VASCA icon 🧪 pytest 📚 docs 🚀 pypi

Variable Source Cluster Analysis (VASCA)¶

  1. Motivation

  2. Pipeline Overview

  3. Key Features

  4. Proof-of-Principle Study

  5. Documentation and Installation

  6. Getting Started

Motivation¶

VASCA is a high-performance software package developed to address the challenges of time-domain astronomy, especially given the increasing volume of data from large-scale surveys such as ZTF, LSST, and ULTRASAT. Designed to analyze time-variable cosmic sources like active galactic nuclei, stars, and transient events, VASCA provides a modular, scalable solution for integrating data from multiple instruments and conducting a cohesive analysis.

Pipeline Overview¶

The VASCA analysis pipeline consists of three primary steps:

  1. Spatial Clustering: Associate detections from repeated observations to unique cosmic sources using mean-shift clustering.

  2. Statistical Variability Detection: Identify time-variable sources by testing flux variations against a constant hypothesis at a 5-σ significance level.

  3. Source Classification: Classify detected sources, including cross-matching with external catalogs (e.g., SIMBAD, Gaia).

The main output of the pipeline is a catalog of time-variable cosmic sources, including detailed classifications and cross-matches with existing astronomical databases.

Key Features¶

  • Simplicity and Modularity: The software uses a hierarchical data model and modular processing to ensure scalability and ease of use. It supports data from multiple instruments seamlessly.

  • Proven Algorithms: VASCA relies on established algorithms and statistical methods, ensuring robustness and reducing the maintenance burden.

  • Focus on Specific Use Case: Optimized for analyzing time-domain astronomical data, VASCA keeps complexity low, simplifying auditing and debugging.

  • Standards Compliance: Outputs are designed for publication readiness by adhering to IAU and CDS standards, using widely-accepted, non-proprietary data formats.

  • Customization and Extensibility: VASCA allows flexible configuration, making it adaptable to different datasets and instrument-specific requirements.

Proof-of-Principle Study¶

VASCA was applied to a proof-of-principle study using the Galaxy Evolution Explorer (GALEX) archive (2003-2013). This study produced a catalog of over 4,000 UV-variable sources, revealing UV variability across all classes of stars. Notably, a massive, pulsating white dwarf exhibited unique long-term variability in the UV. The full article including a description of VASCA’s pipeline can be found here: The time-variable ultraviolet sky: Active galactic nuclei, stars, and white dwarfs.

Documentation and Installation¶

VASCA is distributed as an open-source package. Comprehensive documentation is available here, including example notebooks and an API reference to help users get started. For quick installation, VASCA can be installed via PyPI using:

pip install vasca

For more info see the installation guide.

Documentation!¶

Modules¶

ResourceManager

Manages access to external resources.

GALEXField

Instance of one GALEX field