English

Quantum Detection of Recurrent Dynamics

Quantum Physics 2024-12-24 v2 Mathematical Physics math.MP

Abstract

Quantum dynamics that explore an unexpectedly small fraction of Hilbert space is inherently interesting. Integrable systems, quantum scars, MBL, hidden tensor structures, and systems with gauge symmetries are examples. Beyond dimension and volume, spectral features such as an O(1)O(1)-density of periodic eigenvalues, or other spectral features, can also imply observable recurrence. Low volume dynamics will recur near its initial state ψ0| \psi_0\rangle more rapidly, i.e. Ukψ0ψ0<ϵ\lVert\mathrm{U}^k | \psi_0\rangle - | \psi_0\rangle \rVert < \epsilon, is more likely to occur for modest values of kk, when the (forward) orbit closure({Uk}k=1,2,)\operatorname{closure}(\{\mathrm{U}^k\}_{k=1,2,\dots}) is of relatively low dimension dd and relatively small dd-volume. We describe simple quantum algorithms to detect such approximate recurrence. Applications include detection of certain cases of hidden tensor factorizations UV(U1Un)V\mathrm{U} \cong V^\dagger(\mathrm{U}_1\otimes \cdots \otimes \mathrm{U}_n)V. "Hidden" refers to an unknown conjugation, e.g. U1UvV(U1Un)V\mathrm{U}_1 \otimes \cdots \otimes \mathrm{U}_v \rightarrow V^\dagger(\mathrm{U}_1 \otimes \cdots \otimes \mathrm{U}_n)V, which will obscure the low-volume nature of the dynamics. Hidden tensor structures have been observed to emerge both in a high energy context of operator-level spontaneous symmetry breaking [FSZ21a, FSZ21b, FSZ21c, SZBF23], and at the opposite end of the intellectual world in linguistics [Smo09, MLDS19]. We collect some observations on the computational difficulty of locating these structures and detecting related spectral information. A technical result, Appendix A, is that the language describing unitary circuits with no spectral gap (NUSG) around 1 is QMA-complete. Appendix B connects the Kolmogorov-Arnold representation theorem to hidden tensor structures.

Keywords

Cite

@article{arxiv.2407.16055,
  title  = {Quantum Detection of Recurrent Dynamics},
  author = {Michael H. Freedman},
  journal= {arXiv preprint arXiv:2407.16055},
  year   = {2024}
}
R2 v1 2026-06-28T17:50:12.525Z