$k$-e$\mu$lator: emulating clustering effects of the $k$-essence dark energy

TL;DR

This paper introduces a polynomial chaos expansion emulator for modeling the non-linear clustering effects of $k$-essence dark energy, enabling fast and accurate predictions for cosmological parameter analysis.

Contribution

It develops a PCE-based emulator trained on high-resolution simulations to efficiently model the $$ function in $k$-essence dark energy within the EFT framework, with publicly available code.

Findings

Achieves sub-percent accuracy up to $k \\approx 9.4 ~h$ Mpc$^{-1}$ for $z \\leq 3$

Efficiently captures the impact of cosmological parameters on the $$ function

Provides a tool for Bayesian parameter estimation in dark energy models

Abstract

We build an emulator based on the polynomial chaos expansion (PCE) technique to efficiently model the non-linear effects associated with the clustering of the $k$-essence dark energy in the effective field theory (EFT) framework. These effects can be described through a modification of Poisson's equation, denoted by the function $\mu(k,z)$, which in general depends on wavenumber $k$ and redshift $z$. To emulate this function, we perform $200$ high-resolution $N$-body simulations sampled from a seven-dimensional parameter space with the Latin hypercube method. These simulations are executed using the $\texttt{k-evolution}$ code on a fixed mesh, containing $1200^3$ dark matter particles within a box size of $400~\text{Mpc}/ h$. The emulation process has been carried out within $\texttt{UQLab}$, a $\texttt{MATLAB}$-based software specifically dedicated to emulation and uncertainty quantification tasks. Apart from its role in emulation, the PCE method also facilitates the measurement of Sobol indices, enabling us to assess the relative impact of each cosmological parameter on the $\mu$ function. Our results show that the PCE-based emulator efficiently and accurately reflects the behavior of the $k$-essence dark energy for the cosmological parameter space defined by $w_0 c_s^2 \text{CDM} +\sum m_{\nu}$. Compared against actual simulations, the emulator achieves sub-percent accuracy up to the wavenumber $k \approx 9.4 ~h \text{Mpc}^{-1} $ for redshifts $z \leq 3$. Our emulator provides an efficient and reliable tool for Markov chain Monte Carlo (MCMC) analysis, and its capability to closely mimic the properties of the $k$-essence dark energy makes it a crucial component in Bayesian parameter estimations. The code is publicly available at https://github.com/anourizo/k-emulator .