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arXiv · 2309.12887

New Approaches to Complexity via Quantum Graphs

Eric Culf·Arthur Mehta
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Abstract

Problems based on the structure of graphs -- for example finding cliques, independent sets, or colourings -- are of fundamental importance in classical complexity. Defining well-formulated decision problems for quantum graphs, which are an operator system generalisation of graphs, presents several technical challenges. Consequently, the connections between quantum graphs and complexity have been underexplored. In this work, we introduce and study the clique problem for quantum graphs. Our approach utilizes a well-known connection between quantum graphs and quantum channels. The inputs for our problems are presented as circuits inducing quantum channel, which implicitly determine a corresponding quantum graph. We show that, quantified over all channels, this problem is complete for QMA(2); in fact, it remains QMA(2)-complete when restricted to channels that are probabilistic mixtures of entanglement-breaking and partial trace channels. Quantified over a subset of entanglement-breaking channels, this problem becomes QMA-complete, and restricting further to deterministic or classical noisy channels gives rise to complete problems for NP and MA, respectively. In this way, we exhibit a classical complexity problem whose natural quantisation is QMA(2), rather than QMA, and provide the first problem that allows for a direct comparison of the classes QMA(2), QMA, MA, and NP by quantifying over increasingly larger families of instances. We use methods that are inspired by self-testing to provide a direct proof of QMA(2)-completeness, rather than reducing to a previously-studied complete problem. We also give a new proof of the celebrated reduction of QMA(k) to QMA(2). In parallel, we study a version of the closely-related independent set problem for quantum graphs, and provide preliminary evidence that it may be in general weaker in complexity, contrasting to the classical case.

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Eric Culf, Arthur Mehta. 2023-09-22. New Approaches to Complexity via Quantum Graphs. https://arxiv.org/abs/2309.12887

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