Efficient Microcanonical Histogram Analysis and Application to Peptide Aggregation

Abstract

A novel approach designed to directly estimate microcanonical quantities from energy histograms is proposed, which enables the immediate systematic identification and classification of phase transitions in physical systems of any size by means of the recently introduced generalized microcanonical inflection-point analysis method. The application to the aggregation problem of GNNQQNY heptapeptides, for which the entire transition sequence is revealed, shows the power of this promising method.

arXiv comment6 pages, 2 figures

References in corpus (13)

• An efficient, multiple range random walk algorithm to calculate the density of states
• Exchange Monte Carlo Method and Application to Spin Glass Simulations
• Simulated Tempering: A New Monte Carlo Scheme
• Multicanonical Ensemble: A New Approach to Simulate First-order Phase Transitions
• Determining the density of states for classical statistical models: A random walk algorithm to produce a flat histogram
• Microcanonical Analyses of Peptide Aggregation Processes
• Thermodynamics of alpha- and beta-structure formation in proteins
• Classification of Phase Transitions by Microcanonical Inflection-Point Analysis
• Evidence for additional third-order transitions in the two-dimensional Ising model
• Topological Theory of Phase Transitions
• Microcanonical characterization of first-order phase transitions in a generalized model for aggregation
• The Geometric Theory of Phase Transitions
• Secondary-Structure Phase Formation for Semifelxible Polymers by Bifurcation in Hyperphase Space