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Monte Carlo simulation using Stochastic Approximation Monte Carlo with a Dynamical update factor

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Monte Carlo

A library for simulations in statistical mechanics using Monte Carlo algorithms. This code is architected for quickly testing changes to algorithms, and for comparing different algorithms accross a variety of different physical systems.

This code features a wide variety of Monte Carlo algorithms, including ordinary canonical Monte Carlo, Wang Landau (WL), $1/t$-Wang Landau ($1/t$-WL), Stochastic Approximation Monte Carlo (SAMC), and Statistical Association with Dynamic update factor (SAD), as well as a new Zeno's Monte Carlo algorithm.

This code also features a relatively broad set of relatively simple systems upon which algorithms can be tested. The code supports three simple materials with periodic boundary conditions: the Ising model, the hard-sphere fluid, and the purely-repulsive Weeks-Chandler-Andersen fluid. It supports simulation of isolated clusters of Lennard-Jones atoms. Finally, the code supports a few artificial test systems for which we have analytic densities of states.

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Monte Carlo simulation using Stochastic Approximation Monte Carlo with a Dynamical update factor

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