17 citations · 31 across the 6 of their papers we have counts for
6 papers
Development of next-generation event-driven x-ray hybrid CMOS detectors
Timothy R. Emeigh, Abraham D. Falcone, Joseph M. Colosimo +14
The Penn State University High Energy Astrophysics Detector and Instrumentation Lab, in collaboration with Teledyne Imaging Sensors, has developed a next-generation event-driven X-…
Characterization of Random Telegraph Noise in an H2RG X-ray Hybrid CMOS Detector
William A. Bevidas, Joseph M. Colosimo, Abraham D. Falcone +13
Hybrid CMOS detectors (HCDs) have several excellent features as high-performance X-ray detectors, including rapid readout, deep-depletion silicon for high quantum efficiency, radia…
Million Points of Light (MPoL): a PyTorch library for radio interferometric imaging and inference
Ian Czekala, Jeff Jennings, Brianna Zawadzki +9
Astronomical radio interferometers achieve exquisite angular resolution by cross-correlating signal from a cosmic source simultaneously observed by distant pairs of radio telescope…
Expected Gamma-Ray Burst Detection Rates and Redshift Distributions for the BlackCAT CubeSat Mission
Joseph M. Colosimo, Derek B. Fox, Abraham D. Falcone +17
We report the results of an extensive set of simulations exploring the sensitivity of the BlackCAT CubeSat to long-duration gamma-ray bursts (GRBs). BlackCAT is a NASA APRA-funded…
Updated Catalog of Kepler Planet Candidates: Focus on Accuracy and Orbital Periods
Jack J. Lissauer, Jason F. Rowe, Daniel Jontof-Hutter +5
We present a new catalog of Kepler planet candidates that prioritizes accuracy of planetary dispositions and properties over uniformity. This catalog contains 4376 transiting plane…
Regularized Maximum Likelihood Image Synthesis and Validation for ALMA Continuum Observations of Protoplanetary Disks
Brianna Zawadzki, Ian Czekala, Ryan A. Loomis +6
Regularized Maximum Likelihood (RML) techniques are a class of image synthesis methods that achieve better angular resolution and image fidelity than traditional methods like CLEAN…