Abstract
We test the convergence of fast simulations based on the COmoving Lagrangian Acceleration (COLA) method for predictions of the matter power spectrum, specialising our analysis in the redshift range 1 ≤ z ≤ 1.65, relevant to high-redshift spectroscopic galaxy surveys. We then focus on the enhancement of the matter power spectrum in modified gravity (MG), the boost factor, using the Dvali-Gabadadze-Porrati (DGP) theory as a test case but developing a general approach that can be applied to other MG theories. After identifying the minimal simulation requirements for accurate DGP boost factors, we design and produce a COLA simulation suite that we use to train a neural network emulator for the DGP boost factor. Using MG-AREPO simulations as a reference, we estimate the emulator accuracy to be of ∼ 3% up to k = 5 h Mpc−1 at 0 ≤ z ≤ 2. We make the emulator publicly available at: https://github.com/BartolomeoF/nDGPemu.
| Original language | English |
|---|---|
| Article number | 045 |
| Number of pages | 26 |
| Journal | Journal of Cosmology and Astroparticle Physics |
| Volume | 2023 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 22 Dec 2023 |
Keywords
- UKRI
- STFC
- RF\ERE\210304
- ST/W001225/1
- ERC
- StG 949572
- URF\R1\180009
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