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Register a new userForecasts for Next Generation tSZ Surveys: the Impact of a Cosmology-Dependent Selection Function
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The thermal Sunyaev-Zeldovich (tSZ) effect is one of the primary tools for finding and characterizing galaxy clusters. Several ground-based experiments are either underway or are being planned for mapping wide areas of the sky at $sim 150$ GHz with large-aperture telescopes. We present cosmological forecasts for a straw man tSZ survey that will observe a sky area between $200$ and $10^4$ deg$^2$ to an rms noise level between 2.8 and 20.2 $mu$K-arcmin. The probes we consider are the cluster number counts (as a function of the integrated Compton-$Y$ parameter and redshift) and their angular clustering (as a function of redshift). At fixed observing time, we find that wider surveys constrain cosmology slightly better than deeper ones due to their increased ability to detect rare high-mass clusters. In all cases, we notice that adding the clustering information does not practically improve the constraints derived from the number counts. We compare forecasts obtained by sampling the posterior distribution with the Markov-chain-Monte-Carlo method against those derived using the Fisher-matrix formalism. We find that the latter produces slightly optimistic constraints where errors are underestimated at the 10 per cent level. Most importantly, we use an analytic method to estimate the selection function of the survey and account for its response to variations of the cosmological parameters in the likelihood function. Our analysis demonstrates that neglecting this effect (as routinely done in the literature) yields artificially tighter constraints by a factor of 2.2 and 1.7 for $sigma_8$ and $Omega_mathrm{M}$, respectively.
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We use the results of previous work building a halo model formalism for the distribution of neutral hydrogen, along with experimental parameters of future radio facilities, to place forecasts on astrophysical and cosmological parameters from next generation surveys. We consider 21 cm intensity mapping surveys conducted using the BINGO, CHIME, FAST, TianLai, MeerKAT and SKA experimental configurations. We work with the 5-parameter cosmological dataset of {$Omega_m, sigma_8, h, n_s, Omega_b$} assuming a flat $Lambda$CDM model, and the astrophysical parameters {$v_{c,0}, beta$} which represent the cutoff and slope of the HI- halo mass relation. We explore (i) quantifying the effects of the astrophysics on the recovery of the cosmological parameters, (ii) the dependence of the cosmological forecasts on the details of the astrophysical parametrization, and (iii) the improvement of the constraints on probing smaller scales in the HI power spectrum. For an SKA I MID intensity mapping survey alone, probing scales up to $ell_{rm max} = 1000$, we find a factor of $1.1 - 1.3$ broadening in the constraints on $Omega_b$ and $Omega_m$, and of $2.4 - 2.6$ on $h$, $n_s$ and $sigma_8$, if we marginalize over astrophysical parameters without any priors. However, even the prior information coming from the present knowledge of the astrophysics largely alleviates this broadening. These findings do not change significantly on considering an extended HIHM relation, illustrating the robustness of the results to the choice of the astrophysical parametrization. Probing scales up to $ell_{rm max} = 2000$ improves the constraints by factors of 1.5-1.8. The forecasts improve on increasing the number of tomographic redshift bins, saturating, in many cases, with 4 - 5 redshift bins. We also forecast constraints for intensity mapping with other experiments, and draw similar conclusions.
