DESI's Probabilistic Map of the Cosmic Web Reveals How the Universe's Skeleton Shapes Galaxy Evolution
Preprint using DESI Early Data (175 deg², four tracers) introduces a probabilistic ASTRA catalog classifying galaxies into cosmic web environments without density reconstruction. It shows clear environmental effects on star formation consistent with GAMA/SDSS but with quantified uncertainties, linking galaxy evolution to dark energy studies.
This preprint (arXiv:2604.01456), which has not yet been peer-reviewed, presents the first public cosmic-web environment catalog derived from the Dark Energy Spectroscopic Instrument Early Data Release. Researchers developed the ASTRA algorithm to classify every object into one of four environments—void, sheet, filament, or knot—by combining real galaxy positions with matched random catalogs across 100 realizations per tracer and sky zone. Importantly, the method avoids reconstructing a continuous density field, reducing potential biases in sparse regions. The dataset covers approximately 175 square degrees using four extragalactic tracers: Bright Galaxy Survey (BGS), Luminous Red Galaxies, Emission Line Galaxies, and Quasars. Sample size is modest compared to DESI's full planned survey, representing an early slice that limits statistical power and cosmic variance coverage.
The team calibrated thresholds against GAMA survey volume-filling fractions using BGS as an anchor and recovered consistent web morphology across tracers. Results align with prior GAMA, COSMOS, and SDSS studies on the environmental dependence of star formation, but add probabilistic membership and classification entropy for each object. A normalized mutual information analysis on BGS galaxies shows strong statistical associations between environment and galaxy color, stellar mass, and specific star formation rate.
Previous coverage and earlier catalogs often missed the uncertainty inherent in environment assignment; many studies forced hard classifications from noisy density fields, potentially overinterpreting results in underdense regions. This work synthesizes with Libeskind et al.'s cosmic web classification frameworks (arXiv:1409.6305) and the GAMA environmental quenching papers (arXiv:1508.02030), revealing that DESI's approach provides more robust statistics at slightly higher redshifts. What remains under-appreciated is the direct bridge to DESI's core cosmology mission: the same spectroscopic data used for baryon acoustic oscillation measurements of dark energy now also quantifies how large-scale structure modulates galaxy evolution, potentially tightening constraints on structure growth rates.
Analytically, these patterns suggest 'nurture' effects dominate in knots and filaments where gas accretion and mergers differ markedly from void environments. Limitations include the small survey footprint, tracer-specific selection biases, and calibration dependence on lower-redshift GAMA data. Nonetheless, the open-source pipeline and public catalog enable new lines of inquiry into whether dark energy models correctly predict the observed interplay between cosmic expansion and web-driven galaxy transformation.
HELIX: This probabilistic cosmic web catalog from DESI shows that galaxy properties like star formation are tightly linked to their position in the universe's filamentary network, offering a new way to test how dark energy influences both cosmic expansion and the growth of structure.
Sources (3)
- [1]Primary Source(https://arxiv.org/abs/2604.01456)
- [2]GAMA Environmental Dependence of Star Formation(https://arxiv.org/abs/1508.02030)
- [3]Cosmic Web Classification Review(https://arxiv.org/abs/1409.6305)