Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · cond-mat/0508094

Secondary Structures in Long Compact Polymers

Richard Oberdorf·Allison Ferguson·Jesper L. Jacobsen·Jane' Kondev
View original source ↗Read source document ↗Export metadata ↓

Abstract

Compact polymers are self-avoiding random walks which visit every site on a lattice. This polymer model is used widely for studying statistical problems inspired by protein folding. One difficulty with using compact polymers to perform numerical calculations is generating a sufficiently large number of randomly sampled configurations. We present a Monte-Carlo algorithm which uniformly samples compact polymer configurations in an efficient manner allowing investigations of chains much longer than previously studied. Chain configurations generated by the algorithm are used to compute statistics of secondary structures in compact polymers. We determine the fraction of monomers participating in secondary structures, and show that it is self averaging in the long chain limit and strictly less than one. Comparison with results for lattice models of open polymer chains shows that compact chains are significantly more likely to form secondary structure.

Explore related subjects

cond-mat.softcond-mat.stat-mech

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Richard Oberdorf, Allison Ferguson, Jesper L. Jacobsen, Jane' Kondev. 2005-08-03. Secondary Structures in Long Compact Polymers. https://doi.org/10.1103/physreve.74.051801

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

KEEP EXPLORING

Related papers

arXiv2026

Dynamic clustering of active chemotactic Janus particles

Modeling self-propulsion as an emergent diffusiophoretic effect, we come back to the dynamic clustering experiment of active Janus colloids. Working in the original three-dimensional geometry, and using the chemical solute concentration as a control parameter, we find that the dynamic clustering region occupies a robust fraction of the phase diagram. This behavior is rationalized using a linear stability analysis that efficiently captures the instability of the gas phase to dynamic clusters. We also find that dynamic clustering results from the combined effects of a Keller-Segel collapse and of a motility-induced phase separation, either being arrested by the orientational coupling to the chemical field in agreement with previous work.

cond-mat.soft↗
arXiv2026

Multi-Fidelity Machine Learning for Predicting Startup Stress Growth and Strain Hardening in Wormlike Micellar Solutions

Wormlike micellar solutions exhibit formulation-dependent nonlinear startup responses, including stress overshoot, undershoot, and strain hardening, making prediction across compositions and shear rates challenging. We developed a multi-fidelity machine-learning framework to predict stress-growth curves in cetylpyridinium chloride (CPyCl)-based wormlike micelles from sparse experimental measurements. The framework combines a low-fidelity analytical model describing the overall startup response with high-fidelity experimental data capturing formulation-specific nonlinear features. This approach addresses the limited and uneven coverage of salt chemistry, concentration, and shear rate without relying solely on data-intensive neural-network training. The trained model predicts complete stress-growth responses at untested shear rates and enables extraction of strain-hardening characteristics from interpolated curves. By augmenting sparse rheological measurements, the framework provides a basis for exploring relationships among formulation variables, linear viscoelastic properties, and nonlinear startup behavior, while supporting more efficient characterization of wormlike micellar solutions.

cond-mat.soft↗
arXiv2026

Topology Does Not Determine Defect Mobility in Active Polar Matter

Topological defects are commonly characterized by their charge, although defects with the same charge can have different internal morphologies. We study the annihilation of isolated $\pm1$ defect pairs in a two-dimensional compressible Toner--Tu model, varying the morphology of the $+1$ defect while keeping the initial charges and separation fixed. Activity produces a morphology-dependent mobility asymmetry: reversing the radial orientation of an aster reverses which defect travels farther, and asters show the strongest response. An early-time analysis reveals that the initial morphology selects distinct density modes whose gradients subsequently feed back on the polarization. Consistently, removing the density-gradient coupling strongly suppresses the asymmetry. These results establish defect morphology, in addition to topological charge, as a dynamical variable governing defect-pair motion in active polar matter.

cond-mat.soft↗