Related papers: The Missing CV Population: Results From An Objecti…
Results in epidemiology and social science often require the removal of confounding effects from measurements of the pairwise correlation of variables in survey data. This is typically accomplished by some variant of linear regression…
I review what we know about the donor stars in cataclysmic variables (CVs), focusing particularly on the close link between these binary components and the overall secular evolution of CVs. I begin with a brief overview of the "standard…
(Abridged) We present high-speed, three-colour photometry of seven short period (Porb <= 95 mins) eclipsing CVs from the Sloan Digital Sky Survey. We determine the system parameters via a parametrized model of the eclipse fitted to the…
We present a binary evolution study of cataclysmic variables (CVs) and related systems with white dwarf accretors, including for example, AM CVn systems, classical novae, supersoft X-ray sources, and systems with giant donor stars. Our…
We have searched for optical identifications for 79 Chandra X-ray sources that lie within the half-mass radius of the nearby, core-collapsed globular cluster NGC 6397, using deep Hubble Space Telescope Advanced Camera for Surveys Wide Field…
We present our wide field Halpha+N[II] observations of 15 cataclysmic variables to search for remnant nova shells. Such shells have been found around other cataclysmic variables that were hitherto not known as novae. Our candidates were…
In cataclysmic variables (CVs), accretion onto white dwarfs produces high temperature, high density plasmas. They cool down from kT~10 keV via bremsstrahlung continuum and K and L shell line emissions. The small volume around white dwarfs…
Using high-precision astrometric data from Gaia DR3 and updated systemic velocities from the literature, kinematical properties of cataclysmic variables (CVs) were investigated. By constraining the data according to the total space velocity…
Cataclysmic Variables (CV) are close binary systems, in which the primary, the more massive star, is a white dwarf. CVs usually exhibit a number of periodicities, most of which are now understood. However, recently, a new phenomenon was…
Although a large number of orbital periods of cataclysmic variable stars (CVs) have been measured, comparison of period and luminosity distributions with evolutionary theory is affected by strong selection effects. A test has been…
Cross-validation (CV) is a technique for evaluating the ability of statistical models/learning systems based on a given data set. Despite its wide applicability, the rather heavy computational cost can prevent its use as the system size…
Cross-validation (CV) is a popular approach for assessing and selecting predictive models. However, when the number of folds is large, CV suffers from a need to repeatedly refit a learning procedure on a large number of training datasets.…
Recently, there has been substantial interest in statistical guarantees for cross-validation (CV) methods of uncertainty quantification in statistical learning (cf. Barber et al. 2021a, Liang and Barber 2024, Steinberger and Leeb 2023).…
Enhanced sampling methods typically require predefined collective variables (CVs) that presuppose knowledge of reaction coordinates, restricting the discovery of unanticipated transition mechanisms or intermediates. Here, we show that a…
Using improved, up-to-date stellar input physics tested against observations of low-mass stars and brown dwarfs we calculate the secular evolution of low-mass donor cataclysmic variables (CVs), including those which form with a brown dwarf…
An overview is given of the properties of the various kinds of quasi-periodic luminosity modulations observed in cataclysmic variables (CVs). The two principal types, known in the CV literature as dwarf nova oscillations and quasi-periodic…
High-dimensional metastable molecular system can often be characterised by a few features of the system, i.e. collective variables (CVs). Thanks to the rapid advance in the area of machine learning and deep learning, various deep…
We present a methodology for model evaluation and selection where the sampling mechanism violates the i.i.d. assumption. Our methodology involves a formulation of the bias between the standard Cross-Validation (CV) estimator and the mean…
With growing data volumes from synoptic surveys, astronomers must become more abstracted from the discovery and introspection processes. Given the scarcity of follow-up resources, there is a particularly sharp onus on the frameworks that…
In supervised learning, the estimation of prediction error on unlabeled test data is an important task. Existing methods are usually built on the assumption that the training and test data are sampled from the same distribution, which is…