Edge-based formulation of elastic network models
File(s)
Working paper
Author(s)
Hodges, Maxwell
Yaliraki, Sophia N
Barahona, Mauricio
Type
Working Paper
Abstract
We present an edge-based framework for the study of geometric elastic network
models to model mechanical interactions in physical systems. We use a
formulation in the edge space, instead of the usual node-centric approach, to
characterise edge fluctuations of geometric networks defined in d- dimensional
space and define the edge mechanical embeddedness, an edge mechanical
susceptibility measuring the force felt on each edge given a force applied on
the whole system. We further show that this formulation can be directly related
to the infinitesimal rigidity of the network, which additionally permits three-
and four-centre forces to be included in the network description. We exemplify
the approach in protein systems, at both the residue and atomistic levels of
description.
models to model mechanical interactions in physical systems. We use a
formulation in the edge space, instead of the usual node-centric approach, to
characterise edge fluctuations of geometric networks defined in d- dimensional
space and define the edge mechanical embeddedness, an edge mechanical
susceptibility measuring the force felt on each edge given a force applied on
the whole system. We further show that this formulation can be directly related
to the infinitesimal rigidity of the network, which additionally permits three-
and four-centre forces to be included in the network description. We exemplify
the approach in protein systems, at both the residue and atomistic levels of
description.
Date Issued
2019-12-31
Date Acceptance
2019-11-14
Citation
Physical Review Research, 2019, (3), pp.033211-033211
Publisher
American Physical Society
Start Page
033211
End Page
033211
Journal / Book Title
Physical Review Research
Issue
3
Copyright Statement
© 2019 The Author(s)
Identifier
http://arxiv.org/abs/1911.06152v1
Subjects
physics.chem-ph
physics.chem-ph
q-bio.BM
Publication Status
Published
Date Publish Online
2019-12-31