Journal
ASTROPHYSICAL JOURNAL
Volume 719, Issue 1, Pages 851-864Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0004-637X/719/1/851
Keywords
black hole physics; galaxies: evolution; galaxies: kinematics and dynamics; gravitational waves methods: numerical
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We construct evolutionary tracks for massive black hole binaries (MBHBs) embedded in a surrounding distribution of stars. The dynamics of the binary is evolved by taking into account the erosion of the central stellar cusp bound to the massive black holes, the scattering of unbound stars feeding the binary loss cone, and the emission of gravitational waves (GWs). Stellar dynamics is treated in a hybrid fashion by coupling the results of numerical three-body scattering experiments of bound and unbound stars to an analytical framework for the evolution of the stellar density distribution and for the efficiency of the binary loss-cone refilling. Our main focus is on the behavior of the binary eccentricity, in the attempt of addressing its importance in the merger process and its possible impact for GW detection with the planned Laser Interferometer Space Antenna (LISA), and ongoing and forthcoming pulsar timing array (PTA) campaigns. We produce a family of evolutionary tracks extensively sampling the relevant parameters of the system which are the binary mass, mass ratio and initial eccentricity, the slope of the stellar density distribution, its normalization and the efficiency of loss-cone refilling. We find that, in general, stellar dynamics causes a dramatic increase of the MBHB eccentricity, especially for initially already mildly eccentric and/or unequal mass binaries. This affects the overall system dynamics; high eccentricities enhance the efficiency of GW emission, accelerating the final coalescence process. When applied to standard MBHB population models, our results predict eccentricities in the ranges 10-3-0.2 and 0.03-0.3 for sources detectable by LISA and PTA, respectively. Such figures may have a significant impact on the signal modeling, on source detection, and on the development of parameter estimation algorithms.
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