2007
DOI: 10.1111/j.1365-2966.2006.11258.x
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The influence of selection effects on the observed cataclysmic variable population: modelling and application to the Palomar-Green sample

Abstract: Large differences between the properties of the known sample of cataclysmic variable stars (CVs) and the predictions of the theory of binary star evolution have long been recognized. However, because all existing CV samples suffer from strong selection effects, observational biases must be taken into account before it is possible to tell whether there is an inconsistency. In order to address this problem, we have modelled the impact of selection effects on observed CV samples using a Monte Carlo approach. By s… Show more

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Cited by 50 publications
(88 citation statements)
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“…Similar results are obtained if observational biases are taken into account. In fact, Pretorius et al (2007) have shown that observational biases impose a large discrepancy between the predicted and observed period distribution of CVs. Their predicted period distribution looks very similar to the period distribution of our models (see their Fig.…”
Section: Orbital Period Distributionmentioning
confidence: 99%
“…Similar results are obtained if observational biases are taken into account. In fact, Pretorius et al (2007) have shown that observational biases impose a large discrepancy between the predicted and observed period distribution of CVs. Their predicted period distribution looks very similar to the period distribution of our models (see their Fig.…”
Section: Orbital Period Distributionmentioning
confidence: 99%
“…A very similar approach has been used by Pretorius et al (2007) to assess the influence of selection effects on the observed population of cataclysmic variables (CVs) in the optical domain. These authors also modeled the flux distribution of the observed CV population by assuming certain intrinsic luminosity distribution, spatial distribution of the CVs, their spectral properties, and outburst activity.…”
Section: Xlf Reconstructionmentioning
confidence: 99%
“…The sample of known field CVs suffers from various selection effects (e.g., Pretorius et al 2007;Servillat et al 2011) and is likely biased toward bright and highly variable systems. Population synthesis models indicate that a fainter population showing fewer outbursts may dominate the population of DNe (up to 70%;Kolb 1993;Howell et al 1997).…”
Section: Introductionmentioning
confidence: 99%