As galaxy surveys become more precise and push to smaller scales, the need for accurate covariances beyond the classical Gaussian formula becomes more acute. Here, I investigate the analytical implementation and impact of non-Gaussian covariance terms that I previously derived for galaxy clustering. Braiding covariance is such a class of terms and it gets contribution both from in-survey and super-survey modes. I present an approximation for braiding covariance which speeds up the numerical computation. I show that including braiding covariance is a necessary condition for including other non-Gaussian terms: the in-survey 2-, 3- and 4-halo covariance, which yield covariance matrices with negative eigenvalues if considered on their own. I then quantify the impact on parameter constraints, with forecasts for a Euclid-like survey. Compared to the Gaussian case, braiding and in-survey covariances significantly increase the error bars on cosmological parameters, in particular by 50% for w. The Halo Occupation Distribution (HOD) error bars are also affected between 12% and 39%. Accounting for super-sample covariance (SSC) also increases parameter errors, by 90% for w and between 7% and 64% for HOD. In total, non-Gaussianity increases the error bar on w by 120% (between 15% and 80% for other cosmological parameters), and the error bars on HOD parameters between 17% and 85%. Accounting for the 1-halo trispectrum term on top of SSC is not sufficient for capturing the full non-Gaussian impact: braiding and the rest of in-survey covariance have to be accounted for. Finally, I discuss why the inclusion of non-Gaussianity generally eases up parameter degeneracies, making cosmological constraints more robust to astrophysical uncertainties. The data and a Python notebook reproducing the results and plots of the article are available at url{https://github.com/fabienlacasa/BraidingArticle}. [Abridged]
We study the prospects for constraining the ionized fraction of the intergalactic medium (IGM) at $z>6$ with the next generation of large Ly$alpha$ emitter surveys. We make predictions for the upcoming Subaru Hyper Suprime-Cam (HSC) Ly$alpha$ survey and a hypothetical spectroscopic survey performed with the James Webb Space Telescope (JWST). Considering various scenarios where the observed evolution of the Ly$alpha$ luminosity function of Ly$alpha$ emitters at $z>6$ is explained partly by an increasingly neutral IGM and partly by intrinsic galaxy evolution, we show how clustering measurements will be able to distinguish between these scenarios. We find that the HSC survey should be able to detect the additional clustering induced by a neutral IGM if the global IGM neutral fraction is greater than $sim$20 per cent at $z=6.5$. If measurements of the Ly$alpha$ equivalent widths (EWs) are also available, neutral fractions as small as 10 per cent may be detectable by looking for correlation between the EW and the local number density of objects. In this case, if it should turn out that the IGM is significantly neutral at $z=6.5$ and the intrinsic EW distribution is relatively narrow, the observed EWs can also be used to construct a map of the locations and approximate sizes of the largest ionized regions. For the JWST survey, the results appear a bit less optimistic. Since such surveys probe a large range of redshifts, the effects of the IGM will be mixed up with any intrinsic galaxy evolution that is present, making it difficult to disentangle the effects. However, we show that a survey with the JWST will have a possibility of observing a large group of galaxies at $zsim7$, which would be a strong indication of a partially neutral IGM.
We address key points for an efficient implementation of likelihood codes for modern weak lensing large-scale structure surveys. Specifically, we focus on the joint weak lensing convergence power spectrum-bispectrum probe and we tackle the numerical challenges required by a realistic analysis. Under the assumption of (multivariate) Gaussian likelihoods, we have developed a high performance code that allows highly parallelised prediction of the binned tomographic observables and of their joint non-Gaussian covariance matrix accounting for terms up to the 6-point correlation function and super-sample effects. This performance allows us to qualitatively address several interesting scientific questions. We find that the bispectrum provides an improvement in terms of signal-to-noise ratio (S/N) of about 10% on top of the power spectrum, making it a non-negligible source of information for future surveys. Furthermore, we are capable to test the impact of theoretical uncertainties in the halo model used to build our observables; with presently allowed variations we conclude that the impact is negligible on the S/N. Finally, we consider data compression possibilities to optimise future analyses of the weak lensing bispectrum. We find that, ignoring systematics, 5 equipopulated redshift bins are enough to recover the information content of a Euclid-like survey, with negligible improvement when increasing to 10 bins. We also explore principal component analysis and dependence on the triangle shapes as ways to reduce the numerical complexity of the problem.
The coming decade will be an exciting period for dark energy research, during which astronomers will address the question of what drives the accelerated cosmic expansion as first revealed by type Ia supernova (SN) distances, and confirmed by later observations. The mystery of dark energy poses a challenge of such magnitude that, as stated by the Dark Energy Task Force (DETF), nothing short of a revolution in our understanding of fundamental physics will be required to achieve a full understanding of the cosmic acceleration. The lack of multiple complementary precision observations is a major obstacle in developing lines of attack for dark energy theory. This lack is precisely what next-generation surveys will address via the powerful techniques of weak lensing (WL) and baryon acoustic oscillations (BAO) -- galaxy correlations more generally -- in addition to SNe, cluster counts, and other probes of geometry and growth of structure. Because of their unprecedented statistical power, these surveys demand an accurate understanding of the observables and tight control of systematics. This white paper highlights the opportunities, approaches, prospects, and challenges relevant to dark energy studies with wide-deep multiwavelength photometric redshift surveys. Quantitative predictions are presented for a 20000 sq. deg. ground-based 6-band (ugrizy) survey with 5-sigma depth of r~27.5, i.e., a Stage 4 survey as defined by the DETF.
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