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Quantum advantage for combinatorial optimization problems, Simplified

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arxiv 2212.12572 v1 pith:L2ONHQBA submitted 2022-12-23 quant-ph

classification quant-ph
keywords advantagecomputersoptimizationproblemsquantumapproximatingclassicalcombinatorial
verification ladder T0 review T1 audit T2 compute T3 formal
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We observe that fault-tolerant quantum computers have an optimal advantage over classical computers in approximating solutions to many NP optimization problems. This observation however gives nothing in practice.

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Cited by 3 Pith papers

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

  1. Approximability limits for bounded-degree max-LINSAT and implications for decoded quantum interferometry

    quant-ph 2026-06 unverdicted novelty 6.0 of 10

    Extends NP-hardness of exceeding r/q + O(1/sqrt(D)) for bounded-degree max-Ek-LINSAT(q,r) over F_q and shows quantum decoding is required for DQI to achieve the hardness-optimal 1/sqrt(D) scaling.

  2. Mind the gaps: The fraught road to quantum advantage

    quant-ph 2025-10 unverdicted novelty 4.0 of 10

    The authors identify four transitions needed to reach fault-tolerant application-scale quantum computing from current NISQ devices.

  3. Mind the gaps: The fraught road to quantum advantage

    quant-ph 2025-10 unverdicted novelty 3.0 of 10

    The paper identifies four key hurdles in the transition from NISQ to FASQ quantum computers and argues that targeting them will accelerate progress toward useful quantum advantage.

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