Related papers: Machine Learning based search for Cataclysmic Vari…
We present the Deep-learning Transient Astronomical Object (Deep-TAO), a dataset of 1,249,079 annotated images from the Catalina Real-time Transient Survey, including 3,807 transient and 12,500 non-transient sequences. Deep-TAO has been…
Third-generation gravitational wave (GW) observatories such as the Einstein Telescope and Cosmic Explorer, together with the LSST survey at the Vera Rubin Observatory, will yield an abundance of extra-galactic transient objects. This opens…
Current evolutionary models imply that most Cataclysmic Variables (CVs) have P_orb<2 hours and are Dwarf Nova (DN) systems that are quiescent most of the time. Observations of nearby quiescent DN find that the UV spectrum is dominated by…
Gravitational lensing of gravitational waves (GWs) provides a unique opportunity to study cosmology and astrophysics at multiple scales. Detecting microlensing signatures, in particular, requires efficient parameter estimation methods due…
The evolution of Cataclysmic Variables (CVs) is driven by period-changes ($\dot{P}$), for which the long-venerable consensus is the Magnetic Braking Model (MBM). The MBM has its only distinctive assumption being a power-law `recipe'…
We have performed a study of the orbital properties of seven eclipsing cataclysmic variable (CV) binary systems by analyzing photometric time series from the Transiting Exoplanet Survey Satellite (TESS). We employed Python code to determine…
We report detailed follow-up observations of 8 cataclysmic variable stars (CVs) that are apparently AM Her stars, also called polars. For all, we either determine orbital periods for the first time, or improve on existing determinations.…
Machine learning can be a powerful tool to discover new signal types in astronomical data. We here apply it to search for long-duration transient gravitational waves triggered by pulsar glitches, which could yield physical insight into the…
As engineered systems grow in complexity, there is an increasing need for automatic methods that can detect, diagnose, and even correct transient anomalies that inevitably arise and can be difficult or impossible to diagnose and fix…
We introduce MANTRA, an annotated dataset of 4869 transient and 71207 non-transient object lightcurves built from the Catalina Real Time Transient Survey. We provide public access to this dataset as a plain text file to facilitate…
The ability to discover new transients via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine Learning techniques such as…
Here we present a catalog of 12,993 photometrically-classified supernova-like light curves from the Zwicky Transient Facility, along with candidate host galaxy associations. By training a random forest classifier on spectroscopically…
Errors in measurements are key to weighting the value of data, but are often neglected in Machine Learning (ML). We show how Convolutional Neural Networks (CNNs) are able to learn about the context and patterns of signal and noise, leading…
We present a systematic search for periodic X-ray sources in 10 Galactic globular clusters (GCs) utilizing deep archival Chandra observations. By applying the Gregory-Loredo algorithm, we detect 28 periodic signals among 27 independent…
Temporal sampling does more than add another axis to the vector of observables. Instead, under the recognition that how objects change (and move) in time speaks directly to the physics underlying astronomical phenomena, next-generation…
Magnetic cataclysmic variables (CVs) contain a white dwarf with magnetic field strong enough to control the accretion flow from a late type secondary. In this paper, we discover a magnetic CV (CXOGSG J215544.4+380116) from the $Chandra$…
The Cherenkov Telescope Array (CTA) is the next generation high-energy gamma-ray observatory. It will improve the sensitivity of current instruments up to an order of magnitude, while providing energy coverage for photons from 20 GeV to at…
We present the results of a search for cataclysmic variables (CVs) in the Calan-Tololo survey. We detected a total number of 21 CVs, 12 of them are previously unknown objects. Our results suggest that the mismatch between the theoretically…
Photometric variability detection is often considered as a hypothesis testing problem: an object is variable if the null-hypothesis that its brightness is constant can be ruled out given the measurements and their uncertainties. Uncorrected…
In developing machine learning (ML) models for text classification, one common challenge is that the collected data is often not ideally distributed, especially when new classes are introduced in response to changes of data and tasks. In…