Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations

arXiv:2605.30440 · astro-ph.GA · Submitted 2026-05-28 · Read on arXiv

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Introduction to the show: ident: Astrophysics Radio. Generated commentary on the latest astrophysics papers.

Vera: Today's paper: "Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations".

Jocelyn: Detailed Research Summary: Environmental Regulation of Galaxy Evolution within Cosmic Voids This research investigates how large-scale cosmic environments, specifically cosmic voids,

Vera: First, who's behind it and why it matters.

Paper summary: Vera: We’ve just touched on how this paper uses mock data to examine galaxy properties in cosmic voids across a wide redshift range, and now I want to quickly summarize the core argument of "Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations" Vera Essentially, the thesis is that cosmic voids are environments where we can study galaxy evolution with less interference from the intense physical processes seen in denser regions Vera

Jocelyn: That’s a good starting point, Vera; so what is the central claim they make about these voids and why should we care about this research right now? Is it just mapping out empty space? Jocelyn

Subrahmanyan: No, Jocelyn; the study claims that by using tools like the GAEA mock-observation lightcone which mimics data from Euclid, they can investigate the properties and merger histories of galaxies specifically as a function of their location in these underdense regions Subrahmanyan This matters because it allows us to probe how galaxies evolve when they are situated in environments that are much less dense than typical galaxy clusters or filaments Subrahmanyan

Vera: Right, and the sample they looked at spans a redshift range from zero point four to one point eight, which is exactly where we expect H alpha emission lines to be accessible with Euclid’s slitless spectroscopy Vera So why is this specific redshift range important for understanding these voids? Vera

Jocelyn: It matters because it covers the epoch where we can actually see those specific spectral signatures that allow us to classify the galaxies and measure their properties accurately within these environments Jocelyn

Subrahmanyan: Precisely, and the paper uses this mock lightcone to test how galaxy evolution manifests in these low-density settings compared to what is seen in denser regions, providing constraints on our understanding of structure formation physics Subrahmanyan It helps us see if the environment truly dictates the galaxy’s fate or if other factors are more important Subrahmanyan

Vera: And this work is important because it sets up the framework for what Euclid will be able to observe; it’s essentially preparing us for how we can use that future data to look specifically at these voids Vera It shows how the large-scale structure itself shapes what we see in individual galaxies Vera

Jocelyn: So, to summarize simply, the paper is using a high-quality simulation framework to show that galaxies in cosmic voids have different evolutionary paths than those in dense environments, and this comparison helps us understand the fundamental physics of how structure forms across the Universe Jocelyn

Subrahmanyan: Exactly; it provides concrete evidence that environmental dependencies on galaxy properties are real when we look at underdense regions, which is a key piece for connecting cosmological models to observable galaxy populations Subrahmanyan

Vera: So as we move into the next part, where we discuss the specific findings derived from this analysis, I think it’s time to get into what these galaxies are actually doing differently in those voids Vera

Jocelyn: I agree; I’m eager to hear about those specific differences in star formation and mass assembly they uncovered Jocelyn

Subrahmanyan: We can expect the paper to detail the observed trends, which we know from our discussion on mass segregation and star formation rates, giving us a clearer picture of the physics at work Subrahmanyan

Conclusion: Vera: We’ve covered the specifics of how this paper uses mock data to explore galaxy evolution within cosmic voids across various redshifts, and now I want us to wrap up by looking at the broader implications of "Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations" Vera The authors are G. Papini et al., and their work is really about using these underdense regions as a controlled environment for studying galaxy formation Vera

Jocelyn: I think the implication is that our understanding of how galaxies grow might need to incorporate this environmental context more explicitly, recognizing that voids aren't just empty space but have an active influence on their inhabitants Jocelyn It suggests that we can’t study galaxies in isolation if we want a complete picture of cosmic evolution Jocelyn

Subrahmanyan: From a theoretical standpoint, this work reinforces the idea that structure formation is inherently environmental; whether you are in a dense cluster or an underdense void, the local density dictates how interactions occur and how mass is accumulated over time Subrahmanyan It’s about refining those large-scale structure models to account for these distinct evolutionary pathways Subrahmanyan

Vera: So, to put it simply, the implication is that we are getting better at using observations from future missions like Euclid to see how the environment shapes galaxy properties in a way that current methods might miss Vera It’s about seeing these subtle environmental imprints more clearly Vera

Jocelyn: And what does this mean for the actual universe? Does it change how we think about cosmic structure formation on a grand scale, or is this just fine detail for galaxy studies? Jocelyn

Subrahmanyan: It’s certainly a refinement of the picture, suggesting that the processes governing galaxy assembly are sensitive to the underlying dark matter distribution in ways that need careful modeling Subrahmanyan It gives us better tools to test our assumptions about how gravity operates on galactic scales within different cosmic densities Subrahmanyan

