TESSreduce builds on lightkurve (ascl:1812.013) to reduce TESS data while preserving transient signals. It takes a TPF as input (supplied or constructed with TESScut (https://mast.stsci.edu/tesscut/). The background subtraction accounts for the smooth background and detector straps. In addition to background subtraction, TESSreduce also aligns images, performs difference imaging, detects transient events, and by using PS1 data, can calibrate TESS counts to physical flux or AB magnitudes.

Starkiller simulates and subtracts integral field unit (IFU) data for all cataloged stars. If no catalog is provided, Gaia DR3 is automatically downloaded. Point spread functions (PSFs) are modeled from the input data cube and can include trailing. Stellar spectra are extracted using PSF photometry, matched to the CK model stellar spectral library, and initially normalized to catalog photometry (Gaia G by default). The normalized spectra are injected into a simulated data cube, and a secondary flux correction adjusts the IFU to best match calibration sources. Starkiller subtractes the simulated scene from the calibrated IFU to produce a synthetic differenced cube, which is saved as a FITS file.

SourceDetect utilizes Keras and Tensorflow to train and apply a convolutional neural network model to perform a transient event search through TESS data. The code scans imaging cutouts, computes detection likelihoods, and classifies candidate point-like events as positive, negative, or artifacts and outputs tables of detections including positions, classes, and event confidences. SourceDetect is optimized for large-scale surveys, handling vectorized image inputs and providing programmable filtering criteria to isolate transient, variable, or moving sources.