Transients and Other Time Series Science

• Focusing on the detection and analysis of any object that shows flux variation.
  • For example: variable stars, TDE, and eclipsing binaries.
  • Exoplanet and supernova are also trasients, but they have much broader impact therefore they have their own topics.

Transient Notification

• pycgn - Python package for processing Gamma-ray Coordinates Network (GCN) notices and circulars
  • Anonymous VOEvent client for receiving GCN/TAN notices in XML format

Data Access

• ztfquery - Access ZTF data from Python
  • By Mickael Rigault. ztfquery is a python tool to download ZTF (and SEDM) data

Differential Photometry

• lemon - Differential photometry for humans (and astronomers)
  • By Víctor Terrón. LEMON is a differential-photometry pipeline, written in Python, that determines the changes in the brightness of astronomical objects over time and compiles their measurements into light curves.
• hotpants - High Order Transform of Psf ANd Template Subtraction code
  • By Andy Becker.
• astrobase - Python modules for light curve work and variable star astronomy
  • By Waqas Bhatti. It includes implementations of several period-finding algorithms, batch work drivers for working on large collections of light curves, and a small web-app useful for reviewing and classifying light curves by stellar variability type.

Trasient Identification and Classification

• avocado - Photometric Classification of Astronomical Transients and Variables With Biased Spectroscopic Samples
  • Avocado is a general photometric classification code that is designed to produce classifications of arbitrary astronomical transients and variable objects.
  • The original codebase of avocado was developed for and won the 2018 Kaggle PLAsTiCC challenge.
• astrorapid - Real-time Automated Photometric IDentification (RAPID) of astronomical transients using deep learning
  • By Daniel Muthukrishna. RAPID (Real-time Automated Photometric IDentification) can classify multiband photometric light curves into several different transient classes. It uses a deep recurrent neural network to produce time-varying classifications.
• astrodash - Deep learning for the automated spectral classification of supernovae
  • By Daniel Muthukrishna. Software to classify the type, age, redshift and host for any supernova spectra. Two platforms exists: a python library that enables a user to classify several spectra (can classify thousands of spectra in seconds), and also a graphical interface that enables a user to view and classify a spectrum.
• UPSILoN- Automated Classification of Periodic Variable Stars Using Machine Learning
  • UPSILoN (AUtomated Classification of Periodic Variable Stars using MachIne LearNing)
• SuperNNova - Open Source Photometric classification
  • Using recurrent network technique. Based on SuperNNova: an open-source framework for Bayesian, Neural Network based supernova classification

Lightcurve and Exoplanet

• lightkurve - A friendly package for Kepler & TESS time series analysis in Python
  • Lightkurve is a community-developed, open-source Python package which offers a beautiful and user-friendly way to analyze astronomical flux time series data, in particular the pixels and lightcurves obtained by NASA’s Kepler and TESS exoplanet missions.
• eleanor - light curves from TESS
  • eleanor is a python package to extract target pixel files from TESS Full Frame Images and produce systematics-corrected light curves for any star observed by the TESS mission.
• starry - Analytic occultation light curves for astronomy
  • By Rodrigo Luger. Based on a very nice paper
• everest - EPIC Variability Extraction and Removal for Exoplanet Science Targets
  • A pipeline for de-trending K2 light curves with pixel level decorrelation and Gaussian processes.]
• wotan - Automagically remove trends from time-series data
  • By Michael Hippke. Offers free and open source algorithms to automagically remove trends from time-series data.