# Symbolic Emulators for Cosmology: Accelerating Cosmological Analyses Without Sacrificing Precision

arXiv: https://arxiv.org/abs/2510.18749 · HTML: https://mlsanity.com/paper/2510.18749/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 55 references that are in the map.
- First posted on arXiv 21 Oct 2025.

## Builds on (most cited first, 9 of 9)

- [Pyro: Deep Universal Probabilistic Programming](https://mlsanity.com/paper/1810.09538/) (2018)
- [Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro](https://mlsanity.com/paper/1912.11554/) (2019)
- [Exhaustive Symbolic Regression](https://mlsanity.com/paper/2211.11461/) (2022)
- [Priors for symbolic regression](https://mlsanity.com/paper/2304.06333/) (2023)
- [CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulators](https://mlsanity.com/paper/2305.06347/) (2023)
- [syren-new: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy](https://mlsanity.com/paper/2410.14623/) (2024)
- [A precise symbolic emulator of the linear matter power spectrum](https://mlsanity.com/paper/2311.15865/) (2023)
- [syren-halofit: A fast, interpretable, high-precision formula for the LambdaCDM nonlinear matter power spectrum](https://mlsanity.com/paper/2402.17492/) (2024)
- [syren-baryon: Analytic emulators for the impact of baryons on the matter power spectrum](https://mlsanity.com/paper/2506.08783/) (2025)

## Abstract (arXiv)

In cosmology, emulators play a crucial role by providing fast and accurate predictions of complex physical models, enabling efficient exploration of high-dimensional parameter spaces that would be computationally prohibitive with direct numerical simulations. Symbolic emulators have emerged as promising alternatives to numerical approaches, delivering comparable accuracy with significantly faster evaluation times. While previous symbolic emulators were limited to relatively narrow prior ranges, we expand these to cover the parameter space relevant for current cosmological analyses. We introduce approximations to hypergeometric functions used for the LambdaCDM comoving distance and linear growth factor which are accurate to better than 0.001% and 0.05%, respectively, for all redshifts and for Omegarm m ∈ [0.1, 0.5]. We show that integrating symbolic emulators into a Dark Energy Survey-like 3×2pt analysis produces cosmological constraints consistent with those obtained using standard numerical methods. Our symbolic emulators offer substantial improvements in speed and memory usage, demonstrating their practical potential for scalable, likelihood-based inference.