What is meant by pruning and enrichment?

Click For Summary
SUMMARY

Pruning in the context of the PERM (Pruned Enriched Rosenbluth Method) algorithm refers to the process of deleting certain elements, specifically polymer chains or beads within those chains. Enrichment involves enhancing the weights of either entire polymer chains or individual beads. The discussion raises questions about the specifics of what is being pruned and how the weights are modified, prompting a reference to Grassberger's original article for further clarification.

PREREQUISITES
  • Understanding of the PERM algorithm
  • Familiarity with polymer physics concepts
  • Knowledge of weight modification techniques in algorithms
  • Access to Grassberger's original research article
NEXT STEPS
  • Read Grassberger's original article on the PERM algorithm
  • Explore advanced topics in polymer chain modeling
  • Investigate weight modification strategies in computational algorithms
  • Learn about the implications of pruning in algorithm efficiency
USEFUL FOR

Researchers in computational physics, algorithm developers, and students studying polymer science and optimization techniques.

user366312
Gold Member
Messages
88
Reaction score
3
TL;DR
What does it mean by pruning and enrichment in the case of Rosenbluth method?
As far as I understand:

  1. Pruning means deleting something.
  2. Enrich means to enhance/increase weight.
Now my question is, in the case of the PERM algorithm,

  1. Are we deleting some polymers chains? Or, are we deleting some beads in all polymer chains?
  2. Are we increasing the weights of some polymers? Or, are we increasing the weights of some beads/atoms of all polymers?
When we are modifying the pruned weights, what are we replacing them with?
 
Physics news on Phys.org

Similar threads

  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 9 ·
Replies
9
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 9 ·
Replies
9
Views
2K
Replies
1
Views
2K
Replies
14
Views
2K
Replies
9
Views
3K
  • · Replies 2 ·
Replies
2
Views
1K