We calculate the density of states of a binary Lennard-Jones glass using a recently proposed Monte Carlo algorithm. Unlike traditional molecular simulation approaches, the algorithm samples distinct configurations according to self-consistent estimates of the density of states, thereby giving rise to uniform internal-energy histograms. The method is applied to simulate the equilibrium, low-temperature thermodynamic properties of a widely studied glass former consisting of a binary mixture of Lennard-Jones particles. We show how a density-of-states algorithm can be combined with particle identity swaps and configurational bias techniques to study that system. Results are presented for the energy and entropy below the mode coupling temperature.
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