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TT: Fachverband Tiefe Temperaturen
TT 23: Correlated Electrons – Poster I
TT 23.25: Poster
Montag, 9. März 2026, 18:00–20:00, P1
Investigating Non-Hermitian Dynamics in Neural Quantum States — •Mohammed Boky1,2 and Werner Dobrautz1,2,3,4 — 1Center for Scalable Data Analytics and Artificial Intelligence Dresden/Leipzig, 01069 Dresden, Germany — 2Technical University Dresden, 01069 Dresden, Germany — 3Center for Advanced Systems Understanding, 02826 Görlitz, Germany — 4Helmholtz-Zentrum Dresden-Rossendorf, 01328 Dresden, Germany
Both the Neural Quantum States (NQS) and the Transcorrelated (TC) method have proven to be impactful approaches in Ab Initio quantum chemistry and quantum many-body settings. The potential of combining these methods remains largely unexplored. In this work, the application and impact of the combination of these methods are explored with a focus on the computational cost.
The application of the similarity transform in the TC method yields non-Hermitian Hamiltonians. The optimization and impact of this non-Hermiticity on NQS dynamics pose both a great challenge and a source of unexplored possibilities to navigate physics with correlations that differ in magnitude.
In order to investigate both the impact and challenges of these methods, a study is done on a variety of different systems. These systems range from Ab Initio quantum chemistry problems such as hydrogen chains, to lattice models such as the non-Hermitian Transverse Field Ising and the Hubbard model.
Keywords: Neural Quantum States; Transcorrelated; Machine learning; non-Hermitian; Quantum Chemistry