LightCurveLynx
A Fast and Nimble Package for Time Domain Astronomy
Introduction
Realistic light curve simulations are essential to many time-domain problems. Simulations are needed to evaluate observing strategy, characterize biases, and test pipelines. LightCurveLynx aims to provide a flexible, scalable, and user-friendly time-domain simulation software with realistic effects and survey strategies.
The software package consists of multiple stages:
- A flexible framework for consistently sampling model parameters (and hyperparameters),
- Realistic models of time varying phenomena (such as supernovae and AGNs),
- Effect models (such as dust extinction), and
- Survey characteristics (such as cadence, filters, and noise).
For an overview of the package, we recommend starting with introduction notebook.
Installation
Install from PyPI or conda-forge:
pip install lightcurvelynx
conda install conda-forge::lightcurvelynx
Since LightCurveLynx relies on a large number of existing packages, not all of the packages are installed in the default configuration. You can install most of the optional depenencies with the "dev" or "all" extras:
pip install 'lightcurvelynx[all]'
If you need a package that is not installed as part of the default or all configurations, LightCurveLynx will provide a message with the information on which packages you need to install and how to install them.
Example Usage
The tutorial notebooks documentation page provides a variety of usage examples and technical deep dives.
If you have questions, check out the FAQ page or the getting help page
Dev Guide - Getting Started
Before installing any dependencies or writing code, it's a great idea to create a
virtual environment such as venv
>> python3 -m venv ~/envs/lightcurvelynx
>> source ~/envs/lightcurvelynx/bin/activate
Once you have created a new environment, you can install this project for local development using the following commands:
>> pip install -e .'[dev]'
>> pre-commit install
Notes:
- The single quotes around
'[dev]'may not be required for your operating system. pre-commit installwill initialize pre-commit for this local repository, so that a set of tests will be run prior to completing a local commit. For more information, see the Python Project Template documentation on pre-commit
If you are interested in contributing directly to the package, see our contribution guide.
Citations / Acknowledgements
If you use LightCurveLynx in your research, we ask that you cite the following papers:
- Dai et. al. 2026 "LightCurveLynx: Forward Modeling of Time-Domain Surveys with Application to ZTF SN Ia DR2" (in review; see arxiv.org/abs/2604.07134 )
- Kubica et. al. 2026 "LightCurveLynx: Fast and Nimble Time Domain Simulation for Astronomical Surveys" (in review )
LightCurveLynx relies on numerous open source packages to perform the computation. Please make sure to cite the packages that your study uses.
Advisories
This project is under active development and may see API changes.
Users should always carefully validate the science outputs for their use case. Please reach out to the team if you find any problems.
Acknowledgements
This project is supported by Schmidt Sciences.
3 maintainers
Metadata
3 maintainers
Release files for lightcurvelynx 0.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| lightcurvelynx-0.6.tar.gz | 12.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| lightcurvelynx-0.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 13.1 MB
Release files / lightcurvelynx-0.6.tar.gz
| Download URL | lightcurvelynx-0.6.tar.gz |
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| Size | 12.8 MB |
| Tags | Source |
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| Tags | Python 3 |
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