Authors : Pratham Dungrani; Aarav Upreti; Hans Rajeshkumar Patel

Volume/Issue : Volume 10 - 2025, Issue 11 - November

Google Scholar : https://tinyurl.com/32u2cepy

Scribd : https://tinyurl.com/3u9e3nz3

DOI : https://doi.org/10.38124/ijisrt/25nov734

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Abstract : Dark energy, the source of the universe's accelerated expansion, may indirectly influence galaxy cluster thermal status and formation history. The current paper presents a simplified numerical model to analyze how various dark energy densities affect galaxy cluster virial temperature evolution. In a Python-based simulation, we experiment with the thermal response of idealized clusters under varying cosmological constants (Λ) and dark energy equations of state (w). The model connects gravitational binding energy and dark energy repulsion through a generalized virial equilibrium equation adapted for this purpose. Our Python code (Dark Matter.py) computes the virial temperature for different cluster masses, radii, and Λ values and plots the results through different scenarios: Λ variation, mass–radius scaling, redshift evolution, and equation- of-state variations. Monte Carlo uncertainty analysis also explores sensitivity to measurement error. The results show that for systematically raising Λ (or more negative w), virial temperatures within clusters go down, indicating that dark energy causes suppression of late-time growth and gravitational heating of clusters. The lower Λ models, on the other hand, maintain higher temperatures due to longer collapse and virialization. Though compromised, the model maintains key cosmological–thermodynamic couplings and provides a readily computable scheme for dark energy impact on structure formation research. It provides a pedagogical tool for relating cosmological parameters on large scales and local astrophysical observables such as intra-cluster gas temperature.

Keywords : Dark Energy Density, Galaxy Cluster Evolution, Virial Temperature, Cosmological Constant, Numerical Modeling, Equation of State, Simplified Astrophysics Simulation.

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