Cosmicflows4 Versus Biteau’s Catalog Reveals Factor-Two Density Differences in Local Universe

Scientists are increasingly focused on accurately mapping the distribution of matter in our local universe, a crucial step for understanding phenomena ranging from ultra-high energy cosmic rays to dark matter annihilation signals. Yifei Li and Glennys R. Farrar, from New York University, alongside collaborators, present a compelling comparison between the CosmicFlows project and a novel galaxy catalog developed by Biteau, utilising a ‘cloning’ technique to account for unseen galaxies. This research reveals significant discrepancies , sometimes exceeding a factor of two , between the two approaches, particularly in obscured regions like the Galactic centre zone of avoidance, and highlights the strengths and limitations of each method for determining local mass density and velocity distributions. By rigorously comparing these maps, the team demonstrates that while CosmicFlows excels at tracing the direction and integrated mass of structures, Biteau’s catalog offers a preferable alternative in the zone of avoidance, provided its limitations regarding radial mass distribution are acknowledged.

Farrar, directly contrasts the density fields derived from galaxy catalogs with those inferred from analyzing galaxy motions and peculiar velocities. This innovative study meticulously compares the density field proposed by J. Biteau (2021) with the quasi-linear density fields of CosmicFlows2 (Y. Hoffman et al0.2018) and the mean posterior field of CosmicFlows4 (A.

Valade 2026), revealing significant discrepancies in certain regions. The team achieved a quantitative assessment of these density models, focusing on the local Large Scale Structure of the Universe and its implications for interpreting cosmic ray origins and dark matter distribution. Utilizing the expanded CosmicFlows-4 catalog, comprising data for 55,877 galaxies, the researchers employed the HAMLET algorithm, a Hamiltonian Monte Carlo sampling technique, to generate mean posterior density fields in real space. This approach leverages the information contained in the relative motions of galaxies, offering a means to circumvent limitations imposed by incomplete galaxy surveys and dust obscuration.
Biteau’s method, while effective at larger distances, relies on a “cloning” technique to fill in data within the ZoA, mirroring galaxies across the obscured region. While this addresses data gaps, the research establishes that this cloning procedure introduces artificial large-scale structures, potentially compromising the accuracy of the density map in those directions. The radial distribution of mass in Biteau’s (2021) model is also found to be less robust due to the influence of line-of-sight peculiar velocities. The research proves that while Biteau’s catalog is preferable to CosmicFlows for determining the direction and integrated mass of structures, it should not be used within the ZoA where the “galaxies” are entirely fictitious. By carefully comparing these distinct approaches, scientists can better constrain models of the local matter distribution and improve our ability to identify deviations caused by individual sources, ultimately enhancing our knowledge of the cosmos.

Local Universe Density Field Comparison and Smoothing reveals

Scientists meticulously compared three distinct density fields of the local universe to refine our understanding of matter distribution and its implications for cosmology. This comparative analysis hinged on a robust methodology for smoothing galaxy data and mapping density fluctuations across vast cosmic distances. The study pioneered a spherical shell-based smoothing method, dividing 3D space into shells each 1.43 Mpc wide, centered on the observer. Within each shell, the team employed the Healpix software package at NSIDE = 32, partitioning the sky into equal-area pixels of approximately 3.36 deg², creating voxels uniquely identified by shell and pixel index for consistent data comparison.
This innovative approach facilitated a direct comparison of the three density fields, allowing researchers to pinpoint regions of significant divergence and assess the reliability of each model. Researchers harnessed the significantly expanded CosmicFlows-4 (CF4) catalog, comprising 55,877 galaxies (Tully et al0.2023), to generate a mean posterior density field using the HAMLET algorithm (Valade et al0.2022). HAMLET employs Hamiltonian Monte Carlo sampling, iteratively refining initial conditions to accurately match the observed z = 0 velocity field, delivering a highly constrained reconstruction of the local matter distribution. The team then adopted these mean density fields in real space to create detailed maps for visual analysis and quantitative comparison.

To assess the impact of incomplete data, the work also examined the Biteau (2021) catalog, which incorporates 489,000 galaxies within 350 Mpc. Biteau’s method assigns a mass-upscaling factor to each galaxy based on luminosity, distance, and galactic latitude, effectively recovering galaxy clusters at large distances, however, the study acknowledges potential underestimation of secondary structures like filaments. Crucially, the team addressed data gaps in the ZoA by replicating galaxies across the boundary, mirroring their properties to maintain density continuity, a technique adapted from Lavaux (2016), though the researchers noted potential artificiality introduced by this “cloning” process.

Density Model Discrepancies Near Zone of Avoidance require

Experiments revealed that the radial distribution of mass in Biteau (2021) is less reliable due to the challenges of interpreting line-of-sight peculiar velocities, while the angular positions of structures in CosmicFlows sometimes lack congruence with observed galaxy catalog evidence. Data shows that beyond 40 Mpc, Biteau’s catalog and CosmicFlows4 closely resemble each other, both successfully identifying structures like NGC 5864, Antlia, and Fornax, Eridanus, which are less apparent in CosmicFlows2. The team measured a notable concentration of the Pavo-Indus Clouds within the 40-60 Mpc range in Biteau’s maps, a feature almost absent in the corresponding CosmicFlows maps, representing the largest difference between the two methodologies aside from the effects of cloning. Further analysis indicated that the maximum log(ρ) value for Biteau (10 Mpc) in the 20-40 Mpc range reached 0.39, while the minimum value plummeted to -0.77, showcasing a substantial dynamic range in density estimations.

The researchers found that the maximum log(ρ) value for CosmicFlows4 in the 60-80 Mpc range was 1.24, with a minimum of -0.68, demonstrating a similar, though less extreme, range of density values. The study highlights that the “cloning” process in Biteau’s model artificially inflates density estimations in the ZoA, adding approximately 50% to the mass in that region. The comparison of density maps at various distances, from 20-40 Mpc to 130-180 Mpc, demonstrated consistent differences in the prominence and distribution of structures like the Hydra-Centaurus supercluster and the Perseus-Pisces supercluster across the three models. These findings underscore the importance of carefully considering the methodologies and limitations of each model when studying the large-scale structure of the universe and estimating local mass densities.

Local Density Reconstructions Differ Significantly across brain regions

The research involved smoothing galaxy data and comparing density fields across spherical shells using a Healpix representation, allowing for a consistent basis for analysis across the different catalogues. The authors acknowledge limitations stemming from line-of-sight peculiar velocities affecting the radial mass distribution in the Biteau catalogue, and inconsistencies between CosmicFlows’ angular structure positions and observed galaxy evidence. Future research could focus on refining the modelling of peculiar velocities and improving the alignment of angular structures with observational data, potentially through incorporating more comprehensive galaxy surveys.