# Energy Landscapes for Digital Alchemy

## TL;DR

This paper explores the application of energy landscape methods to digital alchemy, analyzing how potential parameters as degrees of freedom influence minima and transition states in small clusters, revealing concentrated minima and landscape frustration.

## Contribution

It introduces a novel approach by applying energy landscape analysis to digital alchemy, highlighting how potential parameters shape the landscape and transition states.

## Key findings

- Lowest energy minima are easily identifiable.
- Minima distribution is concentrated in specific regions.
- The landscape exhibits increased frustration with high barriers.

## Abstract

We apply energy landscape methods to digital alchemy, defining a system in which the parameters of the potential are treated as degrees of freedom. Using geometrical optimisation, we locate minima and transition states on the landscape for small clusters. We show that it is easy to find the parameters that give the lowest energy minimum, and that the distribution of minima on the alchemical landscape is concentrated in particular areas. We also conclude that the alchemical landscape is more frustrated, in terms of competition between low energy structures separated by high barriers. Transition states on the alchemical landscape are classified by whether they become minima or transition states when the potential parameters are fixed. Those that become minima have a significant alchemical component, while those that remain as transition states can be characterised mainly in terms of atomic displacements.