Regensburg 2025 – wissenschaftliches Programm

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TT: Fachverband Tiefe Temperaturen

TT 17: Correlated Electrons: Method Development

TT 17.3: Vortrag

Dienstag, 18. März 2025, 10:00–10:15, H33

Neural Quantum States as Dynamical Mean Field Theory solvers — •Jonas B. Rigo¹, Wladislaw Krinitsin^1,2, and Markus Schmitt^1,2 — ¹Forschungszentrum Jülich GmbH, Peter Grünberg Institute, Quantum Control, 52425 Jülich, Germany — ²University of Regensburg

Neural Quantum Sates (NQS) constitute a variational wave function ansatz, that can provably efficiently represent even highly entangled quantum many-body states. Beyond their representative power, NQS inherit the speed of modern neural networks (NN) and equally profit from the enormous development that NNs have recently received. In this work we show that NQS can efficiently find the ground state of quantum impurity models with large baths, allowing us to compute high quality real-frequency, zero-temperature Green's functions by means of a Krylov-like method. We demonstrate the capability of this approach and its potential as dynamical mean-field theory (DMFT) solver at the example of the Bethe lattice and other benchmarks.

Keywords: Neural Quantum States; Dynamical Mean Field Theory; Hund's Metals; Variational Monte Carlo; Green's function methods