Quantum computing (QC) is a new paradigm offering the potential of exponential speedups over classical computing for certain computational problems. Each additional qubit doubles the size of the computational state space available to a QC algorithm. This exponential scaling underlies QC’s power, but today’s Noisy IntermediateScale Quantum (NISQ) devices face significant engineering challenges in scalability. The set of quantum circuits that can be reliably run on NISQ devices is limited by their noisy operations and low qubit counts. This paper introduces CutQC, a scalable hybrid computing approach that combines classical computers and quantum computers to enable evaluation of quantum circuits that cannot be run on classical or quantum computers alone. CutQC cuts large quantum circuits into smaller subcircuits, allowing them to be executed on smaller quantum devices. Classical postprocessing can then reconstruct the output of the original circuit. This approach offers significant runtime speedup compared with the only viable current alternative  purely classical simulations  and demonstrates evaluation of quantum circuits that are larger than the limit of QC or classical simulation. Furthermore, in realsystem runs, CutQC achieves much higher quantum circuit evaluation fidelity using small prototype quantum computers than the stateoftheart large NISQ devices achieve. Overall, this hybridmore »
Efficient classical simulation of noisy random quantum circuits in one dimension
Understanding the computational power of noisy intermediatescale quantum (NISQ) devices is of both fundamental and practical importance to quantum information science. Here, we address the question of whether erroruncorrected noisy quantum computers can provide computational advantage over classical computers. Specifically, we study noisy random circuit sampling in one dimension (or 1D noisy RCS) as a simple model for exploring the effects of noise on the computational power of a noisy quantum device. In particular, we simulate the realtime dynamics of 1D noisy random quantum circuits via matrix product operators (MPOs) and characterize the computational power of the 1D noisy quantum system by using a metric we call MPO entanglement entropy. The latter metric is chosen because it determines the cost of classical MPO simulation. We numerically demonstrate that for the twoqubit gate error rates we considered, there exists a characteristic system size above which adding more qubits does not bring about an exponential growth of the cost of classical MPO simulation of 1D noisy systems. Specifically, we show that above the characteristic system size, there is an optimal circuit depth, independent of the system size, where the MPO entanglement entropy is maximized. Most importantly, the maximum achievable MPO entanglement entropy more »
 Publication Date:
 NSFPAR ID:
 10308910
 Journal Name:
 Quantum
 Volume:
 4
 ISSN:
 2521327X
 Sponsoring Org:
 National Science Foundation
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