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Kobulnicky, Henry A; Fryer, Chris L
Astrophysical journal/The Astrophysical journal, 11/2007, Volume: 670, Issue: 1Journal Article
We constrain the properties of massive binaries by comparing radial velocity data on early-type stars in Cygnus OB2 with the expectations of Monte Carlo models. Our comparisons test several popular prescriptions for massive binary parameters. We explore a range of true binary fraction, F, a range of power-law slopes, a, describing the distribution of companion masses between the limits q sub(low) and 1, and a range of power-law slopes, beta , describing the distribution of orbital separations between the limits r sub(in) and r sub(out). We also consider distributions of secondary masses described by a Miller-Scalo type IMF and by a two-component IMF that Includes a substantial "twin" population with M sub(2) unk M sub(1). Several seemingly disparate prescriptions for massive binary characteristics can be reconciled by adopting carefully chosen values for F, r sub(in), and r sub(out). We show that binary fractions F < 0.7 are less probable than F greater than or equal to 0.8 for reasonable choices of r sub(in) and r sub(out). Thus, the true binary fraction is high. For F = 1.0 and a distribution of orbital separations near the canonical "Opik's law distribution (i.e., flat; beta = 0), the power-law slope of the mass ratio distribution is alpha = -0.6 to 0.0. For F unk 0.8, alpha is somewhat larger, in the range -0.4 to 1.0. In any case, the secondary star mass function is inconsistent with a Miller-Scalo-like IMF unless the lower end is truncated below similar to 2-4 M unk. In other words, massive stars preferentially have massive companions. The best-fitting models are described by a Salpeter or Miller-Scalo IMF for 60% of secondary star masses with the other similar to 40% of secondaries having M sub(2) unk M sub(1), i.e., "twins." These model parameters simultaneously predict the fraction of Type Ib/c supernovae to be 30%-40% of all core-collapse supernovae, in agreement with recent observational estimates.
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