Improving VERITAS Sensitivity by Fitting 2D Gaussian Image Parameters
Jodi Christiansen (for the VERITAS Collaboration)
TL;DR
This paper introduces a 2D Gaussian fitting method for VERITAS camera images, significantly enhancing sensitivity and reducing observation time needed for weak sources.
Contribution
It presents a novel image-fitting algorithm using chi-squared minimization to improve VERITAS sensitivity and angular resolution.
Findings
20% reduction in observing time for 5-sigma detection of weak sources
Enhanced acceptance and angular resolution of VERITAS
Optimized analysis cuts based on the new fitting method
Abstract
Our goal is to improve the acceptance and angular resolution of VERITAS by implementing a camera image-fitting algorithm. Elliptical image parameters are extracted from 2D Gaussian distribution fits using a (chi)^2 minimization instead of the standard technique based on the principle moments of an island of pixels above threshold. We optimize the analysis cuts and then characterize the improvements using simulations. We find an improvement of 20% less observing time to reach 5-sigma for weak point sources.
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