The N5K Challenge: Non-Limber Integration for LSST Cosmology

With the rapid advance of wide-field surveys it is increasingly important to perform combined cosmological probe analyses. We present a new pipeline for simulation-based multi-probe analyses, which combines tomographic large-scale structure (LSS) probes (weak lensing and galaxy clustering) with cosmic microwave background (CMB) primary and lensing data. These are combined at the C ℓ-level, yielding 12 distinct auto- and cross-correlations. The pipeline is based on UFalconv2, a framework to generate fast, self-consistent map-level realizations of cosmological probes from input lightcones, which is applied to the CosmoGridV1 N-body simulation suite. It includes a non-Gaussian simulation-based covariance for the LSS tracers, several data compression schemes, and a neural network emulator for accelerated theoretical predictions. We validate the pipeline by comparing the simulations to these predictions, and our derived constraints to earlier analyses. We apply our framework to a simulated 12×2 pt tomographic analysis of KiDS, BOSS, and Planck, and forecast constraints for a ΛCDM model with a variable neutrino mass. We find that, while the neutrino mass constraints are driven by the CMB data, the addition of LSS data helps to break degeneracies and improves the constraint by up to 35%. For a fiducial Mν = 0.15 eV, a full combination of the above CMB+LSS data would enable a 3σ constraint on the neutrino mass. We explore data compression schemes and find that MOPED outperforms PCA and is made robust using the derivatives afforded by our automatically differentiable emulator. We also study the impact of an internal lensing tension in the CMB data, parametrized by AL , on the neutrino mass constraint, finding that the addition of LSS to CMB data including all cross-correlations is able to mitigate the impact of this systematic. UFalconv2 and a MOPED compressed Planck CMB primary + CMB lensing likelihood are made publicly available.[UFalconv2: https://cosmology.ethz.ch/research/software-lab/UFalcon.html, compressed Planck CMB primary + CMB lensing likelihood: https://github.com/alexreevesy/planck_compressed.]

Section: Boss Dr12mentioning

confidence: 99%

12 × 2 pt combined probes: pipeline, neutrino mass, and data compression

Reeves,

Nicola,

Refregier

et al. 2024

“…(3.15) using the Limber approximation to compute the integrals over χ 1 and χ 2 (see appendix A for the details of the derivation): exquisite precision expected from forthcoming cosmological surveys, alternative approximation schemes are currently developed in order to evaluate this type of integrals with greater accuracy, see for example refs. [49,50]. However, all the result presented in this paper were obtained integrating numerically eq.…”

Section: Peeking "Beyond" the Surveymentioning

confidence: 99%

Cross-correlating radial peculiar velocities and CMB lensing convergence

Giani

Howlett

Ruggeri

et al. 2023

We study, for the first time, the cross correlation between the angular distribution of radial peculiar velocities (PV) and the lensing convergence of cosmic microwave background (CMB) photons. We derive theoretical expectations for the signal and its covariance and assess its detectability with existing and forthcoming surveys. We find that such cross-correlations are expected to improve constraints on different gravitational models by partially breaking degeneracies with the matter density. We identify in the distance-scaling dispersion of the peculiar velocities the most relevant source of noise in the cross correlation. For this reason, we also study how the above picture changes assuming a redshift-independent scatter for the PV, obtained for example using a reconstruction technique. Our results show that the cross correlation might be detected in the near future combining PV measurements from DESI and the convergence map from CMB-S4. Using realistic direct PV measurements we predict a cumulative signal-to-noise ratio of approximately 3.8σ using data on angular scales 3 ≤ ℓ ≤ 200. For an idealized reconstructed peculiar velocity map extending up to redshift z = 0.15 and a smoothing scale of 4 Mpc h -1 we predict a cumulative signal-to-noise ratio of approximately 27σ from angular scales 3 ≤ ℓ ≤ 200. We conclude that currently reconstructed peculiar velocities have more constraining power than directly observed ones, even though they are more cosmological-model dependent.

Reconstructing redshift distributions with photometric galaxy clustering

Peng,

2024

The accurate determination of the true redshift distributions in tomographic bins is critical for cosmological constraints from photometric surveys. The proposed redshift self-calibration method, which utilizes the photometric galaxy clustering alone, is highly convenient and avoids the challenges from incomplete or unrepresentative spectroscopic samples in external calibration. However, the imperfection of the theoretical approximation on broad bins as well as the flaw of the algorithm in previous work [1] risk the accuracy and application of the method. In this paper, we propose the improved self-calibration algorithm that incorporates novel update rules, which effectively accounts for heteroskedastic weights and noisy data with negative values. The improved algorithm greatly expands the application range of self-calibration method and accurately reconstructs the redshift distributions for various mock data. Using the luminous red galaxy (LRG) sample of the Dark Energy Spectroscopic Instrument (DESI) survey, we find that the reconstructed results are comparable to the state-of-the-art external calibration. This suggests the exciting prospect of using photometric galaxy clustering to reconstruct redshift distributions in the cosmological analysis of survey data.