Accessing scrambling using matrix product operators

Scrambling, a process in which quantum information spreads over a complex quantum system, becoming inaccessible to simple probes, occurs in generic chaotic quantum many-body systems, ranging from spin chains to metals and even to black holes. Scrambling can be measured using out-of-time-ordered corr...

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Veröffentlicht in:Nature physics 2020-02, Vol.16 (2), p.199-204
Hauptverfasser: Xu, Shenglong, Swingle, Brian
Format: Artikel
Sprache:eng
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Zusammenfassung:Scrambling, a process in which quantum information spreads over a complex quantum system, becoming inaccessible to simple probes, occurs in generic chaotic quantum many-body systems, ranging from spin chains to metals and even to black holes. Scrambling can be measured using out-of-time-ordered correlators (OTOCs), which are closely tied to the growth of Heisenberg operators. We present a general method to calculate OTOCs of local operators in one-dimensional systems based on approximating Heisenberg operators as matrix product operators (MPOs). Contrary to the common belief that such tensor network methods work only at early times, we show that the entire early growth region of the OTOC can be captured using an MPO approximation with modest bond dimension. We analytically establish the goodness of the approximation by showing that, if an appropriate OTOC is close to its initial value, then the associated Heisenberg operator has low entanglement across a given cut. We use the method to study scrambling in a chaotic spin chain with 201 sites. On the basis of these data and previous results, we conjecture a universal form for the dynamics of the OTOC near the wavefront. We show that this form collapses the chaotic spin chain data over more than 15 orders of magnitude. A general method is proposed to calculate the out-of-time-ordered correlators (OTOCs) in one-dimensional systems. Motivated by the results obtained from its application to various systems, a universal form for the dynamics of OTOCs is conjectured.
ISSN:1745-2473
1745-2481
DOI:10.1038/s41567-019-0712-4