| Abstrakt: |
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)-density of periodic eigenvalues, or other spectral features, can also imply observable recurrence. Low volume dynamics will recur near its initial state |ψ0〉 more rapidly, i.e. |Uk|ψ 0〉−|ψ0〉| < 휖, is more likely to occur for modest values of k, when the (forward) orbit closure({Uk} k=1,2,…) is of relatively low dimension d and relatively small d-volume. We describe simple quantum algorithms to detect such approximate recurrence. Applications include detection of certain cases of hidden tensor factorizations U≅V†(U 1 ⊗⋯ ⊗Un)V. “Hidden” refers to an unknown conjugation, e.g. U1 ⊗⋯ ⊗Uv → V†(U 1 ⊗⋯ ⊗Un)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 [M. Freedman and M. Shokrian-Zini, J. High Energy Phys. 2021 (2021) 140; M. Freedman and M. Shokrian-Zini, J. High Energy Phys. 2021 (2021) 102; M. Freedman and M. Shokrian-Zini, arXiv:2112.08613; M. Shokrian-Zini, A. R. Brown and M. Freedman, J. High Energy Phys. 2023 (2023) 82], and at the opposite end of the intellectual world in linguistics [P. Smolensky, Artif. Intell. 46(1–2) (1990) 159; R. T. McCoy, T. Linzen, E. Dunbar and P. Smolensky, RNNs implicitly implement tensor product representations, in The Seventh Int. Conf. Learning Representations (ICLR, 2019), pp. 1–22]. 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. [ABSTRACT FROM AUTHOR] |
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