Author

Flore K. Kunst

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Preprint Aug 2026

Autoregressive Projective Quantum Monte Carlo: From a Hermitian to a Non-Hermitian Perspective

An autoregressive projective quantum Monte Carlo (PQMC) framework that leverages recurrent neural networks (RNNs) to guide the stochastic dynamics is introduced, demonstrating substantial improvements in accuracy compared to standard unguided PQMC, while retaining polynomial computational cost.

Lavoisier Wah, Remmy Zen, Flore K. Kunst · 1 citation

Preprint Jul 2026

Bridging Frustration and Non-Hermiticity via COMPASS: An Adaptive Biorthogonal Neural Quantum State Framework

This work demonstrates that gap frustration provides a quantitative shield against NH spectral instability, with the frustration gap setting a critical threshold for PT-symmetry breaking, and establishes that physically-informed ansatz selection is crucial for reliable NH simulations.

Lavoisier Wah, Flore K. Kunst, Mohamed Hibat-Allah · 3 citations · ⚡1