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Implementation and Validation of Galaxy Clustering Algorithms for Euclid Observations

This document outlines the implementation and validation efforts for galaxy clustering algorithms associated with the Euclid mission. Led by researchers from various institutions across Europe, the project aims to develop prototypes for computing key cosmological statistics, including correlation functions, power spectra, and the bispectrum. Key challenges include handling massive datasets and ensuring statistical errors are controlled to achieve the precise measurements required by Euclid. The work package encompasses both software development and methodological advancements, crucial for the mission's success.

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Implementation and Validation of Galaxy Clustering Algorithms for Euclid Observations

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  1. WP-B1.3: Galaxy clustering - Implementation EnzoBranchini (INAF - Brera, Italy) Lado Samushia (University of Portsmouth, UK) • WP-B2.3: Galaxy clustering – Validation Carlton Baugh (Durham University, UK) MatteoViel (INAF – Trieste, Italy)

  2. Galaxy Clustering – Implementation WP deliverables: Software prototype for computing • Correlation function. • Power-spectrum. • Three-point function. • Bispectrum. and cosmology-independent errors WP Status: • 25 members (mostly staff) - 5 nations. • Mailing list created, census of available expertise performed.

  3. Challenges Standard algorithms for computing 2pt and 3pt statistics exits. They have been tested and used on previous surveys. Numerical challenges: • 50,000,000 galaxies in spectroscopic survey. • 1,500,000,000 galaxies in imaging survey. • Full sky

  4. Challenges Methodology challenges: • Confusion/Purity • Angular dependence of systematics due to slitless spectroscopy • Density dependence of systematics due to slitless spectroscopy

  5. Challenges • Euclid will make possible extremely high precision measurements of clustering statistics. • Level 0 requirements are σ(w0). • Need to make sure that observational/methodology induced statistical errors are under control so that Euclid data can achieve its statistical promise.

  6. sub-workpackages (Software) Software prototype for ξ(σ,π), + covariance matrix. Software prototype for P(k,μ) + covariance matrix. Software prototype for η+ covariance matrix. Software prototype for B + covariance matrix.

  7. sub-workpackages (methodology + systematics) Methodology Pair/Triplet counting algorithms Window functions Cosmology-independent errors Observational systematics angular systematics (star density, zodiacal light, ) radial systematics (redshift failure, confusion) Deep field/Calibration Instrumental systematics (degradation with time, etc.)

  8. Link to other WPs Development/Quality control WP-A1 Management/Inventory WP-A2 Documentation/Definition WP-A3 Selection functions Galaxy clustering – Implementation WP-B1.3 Clusters WP-B1.4 Internal data WP-B1.1 Galaxy clustering – Validation WP-B2.3

  9. Interface with other OUs OU-SIM Mock photometric/spectroscopic surveys OU-PHZ/MER Preliminary version of photometric survey + calibration OU-LE3/Galaxy clustering implementation Preliminary version of spectroscopic survey + calibration OU-SIR/SPE/MER

  10. Interface with GCSWG • Coordinate basis for computing clustering statistics • gauge invariant coordinates z, θ • Generic module for z, θ-> x, y, z • Correlation between cosmology independent and cosmology dependent covariance matrices.

  11. Galaxy Clustering - Validation Validation tasks: • Algorithms for computation redshift-space P(k1,k2) • Algorithms for computation of xi(r_p, pi) • Algorithms for computation of covariance matrices • Algorithms for computation of 3pt function. • Algorithms for likelihood calculation to include cosmology independent terms

  12. Galaxy Clustering - Validation Inputs: • Validation criteria from Galaxy clustering SWG • Algorithms developed and tested by WP-B1.3 • Mock catalogues (with masking + selection functions) from OU-SIM plus Cosmological Simulations WG • Preliminary version of Euclid spectroscopic & photometric surveys

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