Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userFORGE -- the f(R) gravity cosmic emulator project I: Introduction and matter power spectrum emulator
152
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We present a large suite of cosmological simulations, the FORGE (F-of-R Gravity Emulator) simulation suite, which is designed to build accurate emulators for cosmological observables in galaxy clustering, weak gravitational lensing and galaxy clusters, for the $f(R)$ gravity model. The total of 200 simulations explore the cosmological parameter space around the Planck(2018) cosmology with a Latin hypercube, for 50 combinations of $bar{f}_{R0}$, $Omega_m$, $sigma_8$ and $h$ with all other parameters fixed. For each parameter combination, or node, we ran four independent simulations, one pair using $1024^3$ particles in $500 h^{-1} Mpc$ simulation boxes to cover small scales, and another pair using $512^3$ simulation particles in $1500 h^{-1} Mpc$ boxes for larger scales. Each pair of initial conditions are selected such that sample variance on large scales is minimised on average. In this work we present an accurate emulator for the matter power spectrum in $f(R)$ gravity trained on FORGE. We have verified, using the cross-validation technique, that the emulator accuracy is better than $2.5%$ for the majority of nodes, particularly around the center of the explored parameter space, up to scales of $k = 10 h Mpc^{-1}$. We have also checked the power spectrum emulator against simulations which are not part of our training set and found excellent agreement. Due to its high accuracy on small scales, the FORGE matter power spectrum emulator is well suited for weak lensing analysis and can play a key tool in constraining $f(R)$ gravity using current and future observational data.
rate research
Read More
Testing a subset of viable cosmological models beyond General Relativity (GR), with implications for cosmic acceleration and the Dark Energy associated with it, is within the reach of Rubin Observatory Legacy Survey of Space and Time (LSST) and a part of its endeavor. Deviations from GR-w(z)CDM models can manifest in the growth rate of structure and lensing, as well as in screening effects on non-linear scales. We explore the constraining power of small-scale deviations predicted by the f(R) Hu-Sawicki Modified Gravity (MG) candidate, by emulating this model with COLA (COmoving Lagrangian Acceleration) simulations. We present the experimental design, data generation, and interpolation schemes in cosmological parameters and across redshifts for the emulation of the boost in the power spectra due to Modified Gravity effects. Three preliminary applications of the emulator highlight the sensitivity to cosmological parameters, Fisher forecasting and Markov Chain Monte Carlo inference for a fiducial cosmology. This emulator will play an important role for future cosmological analysis handling the formidable amount of data expected from Rubin Observatory LSST.
We present methods for emulating the matter power spectrum which effectively combine information from cosmological $N$-body simulations at different resolutions. An emulator allows estimation of simulation output by interpolating across the parameter space of a handful of simulations. We present the first implementation of multi-fidelity emulation in cosmology, where many low-resolution simulations are combined with a few high-resolution simulations to achieve an increased emulation accuracy. The power spectrums dependence on cosmology is learned from the low-resolution simulations, which are in turn calibrated using high-resolution simulations. We show that our multi-fidelity emulator can achieve percent-level accuracy on average with only $3$ high-fidelity simulations and outperforms a single-fidelity emulator that uses $11$ simulations. With a fixed number of high-fidelity training simulations, we show that our multi-fidelity emulator is $simeq 100$ times better than a single-fidelity emulator at $k leq 2 ,htextrm{Mpc}{^{-1}}$, and $simeq 20$ times better at $3 leq k < 6.4 ,htextrm{Mpc}{^{-1}}$. Multi-fidelity emulation is fast to train, using only a simple modification to standard Gaussian processes. Our proposed emulator shows a new way to predict non-linear scales by fusing simulations from different fidelities.
We study the matter and velocity divergence power spectra in a f(R) gravity theory and their time evolution measured from several large-volume N-body simulations with varying box sizes and resolution. We find that accurate prediction of the matter power spectrum in f(R) gravity places stronger requirements on the simulation than is the case with LCDM, because of the nonlinear nature of the fifth force. Linear perturbation theory is shown to be a poor approximation for the f(R) models, except when the chameleon effect is very weak. We show that the relative differences from the fiducial LCDM model are much more pronounced in the nonlinear tail of the velocity divergence power spectrum than in the matter power spectrum, which suggests that future surveys which target the collection of peculiar velocity data will open new opportunities to constrain modified gravity theories. A close investigation of the time evolution of the power spectra shows that there is a pattern in the evolution history, which can be explained by the properties of the chameleon-type fifth force in f(R) gravity. Varying the model parameter |f_R0|, which quantifies the strength of the departure from standard gravity, mainly varies the epoch marking the onset of the fifth force, as a result of which the different f(R) models are in different stages of the same evolutionary path at any given time
Using N-body simulations, we measure the power spectrum of the effective dark matter density field, which is defined through the modified Poisson equation in $f(R)$ cosmologies. We find that when compared to the conventional dark matter power spectrum, the effective power spectrum deviates more significantly from the $Lambda$CDM model. For models with $f_{R0}=-10^{-4}$, the deviation can exceed 150% while the deviation of the conventional matter power spectrum is less than 50%. Even for models with $f_{R0}=-10^{-6}$, for which the conventional matter power spectrum is very close to the $Lambda$CDM prediction, the effective power spectrum shows sizeable deviations. Our results indicate that traditional analyses based on the dark matter density field may seriously underestimate the impact of $f(R)$ gravity on galaxy clustering. We therefore suggest the use of the effective density field in such studies. In addition, based on our findings, we also discuss several possible methods of making use of the differences between the conventional and effective dark matter power spectra in $f(R)$ gravity to discriminate the theory from the $Lambda$CDM model.
We present a neural-network emulator for baryonic effects in the non-linear matter power spectrum. We calibrate this emulator using more than 50,000 measurements in a 15-dimensional parameters space, varying cosmology and baryonic physics. Baryonic physics is described through a baryonification algorithm, that has been shown to accurately capture the relevant effects on the power spectrum and bispectrum in state-of-the-art hydrodynamical simulations. Cosmological parameters are sampled using a cosmology-rescaling approach including massive neutrinos and dynamical dark energy. The specific quantity we emulate is the ratio between matter power spectrum with baryons and gravity-only, and we estimate the overall precision of the emulator to be 1-2%, at all scales 0.01 < k < 5 h/Mpc, and redshifts 0 < z < 1.5. We also obtain an accuracy of 1-2%, when testing the emulator against a collection of 74 different cosmological hydrodynamical simulations and their respective gravity-only counterparts. We show also that only one baryonic parameter, namely Mc, which set the gas fraction retained per halo mass, is enough to have accurate and realistic predictions of the baryonic feedback at a given epoch. Our emulator will become publicly available in http://www.dipc.org/bacco.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
