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Finding self-similar behavior in quantum many-body dynamics via persistent homology

Daniel Spitz, Jürgen Berges, Markus K. Oberthaler, Anna Wienhard

2021SciPost Physics22 citationsDOIOpen Access PDF

Abstract

Inspired by topological data analysis techniques, we introduce persistent homology observables and apply them in a geometric analysis of the dynamics of quantum field theories. As a prototype application, we consider data from a classical-statistical simulation of a two-dimensional Bose gas far from equilibrium. We discover a continuous spectrum of dynamical scaling exponents, which provides a refined classification of nonequilibrium self-similar phenomena. A possible explanation of the underlying processes is provided in terms of mixing strong wave turbulence and anomalous vortex kinetics components in point clouds. We find that the persistent homology scaling exponents are inherently linked to the geometry of the system, as the derivation of a packing relation reveals. The approach opens new ways of analyzing quantum many-body dynamics in terms of robust topological structures beyond standard field theoretic techniques.

Topics & Concepts

Persistent homologyObservableStatistical physicsScalingQuantumTopological data analysisNon-equilibrium thermodynamicsPhysicsTopology (electrical circuits)Classical mechanicsTheoretical physicsMathematicsGeometryQuantum mechanicsAlgorithmCombinatoricsTopological and Geometric Data AnalysisAdvanced Neuroimaging Techniques and ApplicationsHomotopy and Cohomology in Algebraic Topology
Finding self-similar behavior in quantum many-body dynamics via persistent homology | Litcius