The Music of Black Holes

[beecee]

https://phys.org/news/2018-04-background-space-reveal-hidden-black.html

The background hum of space could reveal hidden black holes:

April 12, 2018, Monash University:

Deep space is not as silent as we have been led to believe. Every few minutes a pair of black holes smash into each other. These cataclysms release ripples in the fabric of spacetime known as gravitational waves. Now Monash University scientists have developed a way to listen in on these events. The gravitational waves from black hole mergers imprint a distinctive whooping sound in the data collected by gravitational-wave detectors. The new technique is expected to reveal the presence of thousands of previously hidden black holes by teasing out their faint whoops from a sea of static.

Last year, in one of the biggest astronomical discoveries of the 21st century, LIGO Scientific Collaboration (LSC) and Virgo Collaboration researchers measured gravitational waves from a pair of merging neutron stars.

Drs Eric Thrane and Rory Smith, from the ARC Centre of Excellence for Gravitational Wave Discovery (OzGrav) and Monash University, were part of the team involved in last year's discovery and were also part of the team involved in the detection of first gravitational-wave discovery in 2015, when ripples in the fabric of space time generated by the collision of two black holes in the distant Universe were first witnessed, confirming Albert Einstein's 1915 general theory of

Read more at: https://phys.org/news/2018-04-background-space-reveal-hidden-black.html#jCp
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The paper:

https://journals.aps.org/prx/accepted/b1077K8cZ6e1a00db22a57164e1aab4bf827ea464

Optimal search for an astrophysical gravitational-wave background:

 

Abstract:

Roughly every \unit[2-10]{minutes}, a pair of stellar mass black holes merge somewhere in the Universe. A small fraction of these mergers are detected as individually resolvable gravitational-wave events by advanced detectors such as LIGO and Virgo. The rest contribute to a stochastic background. We derive the statistically optimal search strategy (producing minimum credible intervals) for a background of unresolved binaries. Our method applies Bayesian parameter estimation to all available data. Using Monte Carlo simulations, we demonstrate that the search is both ``safe'' and effective: it is not fooled by instrumental artifacts such as glitches and it recovers simulated stochastic signals without bias. Given realistic assumptions, we estimate that the search can detect the binary black hole background with about one day of design sensitivity data versus $\approx\unit[40]{months}$ using the traditional cross-correlation search. This framework independently constrains the merger rate and black hole mass distribution, breaking a degeneracy present in the cross-correlation approach. The search provides a unified framework for population studies of compact binaries, which is cast in terms of hyper-parameter estimation. We discuss a number of extensions and generalizations including: application to other sources (such as binary neutron stars and continuous-wave sources), simultaneous estimation of a continuous Gaussian background, and applications to pulsar timing.

and..........

https://arxiv.org/abs/1712.00688

The optimal search for an astrophysical gravitational-wave background:

Roughly every 2-10 minutes, a pair of stellar mass black holes merge somewhere in the Universe. A small fraction of these mergers are detected as individually resolvable gravitational-wave events by advanced detectors such as LIGO and Virgo. The rest contribute to a stochastic background. We derive the statistically optimal search strategy for a background of unresolved binaries. Our method applies Bayesian parameter estimation to all available data. Using Monte Carlo simulations, we demonstrate that the search is both "safe" and effective: it is not fooled by instrumental artefacts such as glitches, and it recovers simulated stochastic signals without bias. Given realistic assumptions, we estimate that the search can detect the binary black hole background with about one day of design sensitivity data versus ≈40 months using the traditional cross-correlation search. This framework independently constrains the merger rate and black hole mass distribution, breaking a degeneracy present in the cross-correlation approach. The search provides a unified framework for population studies of compact binaries, which is cast in terms of hyper-parameter estimation. We discuss a number of extensions and generalizations including: application to other sources (such as binary neutron stars and continuous-wave sources), simultaneous estimation of a continuous Gaussian background, and applications to pulsar timing.

Edited April 12, 2018 by beecee