# Tuning and jamming reduced to their minima

## TL;DR

This paper introduces a method inspired by protein folding to modify cost functions in network tuning and sphere jamming, reducing local minima and improving the likelihood of finding global minima.

## Contribution

It presents a novel approach to smoothing complex landscapes in tuning and jamming problems by incorporating funnel-like structures, enhancing optimization success.

## Key findings

- Modified cost functions increase success rate of reaching global minima
- Introducing funnels reduces local minima in complex landscapes
- Geometrical frustration impacts tuning and jamming processes

## Abstract

Inspired by protein folding, we introduce funnels into the complex cost function landscapes of two processes, the tuning of networks, and the jamming of ideal spheres. In both processes, geometrical frustration plays a role -- tuning pressure differences between pairs of target nodes far from the source in a flow network impedes tuning of nearby pairs more than the reverse process, while unjamming the system in one region can make it more difficult to unjam elsewhere. By modifying the cost functions to control the order in which functions are tuned or regions unjam, we smooth out local minima while leaving global minima unaffected, significantly increasing the success rate of reaching global minima.