ICORE is a command-line driven co-addition, mosaicking, and resolution enhancement (HiRes) tool for creating science quality products from image data in FITS format and with World Coordinate System information following the FITS-WCS standard. It includes preparatory steps such as image background matching, photometric gain-matching, and pixel-outlier rejection. Co-addition and/or HiRes'ing can be performed in either the inertial WCS or in the rest frame of a moving object. Three interpolation methods are supported: overlap-area weighting, drizzle, and weighting by the detector Point Response Function (PRF). The latter enables the creation of matched-filtered products for optimal point-source detection, but most importantly allows for resolution enhancement using a spatially-dependent deconvolution method. This is a variant of the classic Richardson-Lucy algorithm with the added benefit to simultaneously register and co-add multiple images to optimize signal-to-noise and sampling of the instrumental PSF. It can assume real (or otherwise "flat") image priors, mitigate "ringing" artifacts, and assess the quality of image solutions using statistically-motivated convergence criteria. Uncertainties are also estimated and internally validated for all products. The software supports multithreading that can be configured for different architectures. Numerous example scripts are included (with test data) to co-add and/or HiRes image data from Spitzer-IRAC/MIPS, WISE, and Herschel-SPIRE.

braai (Bogus/Real Adversarial AI) performs deep-learning real/bogus classification for the Zwicky Transient Facility (ZTF), separating genuine astrophysical events and objects from false positive detections. It uses a convolutional neural network to enable efficient automated detection of flux transients, recurring flux-variable sources, and moving objects in large-scale astronomical survey data. In production, it achieves low false negative and false positive rates.

Tails identifies and localizes comets in image data from the Zwicky Transient Facility (ZTF), a robotic optical sky survey, using deep-learning with a custom EfficientDet-based architecture. It detects comets in single images in near real time, rather than requiring multiple epochs as in traditional methods. In production, Tails achieves 99% recall, a false positive rate below 0.01%, and 1–2 pixel root mean square error in the predicted position.

The Bayesian-based Gaussian Process model AsteroGaP (Asteroid Gaussian Processes) fits sparsely-sampled asteroid light curves. By utilizing a more flexible Gaussian Process framework for modeling asteroid light curves, it is able to represent light curves in a periodic but non-sinusoidal manner.

ZChecker finds, measures, and visualizes known comets in the Zwicky Transient Facility time-domain survey. Images of targets are identified using on-line ephemeris generation and survey metadata. The photometry of the targets are measured and the images are processed with temporal filtering to highlight morphological variations in time.