This package implements methods for modelling observed Hess diagrams (which are just binned color-magnitude diagrams, also called CMDs) and using them to fit astrophysical star formation histories (SFHs). A paper describing the implemented methodologies is currently in preparation. This package also provides utilities for simulating CMDs given input SFHs and photometric error and completeness functions, which can be useful for planning observations and writing proposals. Please see our documentation (linked in the badge above) for more information. A rendered Jupyter notebook with example usage of this package is available here. This package does not currently ship with stellar models or isochrones, these are expected to be provided by the user and can be sourced from online resources like the CMD webform for PARSEC models.
The paper describing the methodologies used in this package is available on ArXiv here. We ask that published work using this package cite this paper.
This package is registered to Julia's General registry and can be installed via Pkg from the Julia REPL by executing
import Pkg;
Pkg.add("StarFormationHistories");Given an isochrone, one of the main challenges in the SFH fitting process is generating a template (sometimes called a partial CMD) that contains the expected number of stars in each Hess diagram bin per unit solar mass of stars formed (or per unit of star formation rate). The following figure, produced by examples/templates/smooth_template.jl, shows a mock population at left sampled from an isochrone assuming photometric error and completeness functions typical of the JWST/NIRCAM imaging obtained as part of the Resolved Stellar Populations Early Release Science Program (Weisz et al. 2023, Weisz et al. 2024). We discretize it to form a Hess diagram in panel B. In panel C we show the model template we construct from this isochrone. Panel D shows the residual significance, which is the difference between the observed bin counts and those in our template, divided by the Poisson error. The distribution of residuals shows that the template is a robust model of the distribution of the mock population in the Hess diagram space.
Below we additionally show example templates for different combinations of stellar population age and metallicity that bracket the range typically considered in these analyses.
Once templates have been generated for a reasonable set of isochrones, they can be used to estimate the SFH of an observed population by modelling the observed Hess diagram as a linear combination of the templates. The coefficients on the linear combination are simply the desired star formation rates. While this can work, and we provide fitting methods that support this use, this approach is crude as it does not guarantee that the solution has a physically realistic age-metallicity relation (AMR). We additionally define a few parametric AMRs that apply constraints during the fitting process to alleviate this issue. We plan to expand the set of AMR models in the future.
Support for this work was provided by the Owens Family Foundation and by NASA through grant HST-AR-17560 from the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555.