  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 intensive variables as control parameters, because they are not
independent and cannot account for the system size. When the range of the
interactions is comparable with the size of the system, however, these
variables are not truly intensive and may become independent, so equilibrium
states defined by the values of these parameters may exist. Here, we derive a
Monte Carlo algorithm for the unconstrained ensemble and show that simulations
can be performed using chemical potential, pressure, and temperature as control
parameters. We illustrate the algorithm by applying it to physical systems
where either the system has long-range interactions or is confined by external
conditions. The method opens up a new avenue for the simulation of completely
open systems exchanging heat, work, and matter with the environment.

Statistical Mechanics