Population-dynamics method with a multicanonical feedback control

We present a new Monte Carlo algorithm that produces results of high accuracy with reduced simulational effort. Independent random walks are performed (concurrently or serially) in different, restricted ranges of energy, and the resultant density of states is modified continuously to produce locally flat histograms. This method permits us to directly access the free energy and entropy, is independent of temperature, and is efficient for the study of both 1st order and 2nd order phase transitions. It should also be useful for the study of complex systems with a rough energy landscape.

The glass transition is the freezing of a liquid into a solid state without evident structural order. Although glassy materials are well characterized experimentally, the existence of a phase transition into the glass state remains controversial. Here, we present numerical evidence for the existence of a novel first-order dynamical phase transition in atomistic models of structural glass formers. In contrast to equilibrium phase transitions, which occur in configuration space, this transition occurs in trajectory space, and it is controlled by variables that drive the system out of equilibrium. Coexistence is established between an ergodic phase with finite relaxation time and a nonergodic phase of immobile molecular configurations. Thus, we connect the glass transition to a true phase transition, offering the possibility of a unified picture of glassy phenomena.