DAOPHOT-MCMC is a modified version of the subroutine NSTAR.F which implements a Markov chain Monte Carlo (MCMC) routine for fitting crowded stellar positions and fluxes. This code is installed and implemented within the overall DAOPHOT-II structure (note: you must have a pre-installed version of DAOPHOT-II). Instructions and descriptions of the original software suite can be found in the DAOPHOT-II User's Manual (direct download).
Some of the DAOPHOT-MCMC functionality includes:
- Simultaneous 1-star, 2-star, and 3-star PSF fitting.
- Metropolis-Hastings routine to deliver posterior probability distributions for positions, separations, flux ratios, and total flux.
- Best-fit
$\chi^2$ /pixel map. - (Optional) constraints on the total flux and separation(s) for 2-star and 3-star fitting.
- (Optional) shell scripts (.sh) to automate MCMC runs on large datasets.
Detailed information can be found in the DAOPHOT-MCMC User's Manual here.
A Python wrapper (with added functionality) has also been developed, you can find it here.
If you find this code useful in your research, please cite Terry et al. 2021