Introducing BurnMan 1.3


BurnMan is an open source mineral physics and seismological toolkit written in Python which can enable a user to calculate (or fit) the physical and chemical properties of endmember minerals, fluids/melts, solutions, and composite assemblages.

Properties which BurnMan can calculate include:

  • the thermodynamic free energies, allowing phase equilibrium calculations, endmember activities, chemical potentials and oxygen (and other) fugacities.

  • entropy, enabling the user to calculate isentropes for a given assemblage.

  • volume, to allow the user to create density profiles.

  • seismic velocities, including Voigt-Reuss-Hill and Hashin-Strikman bounds and averages.

The toolkit itself comes with a large set of classes and functions which are designed to allow the user to easily combine mineral physics with geophysics, and geodynamics. The features of BurnMan include:

  • the full codebase, which includes implementations of many static and thermal equations of state (including Vinet, Birch Murnaghan, Mie-Debye-Grueneisen, Modified Tait), and solution models (ideal, symmetric, asymmetric, subregular).

  • popular endmember and solution datasets already coded into burnman-usable format (including [HollandPowell11], [SLB05], [SLB11] and [SLB22])

  • Optimal least squares fitting routines for multivariate data with (potentially correlated) errors in pressure and temperature. As an example, such functions can be used to simultaneously fit volumes, seismic velocities and enthalpies.

  • a “Planet” class, which self-consistently calculates gravity profiles, mass, moment of inertia of planets given the chemical and temperature structure of a planet

  • published geotherms

  • a tutorial on the basic use of BurnMan

  • a large collection of annotated examples

  • a set of high-level functions which create files readable by seismological and geodynamic software, including: Mineos [MWF11], AxiSEM [NissenMeyervanDrielStahler+14] and ASPECT

  • an extensive suite of unit tests to ensure code functions as intended

  • a series of benchmarks comparing BurnMan output with published data

  • a directory containing user-contributed code from published papers

BurnMan makes extensive use of SciPy, NumPy and SymPy which are widely used Python libraries for scientific computation. Matplotlib is used to display results and produce publication quality figures. The computations are consistently formulated in terms of SI units.

The code documentation including class and function descriptions can be found online at

This software has been designed to allow the end-user a great deal of freedom to do whatever calculations they may wish and to add their own modules. The underlying Python classes have been designed to make new endmember, solution and composite models easy to read and create. We have endeavoured to provide examples and benchmarks which cover the most popular uses of the software, some of which are included in the figure below. This list is certainly not exhaustive, and we will definitely have missed interesting applications. We will be very happy to accept contributions in form of corrections, examples, or new features.




  • Python 3.8+

  • Python modules: NumPy, SciPy, SymPy, Sparse, Matplotlib

Optional modules

Needed for some functionality:

  • cvxpy: required for some least squares fitting routines and solution polytope calculations.

  • pycddlib: required for solution polytope calculations.

  • autograd: required for esoteric solution models defined using a single excess function. Not required for the vast majority of users.


Installation of BurnMan is mostly platform independent. As long as you know how to use a terminal, the process should be straightforward. The following instructions should help, but let us know if you have any problems.


First, make sure you have a sufficiently recent version of python installed on your machine (see above for the latest requirements). To check your version of python, type the following in a terminal:

python –version

If your version is not recent enough, visit to find out how to install a newer version.

Once you have checked your version of python, you should make sure you have installed the python module pip. We will use this module to install BurnMan. If you don’t have it already, you can install it by opening a terminal window and typing:

python -m ensurepip –upgrade

Mac users will also need to install Xcode, which can be found in the MacStore.

Stable version

If you are only interested in using BurnMan (rather than developing the software), and you aren’t interested in any of the latest changes, you can install the stable version by typing the following into a terminal window:

python -m pip install burnman

This method of installation does not give you easy access to all the examples, or the test suite. These can be found in the latest release package which can be downloaded from

Development version

If you want to install the development version of BurnMan (with all the latest features), you will first need to download the source code. The best way to do this is by using git (a version control system). To install git, follow the instructions at

Then, using a terminal, navigate to the directory into which you want to clone the BurnMan repository, and type

(If you don’t want to use git, you can download the current master branch from

Once the repository is cloned, navigate to the top-level directory by typing cd burnman in the terminal, and then install BurnMan, either in static mode: python -m pip install . or in development mode (if you want to develop or modify the code): python -m pip install -e ..

Checking that the installation worked

To check that the installation has worked, you can run the test suite (./ This takes a few minutes to run.

A more basic check that BurnMan is installed is to navigate to the Burnman examples directory and type:


If figures show up, BurnMan has been installed.

Citing BurnMan

If you use BurnMan in your work, we ask that you cite the following publications:

  • Myhill, R., Cottaar, S., Heister, T., Rose, I., Unterborn, C., Dannberg, J. and Gassmoeller, R. (2023). BurnMan - a Python toolkit for planetary geophysics, geochemistry and thermodynamics. Journal of Open Source Software. (

  • Myhill, R., Cottaar, S., Heister, T., Rose, I., and Unterborn, C. (2023): BurnMan v1.2.0 [Software]. Computational Infrastructure for Geodynamics. Zenodo. (

  • Cottaar S., Heister, T., Rose, I., and Unterborn, C., (2014). BurnMan: A lower mantle mineral physics toolkit, Geochemistry, Geophysics, and Geosystems, 15(4), 1164-1179 (

Contributing to BurnMan

If you would like to contribute bug fixes, new functions or new modules to the existing codebase, please contact us at or make a pull request at

BurnMan also includes a contrib directory that contains python and ipython scripts used to reproduce published results. We welcome the submission of new contributions to this directory. As with the contribution of code, please contact us at or make a pull request at

Acknowledgement and Support

  • This project was initiated at, and follow-up research support was received through, Cooperative Institute of Deep Earth Research, CIDER (NSF FESD grant 1135452) – see

  • We thank all the members of the CIDER Mg/Si team for their input: Valentina Magni, Yu Huang, JiaChao Liu, Marc Hirschmann, and Barbara Romanowicz. We also thank Lars Stixrude for providing benchmarking calculations and Zack Geballe, Motohiko Murakami, Bill McDonough, Quentin Williams, Wendy Panero, and Wolfgang Bangerth for helpful discussions.

  • We thank CIG ( for support and accepting our donation of BurnMan as an official project.