Skip to content
Switch branches/tags
Go to file

Conduct principled inference of stellar population properties from photometric and/or spectroscopic data. Prospector allows you to:

  • Infer high-dimensional stellar population properties using parameteric or nonparametric SFHs (with nested or ensemble MCMC sampling)

  • Combine photometric and spectroscopic data from the UV to Far-IR rigorously using a flexible spectroscopic calibration model.

  • Forward model many aspects of spectroscopic data analysis and calibration, including spectrophotometric calibration and wavelength solution, thus properly incorporating uncertainties in these components in the final parameter uncertainties.

Read the documentation here.


To install to a conda environment with dependencies, see

To install just Prospector:

cd <install_dir>
git clone
cd prospector
python install

Then in Python

import prospect

See installation for requirements. Other files in the doc/ directory explain the usage of the code, and you can read the documentation here.

See also the tutorial or the interactive demo for fitting photometric data with composite stellar populations.


Inference with mock broadband data, showing the change in posteriors as the number of photometric bands is increased. Demonstration of posterior inference with increasing number of photometric bands


If you use this code, please reference

       author = {{Johnson}, Benjamin D. and {Leja}, Joel L. and {Conroy}, Charlie and
         {Speagle}, Joshua S.},
        title = "{Prospector: Stellar population inference from spectra and SEDs}",
     keywords = {Software},
         year = 2019,
        month = may,
          eid = {ascl:1905.025},
        pages = {ascl:1905.025},
archivePrefix = {ascl},
       eprint = {1905.025},
       adsurl = {},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}

and make sure to cite the dependencies as listed in installation

You should also cite:

   author = {{Leja}, J. and {Johnson}, B.~D. and {Conroy}, C. and {van Dokkum}, P.~G. and {Byler}, N.},
   title = "{Deriving Physical Properties from Broadband Photometry with Prospector: Description of the Model and a Demonstration of its Accuracy Using 129 Galaxies in the Local Universe}",
   journal = {\apj},
   year = 2017,
   volume = 837,
   pages = {170},
   eprint = {1609.09073},
   doi = {10.3847/1538-4357/aa5ffe},
  adsurl = {},