• Machine learning
• Quantum optics
• Many-body physics of ultracold atoms
• Multiple scattering theory

• Automated reconstruction of bound states in bilayer graphene quantum dots
  J. Bucko, F. Schäfer, F. Herman, R. Garreis, C. Tong, A. Kurzmann, T. Ihn, E. Greplova
  arXiv:2203.00697
   
• Replacing neural networks by optimal analytical predictors for the detection of phase transitions
  J. Arnold and F. Schäfer
  arXiv:2203.06084
   
• AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia
  F. Schäfer, M. Tarek, L. White, and C. Rackauckas
  arXiv:2109.12449
   

• Control of Stochastic Quantum Dynamics with Differentiable Programming
  F. Schäfer, P. Sekatski, M. Koppenhöfer, C. Bruder, and M. Kloc
  Mach. Learn.: Sci. Technol. 2, 035004 (2021); arXiv:2101.01190

• Interpretable and unsupervised phase classification
  J. Arnold, F. Schäfer, M. Zonda, and A. U. J. Lode
  Phys. Rev. Res. 3, 033052 (2021); arXiv:2010.04730
   
• A differentiable programming method for quantum control
  F. Schäfer, M. Kloc, C. Bruder, and N. Lörch
  Mach. Learn.: Sci. Technol. 1, 035009 (2020); arXiv:2002.08376
   
• Spectral Structure and Many-Body Dynamics of Ultracold Bosons in a Double-Well
  F. Schäfer, M. A. Bastarrachea-Magnani, A. U. Lode, L. de Forges de Parny, and A. Buchleitner
  Entropy 22, 382 (2020); arXiv:2002.00973
   
• Unsupervised identification of topological order using predictive models
  E. Greplova, A. Valenti, G. Boschung, F. Schäfer, N. Lörch, and S. Huber
  New J. Phys. 22, 045003 (2020);  arXiv:1910.10124
   
• Vector field divergence of predictive model output as indication of phase transitions
  F. Schäfer and N. Lörch
  PRE 99, 062107 (2019);  arXiv:1812.00895

• Numerical investigation of strongly interacting bosons at zero temperature
  L. de Forges de Parny, F. Schäfer, J. Mielke, M. A. Bastarrachea-Magnani and A. Buchleitner
  in Proceedings of the 5th bwHPC Symposium (2018);  DOI: 10.15496/publikation-29050

• Cooperative scattering of scalar waves by optimized configurations of point scatterers
  F. Schäfer, F. Eckert and T. Wellens
  J. Phys. B 50, 235502 (2017);  arXiv:1706.06772

I participated in the Google Summer of Code 2020 project within the Julia Language organization and in the Google Summer of Code 2021 project within the NumFocus organization, more information including all blog posts can be found at my github page: 

https://frankschae.github.io/

Please find here my public github repositories. Currently, there is:

• a minimal working example for the divergence-based learning scheme of phase transitions
• a PyTorch implementation of our differentiable programming method for quantum control 
• the code for our paper interpretable and unsupervised phase classification