Utility-Scale Quantum State Preparation: Classical Training using Pauli Path Simulation

• URL: http://arxiv.org/abs/2510.02428v1
• Date: Thu, 02 Oct 2025 18:00:00 GMT
• Title: Utility-Scale Quantum State Preparation: Classical Training using Pauli Path Simulation
• Authors: Cheng-Ju Lin, Hrant Gharibyan, Vincent P. Su,
• Abstract summary: We use Pauli Path simulation to variationally obtain parametrized circuits for preparing ground states of quantum many-body Hamiltonians.<n>We benchmark the Pauli Path simulation results against exact ground-state energies when available, and against density-matrix renormalization group calculations otherwise.
• Score: 0.19116784879310023
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We use Pauli Path simulation to variationally obtain parametrized circuits for preparing ground states of various quantum many-body Hamiltonians. These include the quantum Ising model in one dimension, in two dimensions on square and heavy-hex lattices, and the Kitaev honeycomb model, all at system sizes of one hundred qubits or more, beyond the reach of exact state-vector simulation, thereby reaching utility scale. We benchmark the Pauli Path simulation results against exact ground-state energies when available, and against density-matrix renormalization group calculations otherwise, finding strong agreement. To further assess the quality of the variational states, we evaluate the magnetization in the x and z directions for the quantum Ising models and compute the topological entanglement entropy for the Kitaev honeycomb model. Finally, we prepare approximate ground states of the Kitaev honeycomb model with 48 qubits, in both the gapped and gapless regimes, on Quantinuum's System Model H2 quantum computer using parametrized circuits obtained from Pauli Path simulation. We achieve a relative energy error of approximately $5\%$ without error mitigation and demonstrate the braiding of Abelian anyons on the quantum device beyond fixed-point models.

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