Exploring KSZ velocity reconstruction with $N$-body simulations and the halo model

Abstract

KSZ velocity reconstruction is a recently proposed method for mapping the largest-scale modes of the universe, by applying a quadratic estimator ${\hat{v}}_r$ to the small-scale CMB and a galaxy catalog. We implement kSZ velocity reconstruction in an $N$-body simulation pipeline and explore its properties. We find that the reconstruction noise can be larger than the analytic prediction which is usually assumed. We revisit the analytic prediction and find additional noise terms which explain the discrepancy. The new terms are obtained from a six-point halo model calculation, and are analogous to the $N^{(1)}$ and $N^{(3/2)}$ biases in CMB lensing. We implement an MCMC pipeline which estimates $f_{NL}$ from $N$-body kSZ simulations, and show that it recovers unbiased estimates of $f_{NL}$, with statistical errors consistent with a Fisher matrix forecast. Overall, these results confirm that kSZ velocity reconstruction will be a powerful probe of cosmology in the near future, but new terms should be included in the noise power spectrum.

35 pages, 9 figures

References in corpus (8)

• The imprints of primordial non-gaussianities on large-scale structure: scale dependent bias and abundance of virialized objects
• Measuring primordial non-gaussianity without cosmic variance
• Cosmology with the SPHEREX All-Sky Spectral Survey
• The Atacama Cosmology Telescope: Combined kinematic and thermal Sunyaev-Zel'dovich measurements from BOSS CMASS and LOWZ halos
• Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope
• Using Large Scale Structure to test Multifield Inflation
• Matched filter optimization of kSZ measurements with a reconstructed cosmological flow field
• Analyzing the cosmic variance limit of remote dipole measurements of the cosmic microwave background using the large-scale kinetic Sunyaev Zel'dovich effect

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• Cosmology with the moving lens effect
• Velocity reconstruction with the cosmic microwave background and galaxy surveys
• Reconstructing dark matter distribution with peculiar velocities: Bayesian forward modelling with corrections for inhomogeneous Malmquist bias
• Quantification of high dimensional non-Gaussianities and its implication to Fisher analysis in cosmology
• Robust Neural Network-Enhanced Estimation of Local Primordial Non-Gaussianity
• Subtracting the kinetic Sunyaev-Zeldovich effect from the cosmic microwave background with surveys of large-scale structure
• Inpainting hydrodynamical maps with deep learning
• Maximum likelihood kinetic Sunyaev Zel'dovich velocity reconstruction