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arXiv 2210.02474hep-thcond-mat.str-elquant-ph
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大 $q$ 与双重标度 SYK 模型中的 Krylov 复杂度

Krylov complexity in large-$q$ and double-scaled SYK model

Budhaditya Bhattacharjee, Pratik Nandy, Tanay Pathak

AI总结:

本文在大 $q$ 与双重标度 SYK 模型中计算 Lanczos 系数、Krylov 复杂度及高阶累积量,发现双重标度极限下搅乱时间趋零、增长超快。

摘要:

在两阶段极限下考虑 Sachdev–Ye–Kitaev(SYK)模型的大 $q$ 展开,我们计算了次领头阶的 Lanczos 系数、Krylov 复杂度以及更高阶 Krylov 累积量,同时纳入 $t/q$ 效应。Krylov 复杂度自然地描述分布的“大小”,而更高阶累积量编码更丰富的信息。我们进一步考察了无限温度下 SYK$_q$ 的双重标度极限,其中 $q\sim\sqrt{N}$。在此极限下,我们发现搅乱时间缩短为零,且 Lanczos 系数发散。Krylov 复杂度的增长呈现“超快”特征,此前曾猜想这与 de Sitter 空间中的搅乱有关。

英文摘要:

Considering the large-$q$ expansion of the Sachdev-Ye-Kitaev (SYK) model in the two-stage limit, we compute the Lanczos coefficients, Krylov complexity, and the higher Krylov cumulants in subleading order, along with the $t/q$ effects. The Krylov complexity naturally describes the "size" of the distribution, while the higher cumulants encode richer information. We further consider the double-scaled limit of SYK$_q$ at infinite temperature, where $q \sim \sqrt{N}$. In such a limit, we find that the scrambling time shrinks to zero, and the Lanczos coefficients diverge. The growth of Krylov complexity appears to be "hyperfast", which is previously conjectured to be associated with scrambling in de Sitter space.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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