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We propose a new generalized-ensemble algorithm, which we refer to as the multibaric-multithermal Monte Carlo method. The multibaric-multithermal Monte Carlo simulations perform random walks widely both in volume space and in potential energy space. From only one simulation run, one can calculate isobaric-isothermal-ensemble averages at any pressure and any temperature. We test the effectiveness of this algorithm by applying it to the Lennard-Jones 12-6 potential system with 500 particles. It is found that a single simulation of the new method indeed gives accurate average quantities in isobaric-isothermal ensemble for a wide range of pressure and temperature.
The unconstrained ensemble describes completely open systems whose control parameters are chemical potential, pressure, and temperature. For macroscopic systems with short-range interactions, thermodynamics prevents the simultaneous use of these inte
We present a novel Ensemble Monte Carlo Growth method to sample the equilibrium thermodynamic properties of random chains. The method is based on the multicanonical technique of computing the density of states in the energy space. Such a quantity is
Population annealing is a recent addition to the arsenal of the practitioner in computer simulations in statistical physics and beyond that is found to deal well with systems with complex free-energy landscapes. Above all else, it promises to deliver
In simple ferromagnetic quantum Ising models characterized by an effective double-well energy landscape the characteristic tunneling time of path-integral Monte Carlo (PIMC) simulations has been shown to scale as the incoherent quantum-tunneling time
We use Monte Carlo simulations to study ${rm Ni Fe_2O_4}$ nanoparticles. Finite size and surface effects differentiate them from their bulk counterparts. A continuous version of the Wang-Landau algorithm is used to calculate the joint density of stat