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QAOA for Max-Cut requires hundreds of qubits for quantum speed-up

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arxiv 1812.07589 v1 pith:VQUV73CO submitted 2018-12-18 quant-ph cs.PF

classification quant-phcs.PF
keywords quantumcomputersnoisyqubitsavailablecombinatorialdeviceseven
verification ladder T0 review T1 audit T2 compute T3 formal

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Computational quantum technologies are entering a new phase in which noisy intermediate-scale quantum computers are available, but are still too small to benefit from active error correction. Even with a finite coherence budget to invest in quantum information processing, noisy devices with about 50 qubits are expected to experimentally demonstrate quantum supremacy in the next few years. Defined in terms of artificial tasks, current proposals for quantum supremacy, even if successful, will not help to provide solutions to practical problems. Instead, we believe that future users of quantum computers are interested in actual applications and that noisy quantum devices may still provide value by approximately solving hard combinatorial problems via hybrid classical-quantum algorithms. To lower bound the size of quantum computers with practical utility, we perform realistic simulations of the Quantum Approximate Optimization Algorithm and conclude that quantum speedup will not be attainable, at least for a representative combinatorial problem, until several hundreds of qubits are available.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Effects of Quantum Noise on Quantum Approximate Optimization Algorithm

    quant-ph 2019-09 reject novelty 5.0 of 10

    For dephasing, bit-flip, and depolarizing noise on a 7-qubit Max-Cut QAOA, fidelity, cost, and gradients decay like (1-p)^(αN), and fitted optimal parameters stay close to noiseless values for Np<0.5.

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