoz-Gutiérrez, A. D. Myers, S. Nadathur, J. Nie, W. J. Percival, C. Poppett, M. Rezaie, G. Rossi, E. Sanchez, D. Schlegel, M. Schubnell, H. Seo, D. Sprayberry, G. Tarlé, L. Verde, B. A. Weaver, R. H. Wechsler, S. Yuan, P. Zarrouk, H. Zou

Institute of Cosmology & Gravitation

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Abstract

In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying n_s and allowing for w₀w_aCDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.

Original language	English
Article number	129
Pages (from-to)	1-56
Number of pages	56
Journal	Journal of Cosmology and Astroparticle Physics
Volume	2025
Issue number	1
DOIs	https://doi.org/10.1088/1475-7516/2025/01/129
Publication status	Published - 30 Jan 2025

Keywords

astro-ph.CO
dark energy experiments
galaxy clustering
UKRI
STFC

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10.1088/1475-7516/2025/01/129Licence: CC BY

Ramirez-Solano_2025_J._Cosmol._Astropart._Phys._2025_129Final published version, 3.82 MBLicence: CC BY

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Ramirez-Solano, S., Icaza-Lizaola, M., Noriega, H. E., Vargas-Magaña, M., Fromenteau, S., Aviles, A., Rodriguez-Martinez, F., Aguilar, J., Ahlen, S., Alves, O., Brieden, S., Brooks, D., Claybaugh, T., Cole, S., Macorra, A. D. L., Dey, A., Dey, B., Doel, P., Fanning, K., ... Zou, H. (2025). Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond. Journal of Cosmology and Astroparticle Physics, 2025(1), 1-56. Article 129. https://doi.org/10.1088/1475-7516/2025/01/129

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title = "Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond",

abstract = "In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying ns and allowing for w0waCDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.",

keywords = "astro-ph.CO, dark energy experiments, galaxy clustering, UKRI, STFC",

author = "S. Ramirez-Solano and M. Icaza-Lizaola and Noriega, {H. E.} and M. Vargas-Maga{\~n}a and S. Fromenteau and A. Aviles and F. Rodriguez-Martinez and J. Aguilar and S. Ahlen and O. Alves and S. Brieden and D. Brooks and T. Claybaugh and S. Cole and Macorra, {A. de la} and Arjun Dey and B. Dey and P. Doel and K. Fanning and Forero-Romero, {J. E.} and E. Gazta{\~n}aga and H. Gil-Mar{\'i}n and Gontcho, {S. Gontcho A} and K. Honscheid and C. Howlett and S. Juneau and M. Landriau and M. Manera and M. Maus and R. Miquel and E. Mueller and A. Mu{\~n}oz-Guti{\'e}rrez and Myers, {A. D.} and S. Nadathur and J. Nie and Percival, {W. J.} and C. Poppett and M. Rezaie and G. Rossi and E. Sanchez and D. Schlegel and M. Schubnell and H. Seo and D. Sprayberry and G. Tarl{\'e} and L. Verde and Weaver, {B. A.} and Wechsler, {R. H.} and S. Yuan and P. Zarrouk and H. Zou",

note = "Supporting publication of DESI 2024 KP5",

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doi = "10.1088/1475-7516/2025/01/129",

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Ramirez-Solano, S, Icaza-Lizaola, M, Noriega, HE, Vargas-Magaña, M, Fromenteau, S, Aviles, A, Rodriguez-Martinez, F, Aguilar, J, Ahlen, S, Alves, O, Brieden, S, Brooks, D, Claybaugh, T, Cole, S, Macorra, ADL, Dey, A, Dey, B, Doel, P, Fanning, K, Forero-Romero, JE, Gaztañaga, E, Gil-Marín, H, Gontcho, SGA, Honscheid, K, Howlett, C, Juneau, S, Landriau, M, Manera, M, Maus, M, Miquel, R, Mueller, E, Muñoz-Gutiérrez, A, Myers, AD, Nadathur, S, Nie, J, Percival, WJ, Poppett, C, Rezaie, M, Rossi, G, Sanchez, E, Schlegel, D, Schubnell, M, Seo, H, Sprayberry, D, Tarlé, G, Verde, L, Weaver, BA, Wechsler, RH, Yuan, S, Zarrouk, P & Zou, H 2025, 'Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond', Journal of Cosmology and Astroparticle Physics, vol. 2025, no. 1, 129, pp. 1-56. https://doi.org/10.1088/1475-7516/2025/01/129

TY - JOUR

T1 - Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond

AU - Ramirez-Solano, S.

AU - Icaza-Lizaola, M.

AU - Noriega, H. E.

AU - Vargas-Magaña, M.

AU - Fromenteau, S.

AU - Aviles, A.

AU - Rodriguez-Martinez, F.

AU - Aguilar, J.

AU - Ahlen, S.

AU - Alves, O.

AU - Brieden, S.

AU - Brooks, D.

AU - Claybaugh, T.

AU - Cole, S.

AU - Macorra, A. de la

AU - Dey, Arjun

AU - Dey, B.

AU - Doel, P.

AU - Fanning, K.

AU - Forero-Romero, J. E.

AU - Gaztañaga, E.

AU - Gil-Marín, H.

AU - Gontcho, S. Gontcho A

AU - Honscheid, K.

AU - Howlett, C.

AU - Juneau, S.

AU - Landriau, M.

AU - Manera, M.

AU - Maus, M.

AU - Miquel, R.

AU - Mueller, E.

AU - Muñoz-Gutiérrez, A.

AU - Myers, A. D.

AU - Nadathur, S.

AU - Nie, J.

AU - Percival, W. J.

AU - Poppett, C.

AU - Rezaie, M.

AU - Rossi, G.

AU - Sanchez, E.

AU - Schlegel, D.

AU - Schubnell, M.

AU - Seo, H.

AU - Sprayberry, D.

AU - Tarlé, G.

AU - Verde, L.

AU - Weaver, B. A.

AU - Wechsler, R. H.

AU - Yuan, S.

AU - Zarrouk, P.

AU - Zou, H.

N1 - Supporting publication of DESI 2024 KP5

PY - 2025/1/30

Y1 - 2025/1/30

N2 - In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying ns and allowing for w0waCDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.

AB - In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying ns and allowing for w0waCDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.

KW - astro-ph.CO

KW - dark energy experiments

KW - galaxy clustering

KW - UKRI

KW - STFC

U2 - 10.1088/1475-7516/2025/01/129

DO - 10.1088/1475-7516/2025/01/129

M3 - Article

SN - 1475-7516

VL - 2025

SP - 1

EP - 56

JO - Journal of Cosmology and Astroparticle Physics

JF - Journal of Cosmology and Astroparticle Physics

IS - 1

M1 - 129

ER -

Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond

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