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Unveiling the small-scale web around galaxies with miniJPAS and DESI

This paper presents the first statistical observational study detecting small-scale filaments around galaxies using miniJPAS and DESI data, validating a new probabilistic DisPerSE method that reveals a mild positive correlation between galaxy connectivity to local filaments and star formation rates.

Original authors: Daniela Galárraga-Espinosa, Guinevere Kauffmann, Silvia Bonoli, Luisa Lucie-Smith, Rosa M. González Delgado, Elmo Tempel, Raul Abramo, Siddharta Gurung-López, Valerio Marra, Jailson Alcaniz, Narciso B

Published 2026-01-28

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Daniela Galárraga-Espinosa, Guinevere Kauffmann, Silvia Bonoli, Luisa Lucie-Smith, Rosa M. González Delgado, Elmo Tempel, Raul Abramo, Siddharta Gurung-López, Valerio Marra, Jailson Alcaniz, Narciso Benitez, Saulo Carneiro, Javier Cenarro, David Cristóbal-Hornillos, Renato Dupke, Alessandro Ederoclite, Antonio Hernán-Caballero, Carlos Hernández-Monteagudo, Carlos López-Sanjuan, Antonio Marín-Franch, Claudia Mendes de Oliveira, Mariano Moles, Laerte Sodré, Keith Taylor, Jesús Varela, Hector Vázquez Ramió

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Big Picture: Finding the Invisible Roads

Imagine the universe not as a random scattering of stars, but as a giant, invisible spiderweb. In this web, galaxies (like our Milky Way) are the nodes, and long, thin strands of gas and dark matter called filaments connect them.

Scientists have long believed that these filaments act like highways, delivering the "fuel" (cold gas) that galaxies need to make new stars. However, while we can see the big, thick highways connecting massive galaxy clusters, it has been incredibly hard to see the small, local roads right next to individual galaxies. It's like being able to see the interstate highway system from space, but unable to see the local streets in your own neighborhood.

This paper is the first study to successfully map these "neighborhood roads" around galaxies.

The Challenge: A Blurry Telescope

The main problem the team faced was blur. To map these roads, you need to know exactly where every galaxy is in 3D space.

The Problem: Most galaxy surveys only give us a "photometric" redshift (an estimate of distance based on color). This is like looking at a distant car through a foggy window; you know it's there, but you aren't 100% sure how far away it is.
The Consequence: If you don't know the distance precisely, the "roads" look fuzzy and broken. You might think a road connects two galaxies when it doesn't, or miss a road that actually exists.

The Solution: A "Super-Sharp" Map

The researchers combined two powerful tools to solve this:

miniJPAS: A survey that takes very detailed pictures of a small patch of sky, giving them a dense list of galaxies (like having a high-resolution photo of a neighborhood).
DESI: A spectroscopic survey that gives extremely precise distance measurements for some of those galaxies (like having a GPS signal for specific cars in that neighborhood).

By mixing these two, they created a "hybrid" map. They used the precise GPS data to calibrate their understanding of the blurry photo data.

The Method: Playing "What If?" 100 Times

Because some data is still a bit blurry, the team used a clever statistical trick. Imagine you are trying to draw a map of a city, but you are slightly unsure of the exact location of every building.

Instead of drawing the map once, they drew it 100 times.
In each drawing, they slightly shifted the position of the galaxies within the range of their uncertainty (like rolling a dice to decide exactly where a building is).
They then looked for roads that appeared in almost all 100 drawings.
The Logic: If a road shows up in 95 out of 100 drawings, it's a real road. If it only shows up in 2, it was just a glitch in the data. This allowed them to filter out the "noise" and find the real, small-scale filaments.

The Discovery: How Connected Are You?

The team focused on a specific measurement called "Connectivity."

The Analogy: Think of a galaxy as a house. "Connectivity" is simply counting how many roads (filaments) are directly attached to that house.
- Low Connectivity: A house in the middle of a desert with no roads leading to it.
- High Connectivity: A house at a busy intersection with many roads leading in and out.

What they found:

Heavier Galaxies have More Roads: They confirmed that galaxies with more mass (heavier "houses") tend to have more filaments connected to them. This matches what computer simulations predicted.
Star Formation: They looked to see if having more roads meant a galaxy was making more stars. They found a mild positive trend: galaxies with more connections seemed to be making stars slightly more actively.
- Note: The paper is careful to say this trend is "mild" and needs more data to be confirmed. It's like noticing that houses on busier streets might have more visitors, but you need to watch more houses to be sure.

Why This Matters

This study proves that we can now see the "local web" around galaxies. By counting how many filaments a galaxy is connected to, astronomers have a new, powerful way to describe a galaxy's environment.

Instead of just asking "Is this galaxy in a crowded cluster or an empty void?", we can now ask, "How many fuel pipelines is this galaxy plugged into?" This helps us understand how galaxies grow, how they get their gas, and eventually, why some stop making stars and go quiet (a process called "quenching").

