Systemic Risk and the Dynamics of Financial Networks

Gong, Rui; Page, Frank H.

doi:10.2139/ssrn.2767093

Cited by 2 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Stochastic network models are also of fundamental importance in many other domains, such as in systems biology, 113,114 and in studies of epidemic spread 115 and finance. 116 Further work will focus on the analysis of existing kinetic transition networks, for which evidence for multiple competing pathway ensembles, or otherwise, and assessment of the kinetic relevance of alternative pathway ensembles, yields valuable insight into the underlying dynamics. Variations with temperature in the profiles of distinct path costs and of steady state rate constants for the accumulated networks formed from the distinct paths reflect the entropic character of an interstate transition.…”

Section: Discussionmentioning

confidence: 99%

Identifying mechanistically distinct pathways in kinetic transition networks

Sharpe

Wales

2019

The Journal of Chemical Physics

View full text Add to dashboard Cite

We present an implementation of a scalable path deviation algorithm to find the k most kinetically relevant paths in a transition network, where each path is distinguished on the basis of having a distinct rate-limiting edge. The potential of the algorithm to identify distinct pathways that exist in separate regions of the configuration space is demonstrated for two benchmark systems with double-funnel energy landscapes, namely a model 'three-hole' network embedded on a 2D potential energy surface, and the cluster of 38 Lennard-Jones atoms (LJ 38). The path cost profiles for the interbasin transitions of the two systems reflect the contrasting nature of the landscapes. There are multiple well-defined pathway ensembles for the three-hole system, whereas the transition in LJ 38 effectively involves a single ensemble of pathways via disordered structures. A by-product of the algorithm is a set of edges that constitute a cut of the network, which is related to the discrete analogue of a transition dividing surface. The algorithm ought to be useful for determining the existence, or otherwise, of competing mechanisms in large stochastic network models of dynamical processes, and for assessing the kinetic relevance of distinguishable ensembles of pathways. This capability will provide insight into conformational transitions in biomolecules and other complex slow processes.

show abstract

Section: Discussionmentioning

confidence: 99%