منابع مشابه
Multicanonical chain-growth algorithm.
We present a temperature-independent Monte Carlo method for the determination of the density of states of lattice proteins that combines the fast ground-state search strategy of the new pruned-enriched Rosenbluth chain-growth method and multicanonical reweighting for sampling the complete energy space. Since the density of states contains all energetic information of a statistical system, we ca...
متن کاملReplica-exchange multicanonical algorithm and multicanonical replica-exchange method for simulating systems with rough energy landscape
We propose two efficient algorithms for configurational sampling of systems with rough energy landscape. The first one is a new method for the determination of the multicanonical weight factor. In this method a short replica-exchange simulation is performed and the multicanonical weight factor is obtained by the multiple-histogram reweighting techniques. The second one is a further extension of...
متن کاملPrediction of Peptide Conformation by the Multicanonical Algorithm
We test the effectiveness of the multicanonical algorithm for the tertiary structure prediction of peptides and proteins. As a simple example we study Metenkephalin. The lowest-energy conformation obtained agrees with that determined by other methods such as Monte Carlo simulated annealing. But unlike to simulated annealing the relationship to the canonical ensemble remains exactly controlled. ...
متن کاملScaling properties of a parallel implementation of the multicanonical algorithm
The multicanonical method has been proven powerful for statistical investigations of lattice and offlattice systems throughout the last two decades. We discuss an intuitive but very efficient parallel implementation of this algorithm and analyze its scaling properties for discrete energy systems, namely the Ising model and the 8-state Potts model. The parallelization relies on independent equil...
متن کاملSearching for Rare Growth Factors Using Multicanonical Monte Carlo Methods
The growth factor of a matrix quantifies the amount of potential error growth possible when a linear system is solved using Gaussian elimination with row pivoting. While it is an easy matter [N. J. Higham and D. J. Higham, SIAM J. Matrix Anal. Appl., 10 (1989), pp. 155–164] to construct examples of n × n matrices having any growth factor up to the maximum of 2n−1, the weight of experience and a...
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ژورنال
عنوان ژورنال: Physical Review Letters
سال: 2003
ISSN: 0031-9007,1079-7114
DOI: 10.1103/physrevlett.91.208105