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Critical dynamics within the real-time fRG approach
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abstract
The Schwinger-Keldysh functional renormalization group (fRG) developed in [1] is employed to investigate critical dynamics related to a second-order phase transition. The effective action of model A is expanded to the order of $O(\partial^2)$ in the derivative expansion for the $O(N)$ symmetry. By solving the fixed-point equations of effective potential and wave function, we obtain static and dynamic critical exponents for different values of the spatial dimension $d$ and the field component number $N$. It is found that one has $z \geq 2$ in the whole range of $2\leq d\leq 4$ for the case of $N=1$, while in the case of $N=4$ the dynamic critical exponent turns to $z < 2$ when the dimension approach towards $d=2$.
Forward citations
Cited by 2 Pith papers
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Solving Functional Renormalization Group Equations with Neural Networks
A neural network that learns fRG flows from the equation residual, with a large-N analytic baseline, matches finite-difference and discontinuous-Galerkin solvers for O(N) models.
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Critical fluid dynamics in two and three dimensions
Direct numerical simulations of stochastic model H give a dynamic critical exponent z ≈ 3 in 3D and z ≈ 2 in 2D, with a crossover from mean-field z = 4 controlled by the renormalized shear viscosity.
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