Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data

Kavli Affiliate: Erotokritos Katsavounidis | First 5 Authors: Rahul Biswas, Lindy Blackburn, Junwei Cao, Reed Essick, Kari Alison Hodge | Summary: The sensitivity of searches for astrophysical transients in data from the LIGO is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across […]


Continue.. Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data

Planck 2013 results X. Energetic particle effects: characterization, removal, and simulation

Kavli Affiliate: E. P. S. Shellard | First 5 Authors: Planck Collaboration, P. A. R. Ade, N. Aghanim, C. Armitage-Caplan, M. Arnaud | Summary: We describe the detection, interpretation, and removal of the signal resulting from interactions of high energy particles with the Planck High Frequency Instrument (HFI). There are two types of interactions: heating […]


Continue.. Planck 2013 results X. Energetic particle effects: characterization, removal, and simulation