1. Stochastic renormalization group and gradient flow
- Author
-
Andrea Carosso
- Subjects
High Energy Physics - Theory ,Nuclear and High Energy Physics ,Monte Carlo method ,FOS: Physical sciences ,01 natural sciences ,symbols.namesake ,High Energy Physics - Lattice ,0103 physical sciences ,Effective field theory ,Renormalization Group ,lcsh:Nuclear and particle physics. Atomic energy. Radioactivity ,Statistical physics ,010306 general physics ,Scaling ,Physics ,Stochastic Processes ,Lattice Quantum Field Theory ,010308 nuclear & particles physics ,Stochastic process ,High Energy Physics - Lattice (hep-lat) ,Renormalization group ,High Energy Physics - Theory (hep-th) ,Boltzmann constant ,symbols ,lcsh:QC770-798 ,Markov property ,Balanced flow - Abstract
A non-perturbative and continuous definition of RG transformations as stochastic processes is proposed, inspired by the observation that the functional RG equations for effective Boltzmann factors may be interpreted as Fokker-Planck equations. The result implies a new approach to Monte Carlo RG that is amenable to lattice simulation. Long-distance correlations of the effective theory are shown to approach gradient-flowed correlations, which are simpler to measure. The Markov property of the stochastic RG transformation implies an RG scaling formula which allows for the measurement of anomalous dimensions when transcribed into gradient flow expectation values., 18 pages
- Published
- 2020