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Condensed Matter > Disordered Systems and Neural Networks

Title: Canonical partition function and distance dependent correlation functions of a quasi-one-dimensional system of hard disks

Abstract: The canonical $\,NLT\,$ partition function of a quasi-one dimensional (q1D) one-file system of equal hard disks [J. Chem Phys. \textbf{153}, 144111 (2020)] provides an analytical description of the thermodynamics and ordering in this system (a pore) as a function of linear density $\,Nd/L\,$ where $\,d\,$ is the disk diameter. We derive the analytical formulae for the distance dependence of the translational pair distribution function and the distribution function of distances between next neighbor disks, and then demonstrate their use by calculating the translational order in the pore. In all cases, the order is found to be of a short range and to exponentially decay with the disks' separation. The correlation length presented for different pore widths and densities shows a non-monotonic dependence with a maximum at $\,Nd/L = 1\,$ and tends to the 1D value for a vanishing pore width. The results indicate a special role of this density when the pore length $\,L\,$ is equal exactly to $N$ disk diameters. A comparison between the theoretical results for an infinite system and the results of a molecular dynamics simulation for a finite system with periodic boundary conditions is presented and discussed.
Comments: published in Journal of Molecular Liquids. arXiv admin note: substantial text overlap with arXiv:2206.05980
Subjects: Disordered Systems and Neural Networks (cond-mat.dis-nn); Statistical Mechanics (cond-mat.stat-mech)
Journal reference: Journal of Molecular Liquids, Volume 387, 122572 (2023) and Journal of Molecular Liquids, Volume 393, 123639 (2024)
DOI: 10.1016/j.molliq.2023.122572
Cite as: arXiv:2307.05995 [cond-mat.dis-nn]
  (or arXiv:2307.05995v2 [cond-mat.dis-nn] for this version)

Submission history

From: Taras Bryk [view email]
[v1] Wed, 12 Jul 2023 08:19:37 GMT (804kb)
[v2] Thu, 18 Apr 2024 10:04:20 GMT (1116kb)

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