Pith. sign in

REVIEW 6 cited by

An iterative reconstruction of cosmological initial density fields

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1804.04738 v2 pith:X2JDAG7I submitted 2018-04-12 astro-ph.CO

An iterative reconstruction of cosmological initial density fields

classification astro-ph.CO
keywords fielddensityinitialiterativematterredshiftspacecosmological
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
Share X Bluesky LinkedIn Reddit HN
read the original abstract

We present an iterative method to reconstruct the linear-theory initial conditions from the late-time cosmological matter density field, with the intent of improving the recovery of the cosmic distance scale from the baryon acoustic oscillations (BAOs). We present tests using the dark matter density field in both real and redshift space generated from an $N$-body simulation. In redshift space at $z = 0.5$, we find that the reconstructed displacement field using our iterative method are more than 80\% correlated with the true displacement field of the dark matter particles on scales $k < 0.10h\ {\rm Mpc}^{-1}$. Furthermore, we show that the two-point correlation function of our reconstructed density field matches that of the initial density field substantially better, especially on small scales ($< 40h^{-1}\ {\rm Mpc}$). Our redshift-space results are improved if we use an anisotropic smoothing so as to account for the reduced small-scale information along the line of sight in redshift space.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

    astro-ph.CO 2024-04 accept novelty 7.0

    DESI measures BAO scales in six redshift bins with 0.52% combined precision using 5.7 million objects, detecting the signal at up to 9.1 sigma and finding larger scales than Planck LCDM at z<0.8.

  2. Standard Reconstruction Shifts the Optimal Input Scale for CNN-Based Density-Field Reconstruction

    astro-ph.CO 2026-07 conditional novelty 6.0

    Applying standard reconstruction before a CNN shifts the optimal input cube for z=10 density reconstruction from ~150-200 h^-1 Mpc to ~38-114 h^-1 Mpc, and a single post-reconstruction CNN beats dual-scale CNN inputs.

  3. Cosmic variance or galaxy bias? Disentangling finite-volume and galaxy formation effects in cosmological analysis

    astro-ph.CO 2026-06 unverdicted novelty 6.0

    Develops a galaxy-biasing formalism for cosmic variance using perturbation theory and tests it on the non-linear BAO shift against N-body simulations.

  4. Cosmic variance or galaxy bias? Disentangling finite-volume and galaxy formation effects in cosmological analysis

    astro-ph.CO 2026-06 conditional novelty 6.0

    Cosmic variance is modeled as Eulerian bias parameters of a finite-volume realization relative to the ensemble average, disentangling it from galaxy bias in the nonlinear BAO shift.

  5. The Linear Point Standard Ruler with DESI DR1 and DR2 Data

    astro-ph.CO 2026-01 conditional novelty 6.0

    Linear-point distance measurements on DESI DR1/DR2 galaxy samples agree with template-based BAO measurements once a cosmology-dependent smearing correction is applied.

  6. Impact of fiducial cosmology in model-agnostic cosmological inference with the BAO feature

    astro-ph.CO 2026-06 unverdicted novelty 4.0

    The Zel'dovich smearing approximation for model-agnostic BAO inference is extended to include fiducial cosmology distortions and validated on AbacusSummit simulations of DESI- and Euclid-like samples, producing unbias...