Ultraviolet Variability Analysis is an astronomy pipeline for time-variable sources.
Project description
Variable Source Cluster Analysis (VASCA)
- Motivation
- Pipeline Overview
- Key Features
- Proof-of-Principle Study
- Documentation and Installation
- 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:
- Spatial Clustering: Associate detections from repeated observations to unique cosmic sources using mean-shift clustering.
- Statistical Variability Detection: Identify time-variable sources by testing flux variations against a constant hypothesis at a 5-σ significance level.
- 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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file vasca-1.0.14.tar.gz
.
File metadata
- Download URL: vasca-1.0.14.tar.gz
- Upload date:
- Size: 47.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 71c0b1e8cff1a03fc2e68a07f6c8bb93c335420adceb74eea0d0ab3e4bed2cfc |
|
MD5 | 56d1f30616a43b031377469a677bb393 |
|
BLAKE2b-256 | 4b0a4fef5b136e528114592bb04812d17e4e1efd0a2614573916dd55c0df6147 |
File details
Details for the file vasca-1.0.14-py3-none-any.whl
.
File metadata
- Download URL: vasca-1.0.14-py3-none-any.whl
- Upload date:
- Size: 47.6 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 623964c61d69be75ae2cbe480ffe7e0eb284224b67d517283a5afbbd83bffee0 |
|
MD5 | 194d1c2954060b4fecb88fc0416fde23 |
|
BLAKE2b-256 | c4ea2646afd625ca278015679247fe2bc5c8317189009a4a0caa43019c3386fd |