npj Quantum Information · 2020 · 232 citations · 61 references
ComputingComputer SciencePhysicsComputational PhysicsQuantum ComputingQuantum MechanicsComputational Quantum MechanicsQuantum AlgorithmsQuantum CircuitsQuantum ComputationQuantum GatesQuantum SimulationCircuit Depth OptimizationCoherence TimeEnergy EigenvaluesHeisenberg ModelQuantum Circuit Depth ReductionQuantum Circuit SimulationQuantum Eigenvalue EstimationQuantum Simulation Algorithms
Abstract Trotterization-based, iterative approaches to quantum simulation (QS) are restricted to simulation times less than the coherence time of the quantum computer (QC), which limits their utility in the near term. Here, we present a hybrid quantum-classical algorithm, called variational fast forwarding (VFF), for decreasing the quantum circuit depth of QSs. VFF seeks an approximate diagonalization of a short-time simulation to enable longer-time simulations using a constant number of gates. Our error analysis provides two results: (1) the simulation error of VFF scales at worst linearly in the fast-forwarded simulation time, and (2) our cost function’s operational meaning as an upper bound on average-case simulation error provides a natural termination condition for VFF. We implement VFF for the Hubbard, Ising, and Heisenberg models on a simulator. In addition, we implement VFF on Rigetti’s QC to demonstrate simulation beyond the coherence time. Finally, we show how to estimate energy eigenvalues using VFF.
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