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Portrait photo of Daniel Baurenfeind
Portrait photo of Daniel Baurenfeind
Past

Research Staff

Daniel Bauernfeind, Ph.D.

Associate Data Scientist, Center for Computational Quantum Physics

Bio

Daniel Bauernfeind joined the Center for Computational Quantum Physics (CCQ) in October of 2019. Before that, he was a PhD student at the Graz University of Technology in Austria. During his PhD, he worked on Tensor Network algorithms for impurity problems to study strongly correlated electron systems. An especially suited tensor network geometry allowed to perform such simulation for multiple orbitals solely on the real-frequency axis. Currently he is working on the implementation of this new approach into the TRIQS library as well as trying to adapt this approach to more general impurity problems including off-diagonal hybridizations.

Publications

Aubry-André Anderson model: Magnetic impurities coupled to a fractal spectrum

arxiv:2205.06264, October 1, 2022

Ang-Kun Wu, Daniel Bauernfeind, Sarang Gopalakrishnan, Kevin Ingersent, and J. H. Pixley

Minimally Entangled Typical Thermal States Algorithms for Finite Temperature Matsubara Green Functions

arxiv:2107.13941, 2021

Daniel Bauernfeind, Miles E. Stoudenmire, and Olivier Parcollet

Quantum Quasi-Monte Carlo algorithm for out-of-equilibrium Green functions at long times

arXiv:2012.02803, December 4, 2020

Corentin Bertrand, Daniel Bauernfeind, Philipp Dumitrescu, Marjan Maček, Xavier Waintal, and Olivier Parcollet

Pseudogap Anderson impurity model out of equilibrium: A master equation tensor network approach

November 5, 2026

Delia M. Fugger, Daniel Bauernfeind, Max E. Sorantin, and Enrico Arrigoni

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Center for Computational Quantum Physics

CCQ’s mission is to develop the concepts, theories, algorithms and codes needed to solve the quantum many-body problem and use the solutions to predict the behavior of materials and molecules of scientific and technological interest.

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