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ZWAD (ZTF anomaly detection pipeline) examines data and performs tailored feature extraction. The code then uses machine learning methods to searches for outliers, and identifies anomalies to be examined for validation by experts. Used with the SNAD ZTF data releases object viewer (ascl:2106.034), the infrastructure helps experts to form global views of specific scientifically interesting candidates.
Rainbow is a black-body parametric model for transient light curves. It uses Bazin function as a model for bolometric flux evolution and a logistic function for the temperature evolution; it provides seven fit parameters and goodness of fit (reduced χ2) and is well-suited for transient objects. Also included is RainbowRisingFit, suitable for rising transient objects, which offers six fit parameters. It is based on a rising sigmoid bolometric flux and a sigmoid temperature evolution. These implementations are implemented in the light-curve processing toolbox (ascl:2107.001) for Python.