English

Stabilizer Circuits, Quadratic Forms, and Computing Matrix Rank

Computational Complexity 2019-04-09 v2

Abstract

We show that a form of strong simulation for nn-qubit quantum stabilizer circuits CC is computable in O(s+nω)O(s + n^\omega) time, where ω\omega is the exponent of matrix multiplication. Solution counting for quadratic forms over F2\mathbb{F}_2 is also placed into O(nω)O(n^\omega) time. This improves previous O(n3)O(n^3) bounds. Our methods in fact show an O(n2)O(n^2)-time reduction from matrix rank over F2\mathbb{F}_2 to computing p=  0n    C    0n  2p = |\langle \; 0^n \;|\; C \;|\; 0^n \;\rangle|^2 (hence also to solution counting) and a converse reduction that is O(s+n2)O(s + n^2) except for matrix multiplications used to decide whether p>0p > 0. The current best-known worst-case time for matrix rank is O(nω)O(n^{\omega}) over F2\mathbb{F}_2, indeed over any field, while ω\omega is currently upper-bounded by 2.37282.3728\dots Our methods draw on properties of classical quadratic forms over Z4\mathbb{Z}_4. We study possible distributions of Feynman paths in the circuits and prove that the differences in +1+1 vs. 1-1 counts and +i+i vs. i-i counts are always 00 or a power of 22. Further properties of quantum graph states and connections to graph theory are discussed.

Cite

@article{arxiv.1904.00101,
  title  = {Stabilizer Circuits, Quadratic Forms, and Computing Matrix Rank},
  author = {Chaowen Guan and Kenneth W. Regan},
  journal= {arXiv preprint arXiv:1904.00101},
  year   = {2019}
}

Comments

Main change is to conclusion section: more information about relation to matroids and the generalized Tutte polynomial

R2 v1 2026-06-23T08:23:46.325Z