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quant-ph2026

Learning Low-Energy Subspace Overlaps in Many-Body Systems with Measurement-Based and Coherent Quantum Strategies

Shamminuj Aktar, Rishabh Bhardwaj, Tanmoy Bhattacharya +1

Predicting the overlap of quantum states with specified low-energy subspaces is a key diagnostic for quantum many-body dynamics, with direct applications in state preparation, subs…

quant-ph2026

The Quantum Hamiltonian Analysis Toolkit: Lowering the Barrier to Quantum Computing with Hamiltonians

Brendan K. Krueger, Stephan Eidenbenz, Shamminuj Aktar +8

We present the Quantum Hamiltonian Analysis Toolkit (QHAT), a newly developed application that provides a user-friendly interface for studying Hamiltonians and performing Hamiltoni…

quant-ph2026

Structure-Aware Transformers for Learning Near-Optimal Trotter Orderings with System-Size Generalization in 1D Heisenberg Hamiltonians

Shamminuj Aktar, Reuben Tate, Stephan Eidenbenz

Trotterization is a standard approach for simulating quantum time evolution on quantum computers, where the Hamiltonian is split into local terms and each term is applied in sequen…

quant-ph2026

An Analysis of Commutation-Based Trotter Ordering Strategies on Heisenberg-Style Hamiltonians

Reuben Tate, Shamminuj Aktar, Stephan Eidenbenz

Trotterization is a technique that allows one to approximate a time evolution of a Hamiltonian by repeatedly evolving the individual terms of the Hamiltonian one-at-a-time for smal…

quant-ph2025

Quantum Data Learning of Topological-to-Ferromagnetic Phase Transitions in the 2+1D Toric Code Loop Gas Model

Shamminuj Aktar, Rishabh Bhardwaj, Andreas Bärtschi +2

Quantum data learning (QDL) provides a framework for extracting physical insights directly from quantum states, bypassing the need for any identification of the classical observabl…

quant-ph2024

Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation

Shamminuj Aktar, Andreas Bärtschi, Diane Oyen +2

Parameterized quantum circuits (PQCs) are fundamental to quantum machine learning (QML), quantum optimization, and variational quantum algorithms (VQAs). The expressibility of PQCs…