New Approaches to Complexity via Quantum Graphs
Eric Culf, Arthur Mehta

TL;DR
This paper introduces the quantum graph clique problem, exploring its complexity across various quantum channels, revealing a rich hierarchy of classical and quantum complexity classes, and providing new insights into quantum graph problems.
Contribution
It defines and analyzes the quantum graph clique problem, establishing its complexity as QMA(2)-complete and comparing it with classical complexity classes, offering a novel perspective on quantum graph problems.
Findings
Quantum graph clique problem is QMA(2)-complete over all channels.
Restricted channel classes lead to NP and MA completeness.
Provides the first direct comparison of QMA(2), QMA, MA, and NP complexities.
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…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Complexity and Algorithms in Graphs · Computability, Logic, AI Algorithms
