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Related Experiment Videos

Interacting growth walk: a model for generating compact self-avoiding walks.

S L Narasimhan1, P S R Krishna, K P N Murthy

  • 1Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai - 400 085, India. glass@apsara.barc.ernet.in

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|January 22, 2002
PubMed
Summary

We developed the interacting growth walk (IGW) model for generating self-avoiding walks. This algorithm efficiently creates compact configurations at low temperatures, useful for protein folding studies.

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Area of Science:

  • Computational physics
  • Polymer physics
  • Statistical mechanics

Background:

  • Generating self-avoiding walk (SAW) configurations is crucial for modeling polymers and other systems.
  • Existing algorithms often face limitations, such as attrition at zero temperature on square lattices.

Purpose of the Study:

  • To introduce a novel algorithm, the interacting growth walk (IGW) model, for kinetically generating SAW configurations.
  • To address limitations of existing algorithms, particularly regarding attrition and configuration compactness.

Main Methods:

  • The IGW model utilizes local growth rules to build SAW configurations.
  • The algorithm operates at any given temperature.
  • Simulations were performed on a square lattice.

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Main Results:

  • The IGW model avoids attrition on a square lattice at zero temperature.
  • The model successfully generates compact configurations at lower temperatures.
  • The IGW model accurately describes the collapse transition of a homopolymer in two dimensions.

Conclusions:

  • The IGW model offers an effective method for generating SAW configurations.
  • Its ability to produce compact structures at low temperatures makes it suitable for studying phenomena like protein folding.
  • The model provides a valuable tool for polymer physics and related computational studies.