Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis
Quasiperiodic eruptions (QPEs) are luminous, recurring X-ray outbursts from galactic nuclei, with timescales of hours to days. While their origin remains uncertain, leading models invoke accretion disk instabilities or the interaction of a massive black hole (MBH) with a lower-mass secondary in an e...
| Autores: | , , , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/411707 |
| Acceso en línea: | http://hdl.handle.net/10261/411707 |
| Access Level: | acceso abierto |
| id |
ES_cdcf3a7f06f7beee0334292084be5457 |
|---|---|
| oai_identifier_str |
oai:digital.csic.es:10261/411707 |
| network_acronym_str |
ES |
| network_name_str |
España |
| repository_id_str |
|
| spelling |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysisChakraborty, JoheenDrummond, Lisa V.Bonetti, MatteoFranchini, AlessiaKejriwal, ShubhamMiniutti, GiovanniArcodia, RiccardoHughes, Scott A.Duque, FranciscoKara, ErinSesana, AlbertoGiustini, MargheritaMotta, AmedeoBurdge, KevinQuasiperiodic eruptions (QPEs) are luminous, recurring X-ray outbursts from galactic nuclei, with timescales of hours to days. While their origin remains uncertain, leading models invoke accretion disk instabilities or the interaction of a massive black hole (MBH) with a lower-mass secondary in an extreme mass ratio inspiral (EMRI). EMRI scenarios offer a robust framework for interpreting QPEs by characterizing observational signatures associated with the secondary’s orbital dynamics. This, in turn, enables extraction of the MBH/EMRI physical properties and provides a means to test the EMRI scenario, distinguishing models and addressing the question: what can QPE timings teach us about MBHs and EMRIs? In this study, we employ analytic expressions for Kerr geodesics to efficiently resolve the trajectory of the secondary object and perform GPU-accelerated Bayesian inference to assess the information content of QPE timings. Using our inference framework, referred to as QPE-FIT (Fast Inference with Timing; https://github.com/joheenc/QPE-FIT/tree/main), we explore QPE timing constraints on astrophysical parameters, such as EMRI orbital parameters and MBH mass/spin. We find that mild-eccentricity EMRIs (e ∼ 0.1–0.3) can constrain MBH mass and EMRI semimajor axis/eccentricity to the 10% level within tens of orbital periods, while MBH spin is unconstrained for the explored semimajor axes ≥100Rg and monitoring baselines O (10–100) orbits. Introducing a misaligned precessing disk generally degrades inference of EMRI orbital parameters, but can constrain disk precession properties within 10%–50%. This work both highlights the prospect of QPE observations as dynamical probes of galactic nuclei and outlines the challenge of doing so in the multimodal parameter space of EMRI–disk collisions.L.V.D. is supported by the Sherman Fairchild Postdoctoral Fellowship at the California Institute of Technology. S.A.H. is supported by NSF grants PHY-2110384 and PHY-2409644; NSF grant PHY-2110384 also supported L.V.D. at MIT during a portion of this work. G.M. thanks the Spanish MICIU/AEI/10.13039/501100011033 and ERDF/EU grants Nos. PID2020-115325GB-C31 and PID2023-147338NB-C21 for support. M.G. is funded by Spanish MICIU/AEI/10.13039/501100011033 and ERDF/EU grant PID2023-147338NB-C21.Peer reviewedIOP PublishingCalifornia Institute of TechnologyNational Science Foundation (US)Agencia Estatal de Investigación (España)Ministerio de Ciencia, Innovación y Universidades (España)European CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/411707reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-115325GB-C31info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-147338NB-C21https://doi.org/10.3847/1538-4357/ae003bSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4117072026-05-22T06:33:51Z |
| dc.title.none.fl_str_mv |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis |
| title |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis |
| spellingShingle |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis Chakraborty, Joheen |
| title_short |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis |
| title_full |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis |
| title_fullStr |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis |
| title_full_unstemmed |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis |
