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CMB-S4—the next-generation ground-based cosmic microwave background (CMB) experiment—is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensor-to-scalar ratio, r, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2–3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments, given a desired scientific goal. To form a closed-loop process, we couple this semianalytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for r > 0.003 at greater than 5σ, or in the absence of a detection, of reaching an upper limit of r < 0.001 at 95% CL.

Gravitational coupling between large- and small-scale density perturbations leads to anisotropic distortions to local small-scale matter fluctuations. Such local anisotropic distortions can be used to reconstruct large-scale matter distribution, known as tidal reconstruction. In this paper, we apply the tidal reconstruction methods to simulated galaxies in redshift space. We find that redshift-space distortions (RSDs) lead to anisotropic reconstruction results. While the reconstructed radial modes are more noisy mainly due to the small-scale velocity dispersion, the transverse modes are still reconstructed with high fidelity, and well correlated with the original large-scale density modes. The bias of the reconstructed field at large scales shows a simple angular dependence, which can be described by a form similar to that of the linear RSD. The noise power spectrum is nearly isotropic and scale independent on large scales. This makes the reconstructed tide fields an ideal tracer for cosmic variance cancellation and multi-tracer analysis and has profound implications for future 21 cm intensity mapping surveys.

Modern galaxy surveys focus on the galaxy power spectrum or 2-point correlation function to test and constrain cosmological models. Additional information comes from higher-order N-point functions, but their analysis is challenging. A simple solution is to compute the cross-power spectrum between the squared galaxy density and the galaxy density. Being simple to measure and to plot, this skew-spectrum shares many of the familiar useful properties of the standard galaxy power spectrum. We show that by computing multiple quadratic fields and correlating them with the density, all contributions to the tree-level redshift-space galaxy bispectrum can be captured with skew-spectra. Using synthetic datasets, we show that our measurement pipeline matches analytical predictions, and that their dependence on galaxy bias parameters and the logarithmic growth rate is as expected theoretically.

Relying on a separable modal expansion of the bispectrum, the implementation of a fast estimator for the full bispectrum of a 3d particle distribution is presented. The computational cost of accurate bispectrum estimation is negligible relative to simulation evolution, so the bispectrum can be used as a standard diagnostic whenever the power spectrum is evaluated. As an application, the time evolution of gravitational and primordial dark matter bispectra was measured in a large suite of N-body simulations. The bispectrum shape changes characteristically when the cosmic web becomes dominated by filaments and halos, therefore providing a quantitative probe of 3d structure formation. Our measured bispectra are determined by ∼ 50 coefficients, which can be used as fitting formulae in the nonlinear regime and for non-Gaussian initial conditions. We also compare the measured bispectra with predictions from the Effective Field Theory of Large Scale Structures (EFTofLSS).

The lensing convergence measurable with future CMB surveys like CMB-S4 will be highly correlated with the clustering observed by deep photometric large scale structure (LSS) surveys such as the LSST, with cross-correlation coefficient as high as 95\\%. This will enable use of sample variance cancellation techniques to determine cosmological parameters, and use of cross-correlation measurements to break parameter degeneracies. Assuming large sky overlap between CMB-S4 and LSST, we show that a joint analysis of CMB-S4 lensing and LSST clustering can yield very tight constraints on the matter amplitude \\(_8(z)\\), halo bias, and \\(f_NL\\), competitive with the best stage IV experiment predictions, but using complementary methods, which may carry different and possibly lower systematics. Having no sky overlap between experiments degrades the precision of \\(_8(z)\\) by a factor of 20, and that of \\(f_NL\\) by a factor of 1.5 to 2. Without CMB lensing, the precision always degrades by an order of magnitude or more, showing that a joint analysis is critical. Our results also suggest that CMB lensing in combination with LSS photometric surveys is a competitive probe of the evolution of structure in the redshift range \\(z 1-7\\), probing a regime that is not well tested observationally. We explore predictions against other surveys and experiment configurations, finding that wide patches with maximal sky overlap between CMB and LSS surveys are most powerful for \\(_8(z)\\) and \\(f_NL\\).

Motivated by recent developments in perturbative calculations of the nonlinear evolution of large-scale structure, we present an iterative algorithm to reconstruct the initial conditions in a given volume starting from the dark matter distribution in real space. In our algorithm, objects are first moved back iteratively along estimated potential gradients, with a progressively reduced smoothing scale, until a nearly uniform catalog is obtained. The linear initial density is then estimated as the divergence of the cumulative displacement, with an optional second-order correction. This algorithm should undo nonlinear effects up to one-loop order, including the higher-order infrared resummation piece. We test the method using dark matter simulations in real space. At redshift \\(z=0\\), we find that after eight iterations the reconstructed density is more than \\(95\\%\\) correlated with the initial density at \\(k 0.35\\; hMpc^-1\\). The reconstruction also reduces the power in the difference between reconstructed and initial fields by more than 2 orders of magnitude at \\(k 0.2\\; hMpc^-1\\), and it extends the range of scales where the full broadband shape of the power spectrum matches linear theory by a factor of 2-3. As a specific application, we consider measurements of the baryonic acoustic oscillation (BAO) scale that can be improved by reducing the degradation effects of large-scale flows. In our idealized dark matter simulations, the method improves the BAO signal-to-noise ratio by a factor of 2.7 at \\(z=0\\) and by a factor of 2.5 at \\(z=0.6\\), improving standard BAO reconstruction by \\(70\\%\\) at \\(z=0\\) and \\(30\\%\\) at \\(z=0.6\\), and matching the optimal BAO signal and signal-to-noise ratio of the linear density in the same volume. For BAO, the iterative nature of the reconstruction is the most important aspect.

