SDSS DR17: The Cosmic Slime Value Added Catalog

Abstract

The "cosmic web", the filamentary large-scale structure in a cold dark matter Universe, is readily apparent via galaxy tracers in spectroscopic surveys. However, the underlying dark matter structure is as of yet unobservable and mapping the diffuse gas permeating it lies beyond practical observational capabilities. A recently developed technique, inspired by the growth and movement of Physarum polycephalum 'slime mold', has been used to map the cosmic web of a low redshift sub-sample of the SDSS spectroscopic galaxy catalog. This model, the Monte Carlo Physarum Machine (MCPM) was shown to promisingly reconstruct the cosmic web. Here, we improve the formalism used in calibrating the MCPM to better recreate the Bolshoi-Planck cosmological simulation's density distributions and apply them to a significantly larger cosmological volume than previous works using the Sloan Digital Sky Survey (SDSS, z < 0.1) and the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) Luminous Red Galaxy (LRG, z 0.5) spectroscopic catalogs. We present the 'Cosmic Slime Value Added Catalog' which provides estimates for the cosmic overdensity for the sample of galaxies probed spectroscopically by the above SDSS surveys. In addition, we provide the fully reconstructed 3D density cubes of these volumes. These data products were released as part of Sloan Digital Sky Survey Data Release 17 and are publicly available. We present the input catalogs and the methodology for constructing these data products. We also highlight exciting potential applications to galaxy evolution, cosmology, the intergalactic and circumgalactic medium, and transient phenomenon localization.

Filaments of the Slime Mold Cosmic Web and How They Affect Galaxy Evolution

“…As a starting point for the hyperparameter values, we use previous knowledge of running the MCPM algorithm as well as a priori knowledge based on physical considerations. From the BP simulation, the optimal sampling sharpness was found to be 2.5 at z = 0 and 2.2 at z = 0.5 (Wilde et al 2023). Since the cosmic web becomes more condensed over time, i.e., matter collapses into denser filamentary networks owing to the gravitational pull of structures of ever-increasing masses, we decrease the sampling sharpness with increasing redshift.…”

“…Since the cosmic web becomes more condensed over time, i.e., matter collapses into denser filamentary networks owing to the gravitational pull of structures of ever-increasing masses, we decrease the sampling sharpness with increasing redshift. The persistence coefficient parameter is somewhat dependent on the sparseness of the input data, but previous applications of MCPM (e.g., Burchett et al 2020;Elek et al 2022;Wilde et al 2023) have found it to be optimally around 0.9. The sense distance parameter should roughly follow the volume of the data cube and resolution of the trace field.…”

“…This is what makes the MCPM density field distinct from other methods, such as the Delaunay tessellation field estimator (DTFE; Schaap & van de Weygaert 2000;van de Weygaert & Schaap 2009), which is integrated into DISPERSE and linearly interpolates density field estimates around the locations of galaxies. The MCPM model has been applied to analyze observational galaxy catalogs and fast radio burst data (Burchett et al 2020;Simha et al 2020;Wilde et al 2023). The MCPM density field has successfully recovered the density structure of the cosmic web and provided insights into the intergalactic neutral hydrogen gas (Burchett et al 2020) and hot ionized gas (Simha et al 2020) in the cosmic web.…”

The Evolving Effect of Cosmic Web Environment on Galaxy Quenching

“…) . These are more realistic minimum masses compared to those of large observational surveys such as Sloan Digital Sky Survey (SDSS; e.g., Strauss et al 2002) DR17 (see, e.g., Wilde et al 2023 and our Section 4.3). However, the sharp drop in the number of galaxies in TNG with these higher masses yields increasingly fewer input tracers for DISPERSE, which result in far fewer identified filaments and nodes than in our fiducial…”

“…We are currently applying a new state-of-theart cosmic web reconstruction algorithm called the Monte Carlo Physarum Machine (MCPM), inspired by the Physarum polycephalum (slime mold) organism (Elek et al 2021(Elek et al , 2022, to compare to the local density estimation and global cosmic web characterization from DISPERSE. This method produces continuous cosmic matter densities (as opposed to discrete DTFE densities at the locations of galaxies) and has been applied successfully to both theoretical and observational data sets (e.g., Burchett et al 2020;Simha et al 2020;Wilde et al 2023).…”