Metastability, Spectra, and Eigencurrents of the Lennard-Jones-38 Network
Maria K. Cameron

TL;DR
This paper introduces computational tools for spectral analysis of stochastic networks modeling atomic energy landscapes, applied to the Lennard-Jones-38 cluster, revealing insights into relaxation processes and metastability.
Contribution
It presents a novel spectral analysis methodology for large stochastic networks with varying transition rates, applied to complex atomic clusters.
Findings
No significant spectral gap for escape from the icosahedral funnel.
Detailed characterization of the escape process using eigencurrents.
Superexponential growth of the eigenvalue associated with escape from the icosahedral funnel.
Abstract
We develop computational tools for spectral analysis of stochastic networks representing energy landscapes of atomic and molecular clusters. Physical meaning and some properties of eigenvalues, left and right eigenvectors, and eigencurrents are discussed. We propose an approach to compute a collection of eigenpairs and corresponding eigencurrents describing the most important relaxation processes taking place in the system on its way to the equilibrium. It is suitable for large and complex stochastic networks where pairwise transition rates, given by the Arrhenius law, vary by orders of magnitude. The proposed methodology is applied to the network representing the Lennard-Jones-38 cluster created by Wales's group. Its energy landscape has a double funnel structure with a deep and narrow face-centered cubic funnel and a shallower and wider icosahedral funnel. Contrary to the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
