SearcharxivSearch

arXiv · 2604.11713

Thermodynamic fluctuations in freely jointed chains under force

Abstract

It is common to study polymer physics through the use of idealized single-chain models, and the most popular of these is the freely jointed chain model. In certain thermodynamic ensembles, statistical mechanical treatment of this model is analytically tractable or sometimes exactly solvable. This enables useful relations to be ascertained, like the expected chain end-to-end length as a function of an applied force. However, most of these relations return ensemble averages, which are values with inherent uncertainty, as opposed to deterministic values with no variance. This is an important distinction to understand and quantify, because the majority of studies to date involving single-chain models effectively treat these values as deterministic rather than fluctuating. To address this issue, thermodynamic fluctuations are examined in the freely jointed chain model. Specifically, the probability densities and standard deviations of the longitudinal, lateral, transverse, and radial portions of the chain extension, as well as the extension and link angles, are examined for different numbers of links and applied forces. Fluctuations in these quantities are shown to be considerable until the applied force becomes large. Increasing the number of links in the chain gradually reduces fluctuations in all quantities except for the link angles, since they are independent for freely jointed chains in the isotensional ensemble. Quantities are obtained analytically whenever possible and numerically otherwise. Overall, these results provide intuitive admonitions to consider when modeling the stretching of single polymer chains or the deformation of entire polymer networks.

Explore related subjects

Keep this discovery

BibTeXRIS

Michael R. Buche, Alvin Chen. 2026-04-13. Thermodynamic fluctuations in freely jointed chains under force. https://arxiv.org/abs/2604.11713

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Universal sampling of spin systems across quenched disorder

Statistical physics extracts macroscopic laws by averaging over the many microscopic degrees of freedom of a system. Disordered systems demand a second and far harder average, one over the quenched randomness itself. The classic analytical routes, the replica and cavity methods, become uncontrolled outside mean-field or tree-like limits, and conventional numerical algorithms like parallel tempering require expensive, independent equilibration for every disorder realization. In this work, we introduce a universal neural variational framework that amortizes inference across the disorder ensemble, eliminating both the need for per-instance Markov chain equilibration and the cost of retraining instance-specific variational ansatzes. Built on an encoder-decoder Transformer architecture, after training once, it produces an explicit approximation to the Boltzmann distribution given previously unseen disorder realizations without further optimization. We validate this framework on 2D Edwards-Anderson models, and apply it to the random-bond Ising model, successfully capturing the Binder cumulant crossings near the Nishimori multicritical point. These results shift the object of variational inference from the single instance to the disorder ensemble, opening a route to frustrated many-body systems where instance-by-instance computation is prohibitive.

cond-mat.stat-mech

Information-Theoretic Characterization of Macroscopic Chaos Emerging from the Chemical Master Equation

Open chemical reaction networks exhibit stochastic concentration dynamics at finite system sizes, whereas their macroscopic limit is governed by deterministic rate equations that can display chaos. In this Letter, we show theoretically that a rate of information loss constructed from two-time mutual information recovers the Kolmogorov-Sinai entropy in the deterministic limit. We verify this result through numerical simulations of a Markov jump process for a three-species system involving seven reactions.

cond-mat.stat-mech

Orientational order on non-orientable domains

We study the statistical properties of passive and active many-body systems with orientational degrees of freedom on non-orientable domains. By rephrasing topological constraints as non-local symmetry relations on an orientable double-cover, we show that non-orientability eliminates global rotational soft modes without acting like an external field. In a passive XY model, this results in topological caging, where orientational fluctuations that exhibit conventional diffusive behavior on a torus saturate on a Klein bottle to a finite value that we compute exactly in the thermodynamic limit. In models of active self-propelled particles with orientational degrees of freedom, topological caging persists despite continuously changing interaction neighborhoods. In an active Ising spin model, non-orientability enforces the coexistence of ordered anti-parallel domains with vanishing global polar order, a state that is absent on orientable domains.

cond-mat.stat-mech