No Cover Image

Journal article 132 views 10 downloads

Bayesian reconstruction of primordial perturbations from induced gravitational waves

Aya Ghaleb, Ameek Malhotra Orcid Logo, Gianmassimo Tasinato Orcid Logo, Ivonne Zavala Carrasco Orcid Logo

Physical Review D, Volume: 112, Issue: 12, Start page: 123538

Swansea University Authors: Aya Ghaleb, Ameek Malhotra Orcid Logo, Gianmassimo Tasinato Orcid Logo, Ivonne Zavala Carrasco Orcid Logo

  • 71107.VOR.pdf

    PDF | Version of Record

    Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license.

    Download (2.62MB)

Check full text

DOI (Published version): 10.1103/n23j-5bfc

Abstract

The formation of primordial black holes or other dark matter relics from amplified density fluctuations in the early Universe may also generate scalar-induced gravitational waves (GW), carrying vital information about the primordial power spectrum and the early expansion history of our Universe. We...

Full description

Published in: Physical Review D
ISSN: 2470-0010 2470-0029
Published: American Physical Society (APS) 2025
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa71107
first_indexed 2025-12-08T10:52:43Z
last_indexed 2026-01-10T05:26:19Z
id cronfa71107
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2026-01-09T15:05:16.8069133</datestamp><bib-version>v2</bib-version><id>71107</id><entry>2025-12-08</entry><title>Bayesian reconstruction of primordial perturbations from induced gravitational waves</title><swanseaauthors><author><sid>c48e382157937a3ecaf19ebde29e42d2</sid><firstname>Aya</firstname><surname>Ghaleb</surname><name>Aya Ghaleb</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>dd6ebf069325cdbdbeb597fa64d48063</sid><ORCID>0000-0001-8346-9995</ORCID><firstname>Ameek</firstname><surname>Malhotra</surname><name>Ameek Malhotra</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>cb754b073d1e4949c5e3db97744d3301</sid><ORCID>0000-0002-9835-4864</ORCID><firstname>Gianmassimo</firstname><surname>Tasinato</surname><name>Gianmassimo Tasinato</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>2fb8d4bb665e9a89d3b3478c17f646f8</sid><ORCID>0000-0002-5589-9928</ORCID><firstname>Ivonne</firstname><surname>Zavala Carrasco</surname><name>Ivonne Zavala Carrasco</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2025-12-08</date><deptcode>BGPS</deptcode><abstract>The formation of primordial black holes or other dark matter relics from amplified density fluctuations in the early Universe may also generate scalar-induced gravitational waves (GW), carrying vital information about the primordial power spectrum and the early expansion history of our Universe. We present a Bayesian approach aimed at reconstructing both the shape of the scalar power spectrum and the Universe&#x2019;s equation of state from GW observations, using interpolating splines to flexibly capture features in the GW data. The optimal number of spline nodes is chosen via Bayesian evidence, aiming at balancing complexity of the model and the fidelity of the reconstruction. We test our method using both representative mock data and recent pulsar timing array measurements, demonstrating that it can accurately reconstruct the curvature power spectrum as well as the underlying equation of state, if different from radiation.</abstract><type>Journal Article</type><journal>Physical Review D</journal><volume>112</volume><journalNumber>12</journalNumber><paginationStart>123538</paginationStart><paginationEnd/><publisher>American Physical Society (APS)</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2470-0010</issnPrint><issnElectronic>2470-0029</issnElectronic><keywords/><publishedDay>24</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2025</publishedYear><publishedDate>2025-12-24</publishedDate><doi>10.1103/n23j-5bfc</doi><url/><notes/><college>COLLEGE NANME</college><department>Biosciences Geography and Physics School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BGPS</DepartmentCode><institution>Swansea University</institution><apcterm>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>STFC Grants No. ST/T000813/1 and No. ST/X000648/1; UKRI AIMLAC CDT (Artificial Intelligence, Machine Learning and Advanced Computing)-(Center for Doctoral Training), funded by Grant No. EP/S023992/1; We also acknowledge the support of the Supercomputing Wales project, which is part-funded by the European Regional Development Fund (ERDF) via Welsh Government.</funders><projectreference/><lastEdited>2026-01-09T15:05:16.8069133</lastEdited><Created>2025-12-08T10:51:23.3313328</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Biosciences, Geography and Physics - Physics</level></path><authors><author><firstname>Aya</firstname><surname>Ghaleb</surname><order>1</order></author><author><firstname>Ameek</firstname><surname>Malhotra</surname><orcid>0000-0001-8346-9995</orcid><order>2</order></author><author><firstname>Gianmassimo</firstname><surname>Tasinato</surname><orcid>0000-0002-9835-4864</orcid><order>3</order></author><author><firstname>Ivonne</firstname><surname>Zavala Carrasco</surname><orcid>0000-0002-5589-9928</orcid><order>4</order></author></authors><documents><document><filename>71107__35951__ed834642d8664bd0a962bc96f410c6f1.pdf</filename><originalFilename>71107.VOR.pdf</originalFilename><uploaded>2026-01-09T15:02:18.2565611</uploaded><type>Output</type><contentLength>2747825</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2026-01-09T15:05:16.8069133 