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Science with the space-based interferometer LISA. V. Extreme mass-ratio inspirals

Babak, Stanislav
•
Gair, Jonathan
•
Sesana, Alberto
altro
Klein, Antoine
2017
  • journal article

Periodico
PHYSICAL REVIEW D
Abstract
The space-based Laser Interferometer Space Antenna (LISA) will be able to observe the gravitational-wave signals from systems comprised of a massive black hole and a stellar-mass compact object. These systems are known as extreme-mass-ratio inspirals (EMRIs) and are expected to complete ∼104-105 cycles in band, thus allowing exquisite measurements of their parameters. In this work, we attempt to quantify the astrophysical uncertainties affecting the predictions for the number of EMRIs detectable by LISA, and find that competing astrophysical assumptions produce a variance of about three orders of magnitude in the expected intrinsic EMRI rate. However, we find that irrespective of the astrophysical model, at least a few EMRIs per year should be detectable by the LISA mission, with up to a few thousands per year under the most optimistic astrophysical assumptions. We also investigate the precision with which LISA will be able to extract the parameters of these sources. We find that typical fractional statistical errors with which the intrinsic parameters (redshifted masses, massive black hole spin and orbital eccentricity) can be recovered are ∼10-6-10-4. Luminosity distance (which is required to infer true masses) is inferred to about 10% precision and sky position is localized to a few square degrees, while tests of the multipolar structure of the Kerr metric can be performed to percent-level precision or better.
DOI
10.1103/PhysRevD.95.103012
WOS
WOS:000402474100002
Archivio
http://hdl.handle.net/20.500.11767/89662
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85020231368
http://harvest.aps.org/bagit/articles/10.1103/PhysRevD.95.103012
https://arxiv.org/abs/1703.09722
Diritti
open access
Soggetti
  • Physics and Astronomy...

  • Settore FIS/05 - Astr...

Scopus© citazioni
210
Data di acquisizione
Jun 14, 2022
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Web of Science© citazioni
332
Data di acquisizione
Mar 26, 2024
Visualizzazioni
3
Data di acquisizione
Apr 19, 2024
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