Literature DB >> 33015351

Prospects for observing and localizing gravitational-wave transients with Advanced LIGO, Advanced Virgo and KAGRA.

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Abstract

We present our current best estimate of the plausible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next several years, with the intention of providing information to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals for the third (O3), fourth (O4) and fifth observing (O5) runs, including the planned upgrades of the Advanced LIGO and Advanced Virgo detectors. We study the capability of the network to determine the sky location of the source for gravitational-wave signals from the inspiral of binary systems of compact objects, that is binary neutron star, neutron star-black hole, and binary black hole systems. The ability to localize the sources is given as a sky-area probability, luminosity distance, and comoving volume. The median sky localization area (90% credible region) is expected to be a few hundreds of square degrees for all types of binary systems during O3 with the Advanced LIGO and Virgo (HLV) network. The median sky localization area will improve to a few tens of square degrees during O4 with the Advanced LIGO, Virgo, and KAGRA (HLVK) network. During O3, the median localization volume (90% credible region) is expected to be on the order of 10 5 , 10 6 , 10 7 Mpc 3 for binary neutron star, neutron star-black hole, and binary black hole systems, respectively. The localization volume in O4 is expected to be about a factor two smaller than in O3. We predict a detection count of 1 - 1 + 12 ( 10 - 10 + 52 ) for binary neutron star mergers, of 0 - 0 + 19 ( 1 - 1 + 91 ) for neutron star-black hole mergers, and 17 - 11 + 22 ( 79 - 44 + 89 ) for binary black hole mergers in a one-calendar-year observing run of the HLV network during O3 (HLVK network during O4). We evaluate sensitivity and localization expectations for unmodeled signal searches, including the search for intermediate mass black hole binary mergers.
© The Author(s) 2020.

Entities:  

Keywords:  Data analysis; Electromagnetic counterparts; Gravitational waves; Gravitational-wave detectors

Year:  2020        PMID： 33015351      PMCID： PMC7520625          DOI： 10.1007/s41114-020-00026-9

Source DB:  PubMed          Journal:  Living Rev Relativ        ISSN： 1433-8351            Impact factor:   40.429


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5.  Deep Learning for Gravitational-Wave Data Analysis: A Resampling White-Box Approach.

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