Canonical dual theory applied to a Lennard-Jones potential minimization problem

TL;DR

This paper applies canonical dual theory to effectively solve the complex Lennard-Jones potential minimization problem, which is characterized by nonconvexity and numerous local minima, relevant in molecular modeling.

Contribution

The paper introduces a novel application of canonical dual theory to address the Lennard-Jones potential minimization, providing a new approach to global optimization in molecular modeling.

Findings

Successfully applied canonical dual theory to Lennard-Jones minimization

Achieved global solutions despite nonconvexity and local minima

Enhanced understanding of molecular structure optimization

Abstract

The simplified Lennard-Jones (LJ) potential minimization problem is $f(x)=4\sum_{i=1}^N \sum_{j=1,j<i}^N (\frac{1}{\tau_{ij}^6} -\frac{1}{\tau_{ij}^3}) {subject to} x\in \mathbb{R}^n,$ where $\tau_{ij}=(x_{3i-2}-x_{3j-2})^2 +(x_{3i-1}-x_{3j-1})^2 +(x_{3i} -x_{3j})^2$, $(x_{3i-2},x_{3i-1},x_{3i})$ is the coordinates of atom $i$ in $\mathbb{R}^3$, $i,j=1,2,...,N(\geq 2 \quad \text{integer})$, $n=3N$ and $N$ is the whole number of atoms. The nonconvexity of the objective function and the huge number of local minima, which is growing exponentially with $N$, interest many mathematical optimization experts. In this paper, the canonical dual theory elegantly tackles this problem illuminated by the amyloid fibril molecular model building. Keywords: Mathematical Canonical Duality Theory $\cdot$ Mathematical Optimization $\cdot$ Lennard-Jones Potential Minimization Problem $\cdot$ Global Optimization.