A hybrid optimization strategy using classical pre-compilation, iterative extrapolation, and noise-aware quantum refinement achieves orders-of-magnitude gains in fidelity for state preparation in analog simulators with programmable long-range interactions.
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quant-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Structure-aware VQE ansatze for long-range Ising models cut required circuit layers by 2.5x to 3.8x in non-local regimes while two-qubit gate counts scale quadratically with system size, consistent with the number of Hamiltonian terms.
citing papers explorer
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Programming long-range interactions in analog quantum simulators
A hybrid optimization strategy using classical pre-compilation, iterative extrapolation, and noise-aware quantum refinement achieves orders-of-magnitude gains in fidelity for state preparation in analog simulators with programmable long-range interactions.
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Scaling of Quantum Resources for Simulating a Long-Range System
Structure-aware VQE ansatze for long-range Ising models cut required circuit layers by 2.5x to 3.8x in non-local regimes while two-qubit gate counts scale quadratically with system size, consistent with the number of Hamiltonian terms.