Isobaric Reconstruction of the Baryonic Acoustic Oscillation

Abstract

In this paper, we report a significant recovery of the linear baryonic acoustic oscillation (BAO) signature by applying the isobaric reconstruction algorithm to the non-linear matter density field. Assuming only the longitudinal component of the displacement being cosmologically relevant, this algorithm iteratively solves the coordinate transform between the Lagrangian and Eulerian frames without requiring any specific knowledge of the dynamics. For dark matter field, it produces the non-linear displacement potential with very high fidelity. The reconstruction error at the pixel level is within a few percent, and is caused only by the emergence of the transverse component after the shell-crossing. As it circumvents the strongest non-linearity of the density evolution, the reconstructed field is well-described by linear theory and immune from the bulk-flow smearing of the BAO signature. Therefore this algorithm could significantly improve the measurement accuracy of the sound horizon scale. For a perfect large-scale structure survey at redshift zero without Poisson or instrumental noise, the fractional error is reduced by a factor of 2.7, very close to the ideal limit with linear power spectrum and Gaussian covariance matrix.

5 pages, 3 figures, accepted version

References in corpus (6)

• Improving Cosmological Distance Measurements by Reconstruction of the Baryon Acoustic Peak
• Nonlinear Evolution of Baryon Acoustic Oscillations
• Iterative initial condition reconstruction
• Reconstructing the cosmic density field with the distribution of dark matter halos
• Halo nonlinear reconstruction
• The Monge-Ampère-Kantorovich approach to reconstruction in cosmology

Cited by in corpus (30)

• Modeling Biased Tracers at the Field Level
• A rigorous EFT-based forward model for large-scale structure
• An iterative reconstruction of cosmological initial density fields
• Probing Primordial Chirality with Galaxy Spins
• New method for initial density reconstruction
• Baryon acoustic oscillations reconstruction using convolutional neural networks
• A fast semi-discrete optimal transport algorithm for a unique reconstruction of the early Universe
• Euclid: The search for primordial features
• Nonlinear reconstruction of redshift space distortions
• CUBE: An Information-optimized parallel Cosmological $N$-body Algorithm
• Reconstructing the baryon acoustic oscillations using biased tracers
• Improving baryon acoustic oscillation measurement with the combination of cosmic voids and galaxies
• Perturbation theory for the redshift-space matter power spectra after reconstruction
• Accurate Baryon Acoustic Oscillations reconstruction via semi-discrete optimal transport
• Covariance of the redshift-space matter power spectrum after reconstruction
• BAO scale inference from biased tracers using the EFT likelihood
• Biased tracer reconstruction with halo mass information
• Understanding the Reconstruction of the Biased Tracer
• BAO Modulation as a Probe of Compensated Isocurvature Perturbations
• Nonlinear reconstruction of features in the primordial power spectrum from large-scale structure
• The cosmic spiderweb: equivalence of cosmic, architectural, and origami tessellations
• Extended Fast Action Minimisation method: application to SDSS-DR12 Combined Sample
• Straightening the Ruler: Field-Level Inference of the BAO Scale with LEFTfield
• Lagrangian displacement field estimators in cosmology
• Baryon Acoustic Oscillations analyses with Density-Split Statistics
• Dipole Distortions in the Intergalactic Medium
• Lagrangian space remapping and the angular momentum reconstruction from cosmic structures
• Constraining effective neutrino species with bispectrum of large scale structures
• Iterative reconstruction excursions for Baryon Acoustic Oscillations and beyond
• Searching optimal scales for reconstructing cosmological initial conditions using convolutional neural networks