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Stochastic renormalization group and gradient flow
- Source :
- Journal of High Energy Physics, Journal of High Energy Physics, Vol 2020, Iss 1, Pp 1-21 (2020)
- Publication Year :
- 2020
- Publisher :
- Springer, 2020.
-
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.<br />18 pages
- 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
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Journal of High Energy Physics
- Accession number :
- edsair.doi.dedup.....e0bdb4b4e2dbf68d2c9a618b73629d8d