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版本更新 · v4arXiv:2510.16420

Exact Quantum Circuit Optimization is co-NQP-hard

Adam Husted Kjelstrøm, Andreas Pavlogiannis, Jaco van de Pol

原文摘要

As quantum computing resources remain scarce and error rates high, minimizing the resource consumption of quantum circuits is essential for achieving practical quantum advantage. Here we consider the natural problem of, given a circuit $C$, computing a circuit $C'$ that behaves equivalently on a desired subspace, and that minimizes a quantum resource type, expressed as the count or depth of (i) all gates, or (ii) non-Clifford gates, or (iii) superposition gates, or (iv) entanglement gates. We show that, when $C$ is expressed over any gate-set that can implement the H and TOF gates exactly, a standard property of approximately universal gate-sets, each of the above optimization problems is hard for co-NQP, and hence outside the Polynomial Hierarchy, unless the Polynomial Hierarchy collapses. This complements a recent result of Van de Wetering and Amy (arXiv, 2023) which establishes an NP-hardness lower bound when equivalence is over the full state space, and tightens the gap to the corresponding $\text{NP}^\text{NQP}$ upper bound known for cases (i)-(iii) over Clifford+T and (i)-(iv) over H+TOF circuits. Our result also generalizes a result by Tanaka (Int. J. Quantum Inf., 2010) to other gate-sets and quantum resources.

quant-ph · cs.CC

新论文 · v1arXiv:2611.04381

On the Hardness of Approximate Quantum Circuit Membership and Optimization

Adam Husted Kjelstrøm, Jaco van de Pol, Andreas Pavlogiannis

原文摘要

Quantum circuit optimization is an indispensable component of the quantum software stack, used to reduce noise, maximize performance, alleviate costs of quantum error correction, or target specific hardware. A related problem is approximate membership: for a fixed set of unitaries $S$, decide whether a given circuit $C$ is within distance $\varepsilon$ of a unitary in $S$ under some metric $m$. Membership is a special case of optimization, where $S$ is a set of unitaries implementable at no cost (e.g., with noise-minimal circuits, or without magic states). Janzing, Wocjan, and Beth (Int. J. Quantum Inf., 2005) showed that, for the operator metric, the case $S=\{I\}$ (approximate identity) is QMA-complete when $C$ is promised to be either close to the identity or far from it. We generalize this setting in three directions: (i) promise-free inputs, (ii) besides $S=\{I\}$, sets $S$ containing only Clifford unitaries, or only generalized permutation matrices (i.e., no superposition), and (iii) the trace-based, spectral, and operator metrics. We show that, in all cases, approximate membership is PP-hard for wide ranges of $\varepsilon$, provided $C$'s gate-set can implement Clifford+T, as the gate-sets of standard hardware do. If $S=\{I\}$, or if $S$ contains only generalized permutation matrices, $I\in S$, and $m$ is a trace-based distance, PP-hardness holds for all non-trivial $\varepsilon$. If $S=\{I\}$ and $m$ is a trace-based distance, PP-hardness holds even for circuits over classical-reversible gate-sets. Our results indicate that approximate membership is harder over promise-free inputs than the QMA-complete promise version, and that this hardness persists across quantum resources (any gates, non-Clifford, superposition) and distance metrics. They directly imply PP-hardness of circuit optimization when minimizing total, non-Clifford, or superposition gate depth or count.

quant-ph · cs.CC