TY - JOUR

T1 - The mass distribution of stellar-mass black holes

AU - Farr, Will M.

AU - Sravan, Niharika

AU - Cantrell, Andrew

AU - Kreidberg, Laura

AU - Bailyn, Charles D.

AU - Mandel, Ilya

AU - Kalogera, Vicky

PY - 2011/11/10

Y1 - 2011/11/10

N2 - We perform a Bayesian analysis of the mass distribution of stellar-mass black holes using the observed masses of 15 low-mass X-ray binary systems undergoing Roche lobe overflow and 5 high-mass, wind-fed X-ray binary systems. Using Markov Chain Monte Carlo calculations, we model the mass distribution both parametrically - as a power law, exponential, Gaussian, combination of two Gaussians, or log-normal distribution - and non-parametrically - as histograms with varying numbers of bins. We provide confidence bounds on the shape of the mass distribution in the context of each model and compare the models with each other by calculating their relative Bayesian evidence as supported by the measurements, taking into account the number of degrees of freedom of each model. The mass distribution of the low-mass systems is best fit by a power law, while the distribution of the combined sample is best fit by the exponential model. This difference indicates that the low-mass subsample is not consistent with being drawn from the distribution of the combined population. We examine the existence of a "gap" between the most massive neutron stars and the least massive black holes by considering the value, M 1%, of the 1% quantile from each black hole mass distribution as the lower bound of black hole masses. Our analysis generates posterior distributions for M 1%; the best model (the power law) fitted to the low-mass systems has a distribution of lower bounds with M 1%>4.3 M ⊙ with 90% confidence, while the best model (the exponential) fitted to all 20systems has M 1%>4.5 M ⊙ with 90% confidence. We conclude that our sample of black hole masses provides strong evidence of a gap between the maximum neutron star mass and the lower bound on black hole masses. Our results on the low-mass sample are in qualitative agreement with those of Ozel et al., although our broad model selection analysis more reliably reveals the best-fit quantitative description of the underlying mass distribution. The results on the combined sample of low- and high-mass systems are in qualitative agreement with Fryer & Kalogera, although the presence of a mass gap remains theoretically unexplained.

AB - We perform a Bayesian analysis of the mass distribution of stellar-mass black holes using the observed masses of 15 low-mass X-ray binary systems undergoing Roche lobe overflow and 5 high-mass, wind-fed X-ray binary systems. Using Markov Chain Monte Carlo calculations, we model the mass distribution both parametrically - as a power law, exponential, Gaussian, combination of two Gaussians, or log-normal distribution - and non-parametrically - as histograms with varying numbers of bins. We provide confidence bounds on the shape of the mass distribution in the context of each model and compare the models with each other by calculating their relative Bayesian evidence as supported by the measurements, taking into account the number of degrees of freedom of each model. The mass distribution of the low-mass systems is best fit by a power law, while the distribution of the combined sample is best fit by the exponential model. This difference indicates that the low-mass subsample is not consistent with being drawn from the distribution of the combined population. We examine the existence of a "gap" between the most massive neutron stars and the least massive black holes by considering the value, M 1%, of the 1% quantile from each black hole mass distribution as the lower bound of black hole masses. Our analysis generates posterior distributions for M 1%; the best model (the power law) fitted to the low-mass systems has a distribution of lower bounds with M 1%>4.3 M ⊙ with 90% confidence, while the best model (the exponential) fitted to all 20systems has M 1%>4.5 M ⊙ with 90% confidence. We conclude that our sample of black hole masses provides strong evidence of a gap between the maximum neutron star mass and the lower bound on black hole masses. Our results on the low-mass sample are in qualitative agreement with those of Ozel et al., although our broad model selection analysis more reliably reveals the best-fit quantitative description of the underlying mass distribution. The results on the combined sample of low- and high-mass systems are in qualitative agreement with Fryer & Kalogera, although the presence of a mass gap remains theoretically unexplained.

KW - X-rays: binaries

KW - methods: data analysis

UR - http://www.scopus.com/inward/record.url?scp=80155187137&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80155187137&partnerID=8YFLogxK

U2 - 10.1088/0004-637X/741/2/103

DO - 10.1088/0004-637X/741/2/103

M3 - Article

AN - SCOPUS:80155187137

SN - 0004-637X

VL - 741

JO - Astrophysical Journal

JF - Astrophysical Journal

IS - 2

M1 - 103

ER -