Fast and accurate parameter estimation of high-redshift sources with the Einstein Telescope

Fuente: arXiv
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Autori principali: Santoliquido, Filippo, Tissino, Jacopo, Dupletsa, Ulyana, Branchesi, Marica, Harms, Jan, Sedda, Manuel Arca, Dax, Maximilian, Kofler, Annalena, Green, Stephen R., Gupte, Nihar, Romero-Shaw, Isobel M., Berti, Emanuele
Natura: Preprint
Pubblicazione: 2025
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author Santoliquido, Filippo
Tissino, Jacopo
Dupletsa, Ulyana
Branchesi, Marica
Harms, Jan
Sedda, Manuel Arca
Dax, Maximilian
Kofler, Annalena
Green, Stephen R.
Gupte, Nihar
Romero-Shaw, Isobel M.
Berti, Emanuele
author_facet Santoliquido, Filippo
Tissino, Jacopo
Dupletsa, Ulyana
Branchesi, Marica
Harms, Jan
Sedda, Manuel Arca
Dax, Maximilian
Kofler, Annalena
Green, Stephen R.
Gupte, Nihar
Romero-Shaw, Isobel M.
Berti, Emanuele
contents The Einstein Telescope (ET), along with other third-generation gravitational wave (GW) detectors, will be a key instrument for detecting GWs in the coming decades. However, analyzing the data and estimating source parameters will be challenging, especially given the large number of expected detections-on the order of $10^5$ per year-which makes current methods based on stochastic sampling impractical. In this work, we use Dingo-IS to perform neural posterior estimation (NPE) of high-redshift events detectable with ET in its triangular configuration. NPE is a likelihood-free inference technique that leverages normalizing flows to approximate posterior distributions. After training, inference is fast, requiring only a few minutes per source, and accurate, as corrected through importance sampling and validated against standard Bayesian inference methods. To confirm previous findings on the ability to estimate parameters for high-redshift sources with ET, we compare NPE results with predictions from the Fisher information matrix (FIM) approximation. We find that NPE correctly recovers the eight degenerate sky modes induced by the triangular detector geometry, missed by the FIM analysis, resulting in an underestimation of sky localization uncertainties for most sources. FIM also overestimates the uncertainty in luminosity distance by a factor of $\sim 3$ on average when the injected luminosity distance is $d^{\mathrm{inj}}_{\mathrm{L}} > 10^5~$Mpc, further confirming that ET will be particularly well suited for studying the early Universe.
format Preprint
id arxiv_https___arxiv_org_abs_2504_21087
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fast and accurate parameter estimation of high-redshift sources with the Einstein Telescope
Santoliquido, Filippo
Tissino, Jacopo
Dupletsa, Ulyana
Branchesi, Marica
Harms, Jan
Sedda, Manuel Arca
Dax, Maximilian
Kofler, Annalena
Green, Stephen R.
Gupte, Nihar
Romero-Shaw, Isobel M.
Berti, Emanuele
High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
General Relativity and Quantum Cosmology
The Einstein Telescope (ET), along with other third-generation gravitational wave (GW) detectors, will be a key instrument for detecting GWs in the coming decades. However, analyzing the data and estimating source parameters will be challenging, especially given the large number of expected detections-on the order of $10^5$ per year-which makes current methods based on stochastic sampling impractical. In this work, we use Dingo-IS to perform neural posterior estimation (NPE) of high-redshift events detectable with ET in its triangular configuration. NPE is a likelihood-free inference technique that leverages normalizing flows to approximate posterior distributions. After training, inference is fast, requiring only a few minutes per source, and accurate, as corrected through importance sampling and validated against standard Bayesian inference methods. To confirm previous findings on the ability to estimate parameters for high-redshift sources with ET, we compare NPE results with predictions from the Fisher information matrix (FIM) approximation. We find that NPE correctly recovers the eight degenerate sky modes induced by the triangular detector geometry, missed by the FIM analysis, resulting in an underestimation of sky localization uncertainties for most sources. FIM also overestimates the uncertainty in luminosity distance by a factor of $\sim 3$ on average when the injected luminosity distance is $d^{\mathrm{inj}}_{\mathrm{L}} > 10^5~$Mpc, further confirming that ET will be particularly well suited for studying the early Universe.
title Fast and accurate parameter estimation of high-redshift sources with the Einstein Telescope
topic High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
General Relativity and Quantum Cosmology
url https://arxiv.org/abs/2504.21087