Analysis Tools for large-scale galaxy surveys

Our understanding of the Universe has been reshaped over the past decade with the study of the Cosmic Microwave Background combined with the analysis of galaxy distributions on large scales from surveys like the recent BOSS, VIPERS and WiggleZ. This led to the development of a well-founded cosmologial model, where structure grows hierarchically, mainly due to gravitational instabilities, from small initial perturbations to a vast distribution of galaxies in clusters, filaments and voids.
Yet, there are still many open questions that need to be understood to strenghten the fundation of such cosmological paradigma or change it altogether.
Foremost, the striking discovery that the expansion of the Universe is accelerating, with explanations that range from new repulsive forces, as the dark energy, or the failure of Einstein's General Relativity. Not least, the overwhelming evidence that most of the counterpart to such acceleration is provided by a yet un-discovered form of matter, the dark-matter. The physics of the early inflationary universe can also be understood from large-scale structures. Broadly speaking the aims are
Dynamical Dark Energy: Is the dark energy simply a cosmological constant, or is it a field that evolves dynamically with the expansion of the Universe?
Modification of Gravity: Alternatively, is the apparent acceleration instead a manifestation of a breakdown of General Relativity on the largest scales, or a failure of the cosmological assumptions of homogeneity and isotropy?
Dark Matter and neutrinos: What is dark matter? What is the absolute neutrino mass scale and what is the number of relativistic species in the Universe?
Initial Conditions: What is the power spectrum of primordial density fluctuations, which seeded large-scale structure? Are they described by a Gaussian probability distribution?
Solving these open issues make the research in Cosmology very exciting and timely!
The scientific community has tackled these challenges through large astronomical surveys that scan the way millions of galaxies distribute across huge volumes and well into the past, when the Universe was half its current age. We can then relate the distribution of galaxies to the aforementioned problems through the use of n-point correlation functions.
Several such surveys are ongoing, just finished or will start in the near future. Their common denominator is the unprecedented level of precision at which they will render the large scale structure of the Cosmos. In particular we highlight the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS), the ESA/Euclid satellite and Dark Energy Spectroscopic Instrument (DESI). All of them are state-of-the-art surveys in which our group is actively involved, often leading science working groups.
Yet, the exquisite statistical precision this data will achieve needs to be matched by an unprecedented level of accuracy in our theoretical models and scientific pipelines or tools to interpret it. And this level of accomplishment has not been reached yet because the physics becomes non-linear and more complex in the most interesting scales, those of best signal to noise. Unless our models improve we are forced to use data in a regime were theory is simpler but where statistical error bars are larger.

To best exploit the galaxy survey data we must model complex processes such as the nonlinear gravitational collapse of the dark matter, the way galaxies form and trace this matter field (galaxy biasing) and the contamination of derived redshifts from peculiar velocities (redshift space distortions). These represent some of the biggest obstacles in interpreting galaxy clustering data as well as weak gravitational lensing. We also need to have tools for a detailed control of different observational systematics and scientific pipelines to combined different observables.
Our group is actively involved in developing and testing models of structure formation based on perturbation theory (PT) to account for:
Nonlinear clustering: At the linear and weakly nonlinear level the gravitational clustering of dark matter can be well understood using PT, giving the large-scale behavior of the two-point correlations. However, the level of future statistical errors makes the use of standard PT very limited. Over the past years novel re-summation techniques were used to incorporate higher order terms and go beyond standard PT. Our group leads some of this effort and its extension to non-standard cosmologies.
Galaxy Biasing: On large-scales gravity dominates and we expect galaxies to fall into the gravitational potential wells of the dark-matter. In detail we need to study statistically how galaxies are distributed with respect to dark matter, something we call galaxy biasing. On large-scales galaxy biasing is linear and local. This is no longer true in a large range of observationally interesting scales, where the relation becomes non-local and non-linear. Understanding this regime is one of our key goals.
Redshift Space Distortions: The recession velocity of galaxies away from us, due to the cosmic expansion, is used to measure their distances. But galaxies have their own peculiar velocities on top of the cosmic flow. On the one hand this contaminates the measurement of distances. On the other, represents a unique window to study velocity flows that set the growth rate of structure. And through this attack the dark energy problem. Understanding this contamination is also one of our goals. In parallel to the theoretical lines we also focus in

Photometric Redshifts: We are also active in understanding how to best derive galaxy distances from narrow or broad-band photometry, rather than spectrography.  This includes different techniques (template or machine learning photo-z, clustering redshifts) and is a key necessity in PAU and DES for instance.

Combination of probes: Probes such as 2 and 3-point correlations, redshift space distortions, galaxy environment, intrinsic alignment correlations, galaxy/cluster/halo abundance and weak gravitational lensing, hold a wealth of information. While we have successful models to interpret these separate measurements on linear scales, we need to better exploit their combination and model their covariance, taking advantage of photometric redshift self calibration, sample variance cancellation and joint marginalization over systematic and model uncertainties.

Science Pipelines: We develop pipelines that integrate the models described above into likelihood packages to explore what cosmological parameters agree better with the data. We do this in combination with the use and development of cosmological simulations to calibrate the models and estimate statistical errors. 
The end product on the line of research, besides basic knowledge, is the integration and development of analysis tools for optimization and combination of survey data.
Selected publications
- "Large-scale structure of the Universe and cosmological perturbation theory"
F. Bernardeau, S. Colombi, E. Gaztañaga, R. Scoccimarro
Physics Reports, Vol. 367, 1-3, p. 1-248 (2002)
- "MPTbreeze: A fast renormalized perturbative scheme"
M. Crocce, R. Soccimarro, F. Bernardeau
Monthly Notices of the Royal Astronomical Society, Vol. 427, 3, p. 2537 (2012)
- "Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data"
M. Crocce, J. Carretero, A. Bauer, et al.
Monthly Notices of the Royal Astronomical Society, Vol. 455, 4, p. 4301 (2016)
- "Linear and non-linear bias: predictions vs. measurements"
K. Hoffmann, J. Bel, E. Gaztañaga
Monthly Notices of the Royal Astronomical Society, Vol. 465, 2, p. 2225 (2017)
Senior Institute members involved
M. Crocce, F. Castander, P. Fosalba and E. Gaztañaga.
Institute of Space Sciences (IEEC-CSIC)

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An institute of the Consejo Superior de Investigaciones Científicas

An institute of the Consejo Superior de Investigaciones Científicas
Affiliated with the Institut d'Estudis Espacials de Catalunya

Affiliated with the Institut d'Estudis Espacials de Catalunya