Title: Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter,
Abstract: We present a new matched filter algorithm for direct detection of point
sources in the immediate vicinity of bright stars. The stellar Point Spread
Function (PSF) is first subtracted using a Karhunen-Loéve Image Processing
(KLIP) algorithm with Angular and Spectral Differential Imaging (ADI and SDI).
The KLIP-induced distortion of the astrophysical signal is included in the
matched filter template by computing a forward model of the PSF at every
position in the image. To optimize the performance of the algorithm, we conduct
extensive planet injection and recovery tests and tune the exoplanet spectra
template and KLIP reduction aggressiveness to maximize the Signal-to-Noise
Ratio (SNR) of the recovered planets. We show that only two spectral templates
are necessary to recover any young Jovian exoplanets with minimal SNR loss. We
also developed a complete pipeline for the automated detection of point source
candidates, the calculation of Receiver Operating Characteristics (ROC), false
positives based contrast curves, and completeness contours. We process in a
uniform manner more than 330 datasets from the Gemini Planet Imager Exoplanet
Survey (GPIES) and assess GPI typical sensitivity as a function of the star and
the hypothetical companion spectral type. This work allows for the first time a
comparison of different detection algorithms at a survey scale accounting for
both planet completeness and false positive rate. We show that the new forward
model matched filter allows the detection of $50\%$ fainter objects than a
conventional cross-correlation technique with a Gaussian PSF template for the
same false positive rate.