<ul><li>Out-of-Time Ordered Correlators (OTOCs) are commonly used to study information scrambling in quantum systems.</li><li>Directly computing OTOCs with classical computers is computationally expensive.</li><li>A study explores the use of classical kernel methods (KMs) to accurately learn OTOCs and related quantities of local one-dimensional quantum systems.</li><li>The proposed method can assist in evaluating OTOC functions of the parameterized quantum systems.</li></ul>

Learning out-of-time-ordered correlators with classical kernel methods

Discover more