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Register a new userValidating the Fisher approach for stage IV spectroscopic surveys
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In recent years forecasting activities have become a very important tool for designing and optimising large scale structure surveys. To predict the performance of such surveys, the Fisher matrix formalism is frequently used as a fast and easy way to compute constraints on cosmological parameters. Among them lies the study of the properties of dark energy which is one of the main goals in modern cosmology. As so, a metric for the power of a survey to constrain dark energy is provided by the Figure of merit (FoM). This is defined as the inverse of the surface contour given by the joint variance of the dark energy equation of state parameters ${w_0,w_a}$ in the Chevallier-Polarski-Linder parameterisation, which can be evaluated from the covariance matrix of the parameters. This covariance matrix is obtained as the inverse of the Fisher matrix. Inversion of an ill-conditioned matrix can result in large errors on the covariance coefficients if the elements of the Fisher matrix have been estimated with insufficient precision. The conditioning number is a metric providing a mathematical lower limit to the required precision for a reliable inversion, but it is often too stringent in practice for Fisher matrices with size larger than $2times2$. In this paper we propose a general numerical method to guarantee a certain precision on the inferred constraints, like the FoM. It consists on randomly vibrating (perturbing) the Fisher matrix elements with Gaussian perturbations of a given amplitude, and then evaluating the maximum amplitude that keeps the FoM within the chosen precision. The steps used in the numerical derivatives and integrals involved in the calculation of the Fisher matrix elements can then be chosen accordingly in order to keep the precision of the Fisher matrix elements below this maximum amplitude...
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We provide in depth MCMC comparisons of two different models for the halo redshift space power spectrum, namely a variant of the commonly applied Taruya-Nishimichi-Saito (TNS) model and an effective field theory of large scale structure (EFTofLSS) inspired model. Using many simulation realisations and Stage IV survey-like specifications for the covariance matrix, we check each models range of validity by testing for bias in the recovery of the fiducial growth rate of structure formation. The robustness of the determined range of validity is then tested by performing additional MCMC analyses using higher order multipoles, a larger survey volume and a more highly biased tracer catalogue. We find that under all tests, the TNS models range of validity remains robust and is found to be much higher than previous estimates. The EFTofLSS model fails to capture the spectra for highly biased tracers as well as becoming biased at higher wavenumbers when considering a very large survey volume. Further, we find that the marginalised constraints on $f$ for all analyses are stronger when using the TNS model.
Starting from the Fisher matrix for counts in cells, I derive the full Fisher matrix for surveys of multiple tracers of large-scale structure. The key assumption is that the inverse of the covariance of the galaxy counts is given by the naive matrix inverse of the covariance in a mixed position-space and Fourier-space basis. I then compute the Fisher matrix for the power spectrum in bins of the three-dimensional wavenumber k; the Fisher matrix for functions of position x (or redshift z) such as the linear bias of the tracers and/or the growth function; and the cross-terms of the Fisher matrix that expresses the correlations between estimations of the power spectrum and estimations of the bias. When the bias and growth function are fully specified, and the Fourier-space bins are large enough that the covariance between them can be neglected, the Fisher matrix for the power spectrum reduces to the widely used result that was first derived by Feldman, Kaiser and Peacock (1994). Assuming isotropy, an exact calculation of the Fisher matrix can be performed in the case of a constant-density, volume-limited survey. I then show how the exact Fisher matrix in the general case can be obtained in terms of a series of volume-limited surveys.
We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Ly$alpha$ forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, $r_d$, from eight different samples and six measurements of the growth rate parameter, $fsigma_8$, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, $Lambda$CDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization the BAO data provide nearly an order of magnitude improvement on curvature constraints. The RSD measurements indicate a growth rate that is consistent with predictions from Planck primary data and with General Relativity. When combining the results of SDSS BAO and RSD with external data, all multiple-parameter extensions remain consistent with a $Lambda$CDM model. Regardless of cosmological model, the precision on $Omega_Lambda$, $H_0$, and $sigma_8$, remains at roughly 1%, showing changes of less than 0.6% in the central values between models. The inverse distance ladder measurement under a o$w_0w_a$CDM yields $H_0= 68.20 pm 0.81 , rm km, s^{-1} Mpc^{-1}$, remaining in tension with several direct determination methods. (abridged)
We investigate optimization strategies to measure primordial non-Gaussianity with future spectroscopic surveys. We forecast measurements coming from the 3D galaxy power spectrum and compute constraints on primordial non-Gaussianity parameters f_NL and n_NG. After studying the dependence on those parameters upon survey specifications such as redshift range, area, number density, we assume a reference mock survey and investigate the trade-off between number density and area surveyed. We then define the observational requirements to reach the detection of f_NL of order 1. Our results show that while power spectrum constraints on non-Gaussianity from future spectroscopic surveys can be competitive with current CMB limits, measurements from higher-order statistics will be needed to reach a sub unity precision in the measurements of the non-Gaussianity parameter f_NL.
The BigBOSS experiment is a proposed DOE-NSF Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with an all-sky galaxy redshift survey. The project is designed to unlock the mystery of dark energy using existing ground-based facilities operated by NOAO. A new 4000-fiber R=5000 spectrograph covering a 3-degree diameter field will measure BAO and redshift space distortions in the distribution of galaxies and hydrogen gas spanning redshifts from 0.2<z<3.5. The Dark Energy Task Force figure of merit (DETF FoM) for this experiment is expected to be equal to that of a JDEM mission for BAO with the lower risk and cost typical of a ground-based experiment. This project will enable an unprecedented multi-object spectroscopic capability for the U.S. community through an existing NOAO facility. The U.S. community would have access directly to this instrument/telescope combination, as well as access to the legacy archives that will be created by the BAO key project.
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