Aperture Photometry Tool (APT) is software for astronomers and students interested in manually exploring the photometric qualities of astronomical images. It has a graphical user interface (GUI) which allows the image data associated with aperture photometry calculations for point and extended sources to be visualized and, therefore, more effectively analyzed. Mouse-clicking on a source in the displayed image draws a circular or elliptical aperture and sky annulus around the source and computes the source intensity and its uncertainty, along with several commonly used measures of the local sky background and its variability. The results are displayed and can be optionally saved to an aperture-photometry-table file and plotted on graphs in various ways using functions available in the software. APT is geared toward processing sources in a small number of images and is not suitable for bulk processing a large number of images, unlike other aperture photometry packages (e.g., SExtractor). However, APT does have a convenient source-list tool that enables calculations for a large number of detections in a given image. The source-list tool can be run either in automatic mode to generate an aperture photometry table quickly or in manual mode to permit inspection and adjustment of the calculation for each individual detection. APT displays a variety of useful graphs, including image histogram, and aperture slices, source scatter plot, sky scatter plot, sky histogram, radial profile, curve of growth, and aperture-photometry-table scatter plots and histograms. APT has functions for customizing calculations, including outlier rejection, pixel “picking” and “zapping,” and a selection of source and sky models. The radial-profile-interpolation source model, accessed via the radial-profile-plot panel, allows recovery of source intensity from pixels with missing data and can be especially beneficial in crowded fields.

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.

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.