Free-then-freeze: transient learning degrees of freedom for introducing function in materials

TL;DR

This paper introduces a novel transient degrees of freedom approach to material design, enabling the creation of highly stable jammed packings with deep energy minima by temporarily adding and removing certain system variables.

Contribution

It proposes a new framework for transient learning degrees of freedom in materials, demonstrating how different choices affect stability and training outcomes.

Findings

Stable jammed packings in deep energy minima without low-frequency modes

Particle radii as transient degrees of freedom lead to more stable minima than stiffnesses

Stability persists in the thermodynamic limit

Abstract

The introduction of transient learning degrees of freedom into a system can lead to novel material design and training protocols that guide a system into a desired metastable state. In this approach, some degrees of freedom, which were not initially included in the system dynamics, are first introduced and subsequently removed from the energy minimization process once the desired state is reached. Using this conceptual framework, we create stable jammed packings that exist in exceptionally deep energy minima marked by the absence of low-frequency quasilocalized modes; this added stability persists in the thermodynamic limit. The inclusion of particle radii as transient degrees of freedom leads to deeper and much more stable minima than does the inclusion of particle stiffnesses. This is because particle radii couple to the jamming transition whereas stiffnesses do not. Thus different choices for the added degrees of freedom can lead to very different training outcomes.