The Coyote Universe Extended: Precision Emulation of the Matter Power Spectrum

208

499

Large scale structure surveys promise to be the next leading probe of cosmological information. It is therefore crucial to reliably predict their observables. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a manifestly convergent perturbation theory for the weakly non-linear regime of dark matter, where correlation functions are computed in an expansion of the wavenumber k of a mode over the wavenumber associated with the non-linear scale k NL . Since most of the information is contained at high wavenumbers, it is necessary to compute higher order corrections to correlation functions. After the one-loop correction to the matter power spectrum, we estimate that the next leading one is the two-loop contribution, which we compute here. At this order in k/k NL , there is only one counterterm in the EFTofLSS that must be included, though this term contributes both at tree-level and in several one-loop diagrams. We also discuss correlation functions involving the velocity and momentum fields. We find that the EFTofLSS prediction at two loops matches to percent accuracy the non-linear matter power spectrum at redshift zero up to k ∼ 0.6 h Mpc −1 , requiring just one unknown coefficient that needs to be fit to observations. Given that Standard Perturbation Theory stops converging at redshift zero at k ∼ 0.1 h Mpc −1 , our results demonstrate the possibility of accessing a factor of order 200 more dark matter quasi-linear modes than naively expected. If the remaining observational challenges to accessing these modes can be addressed with similar success, our results show that there is tremendous potential for large scale structure surveys to explore the primordial universe.

Section: Resultsmentioning

confidence: 98%

The Effective Field Theory of Large Scale Structures at two loops

Carrasco

Foreman

Green

et al. 2014

208

499

“…A common approach in the prediction of the P(k) is to compute the non linearities using the Halofit recipe [31] revised in [32]. In [45], it was introduced the HMcode 3 , a fit of the Halo model [46] on the Coyote suite simulations [47] including also the effect of baryons physics as quantified in [48], that implemented star formation, supernovae and active galactic nucleus feedback. Despite these methods are built on simulations of models including w = const.…”

Section: Non Linear Power Spectrummentioning

confidence: 99%

“…Recently, in [34] it was described a public package called PKequal 4 , that extends both Halofit and Coyote suite from w = const to CPL models. In this work, we modified the PKequal code in order to also include the Linear and BA cases and chose to extend the predictions of the code described in [47]. The results are shown in Figure 6.…”

Section: Non Linear Power Spectrummentioning

confidence: 99%

Linear and non-linear perturbations in dark energy models

Escamilla-Rivera

Casarini

Fabris

et al. 2016

Abstract. In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state w(z). In order to determine the dynamics associated with these models, we calculate their background evolution and perturbations in a scalar field representation. After performing a complete treatment of linear perturbations, we also show that the non-linear contribution of the selected w(z) parameterisations to the matter power spectra is almost the same for all scales, with no significant difference from the predictions of the standard ΛCDM model.

“…[68] The accuracy of predictions of the non-linear power spectrum can be improved moving from semi-analytic methods like the Halofit model to numerical simulations and machinelearning techniques. For example, with "The Coyote Universe", Heitmann et al (2009Heitmann et al ( , 2010Heitmann et al ( , 2014 [69][70][71] developed a prediction scheme for the non-linear power spectrum at 1% accuracy over a wide dynamic range and redshift interval. The scheme was implemented through an emulator based on a set of high-accuracy N-body simulations.…”

Section: Jcap04(2017)029mentioning

confidence: 99%

An optimally weighted estimator of the linear power spectrum disentangling the growth of density perturbations across galaxy surveys

Sorini

2017

Measuring the clustering of galaxies from surveys allows us to estimate the power spectrum of matter density fluctuations, thus constraining cosmological models. This requires careful modelling of observational effects to avoid misinterpretation of data. In particular, signals coming from different distances encode information from different epochs. This is known as "light-cone effect" and is going to have a higher impact as upcoming galaxy surveys probe larger redshift ranges. Generalising the method by Feldman et al. (1994) [1], I define a minimum-variance estimator of the linear power spectrum at a fixed time, properly taking into account the light-cone effect. An analytic expression for the estimator is provided, and that is consistent with the findings of previous works in the literature. I test the method within the context of the halo model, assuming the cosmological parameters given by Planck Collaboration et al. (2014) [2]. I show that the estimator presented recovers the fiducial linear power spectrum at present time within 5% accuracy up to k ∼ 0.80 h Mpc −1 and within 10% up to k ∼ 0.94 h Mpc −1 , well into the non-linear regime of the growth of density perturbations. As such, the method could be useful in the analysis of the data from future large-scale surveys, like Euclid.