Bayesian Estimator for Stellar Population Analysis
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Bayesian Estimator for Stellar Population Analysis (BESTA)
BESTA is a Python package for inferring stellar population properties from spectroscopic and/or photometric data using Bayesian inference and Monte Carlo methods.
Full documentation is available at besta.readthedocs.io.
Framework
BESTA is built on top of two core libraries:
- Population Synthesis Toolkit (PST) — flexible stellar population synthesis models.
- CosmoSIS — modular parameter estimation via Monte Carlo sampling.
Features
Pipeline modules
Ready-to-use CosmoSIS pipeline modules are provided in besta.pipeline_modules:
| Module | Description |
|---|---|
GalaxySpectraModule |
Full spectroscopic SED fitting |
FullSpectralFitModule |
Joint stellar population and kinematics fit from spectra |
GalaxyPhotometryModule |
Broadband photometric SED fitting |
SFHPhotometryGridModule |
SFH inference from photometry via model grid |
SFHPhotometryEmulatorModule |
SFH inference from photometry via emulator |
Star formation history models
Analytic: ExponentialSFH, DelayedTauSFH, DelayedTauQuenchedSFH, LogNormalSFH, LogNormalQuenchedSFH
Piece-wise: FixedTimeSFH, FixedTime_sSFR_SFH, FixedMassFracSFH
Installation
pip install besta
Requires Python ≥ 3.10. See the installation guide for CosmoSIS setup instructions.
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