Renormalization group flow as optimal transport

Renormalization Multigrid (RMG): Statistically Optimal Renormalization Group Flow and Coarse-to-Fine Monte Carlo Acceleration

New renormalization-group algorithms are developed with adaptive representations of the renormalized system which automatically express only signi cant interactions. As the amount of statistics grows, more interactions enter, thereby systematically reducing the truncation error. This allows statistically optimal calculation of thermodynamic limits, in the sense that it achieves accuracy " in ju...

Renormalization Group Renormalization Group

Renormalization Group Flow Equation at Finite Density

For the linear sigma model with quarks we derive renormalization group flow equations for finite temperature and finite baryon density using the heat kernel cutoff. At zero temperature we evolve the effective potential to the Fermi momentum and compare the solutions of the full evolution equation with those in the mean field approximation. We find a first order phase transition either from a ma...

Renormalization Group Flow in Algebraic Holography

The remarkable scaling properties of the AdSCFT correspondence[5] have been proven extremely useful as a calculational device for the scaling behaviour of holographic pairs, known as the Holographic Renormalization Group (RG). In this communication, the aforementioned scaling properties will be studied in a somewhat different context. We’ll adopt the formalism of Local Quantum Physics[1], in te...

On Renormalization Group Flow In Matrix Model

The renormalization group flow recently found by Brézin and Zinn-Justin by integrating out redundant entries of the (N+1)×(N+1) Hermitian random matrix is studied. By introducing explicitly the RG flow parameter, and adding suitable counter terms to the matrix potential of the one matrix model, we deduce some interesting properties of the RG trajectories. In particular, the string equation for ...