Non-Gaussian polymers described by alpha-stable chain statistics: model, applications and effective interactions in binary mixtures
M. Majka, P. F. G\'ora

TL;DR
This paper extends the classical Gaussian polymer chain model to alpha-stable distributions, enabling analytical descriptions of chain behavior, interactions, and phase separation in systems with heavy-tailed statistics.
Contribution
It introduces the alpha-stable chain model, generalizing Gaussian chains to include heavy-tailed distributions, with analytical formulas for segment distribution and interactions.
Findings
Derived the segment distribution for alpha-stable chains.
Constructed coarse-grained interaction potentials.
Analyzed phase separation in heavy-tailed polymer systems.
Abstract
The Gaussian chain model is the classical description of a polymeric chain, which provides the analytical results regarding end-to-end distance, the distribution of segments around the mass center of a chain, coarse grained interactions between two chains and effective interactions in binary mixtures. This hierarchy of results can be calculated thanks to the alpha stability of the Gaussian distribution. In this paper we show that it is possible to generalize the model of Gaussian chain to the entire class of alpha stable distributions, obtaining the analogous hierarchy of results expressed by the analytical closed-form formulas in the Fourier space. This allows us to establish the alpha-stable chain model. We begin with reviewing the applications of Levy flights in the context of polymer sciences, which include: chains with heavy-tailed distributions of persistence length, polymers…
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