Modeling the large-scale structure of the universe on nonlinear scales has the potential to substantially increase the science return of upcoming surveys by increasing the number of modes available for model comparisons. One way to achieve this is to model nonlinear scales perturbatively. Unfortunately, this involves high-dimensional loop integrals that are cumbersome to evaluate. Trying to simplify this, we show how two-loop (next-to-next-to-leading order) corrections to the density power spectrum can be reduced to low-dimensional, radial integrals. Many of those can be evaluated with a one-dimensional Fast Fourier Transform, which is significantly faster than the five-dimensional Monte-Carlo integrals that are needed otherwise. The general idea of this FFT-PT method is to switch between Fourier and position space to avoid convolutions and integrate over orientations, leaving only radial integrals. This reformulation is independent of the underlying shape of the initial linear density power spectrum and should easily accommodate features such as those from baryonic acoustic oscillations. We also discuss how to account for halo bias and redshift space distortions.

Compensated isocurvature perturbations (CIPs) are opposite spatial fluctuations in the baryon and dark matter density. They can be generated for example in the curvaton model in the early Universe but are difficult to observe because their gravitational imprint nearly cancels. We therefore propose a new measurement method by searching for a spatial modulation of the baryon acoustic oscillation (BAO) scale that CIPs induce. We find that for a Euclid-like survey the sensitivity is marginally better than the WMAP cosmic microwave background (CMB) constraint, which exploits the CIP-induced modulation of the CMB sound horizon. For a cosmic-variance limited BAO survey using emission-line galaxies up to \\(z7\\) the sensitivity is between stage 3 and stage 4 CMB experiments. These results include using CIP-galaxy cross-correlations, which improves the sensitivity by a factor of \\(2-3\\) for correlated CIPs. The method could be further improved with an optimal estimator, similarly to the CMB, and could provide a useful cross-check of other CIP probes. Finally, if CIPs exist, they can bias cosmological measurements made assuming no CIPs. In particular, they can act as a super-sample fluctuation of the baryon density and bias measurements of the BAO scale. For modern BAO surveys, the largest 2\\(\\) CIP fluctuation allowed by Planck's 95\\% bound could bias BAO measurements of \\(H(z)\\) by 2.2\\%, partially reducing the tension with the local \\(H_0\\) measurements from 3.1\\(\\) to 2.3\\(\\).

The density field reconstruction technique has been widely used for recovering the Baryon Acoustic Oscillation (BAO) feature in galaxy surveys that has been degraded due to nonlinearities. Recent studies advocated adopting iterative steps to improve the recovery much beyond that of the standard technique. In this paper, we investigate the performance of a few selected iterative reconstruction techniques focusing on the BAO and the broadband-shape of the two-point clustering. We include redshift-space distortions, halo bias, and shot noise and inspect the components of the reconstructed field in Fourier space and in configuration space using both density field-based reconstruction and displacement field-based reconstruction. We find that the displacement field reconstruction becomes quickly challenging in the presence of non-negligible shot noise and therefore present surrogate methods that can be practically applied to a much more sparse field such as galaxies. For a galaxy field, implementing a debiasing step to remove the Lagrangian bias appears crucial for the displacement field reconstruction. We show that the iterative reconstruction does not substantially improve the BAO feature beyond an aggressively optimized standard reconstruction with a small smoothing kernel. However, we find taking iterative steps allows us to use a small smoothing kernel more `stably', i.e., without causing a substantial deviation from the linear power spectrum on large scales. In one specific example we studied, we find that a deviation of 13\\% in \\(P( k 0.1h/Mpc)\\) with an aggressive standard reconstruction can reduce to 3-4\\% with iterative steps.

As a major source of cosmological information, galaxy clustering is susceptible to long-wavelength density and tidal fluctuations. These long modes modulate the growth and expansion rate of local structures, shifting them in both amplitude and scale. These effects are often named the growth and dilation effects, respectively. In particular the dilation shifts the baryon acoustic oscillation (BAO) peak and breaks the assumption of the Alcock-Paczynski (AP) test. This cannot be removed with reconstruction techniques because the effect originates from long modes outside the survey. In redshift space, the long modes generate a large-scale radial peculiar velocity that affects the redshift-space distortion (RSD) signal. We compute the redshift-space response functions of the galaxy power spectrum to long density and tidal modes at leading order in perturbation theory, including both the growth and dilation terms. We validate these response functions against measurements from simulated galaxy mock catalogs. As one application, long density and tidal modes beyond the scale of a survey correlate various observables leading to an excess error known as the super-sample covariance, and thus weaken their constraining power. We quantify the super-sample effect on BAO, AP, and RSD measurements, and study its impact on current and future surveys.