A structure-aware transformer trained on 3-14 qubit systems predicts Trotter orderings for 16-20 qubit 1D Heisenberg Hamiltonians with a mean fidelity gap of 0.00115 to the best of 24 candidates.
Hastings, Robin Kothari, and Guang Hao Low
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Empirical scaling study reports VQS requires shallower circuits than Trotterization for time evolution as system size and simulation time grow.
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Structure-Aware Transformers for Learning Near-Optimal Trotter Orderings with System-Size Generalization in 1D Heisenberg Hamiltonians
A structure-aware transformer trained on 3-14 qubit systems predicts Trotter orderings for 16-20 qubit 1D Heisenberg Hamiltonians with a mean fidelity gap of 0.00115 to the best of 24 candidates.
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Performance and scaling analysis of variational quantum simulation
Empirical scaling study reports VQS requires shallower circuits than Trotterization for time evolution as system size and simulation time grow.