| title_sort |
Prospects for EMRI/MBH parameter estimation using quasiperiodic eruption timings: Short-timescale analysis |
| dc.creator.none.fl_str_mv |
Chakraborty, Joheen Drummond, Lisa V. Bonetti, Matteo Franchini, Alessia Kejriwal, Shubham Miniutti, Giovanni Arcodia, Riccardo Hughes, Scott A. Duque, Francisco Kara, Erin Sesana, Alberto Giustini, Margherita Motta, Amedeo Burdge, Kevin |
| author |
Chakraborty, Joheen |
| author_facet |
Chakraborty, Joheen Drummond, Lisa V. Bonetti, Matteo Franchini, Alessia Kejriwal, Shubham Miniutti, Giovanni Arcodia, Riccardo Hughes, Scott A. Duque, Francisco Kara, Erin Sesana, Alberto Giustini, Margherita Motta, Amedeo Burdge, Kevin |
| author_role |
author |
| author2 |
Drummond, Lisa V. Bonetti, Matteo Franchini, Alessia Kejriwal, Shubham Miniutti, Giovanni Arcodia, Riccardo Hughes, Scott A. Duque, Francisco Kara, Erin Sesana, Alberto Giustini, Margherita Motta, Amedeo Burdge, Kevin |
| author2_role |
author author author author author author author author author author author author author |
| dc.contributor.none.fl_str_mv |
California Institute of Technology National Science Foundation (US) Agencia Estatal de Investigación (España) Ministerio de Ciencia, Innovación y Universidades (España) European Commission Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72] |
| description |
Quasiperiodic eruptions (QPEs) are luminous, recurring X-ray outbursts from galactic nuclei, with timescales of hours to days. While their origin remains uncertain, leading models invoke accretion disk instabilities or the interaction of a massive black hole (MBH) with a lower-mass secondary in an extreme mass ratio inspiral (EMRI). EMRI scenarios offer a robust framework for interpreting QPEs by characterizing observational signatures associated with the secondary’s orbital dynamics. This, in turn, enables extraction of the MBH/EMRI physical properties and provides a means to test the EMRI scenario, distinguishing models and addressing the question: what can QPE timings teach us about MBHs and EMRIs? In this study, we employ analytic expressions for Kerr geodesics to efficiently resolve the trajectory of the secondary object and perform GPU-accelerated Bayesian inference to assess the information content of QPE timings. Using our inference framework, referred to as QPE-FIT (Fast Inference with Timing; https://github.com/joheenc/QPE-FIT/tree/main), we explore QPE timing constraints on astrophysical parameters, such as EMRI orbital parameters and MBH mass/spin. We find that mild-eccentricity EMRIs (e ∼ 0.1–0.3) can constrain MBH mass and EMRI semimajor axis/eccentricity to the 10% level within tens of orbital periods, while MBH spin is unconstrained for the explored semimajor axes ≥100Rg and monitoring baselines O (10–100) orbits. Introducing a misaligned precessing disk generally degrades inference of EMRI orbital parameters, but can constrain disk precession properties within 10%–50%. This work both highlights the prospect of QPE observations as dynamical probes of galactic nuclei and outlines the challenge of doing so in the multimodal parameter space of EMRI–disk collisions. |
| publishDate |
2025 |
| dc.date.none.fl_str_mv |
2025 2025 2025 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article http://purl.org/coar/resource_type/c_6501 Publisher's version info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/10261/411707 |
| url |
http://hdl.handle.net/10261/411707 |
| dc.language.none.fl_str_mv |
Inglés |
| language_invalid_str_mv |
Inglés |
| dc.relation.none.fl_str_mv |
#PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-115325GB-C31 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-147338NB-C21 https://doi.org/10.3847/1538-4357/ae003b Sí |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
IOP Publishing |
| publisher.none.fl_str_mv |
IOP Publishing |
| dc.source.none.fl_str_mv |
reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC instname:Consejo Superior de Investigaciones Científicas (CSIC) |
| instname_str |
Consejo Superior de Investigaciones Científicas (CSIC) |
| reponame_str |
DIGITAL.CSIC. Repositorio Institucional del CSIC |
| collection |
DIGITAL.CSIC. Repositorio Institucional del CSIC |
| repository.name.fl_str_mv |
|
| repository.mail.fl_str_mv |
|
| _version_ |
1869419888991272960 |
| score |
15,812429 |