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Register a new userSolving Large Scale Structure in Ten Easy Steps with COLA
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We present the COmoving Lagrangian Acceleration (COLA) method: an N-body method for solving for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). Unlike standard N-body methods, the COLA method can straightforwardly trade accuracy at small-scales in order to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing, as those catalogs are essential for performing detailed error analysis for ongoing and future surveys of LSS. As an illustration, we ran a COLA-based N-body code on a box of size 100Mpc/h with particles of mass ~5*10^9Msolar/h. Running the code with only 10 timesteps was sufficient to obtain an accurate description of halo statistics down to halo masses of at least 10^11Msolar/h. This is only at a modest speed penalty when compared to mocks obtained with LPT. A standard detailed N-body run is orders of magnitude slower than our COLA-based code. The speed-up we obtain with COLA is due to the fact that we calculate the large-scale dynamics exactly using LPT, while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos. Achieving a similar level of accuracy in halo statistics without the COLA method requires at least 3 times more timesteps than when COLA is employed.
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We present a numerically cheap approximation to super-sample covariance (SSC) of large scale structure cosmological probes, first in the case of angular power spectra. It necessitates no new elements besides those used for the prediction of the considered probes, thus relieving analysis pipelines from having to develop a full SSC modeling, and reducing the computational load. The approximation is asymptotically exact for fine redshift bins $Delta z rightarrow 0$. We furthermore show how it can be implemented at the level of a Gaussian likelihood or a Fisher matrix forecast, as a fast correction to the Gaussian case without needing to build large covariance matrices. Numerical application to a Euclid-like survey show that, compared to a full SSC computation, the approximation recovers nicely the signal-to-noise ratio as well as Fisher forecasts on cosmological parameters of the $w$CDM cosmological model. Moreover it allows for a fast prediction of which parameters are going to be the most affected by SSC and at which level. In the case of photometric galaxy clustering with Euclid-like specifications, we find that $sigma_8$, $n_s$ and the dark energy equation of state $w$ are particularly heavily affected. We finally show how to generalize the approximation for probes other than angular spectra (correlation functions, number counts and bispectra), and at the likelihood level, allowing for the latter to be non-Gaussian if needs be. We release publicly a Python module allowing to implement the SSC approximation, as well as a notebook reproducing the plots of the article, at https://github.com/fabienlacasa/PySSC
We present a general parallelized and easy-to-use code to perform numerical simulations of structure formation using the COLA (COmoving Lagrangian Acceleration) method for cosmological models that exhibit scale-dependent growth at the level of first and second order Lagrangian perturbation theory. For modified gravity theories we also include screening using a fast approximate method that covers all the main examples of screening mechanisms in the literature. We test the code by comparing it to full simulations of two popular modified gravity models, namely $f(R)$ gravity and nDGP, and find good agreement in the modified gravity boost-factors relative to $Lambda$CDM even when using a fairly small number of COLA time steps.
Upcoming 21-cm intensity surveys will use the hyperfine transition in emission to map out neutral hydrogen in large volumes of the universe. Unfortunately, large spatial scales are completely contaminated with spectrally smooth astrophysical foregrounds which are orders of magnitude brighter than the signal. This contamination also leaks into smaller radial and angular modes to form a foreground wedge, further limiting the usefulness of 21-cm observations for different science cases, especially cross-correlations with tracers that have wide kernels in the radial direction. In this paper, we investigate reconstructing these modes within a forward modeling framework. Starting with an initial density field, a suitable bias parameterization and non-linear dynamics to model the observed 21-cm field, our reconstruction proceeds by combining the likelihood of a forward simulation to match the observations (under given modeling error and a data noise model) with the Gaussian prior on initial conditions and maximizing the obtained posterior. For redshifts $z=2$ and $4$, we are able to reconstruct 21cm field with cross correlation, $r_c > 0.8$ on all scales for both our optimistic and pessimistic assumptions about foreground contamination and for different levels of thermal noise. The performance deteriorates slightly at $z=6$. The large-scale line-of-sight modes are reconstructed almost perfectly. We demonstrate how our method also reconstructs baryon acoustic oscillations, outperforming standard methods on all scales. We also describe how our reconstructed field can provide superb clustering redshift estimation at high redshifts, where it is otherwise extremely difficult to obtain dense spectroscopic samples, as well as open up cross-correlation opportunities with projected fields (e.g. lensing) which are restricted to modes transverse to the line of sight.
An axion-like field comprising $sim 10%$ of the energy density of the universe near matter-radiation equality is a candidate to resolve the Hubble tension; this is the early dark energy (EDE) model. However, as shown in Hill et al. (2020), the model fails to simultaneously resolve the Hubble tension and maintain a good fit to both cosmic microwave background (CMB) and large-scale structure (LSS) data. Here, we use redshift-space galaxy clustering data to sharpen constraints on the EDE model. We perform the first EDE analysis using the full-shape power spectrum likelihood from the Baryon Oscillation Spectroscopic Survey (BOSS), based on the effective field theory (EFT) of LSS. The inclusion of this likelihood in the EDE analysis yields a $25%$ tighter error bar on $H_0$ compared to primary CMB data alone, yielding $H_0 = 68.54^{+0.52}_{-0.95}$ km/s/Mpc ($68%$ CL). In addition, we constrain the maximum fractional energy density contribution of the EDE to $f_{rm EDE} < 0.072$ ($95%$ CL). We explicitly demonstrate that the EFT BOSS likelihood yields much stronger constraints on EDE than the standard BOSS likelihood. Including further information from photometric LSS surveys,the constraints narrow by an additional $20%$, yielding $H_0 = 68.73^{+0.42}_{-0.69}$ km/s/Mpc ($68%$ CL) and $f_{rm EDE}<0.053$ ($95%$ CL). These bounds are obtained without including local-universe $H_0$ data, which is in strong tension with the CMB and LSS, even in the EDE model. We also refute claims that MCMC analyses of EDE that omit SH0ES from the combined dataset yield misleading posteriors. Finally, we demonstrate that upcoming Euclid/DESI-like spectroscopic galaxy surveys can greatly improve the EDE constraints. We conclude that current data preclude the EDE model as a resolution of the Hubble tension, and that future LSS surveys can close the remaining parameter space of this model.
We show how the non-linearity of general relativity generates a characteristic non-Gaussian signal in cosmological large-scale structure that we calculate at all perturbative orders in a large scale limit. Newtonian gravity and general relativity provide complementary theoretical frameworks for modelling large-scale structure in $Lambda$CDM cosmology; a relativistic approach is essential to determine initial conditions which can then be used in Newtonian simulations studying the non-linear evolution of the matter density. Most inflationary models in the very early universe predict an almost Gaussian distribution for the primordial metric perturbation, $zeta$. However, we argue that it is the Ricci curvature of comoving-orthogonal spatial hypersurfaces, $R$, that drives structure formation at large scales. We show how the non-linear relation between the spatial curvature, $R$, and the metric perturbation, $zeta$, translates into a specific non-Gaussian contribution to the initial comoving matter density that we calculate for the simple case of an initially Gaussian $zeta$. Our analysis shows the non-linear signature of Einsteins gravity in large-scale structure.
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