# Difference between revisions of "Perturbation Spreading in Many-Particle Systems: A Random Walk Approach"

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The authors of this paper examine the propagation dynamics of a perturbation traveling through a non-dissipative medium (energy is conserved and not lost due to friction). They modeled the medium as a collection of many interacting particles. As energy was conserved, they were able to apply Hamiltonian dynamics to analyze the system. | The authors of this paper examine the propagation dynamics of a perturbation traveling through a non-dissipative medium (energy is conserved and not lost due to friction). They modeled the medium as a collection of many interacting particles. As energy was conserved, they were able to apply Hamiltonian dynamics to analyze the system. | ||

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+ | The authors knew that a propagation would travel through the material at approximately a finite velocity. Typical diffusion equations, however, imply infinite propagation speeds; the authors consequently knew this would not accurately describe their system's behavior. Consequently, the authors decided to model the perturbation kinetics by treating the particles as if they were undergoing a random walk. | ||

==Discussion== | ==Discussion== | ||

==References== | ==References== |

## Revision as of 21:50, 18 September 2012

Original entry by Bryan Weinstein, Fall 2012

## General Information

**Authors**: V. Zaburdaev, S. Denisov, and P. Hanggi

**Keywords**:

## Summary

The authors of this paper examine the propagation dynamics of a perturbation traveling through a non-dissipative medium (energy is conserved and not lost due to friction). They modeled the medium as a collection of many interacting particles. As energy was conserved, they were able to apply Hamiltonian dynamics to analyze the system.

The authors knew that a propagation would travel through the material at approximately a finite velocity. Typical diffusion equations, however, imply infinite propagation speeds; the authors consequently knew this would not accurately describe their system's behavior. Consequently, the authors decided to model the perturbation kinetics by treating the particles as if they were undergoing a random walk.