When Dark Matter Heats Up: A Model-Independent Search for Non-Cold Behavior

TL;DR

This paper investigates the possibility of non-zero dark matter pressure using non-parametric methods and current cosmological data, challenging the standard assumption of cold, pressureless dark matter in a model-independent way.

Contribution

It introduces a non-parametric approach to test for non-zero dark matter equation of state using Gaussian Process Regression on multiple cosmological datasets.

Findings

Mild statistical support for a dynamical dark matter EoS.

Evidence of a slight preference for negative $w_{DM}$ at present.

Inconsistencies between BAO data sets influence results.

Abstract

This article questions the common assumption of cold dark matter (DM) by exploring the possibility of a non-zero equation of state (EoS) without relying on any parametric approach. In standard cosmological analyses, DM is typically modeled as pressureless dust with $w_{\rm DM} = 0$, an assumption that aligns with large-scale structure formation, supports the empirical success of the $\Lambda$CDM model, and simplifies cosmological modeling. However, there is no fundamental reason to exclude a non-zero $w_{\rm DM}$ from the cosmological framework. In this work, we explore this possibility through non-parametric and parametric reconstructions based on Gaussian Process Regression. The reconstructions use Hubble parameter measurements from Cosmic Chronometers (CC), the Pantheon+ sample of Type Ia supernovae, and Baryon Acoustic Oscillation (BAO) data from DESI DR1 and DR2. Our findings suggest that a dynamical EoS for DM, although only mildly supported statistically, cannot be conclusively ruled out. Notably, we observe a mild tendency ($\sim 1\sigma$) toward a negative $w_{\rm DM}$ at the present epoch, which is most likely due to inconsistencies between the BAO data from DESI and other datasets.