Related papers: Machine Learning applications for Cataclysmic Vari…
Wide-field time domain facilities detect transient events in large numbers through difference imaging. For example, Zwicky Transient Facility produces alerts for hundreds of thousands of transient events per night, a rate set to be dwarfed…
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…
Cataclysmic variables (CVs) are compact binary systems in which a white dwarf accretes matter from a Roche-lobe-filling companion star. In this study, we searched for new CVs in the Milky Way in the Chandra Source Catalog v2.0,…
The increasing number of synoptic surveys made by small robotic telescopes, such as the photometric Catalina Real-Time Transient Survey (CRTS), represents a unique opportunity for the discovery of variable sources and improves the…
Using a filter in the GROWTH Marshal based on color and the amplitude and the timescale of variability, we have identified 372 objects as known or candidate cataclysmic variables (CVs) during the second year of operation of the Zwicky…
The problem of classifying turbulent environments from partial observation is key for some theoretical and applied fields, from engineering to earth observation and astrophysics, e.g. to precondition searching of optimal control policies in…
Using selection criteria based on amplitude, time and color, we have identified 329 objects as known or candidate cataclysmic variable (CVs) during the first year of testing and operation of the Zwicky Transient Facility (ZTF). Of these, 90…
Cataclysmic variables (CVs) are binary systems with a white dwarf accreting matter from a low-mass star, making them significant sources of X-ray emission in the Galaxy. We present a systematic search for X-ray emitting CV candidates by…
Over six years of operation, the Catalina Real-time Transient Survey (CRTS) has identified 1043 cataclysmic variable (CV) candidates --- the largest sample of CVs from a single survey to date. Here we provide spectroscopic identification of…
We reconstruct the evolutionary path followed by cataclysmic variables (CVs) from the observed mass-radius relationship of their donor stars. Along the way, we update the semi-empirical CV donor sequence of Knigge (2006) and present a…
Strong selection effects are present in observational samples of cataclysmic variables (CVs), complicating comparisons to theoretical predictions. The selection criteria used to define most CV samples discriminate heavily against the…
Recent years have witnessed a growing interest in using machine learning to predict and identify phase transitions in various systems. Here we adopt convolutional neural networks (CNNs) to study the phase transitions of Vicsek model,…
Virtual high throughput screening (VHTS) and machine learning (ML) have greatly accelerated the design of single-site transition-metal catalysts. VHTS of catalysts, however, is often accompanied with high calculation failure rate and wasted…
As a technique that can compactly represent complex patterns, machine learning has significant potential for predictive inference. K-fold cross-validation (CV) is the most common approach to ascertaining the likelihood that a machine…
Computer Vision (CV) classifiers which distinguish and detect nonverbal social human behavior and mental state can aid digital diagnostics and therapeutics for psychiatry and the behavioral sciences. While CV classifiers for traditional and…
In complex molecular systems, the reaction coordinate (RC) that characterizes transition pathways is essential to understand underlying molecular mechanisms. This review surveys a framework for identifying the RC by applying deep learning…
Modern astronomical surveys, such as the Zwicky Transient Facility (ZTF), are capable of detecting thousands of transient events per year, necessitating the use of automated and scalable data analysis techniques. Recent advances in machine…
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…
This is the second paper of a series presenting our search for magnetic Cataclysmic Variables (mCVs) among candidates selected mostly from the Catalina Real-Time Transient Survey (CRTS). We present the identification spectra, obtained at…
Aims: We present discovery observations of the new cataclysmic variable star (CV) 1RXS J092737.4-191529, as well as spectra and photometry of SY Vol. The selection technique that turned up these two CVs is described; it should be efficient…