315 citations · 619 across the 6 of their papers we have counts for
7 papers
A data science platform to enable time-domain astronomy
Michael W. Coughlin, Joshua S. Bloom, Guy Nir +50
SkyPortal is an open-source software package designed to efficiently discover interesting transients, manage follow-up, perform characterization, and visualize the results. By enab…
SN 2019zrk, a bright SN 2009ip analog with a precursor
Claes Fransson, Jesper Sollerman, Nora L. Strotjohann +12
We present photometric and spectroscopic observations of the Type IIn supernova SN 2019zrk (also known as ZTF20aacbyec). The SN shows a 100 day precursor, with a slow ris…
HEALPix Alchemy: Fast All-Sky Geometry and Image Arithmetic in a Relational Database for Multimessenger Astronomy Brokers
Leo P. Singer, B. Parazin, Michael W. Coughlin +4
Efficient searches for electromagnetic counterparts to gravitational wave, high-energy neutrino, and gamma-ray burst events demand rapid processing of image arithmetic and geometry…
Fast-transient Searches in Real Time with ZTFReST: Identification of Three Optically-discovered Gamma-ray Burst Afterglows and New Constraints on the Kilonova Rate
Igor Andreoni, Michael W. Coughlin, Erik C. Kool +32
While optical surveys regularly discover slow transients like supernovae on their own, the most common way to discover extragalactic fast transients, fading away in a few nights, i…
cesium: Open-Source Platform for Time-Series Inference
Brett Naul, Stéfan van der Walt, Arien Crellin-Quick +2
Inference on time series data is a common requirement in many scientific disciplines and internet of things (IoT) applications, yet there are few resources available to domain scie…
Construction of a Calibrated Probabilistic Classification Catalog: Application to 50k Variable Sources in the All-Sky Automated Survey
Joseph W. Richards, Dan L. Starr, Adam A. Miller +4
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,…
On Machine-Learned Classification of Variable Stars with Sparse and Noisy Time-Series Data
Joseph W. Richards, Dan L. Starr, Nathaniel R. Butler +6
With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for new…