A path integral approximation of conditional probability densities with application to stochastic elastic rods
Giulio Corazza

TL;DR
This paper develops a generalized path integral method for Gaussian integrals in elastic rods, enabling estimation of end-to-end probability densities in complex boundary conditions, with applications to polymers and DNA.
Contribution
It extends Gelfand-Yaglom methods to vector cases with boundary conditions and zero modes, applying path integral techniques to stochastic elastic rods and polymer physics.
Findings
Derived approximate conditional probability densities for elastic rods.
Validated results with Monte Carlo simulations showing good agreement.
Applied methods to DNA and polymer models in thermodynamic equilibrium.
Abstract
In this work, we generalise Gelfand-Yaglom-type methods in the vector case for the computation of Gaussian path integrals. The extension we propose allows to consider general second variation operators subject to different boundary conditions and to regularise the divergence in presence of zero modes. The derived methods are exploited to study the statistical physics of polymers at thermodynamic equilibrium (e.g. DNA). The energy of equilibria combined with suitable Jacobi field determinants can be used to estimate the distribution of end-to-end displacements when the filament is interacting with a heat bath. In the continuum limit of Cosserat elastic rods, we demonstrate how to derive approximate conditional probability density functions governing the relative location and orientation of the two ends, first for the looping problem and second when the rod is subject to a prescribed…
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Taxonomy
TopicsLipid Membrane Structure and Behavior · Orbital Angular Momentum in Optics · Force Microscopy Techniques and Applications
