Quadratic Sums-of-Powers for Fixed-Parameter Tractable Quantum-Circuit Simulation

2026-05-28

AI Summary

This work addresses the computational hardness of strongly simulating quantum circuits—specifically, computing output amplitudes—which is generally intractable and highly dependent on the structure of the path-variable graph. The authors reformulate amplitude computation as a weighted counting problem over path variables and establish, for the first time, that the rank-width of this graph serves as the key parameter governing simulation complexity. Building on this insight, they devise a fixed-parameter tractable algorithm whose runtime scales polynomially with circuit size and exponentially only in the rank-width. This approach unifies and generalizes existing techniques such as binary decision diagrams and tensor networks. Notably, on circuit families containing Hadamard and diagonal gates—including Clifford+T circuits—the proposed algorithm substantially outperforms current state-of-the-art methods.

Abstract

Strongly simulating a quantum circuit, that is, computing an output amplitude, amounts to summing the circuit's Feynman paths, a weighted count over assignments to the Boolean ``path'' variables. The circuit's gates induce correlations among these variables, forming a graph whose structure determines the hardness of the simulation task. This sum-of-powers viewpoint underlies recent simulators built on knowledge-representation tools from artificial intelligence, namely binary decision diagrams and weighted model counting. We show that the structural quantity most accurately governing the difficulty is the rank-width of the path-variable graph, and we give an algorithm that evaluates the amplitude in time that is exponential only in this rank-width and polynomial in the circuit size. Rank-width can be far smaller than the widths that control competing methods: as corollaries, our algorithm reproduces a recent decision-diagram simulation breakthrough as a special case and matches the Markov--Shi tensor-network contraction bound. To complement this, we exhibit circuit families on which our algorithm provably beats both competing methods. The new method applies to every circuit built from Hadamard and diagonal gates, in particular to circuits over Clifford+T. In practical terms, general-purpose decision-diagram and model-counting tools can serve as the workhorse, with our specialized algorithm dispatched to exploit a small rank-width of the associated graph when it is present.

Problem

• quantum circuit simulation
• strong simulation
• rank-width
• sum-of-powers
• fixed-parameter tractability

Innovation

• rank-width
• quantum circuit simulation
• sum-of-powers
• fixed-parameter tractability
• weighted model counting