Astrophysics - Instrumentation and Methods for Astrophysics

A Bayesian approach to calibrating period-luminosity relations of RR Lyrae stars in the mid-infrared

A Bayesian approach to calibrating period-luminosity (PL) relations has substantial benefits over generic least-squares fits. In particular, the Bayesian approach takes into account the full prior distribution of the model parameters, such as the a …

Discovery of Bright Galactic R Coronae Borealis and DY Persei Variables: Rare Gems Mined from ACVS

We present the results of a machine-learning (ML)-based search for new R Coronae Borealis (RCB) stars and DY Persei-like stars (DYPers) in the Galaxy using cataloged light curves from the All-Sky Automated Survey (ASAS) Catalog of Variable Stars …

The Palomar Transient Factory photometric catalog 1.0

We constructed a photometrically calibrated catalog of non-variable sources from the Palomar Transient Factory (PTF) observations. The first version of this catalog presented here, the PTF photometric catalog 1.0, contains calibrated R$_PTF$-filter …

Optimizing Automated Classification of Variable Stars in New Synoptic Surveys

Efficient and automated classification of periodic variable stars is becoming increasingly important as the scale of astronomical surveys grows. Several recent articles have used methods from machine learning and statistics to construct classifiers …

Rapid, Machine-learned Resource Allocation: Application to High-redshift Gamma-Ray Burst Follow-up

As the number of observed gamma-ray bursts (GRBs) continues to grow, follow-up resources need to be used more efficiently in order to maximize science output from limited telescope time. As such, it is becoming increasingly important to rapidly …

Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often …

Data Mining and Machine Learning in Time-Domain Discovery and Classification

The changing heavens have played a central role in the scientific effort of astronomers for centuries. Galileo's synoptic observations of the moons of Jupiter and the phases of Venus starting in 1610, provided strong refutation of Ptolemaic …

The Palomar Transient Factory Photometric Calibration

The Palomar Transient Factory (PTF) provides multiple epoch imaging for a large fraction of the celestial sphere. Here, we describe the photometric calibration of the PTF data products that allows the PTF magnitudes to be related to other magnitude …

Sky Event Reporting Metadata Version 2.0

On Machine-learned Classification of Variable Stars with Sparse and Noisy Time-series Data

With the coming data deluge from synoptic surveys, there is a need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly observed variables based on small numbers of time-series measurements. In …