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Register a new userExtracting key information from spectroscopic galaxy surveys
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We develop a novel method to extract key cosmological information, which is primarily carried by the baryon acoustic oscillations (BAO) and redshift space distortions (RSD), from spectroscopic galaxy surveys, based on a joint principal component analysis (PCA) and Karhunen-Lo`eve (KL) data compression scheme. Comparing to the traditional methods using the multipoles or wedges of the galaxy correlation functions, we find that our method is able to extract the key information more efficiently, with a better control of the potential systematics, which manifests it as a powerful tool for clustering analysis for ongoing and forthcoming galaxy surveys.
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The age and chemical composition of the stars in present-day galaxies carry important clues about their star formation processes. The latest generation of population synthesis models have allowed to derive age and stellar metallicity estimates for large samples of low-redshift galaxies. After reviewing the main results about the distribution in ages and metallicities as a function of galaxy mass, I will concentrate on recent analysis that aims at disentangling the dependences of stellar populations properties on environment and on galaxy stellar mass. Finally, new models that predict the response of the full spectrum to variations in [alpha/Fe] will allow us to derive accurate estimates of element abundance ratios and gain deeper insight into the timescales of star formation cessation.
A large fraction of this thesis is dedicated to the study of the information content of random fields with heavy tails, in particular the lognormal field, a model for the matter density fluctuation field. It is well known that in the nonlinear regime of structure formation, the matter fluctuation field develops such large tails. It has also been suggested that fields with large tails are not necessarily well described by the hierarchy of $N$-point functions. In this thesis, we are able to make this last statement precise and with the help of the lognormal model to quantify precisely its implications for inference on cosmological parameters : we find as our main result that only a tiny fraction of the total Fisher information of the field is still contained in the hierarchy of $N$-point moments in the nonlinear regime, rendering parameter inference from such moments very inefficient. We show that the hierarchy fails to capture the information that is contained in the underdense regions, which at the same time are found to be the most rich in information. We find further our results to be very consistent with numerical analysis using $N$-body simulations. We also discuss these issues with the help of explicit families of fields with the same hierarchy of $N$-point moments defined in this work. A similar analysis is then applied to the convergence field, the weighted projection of the matter density fluctuation field along the line of sight, with similar conclusions. We also show how simple mappings can correct for this inadequacy, consistently with previous findings in the literature (Abridged) .
The main energy-generating mechanisms in galaxies are black hole (BH) accretion and star formation (SF) and the interplay of these processes is driving the evolution of galaxies. MIR/FIR spectroscopy are able to distinguish between BH accretion and SF, as it was shown in the past by infrared spectroscopy from the space by the Infrared Space Observatory and Spitzer. Spitzer and Herschel spectroscopy together can trace the AGN and the SF components in galaxies, with extinction free lines, almost only in the local Universe, except for a few distant objects. One of the major goals of the study of galaxy evolution is to understand the history of the luminosity source of galaxies along cosmic time. This goal can be achieved with far-IR spectroscopic cosmological surveys. SPICA in combination with ground based large single dish submillimeter telescopes, such as CCAT, will offer a unique opportunity to do this. We use galaxy evolution models linked to the observed MIR-FIR counts (including Herschel) to predict the number of sources and their IR lines fluxes, as derived from observations of local galaxies. A shallow survey in an area of 0.5 square degrees, with a typical integration time of 1 hour per pointing, will be able to detect thousands of galaxies in at least three emission lines, using SAFARI, the far-IR spectrometer onboard of SPICA.
[Abridged] We consider how galaxy clustering data, from Mpc to Gpc scales, from upcoming large scale structure surveys, such as Euclid and DESI, can provide discriminating information about the bispectrum shape arising from a variety of inflationary scenarios. Through exploring in detail the weighting of shape properties in the calculation of the halo bias and halo mass function we show how they probe a broad range of configurations, beyond those in the squeezed limit, that can help distinguish between shapes with similar large scale bias behaviors. We assess the impact, on constraints for a diverse set of non-Gaussian shapes, of galaxy clustering information in the mildly non-linear regime, and surveys that span multiple redshifts and employ different galactic tracers of the dark matter distribution. Fisher forecasts are presented for a Euclid-like spectroscopic survey of H$alpha$-selected emission line galaxies (ELGs) using recent revisions of the expected H$alpha$ luminosity function, and a DESI-like survey, of luminous red galaxies (LRGs) and [O-II] doublet-selected ELGs, in combination with Planck-like CMB temperature and polarization data. While ELG samples provide better probes of shapes that are divergent in the squeezed limit, LRG constraints, centered below $z<1$, yield stronger constraints on shapes with scale-independent large-scale halo biases, such as the equilateral template. The ELG and LRG samples provide complementary degeneracy directions for distinguishing between different shapes. If the Gaussian galaxy bias is constrained to better than a percent level, such as can be determined from the galaxy bispectrum or weak lensing, then the LSS and CMB data could provide complementary constraints that will enable differentiation of bispectra with distinct theoretical origins but with similar large scale, squeezed-limit properties.
Contamination of interloper galaxies due to misidentified emission lines can be a big issue in the spectroscopic galaxy clustering surveys, especially in future high-precision observations. We propose a statistical method based on the cross-correlations of the observational data itself between two redshift bins to efficiently reduce this effect, and it also can derive the interloper fraction f_i in a redshift bin with a high level of accuracy. The ratio of cross and auto angular correlation functions or power spectra between redshift bins are suggested to estimate f_i, and the key equations are derived for theoretical discussion. In order to explore and prove the feasibility and effectiveness of this method, we also run simulations, generate mock data, and perform cosmological constraints considering systematics based on the observation of the China Space Station Telescope (CSST). We find that this method can effectively reduce the interloper effect, and accurately constrain the cosmological parameters for f_i<1%~10%, which is suitable for most future surveys. This method also can be applied to other kinds of galaxy clustering surveys like line intensity mapping.
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