Author

Mohamed Hibat-Allah

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#artificial intelligence Preprint Feb 2026

Graph-Theoretic Formulation of Hamiltonian and Ground-State Sign Structures in Heisenberg Antiferromagnets

We study Heisenberg antiferromagnets through a graph-theoretic representation of their Hamiltonians. In the computational basis of a fixed-magnetization sector, the Heisenberg Hamiltonian equals a constant minus the weighted Laplacian of a graph whose vertices are spin configurations and whose edges connect configurati...

Mahmud Ashraf Shamim, M. Raj, Mohamed Hibat-Allah et al. · 2 citations

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

Preprint Aug 2026

Quantum Geometric Tensor Preconditioning for Stable Training of Recurrent Neural Quantum States

This work shows that minSR can be stabilized through simple regularization techniques, enabling robust training of RNN-based NQS with only a few samples, and offers a promising pathway for using modern optimization techniques with autoregressive NQS to address open questions in quantum simulation.

Adi Attar, A. M. Aboussalah, Mohamed Hibat-Allah · 1 citation