A Growth-based Optimization Algorithm for Lattice Heteropolymers
Hsiao-Ping Hsu, Vishal Mehra, Walter Nadler, Peter Grassberger
Abstract
An improved version of the pruned-enriched-Rosenbluth method (PERM) is proposed and tested on finding lowest energy states in simple models of lattice heteropolymers. It is found to outperform not only the previous version of PERM, but also all other fully blind general purpose stochastic algorithms which have been employed on this problem. In many cases it found new lowest energy states missed in previous papers. Limitations are discussed.
Create a lesson
Related papers
Global Minima of the Thomson Problem in a Disk: A Molecular Dynamics Approach with Fixed Border Charges
Georgiy K. Lavrov, Eduard G. Nikonov
Martingale theory for heat and phase-space contraction in heterogeneous diffusions
Jing Qin, Nariya Uchida, Édgar Roldán
Formal Fluctuation-Response Relations for Non-Stationary Systems: The Dynamic Conjugate Variable
Igor M. Sokolov
Khinchin's ergodicity and typicality in statistical mechanics
Dario Lucente, Marco Baldovin, Giacomo Gradenigo et al.
Universal 1/f Noise in the Power Spectra of Energy Time-series in Solvated DNA Dynamics
Harsh Sahu, Deepika Sardana, Pramod Kumar et al.
Landau diamagnetism and the de Haas-van Alphen effect from a single geometric construction
Sung-Hoon Lee