Effort: a fast and differentiable emulator for the Effective Field Theory of the Large Scale Structure of the Universe

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Main Authors: Bonici, Marco, D'Amico, Guido, Bel, Julien, Carbone, Carmelita
Format: Preprint
Published: 2025
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author Bonici, Marco
D'Amico, Guido
Bel, Julien
Carbone, Carmelita
author_facet Bonici, Marco
D'Amico, Guido
Bel, Julien
Carbone, Carmelita
contents We present the official release of the EFfective Field theORy surrogaTe (Effort), a novel and efficient emulator designed for the Effective Field Theory of Large-Scale Structure (EFTofLSS). This tool combines state-of-the-art numerical methods and clever preprocessing strategies to achieve exceptional computational performance without sacrificing accuracy. To validate the emulator reliability, we compare Bayesian posteriors sampled using Effort via Hamiltonian MonteCarlo methods to the ones sampled using the widely-used pybird code, via the Metropolis-Hastings sampler. On a large-volume set of simulations, and on the BOSS dataset, the comparison confirms excellent agreement, with deviations compatible with MonteCarlo noise. Looking ahead, Effort is poised to analyze next-generation cosmological datasets and to support joint analyses with complementary tools.
format Preprint
id arxiv_https___arxiv_org_abs_2501_04639
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Effort: a fast and differentiable emulator for the Effective Field Theory of the Large Scale Structure of the Universe
Bonici, Marco
D'Amico, Guido
Bel, Julien
Carbone, Carmelita
Cosmology and Nongalactic Astrophysics
Instrumentation and Methods for Astrophysics
We present the official release of the EFfective Field theORy surrogaTe (Effort), a novel and efficient emulator designed for the Effective Field Theory of Large-Scale Structure (EFTofLSS). This tool combines state-of-the-art numerical methods and clever preprocessing strategies to achieve exceptional computational performance without sacrificing accuracy. To validate the emulator reliability, we compare Bayesian posteriors sampled using Effort via Hamiltonian MonteCarlo methods to the ones sampled using the widely-used pybird code, via the Metropolis-Hastings sampler. On a large-volume set of simulations, and on the BOSS dataset, the comparison confirms excellent agreement, with deviations compatible with MonteCarlo noise. Looking ahead, Effort is poised to analyze next-generation cosmological datasets and to support joint analyses with complementary tools.
title Effort: a fast and differentiable emulator for the Effective Field Theory of the Large Scale Structure of the Universe
topic Cosmology and Nongalactic Astrophysics
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2501.04639