CHARACTERIZING THE GALACTIC WHITE DWARF BINARY POPULATION WITH SPARSELY SAMPLED RADIAL VELOCITY DATA

We present a method to characterize statistically the parameters of a detached binary sample-binary fraction, separation distribution, and mass-ratio distribution-using noisy radial velocity data with as few as two, randomly spaced, epochs per object. To do this, we analyze the distribution of Delta...

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Bibliographic Details
Published in:	The Astrophysical journal 2012-06, Vol.751 (2), p.1-11
Main Authors:	MAOZ, Dan, BADENES, Carles, BICKERTON, Steven J
Format:	Article
Language:	eng
Subjects:	ASTRONOMY ASTROPHYSICS ASTROPHYSICS, COSMOLOGY AND ASTRONOMY COMPARATIVE EVALUATIONS Computer simulation COMPUTERIZED SIMULATION Detaching Earth, ocean, space EMISSION Exact sciences and technology GRAVITATIONAL WAVES MASS Mathematical models MILKY WAY MONTE CARLO METHOD Monte Carlo methods RADIAL VELOCITY Samples SAMPLING SENSITIVITY SUPERNOVAE WHITE DWARF STARS
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Summary:	We present a method to characterize statistically the parameters of a detached binary sample-binary fraction, separation distribution, and mass-ratio distribution-using noisy radial velocity data with as few as two, randomly spaced, epochs per object. To do this, we analyze the distribution of Delta RV sub(max), the maximum radial velocity difference between any two epochs for the same object. We use Monte Carlo techniques to produce grids of simulated Delta RV sub(max) distributions with specific binary population parameters, and the same sampling cadences and radial velocity errors as the observations, and we compare them to the real Delta RV sub(max) distribution to constrain the properties of the binary population. In the particular case of binary WDs, every model population predicts a merger rate per star which can easily be compared to specific Type Ia supernova rates. In a companion paper, we apply the method to a sample of ~4000 WDs from the Sloan Digital Sky Survey.
ISSN:	0004-637X 1538-4357