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Exponentially Reduced Circuit Depths Using Trotter Error Mitigation
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Exponentially Reduced Circuit Depths Using Trotter Error Mitigation
abstract
Product formulae are a popular class of digital quantum simulation algorithms due to their conceptual simplicity, low overhead, and performance which often exceeds theoretical expectations. Recently, Richardson extrapolation and polynomial interpolation have been proposed to mitigate the Trotter error incurred by use of these formulae. This work provides an improved, rigorous analysis of these techniques for the task of calculating time-evolved expectation values. We demonstrate that, to achieve error $\epsilon$ in a simulation of time $T$ using a $p^\text{th}$-order product formula with extrapolation, circuits depths of $O\left(T^{1+1/p} \textrm{polylog}(1/\epsilon)\right)$ are sufficient -- an exponential improvement in the precision over product formulae alone. Furthermore, we achieve commutator scaling, improve the complexity with $T$, and do not require fractional implementations of Trotter steps. Our results provide a more accurate characterisation of the algorithmic error mitigation techniques currently proposed to reduce Trotter error.
Forward citations
Cited by 3 Pith papers
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Optimal Lower Bounds for Hamiltonian Simulation
There exist simple weighted-local Hamiltonians for which quantum simulation requires Ω(min over K of (Kt + t²λ_K²/ε)) gates — exactly matching the composite qDRIFT algorithm's cost.
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Circuit Depth Reduction of One-Ancilla Quantum Differential Equation Solver via Extrapolation
Classical step-size extrapolation reduces the maximum single-run circuit depth of a one-ancilla quantum ODE solver from O(1/ε) to O(polylog(1/ε)) without adding ancillae.
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Unbiased Hamiltonian Simulation by Reversing Trotter Error Dynamics
PTER removes Trotter errors in quantum Hamiltonian simulation via quasi-probabilistic reversal of the error dynamics, producing unbiased results with constant overhead.
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