v2 71107 2025-12-08 Bayesian reconstruction of primordial perturbations from induced gravitational waves c48e382157937a3ecaf19ebde29e42d2 Aya Ghaleb Aya Ghaleb true false dd6ebf069325cdbdbeb597fa64d48063 0000-0001-8346-9995 Ameek Malhotra Ameek Malhotra true false cb754b073d1e4949c5e3db97744d3301 0000-0002-9835-4864 Gianmassimo Tasinato Gianmassimo Tasinato true false 2fb8d4bb665e9a89d3b3478c17f646f8 0000-0002-5589-9928 Ivonne Zavala Carrasco Ivonne Zavala Carrasco true false 2025-12-08 BGPS The formation of primordial black holes or other dark matter relics from amplified density fluctuations in the early Universe may also generate scalar-induced gravitational waves (GW), carrying vital information about the primordial power spectrum and the early expansion history of our Universe. We present a Bayesian approach aimed at reconstructing both the shape of the scalar power spectrum and the Universe’s equation of state from GW observations, using interpolating splines to flexibly capture features in the GW data. The optimal number of spline nodes is chosen via Bayesian evidence, aiming at balancing complexity of the model and the fidelity of the reconstruction. We test our method using both representative mock data and recent pulsar timing array measurements, demonstrating that it can accurately reconstruct the curvature power spectrum as well as the underlying equation of state, if different from radiation. Journal Article Physical Review D 112 12 123538 American Physical Society (APS) 2470-0010 2470-0029 24 12 2025 2025-12-24 10.1103/n23j-5bfc COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University SU Library paid the OA fee (TA Institutional Deal) STFC Grants No. ST/T000813/1 and No. ST/X000648/1; UKRI AIMLAC CDT (Artificial Intelligence, Machine Learning and Advanced Computing)-(Center for Doctoral Training), funded by Grant No. EP/S023992/1; We also acknowledge the support of the Supercomputing Wales project, which is part-funded by the European Regional Development Fund (ERDF) via Welsh Government. 2026-01-09T15:05:16.8069133 2025-12-08T10:51:23.3313328 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Physics Aya Ghaleb 1 Ameek Malhotra 0000-0001-8346-9995 2 Gianmassimo Tasinato 0000-0002-9835-4864 3 Ivonne Zavala Carrasco 0000-0002-5589-9928 4 71107__35951__ed834642d8664bd0a962bc96f410c6f1.pdf 71107.VOR.pdf 2026-01-09T15:02:18.2565611 Output 2747825 application/pdf Version of Record true Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. true eng https://creativecommons.org/licenses/by/4.0/
title Bayesian reconstruction of primordial perturbations from induced gravitational waves
spellingShingle Bayesian reconstruction of primordial perturbations from induced gravitational waves
Aya Ghaleb
Ameek Malhotra
Gianmassimo Tasinato
Ivonne Zavala Carrasco
title_short Bayesian reconstruction of primordial perturbations from induced gravitational waves
title_full Bayesian reconstruction of primordial perturbations from induced gravitational waves
title_fullStr Bayesian reconstruction of primordial perturbations from induced gravitational waves
title_full_unstemmed Bayesian reconstruction of primordial perturbations from induced gravitational waves
title_sort Bayesian reconstruction of primordial perturbations from induced gravitational waves
author_id_str_mv c48e382157937a3ecaf19ebde29e42d2
dd6ebf069325cdbdbeb597fa64d48063
cb754b073d1e4949c5e3db97744d3301
2fb8d4bb665e9a89d3b3478c17f646f8
author_id_fullname_str_mv c48e382157937a3ecaf19ebde29e42d2_***_Aya Ghaleb
dd6ebf069325cdbdbeb597fa64d48063_***_Ameek Malhotra
cb754b073d1e4949c5e3db97744d3301_***_Gianmassimo Tasinato
2fb8d4bb665e9a89d3b3478c17f646f8_***_Ivonne Zavala Carrasco
author Aya Ghaleb
Ameek Malhotra
Gianmassimo Tasinato
Ivonne Zavala Carrasco
author2 Aya Ghaleb
Ameek Malhotra
Gianmassimo Tasinato
Ivonne Zavala Carrasco
format Journal article
container_title Physical Review D
container_volume 112
container_issue 12
container_start_page 123538
publishDate 2025
institution Swansea University
issn 2470-0010
2470-0029
doi_str_mv 10.1103/n23j-5bfc
publisher American Physical Society (APS)
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Physics{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Physics
document_store_str 1
active_str 0
description The formation of primordial black holes or other dark matter relics from amplified density fluctuations in the early Universe may also generate scalar-induced gravitational waves (GW), carrying vital information about the primordial power spectrum and the early expansion history of our Universe. We present a Bayesian approach aimed at reconstructing both the shape of the scalar power spectrum and the Universe’s equation of state from GW observations, using interpolating splines to flexibly capture features in the GW data. The optimal number of spline nodes is chosen via Bayesian evidence, aiming at balancing complexity of the model and the fidelity of the reconstruction. We test our method using both representative mock data and recent pulsar timing array measurements, demonstrating that it can accurately reconstruct the curvature power spectrum as well as the underlying equation of state, if different from radiation.
published_date 2025-12-24T05:34:27Z
_version_ 1856987062640574464
score 11.096068

Similar Items