摘要：The Transiting Exoplanet Survey Satellite (TESS) will observe ∼150million stars brighter than T 16mag », withphotometric precision from 60ppm to 3%, enabling an array of exoplanet and stellar astrophysics investigations.While light curves will be provided for ∼400,000 targets observed at 2 minute cadence, observations of most starswill only be provided as full-frame images (FFIs) at 30minute cadence. The TESS image scale of ∼21″/pix ishighly susceptible to crowding, blending, and source confusion, and the highly spatially variable point-spreadfunction (PSF) will challenge traditional techniques, such as aperture and Gaussian-kernel PSF photometry. Weuse official “End-to-End6” TESS simulated FFIs to demonstrate a difference image analysis pipeline, using a δ-function kernel, that achieves the mission specification noise floor of 60ppmhr −1/2 . We show that the pipelineperformance does not depend on position across the field, and only ∼2% of stars appear to exhibit residualsystematics at the level of ∼5ppt. We also demonstrate recoverability of planet transits, eclipsing binaries, andother variables. We provide the pipeline as an open-source tool at https://github.com/ryanoelkers/DIA in bothIDL and PYTHON. We intend to extract light curves for all point sources in the TESS FFIs as soon as they becomepublicly available, and will provide the light curves through the Filtergraph data visualization service. An exampledata portal based on the simulated FFIs is available for inspection at https://filtergraph.com/tess_ffi.
关键词：catalogs;methods: data analysis;techniques: image processing