In short: The team built a new, sharper map of the universe's neighborhood roads, proving that galaxies are indeed connected to a local web, and that the number of these connections might influence how actively they are born and grow.

Technical Summary: Unveiling the small-scale web around galaxies with miniJPAS and DESI

Problem Statement
Understanding the mechanisms driving galaxy star formation quenching remains a central challenge in astrophysics. While internal processes (e.g., AGN feedback) and external environmental effects (e.g., gas stripping) are well-studied, the origin of the cold gas fuel itself is often overlooked. Cosmological simulations predict that cold gas is channeled into galaxies via filamentary structures within the cosmic web. However, direct observational evidence for this process at small scales has been limited. Previous studies have largely focused on large-scale filaments (Mpc widths) connecting galaxy clusters, which at low redshift ( $z \sim 0$ ) are often filled with warm, diffuse gas unlikely to fuel star formation. Furthermore, existing observational studies of galaxy connectivity have been hindered by the lack of high spatial resolution, high tracer density, and sufficient redshift accuracy required to reconstruct the local web (tens of kiloparsecs in width) surrounding individual galaxies.

Methodology
To address these limitations, the authors present the first systematic statistical observational study detecting filaments in the immediate surroundings of galaxies ( $M_\star > 10^{10} M_\odot$ ) within the redshift range $0.2 < z < 0.8$ .

Data Construction: The study utilizes a combined dataset from the miniJPAS survey (providing high-density spectro-photometric data via 56 narrow-band filters) and the DESI Bright Galaxy Survey (providing precise spectroscopic redshifts for a subset of galaxies). This combination yields a final catalogue of 4,328 galaxies, with 2,272 "target" galaxies selected based on stellar mass and distance from survey edges.
Mock Validation: To validate the methodology and assess detection reliability, the authors constructed mock catalogues using a simulated lightcone from the L-galaxies model (Henriques et al. 2015). A Random Forest classifier was trained on miniJPAS data to mimic the survey's selection function and intrinsic property correlations. Redshift errors were modeled to match the specific precision distributions of both the miniJPAS photometric redshifts and DESI spectroscopic redshifts.
Filament Reconstruction:
- Probabilistic Approach: To overcome photometric redshift uncertainties, the authors employ a Monte Carlo (MC) sampling technique. They generate 100 realizations of the galaxy catalogue, varying redshifts according to their probability distributions.
- Local Environment Definition: For each target galaxy, a cylindrical volume (radius 3 pMpc, height 30 pMpc along the line of sight) is defined to encompass the local environment and redshift uncertainties.
- Topology Detection: Filaments are identified within these volumes using the DisPerSE algorithm, which analyzes the topology of the density field derived from the Delaunay Tessellation Field Estimator (DTFE). The density field vertices are mass-weighted by stellar mass to enhance the contrast of the underlying potential.
- Connectivity Metric: The primary environmental metric is connectivity ( $K$ ), defined as the number of filaments attached to a galaxy. This is determined by counting filaments consistently detected across the MC realizations within a specific aperture ( $20 \times R_1$ ) around the target.

Key Results

Validation: The methodology was successfully validated against the mock catalogues. The study demonstrated that the connectivity measurements derived from the observational data agree with the 3D reference estimates from the mock galaxies, confirming the robustness of the probabilistic filament detection method despite photometric redshift uncertainties.
Connectivity Trends: The analysis recovered the expected trend where galaxy connectivity increases with stellar mass.
Star Formation Relation: The authors explored the relationship between small-scale connectivity and galaxy star formation rates (SFR). They identified a mild positive trend, suggesting that galaxies connected to more local filaments may exhibit slightly higher star formation rates. However, the authors explicitly note that this trend requires confirmation by follow-up studies with larger sample sizes.
Filament Detection: The study successfully mapped local filamentary structures within a 3 Mpc physical radius of galaxies, distinguishing them from the larger-scale cosmic web.

Significance and Claims
The paper claims to provide the first systematic observational detection of the "local web" around galaxies, moving beyond the large-scale structures previously studied. By combining high-density miniJPAS data with DESI spectroscopy and a probabilistic reconstruction method, the authors demonstrate that it is possible to map the small-scale cosmic web (widths of tens of kiloparsecs) where cold gas accretion is most likely to occur.

The authors propose galaxy connectivity to local filaments as a powerful and physically motivated metric of environment. Unlike traditional descriptors such as overdensity or group membership, connectivity captures the geometric anisotropy of the field and the specific channels through which gas, satellites, and angular momentum are delivered. This approach offers new insights into the role of cosmic structure in galaxy evolution, specifically regarding the fueling of star formation and the potential mechanisms of quenching via disconnection from these supply channels. The study emphasizes that while the observed positive trend between connectivity and SFR is promising, it remains a preliminary finding requiring further statistical confirmation.