Publications of D. Hofmann

G. Passetti, D. Hofmann, P. Neitemeier, L. Grunwald, M. A. Sentef, and D. M. Kennes, Can Neural Quantum States Learn Volume-Law Ground States?, Physical Review Letters 131 (3), 036502 (2023).

D. R. Baykusheva, M. Kalthoff, D. Hofmann, M. Claassen, D. M. Kennes, M. A. Sentef, and M. Mitrano, Witnessing Nonequilibrium Entanglement Dynamics in a Strongly Correlated Fermionic Chain, Physical Review Letters 130 (10), 106902 (2023).

F. Vicentini, D. Hofmann, A. Szabó, D. Wu, C. Roth, C. Giuliani, G. Pescia, J. Nys, V. Vargas-Calderón, N. Astrakhantsev, and G. Carleo, NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems, SciPost Physics Codebases 7(2022).

D. Hofmann, G. Fabiani, J. H. Mentink, G. Carleo, and M. A. Sentef, Role of stochastic noise and generalization error in the time propagation of neural-network quantum states, SciPost Physics 12 (5), 165 (2022).

D. Hofmann and M. A. Sentef, Resonant laser excitation and time-domain imaging of chiral topological polariton edge states, Physical Review Research 2 (3), 033386 (2020).

P. Wrzosek, K. Wohlfeld, D. Hofmann, T. Sowiński, and M. A. Sentef, Quantum walk versus classical wave: Distinguishing ground states of quantum magnets by spacetime dynamics, Physical Review B 102 (2), 024440 (2020).

G. Carleo, K. Choo, D. Hofmann, J. E. T. Smith, T. Westerhout, F. Alet, E. J. Davis, S. Efthymiou, I. Glasser, S.-H. Lin, M. Mauri, G. Mazzola, C. B. Mendl, E. van Nieuwenburg, O. O’Reilly, H. Théveniaut, G. Torlai, F. Vicentini, and A. Wietek, NetKet: A machine learning toolkit for many-body quantum systems, SoftwareX 10, 100311 (2019).

D. Hofmann, Neural quantum state methods for simulating quantum many-body systems, PhD Thesis, Universität Hamburg, Hamburg, 2023.

D. Hofmann, Laser Control of Topological Polaritons, Master's Thesis, Universität Hamburg, Hamburg, 2018.