MITIM toolset

MITIM (MIT Integrated Modeling) is an open-source Python library for modeling tasks in plasma physics and fusion energy, developed and maintained by the MFE-IM group. It does two things: it runs physics codes and reads their results through simple Python objects, and it couples those codes with surrogate-based optimization. PORTALS and MAESTRO, the tools behind much of our research, are part of MITIM.

Code on GitHubDocumentationRelease notes

Open source under the MIT license. Python 3.10 to 3.12.

Optimization workflows

These workflows solve fusion problems with Bayesian optimization, where each evaluation is an expensive simulation.

PORTALS

Predicts steady-state core profiles by matching transport fluxes to their targets. It trains surrogates of the transport model with Bayesian optimization, which makes predictions with nonlinear gyrokinetic simulations (CGYRO) affordable. It also runs with reduced models such as TGLF.

MAESTRO

Couples PORTALS with equilibrium, pedestal, divertor and heating solvers, for steady-state scenario predictions with full physics models.

VITALS

Validates local transport models against experiments with uncertain inputs, across several transport channels and fluctuation measurements, using TGLF.

FreeGS-U

Finds Grad-Shafranov equilibria that satisfy user-specified constraints, using FreeGS.

Your own problem

Any function or simulation can be optimized with the same machinery, which is built on BoTorch.

Schematic diagram of the MAESTRO workflow
Schematic diagram of the MAESTRO workflow. P. Rodriguez-Fernandez et al. Plasma Phys. Control. Fusion (2026)

Interfaces to physics codes

MITIM prepares the inputs, launches the run (locally or on a remote cluster), and reads and plots the results of:

TGLFCGYRONEOTGYROTRANSPASTRAEPEDQuaLiKiz

It also reads and converts tokamak equilibrium files and input.gacode profile files. MITIM does not include these codes; each one has to be installed separately. See the standalone capabilities in the documentation.

Get started

git clone git@github.com:pabloprf/MITIM-fusion.git
pip install -e MITIM-fusion[pyqt]

Leave out [pyqt] on machines without a graphical interface, such as computing clusters. The installation guide covers the user configuration.

MITIM is research software, provided as is. It is meant to shorten the learning curve of transport codes; for publication-quality results, understand and verify each step of the workflow. Questions, bug reports and feature requests are welcome on GitHub.

How to cite

If you use MITIM in your work, please cite:

  • NFP. Rodriguez-Fernandez, N.T. Howard, A. Saltzman, S. Kantamneni, J. Candy, C. Holland, M. Balandat, S. Ament and A.E. White, “Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers”, Nucl. Fusion 64 076034 (2024). DOI: 10.1088/1741-4326/ad4b3d

For specific workflows, please also cite:

  • NFPORTALS: P. Rodriguez-Fernandez, N.T. Howard and J. Candy, “Nonlinear gyrokinetic predictions of SPARC burning plasma profiles enabled by surrogate modeling”, Nucl. Fusion 62, 076036 (2022). DOI: 10.1088/1741-4326/ac64b2
  • PPCFMAESTRO: P. Rodriguez-Fernandez, N.T. Howard, J. Hall, A. Saltzman, A. Martin-Sanabria, A. Ho, G. Snoep, J. Pimentel-Aldaz, C. Holland, M. Muraca, P. de Lara Montoya, K. Yanna, A.E. White, T.A. Body, A.J. Creely, J. Hillesheim and P.B. Snyder, “Accelerating integrated modeling with surrogate-based optimization: the MAESTRO workflow”, Plasma Phys. Control. Fusion, published online (2026). DOI: 10.1088/1361-6587/aea7d0
  • FSTVITALS: P. Rodriguez-Fernandez, A. E. White, A. J. Creely, M. J. Greenwald, N. T. Howard, F. Sciortino and J. C. Wright, “VITALS: A surrogate-based optimization framework for the accelerated validation of plasma transport codes”, Fusion Sci. Technol. 74, 65-76 (2018). DOI: 10.1080/15361055.2017.1396166

Publications that used MITIM

A selection; the full list of the group’s publications is on the Research page.

  • NFN. T. Howard, P. Rodriguez-Fernandez, C. Holland and J. Candy, “Prediction of performance and turbulence in ITER burning plasmas via nonlinear gyrokinetic profile prediction”, Nucl. Fusion 65 016002 (2025). DOI: 10.1088/1741-4326/ad8804
  • POPP. Rodriguez-Fernandez, N. T. Howard, A. Saltzman, L. Shoji, T. Body, D. J. Battaglia, J. W. Hughes, J. Candy, G. M. Staebler, A. J. Creely, “Core performance predictions in projected SPARC first-campaign plasmas with nonlinear CGYRO”, Phys. Plasmas 31, 062501 (2024). DOI: 10.1063/5.0209752
  • NFR. Bielajew, U. Plank, G.D. Conway, A.E. Hubbard, P. Rodriguez-Fernandez, B. Vanovac, C. Yoo, A.E. White and the ASDEX Upgrade Team, “Edge radiated temperature fluctuations across confinement regime transitions in favorable and unfavorable drift configurations at ASDEX Upgrade”, Nucl. Fusion 63 126022 (2023). DOI: 10.1088/1741-4326/acfcc9
  • POPP. A. Molina Cabrera, P. Rodriguez-Fernandez, T. Görler, M. Bergmann, K. Höfler, S. S. Denk, R. Bielajew, G. D. Conway, C. Yoo, A. E. White, and the ASDEX Upgrade Team, “Isotope effects on energy transport in the core of ASDEX-Upgrade tokamak plasmas: turbulence measurements and model validation”, Physics of Plasmas 30, 082304 (2023). DOI: 10.1063/5.0143416
  • NFS.J. Frank, C.J. Perks, A.O. Nelson, T. Qian, S. Jin, A. Cavallaro, A. Rutkowski, A. Reiman, J.P. Freidberg, P. Rodriguez-Fernandez and D. Whyte, “Radiative pulsed L-mode operation in ARC-class reactors“, Nucl. Fusion 62 126036 (2022). DOI: 10.1088/1741-4326/ac95ac
  • JPPP. Rodriguez-Fernandez, N. T. Howard, M. J. Greenwald, A. J. Creely, J. W. Hughes, J. C. Wright, C. Holland, Y. Lin, F. Sciortino and the SPARC team, “Predictions of core plasma performance for the SPARC tokamak“, Journal of Plasma Physics, 86(5), 865860503 (2020). DOI: 10.1017/S0022377820001075