Astrophysics - Instrumentation and Methods for Astrophysics

Automating Inference of Binary Microlensing Events with Neural Density Estimation

On Neural Architectures for Astronomical Time-series Classification with Application to Variable Stars

deepSIP: linking Type Ia supernova spectra to photometric quantities with deep learning

Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters

deepCR: Cosmic Ray Rejection with Deep Learning

Cosmic ray (CR) identification and replacement are critical components of imaging and spectroscopic reduction pipelines involving solid-state detectors. We present deepCR, a deep-learning-based framework for CR identification and subsequent image …

deepCR: Cosmic Ray Rejection with Deep Learning

Cosmic ray (CR) identification and replacement are critical components of imaging and spectroscopic reduction pipelines involving solid-state detectors. We present deepCR, a deep learning based framework for CR identification and subsequent image …

GROWTH on S190426c: Real-time Search for a Counterpart to the Probable Neutron Star-Black Hole Merger using an Automated Difference Imaging Pipeline for DECam

The discovery of a transient kilonova following the gravitational-wave (GW) event GW170817 highlighted the critical need for coordinated rapid and wide-field observations, inference, and follow-up across the electromagnetic spectrum. In the southern …

GROWTH on S190510g: DECam Observation Planning and Follow-up of a Distant Binary Neutron Star Merger Candidate

The first two months of the third Advanced LIGO and Virgo observing run (2019 April-May) showed that distant gravitational-wave (GW) events can now be readily detected. Three candidate mergers containing neutron stars (NS) were reported in a span of …

A recurrent neural network for classification of unevenly sampled variable stars

Astronomical surveys of celestial sources produce streams of noisy time series measuring flux versus time (`light curves'). Unlike in many other physical domains, however, large (and source- specific) temporal gaps in data arise naturally due to …

Multi-Messenger Astrophysics: Harnessing the Data Revolution

The past year has witnessed discovery of the first identified counterparts to a gravitational wave transient (GW 170817A) and a very high-energy neutrino (IceCube-170922A). These source identifications, and ensuing detailed studies, have realized …