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Probabilistic Approximate Optimization: A New Variational Monte Carlo Algorithm
Abdelrahman S. Abdelrahman, Shuvro Chowdhury, Flaviano Morone, Kerem Y. Camsari
https://arxiv.org/abs/2507.07420

Probabilistic Approximate Optimization: A New Variational Monte Carlo Algorithm
We introduce a generalized \textit{Probabilistic Approximate Optimization Algorithm (PAOA)}, a classical variational Monte Carlo framework that extends and formalizes prior work by Weitz \textit{et al.}~\cite{Combes_2023}, enabling parameterized and fast sampling on present-day Ising machines and probabilistic computers. PAOA operates by iteratively modifying the couplings of a network of binary stochastic units, guided by cost evaluations from independent samples. We establish a direct corresp…

Dynamic modes of active Potts models with factorizable numbers of states
Hiroshi Noguchi
https://arxiv.org/abs/2506.23687 https://arx…

Dynamic modes of active Potts models with factorizable numbers of states
We studied the long-term nonequilibrium dynamics of q-state Potts models with q = 4, 5, 6, and 8 using Monte Carlo simulations on a two-dimensional square lattice. When the contact energies between the nearest neighbors for the standard Potts models are used, cyclic changes in the q homogeneous phases and q-state coexisting wave mode appear at low and high flipping energies, respectively, for all values of q. However, for a factorizable q value, dynamic modes with skipping states emerge, depend…