A spinodal decomposition model for the large-scale structure of the universe

TL;DR

This paper introduces a thermodynamic spinodal decomposition model for the universe's large-scale structure, providing a computationally efficient alternative to N-body simulations that aligns well with observational data.

Contribution

It presents a novel application of the Cahn-Hilliard spinodal decomposition model to cosmology, offering a new framework for simulating cosmic structure formation.

Findings

Simulated matter distribution matches observational survey metrics.

Void fraction and filamentarity are consistent with established models.

Linear growth factor closely follows Lambda-CDM predictions.

Abstract

Understanding the large-scale structure of the universe remains a fundamental challenge in cosmology, with computational simulations providing critical insights into non-linear structure growth. Particularly, computational simulations critical information about the non-linear growth processes behind the observed large-scale structures. Inspired by the similarly porous structure of polymer membranes prepared using phase-inversion, this work presents a novel thermodynamic approach to cosmic structure formation. A numerical framework is presented, based on the Cahn-Hilliard model of spinodal decomposition for a binary mixture treating the universe as a two-component fluid of matter and dark-energy. The dimensionless Cahn-Hilliard equation is solved using finite-element methods, with parameters calibrated to Planck 2018 cosmology. The simulation evolves an initially homogeneous matter distribution through 500 timesteps, corresponding to 35 million years of cosmological evolution. The simulated matter distribution exhibits quantitative agreement with observational surveys across multiple metrics. Void fraction evolves to 0.416 at z ~ 0.65, right at the edge of domain of applicability of Lambda-CDM model. Filamentarity reaches 0.42, comparable to Millennium Simulation results. The linear growth factor extracted from simulated density fields also closely agrees with {\Lambda}CDM predictions over the interval 9.300 < t < 9.335 Gyr. This work establishes spinodal decomposition as a viable thermodynamic framework for cosmic structure formation, offering a computationally efficient alternative to traditional N-body methods while reproducing key quantitative observables. The approach opens new avenues for exploring matter-dark energy interactions and may prove valuable for next-generation survey analysis.