Out-of-equilibrium simulations with open-to-periodic boundary switching plus a tailored stochastic normalizing flow enable efficient topology sampling in the continuum limit of four-dimensional SU(3) Yang-Mills theory.
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Exhaustive ε-dense paths in d>1 thermo state spaces have length L ≥ C ε^{1-d}, implying excess work Ω(ε^{2(1-d)}/τ) or time Ω(ε^{2(1-d)}) at fixed budget when friction ζ dominates g.
In linear response for weakly driven processes, the optimal protocol under constraints on the derivative is linear (constant speed), with minimal work depending only on the integrated relaxation function.
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Scaling flow-based approaches for topology sampling in $\mathrm{SU}(3)$ gauge theory
Out-of-equilibrium simulations with open-to-periodic boundary switching plus a tailored stochastic normalizing flow enable efficient topology sampling in the continuum limit of four-dimensional SU(3) Yang-Mills theory.
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Finite-resolution exhaustive traversal of thermodynamic state spaces has divergent thermodynamic length
Exhaustive ε-dense paths in d>1 thermo state spaces have length L ≥ C ε^{1-d}, implying excess work Ω(ε^{2(1-d)}/τ) or time Ω(ε^{2(1-d)}) at fixed budget when friction ζ dominates g.
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Linear optimal protocol for physical constraints in weakly driven processes
In linear response for weakly driven processes, the optimal protocol under constraints on the derivative is linear (constant speed), with minimal work depending only on the integrated relaxation function.