Publication | Open Access
Quantum simulation via randomized product formulas: Low gate complexity with accuracy guarantees
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2020
Year
Quantum ScienceRandomized Product FormulasEngineeringQuantum ComputingPhysicsQuantum Optimization AlgorithmEntropyNatural SciencesQuantum SimulationQuantum InformationQuantum AlgorithmRandom Product FormulaRandom Product FormulasLow Gate ComplexityQuantum EntanglementQuantum Error CorrectionQuantum Algorithms
Quantum simulation has wide applications in quantum chemistry and physics. Recently, scientists have begun exploring the use of randomized methods for accelerating quantum simulation. Among them, a simple and powerful technique, called qDRIFT, is known to generate random product formulas for which the average quantum channel approximates the ideal evolution. This work provides a comprehensive analysis of a single realization of the random product formula produced by qDRIFT. The main results prove that a typical realization of the randomized product formula approximates the ideal unitary evolution up to a small diamond-norm error. The gate complexity is independent of the number of terms in the Hamiltonian, but it depends on the system size and the sum of the interaction strengths in the Hamiltonian. Remarkably, the same random evolution starting from an arbitrary, but fixed, input state yields a much shorter circuit suitable for that input state. If the observable is also fixed, the same random evolution provides an even shorter product formula. The proofs depend on concentration inequalities for vector and matrix martingales. Numerical experiments verify the theoretical predictions.