Vera: So, we’re looking at a powerful tool here for future observational astronomy; this paper shows us exactly what kind of signals we should be hunting for when we look at the large-scale structure of the universe Vera It’s about turning those big cosmic maps into detailed stories about individual galaxies Vera

Jocelyn: I think it really gives us a better way to use Euclid data, knowing that these voids are crucial areas to investigate for understanding galaxy evolution Jocelyn

Subrahmanyan: Indeed, by providing this foundation in simulation, the authors are setting a clear path for what kind of observational results we should expect from the Euclid Deep Survey regarding these environmental influences Subrahmanyan

Vera: That’s it for our discussion on "Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations." We’ve really explored how the structure of the cosmos dictates how galaxies evolve, and it's a fascinating topic to keep watching Vera

ESO

astro-ph.GA

Submitted: 2026-05-28

Updated: 2026-05-28

DOI: 10.1051/0004-6361/202659804

License: http://creativecommons.org/licenses/by/4.0/

Importance score: 89/100

The gist: This research investigates how large-scale cosmic environments, specifically cosmic voids, regulate the properties and assembly histories of galaxies as a function of their location within these

Key concepts

Cosmic Voids
These are large, underdense regions in the universe where there is very little matter. The study examines how living things like galaxies behave when they are situated within these vast empty spaces to see if the lack of surrounding matter changes their development.
Mass Segregation
This refers to the trend where more massive galaxies tend to cluster together in denser areas of the universe. The research showed that galaxies near void centers are systematically less massive than those in dense environments, indicating a difference in how mass is distributed based on location.
Specific Star Formation Rate (sSFR)
This measures how quickly a galaxy is forming new stars relative to its existing size. Galaxies near voids showed higher sSFRs, meaning they were actively forming stars more rapidly than galaxies in crowded regions at the same time.
Delayed Stellar Mass Assembly
Galaxies in low-density voids grow their stellar mass much slower. They take about half a billion years longer to reach 50% of their final mass compared to galaxies in dense environments, proving that the environment controls the speed of galaxy growth.

Terminology

Summary

This research investigates how large-scale cosmic environments, specifically cosmic voids, regulate the properties and assembly histories of galaxies as a function of their location within these underdense regions. The study leverages the GAlaxy Evolution and Assembly (GAEA) mock-observation lightcone, which replicates data from the Euclid Deep Survey, to explore these environmental dependencies across a significant redshift range (0.4 < z < 1.8).

A critical component of this study is the robust identification of cosmic voids. The authors employed a comprehensive comparison of void-finding algorithms to ensure that the observed environmental trends are genuine physical signatures rather than artifacts of a specific detection method. They tested four distinct void-finding approaches:

  1. Revolver: A tessellation and watershed-based approach, which is used as the primary analysis method.

  2. DisPerSE: A tessellation-based finder applied to the mock lightcone, with galaxies weighted by stellar mass and a persistence threshold of N sigma = 3.

  3. Sparkling: A spherical finder utilizing a fixed integrated density contrast (= -0.7).

  4. 2D void-finder: A photometric approach that measures transverse radii while fixing the line-of-sight radius at 50, h-1 Mpc.

The consistency across these diverse methods is highly significant: the qualitative trends observed—namely, that galaxies closer to void centers exhibit distinct properties—are robust regardless of the geometric assumptions or dimensionality of the finder used. This cross-validation confirms that the observed dependence on environment is a genuine imprint of the underdense large-scale structure, not an artifact of any single void-identification technique. Furthermore, a 'Ground Truth' catalogue based on a De Lucia et al. (2024) model was used to verify that these trends are qualitatively recovered in the DR1 data.

The analysis reveals several statistically significant and physically coherent patterns linking galaxy properties to their void-centric distance (d cc/R v) and local density contrast:

1. Mass Segregation:

Galaxies located closer to void centers (d cc 0.7 R v) are systematically less massive compared to those in denser regions. Specifically, the fraction of massive systems (10(M*/M) > 10.5) increases from approximately 20% in void interiors to about 30% in dense environments. While this mass segregation is measurable and statistically distinct (pKS 10-5), the amplitude of this difference is subtle, suggesting a nuanced environmental influence on galaxy mass.

2. Star Formation Activity:

Despite matching stellar mass distributions across environments, galaxies situated closer to void centers exhibit higher specific star formation rates (sSFRs) than their counterparts in denser regions at all observed redshifts. This indicates enhanced star-forming activity within the low-density environment. Importantly, this environmental separation in star formation activity weakens as redshift increases, becoming statistically weak for z 1.15. This suggests that the regulatory effect of the environment on star formation strengthens only after cosmic structures have had sufficient time to mature.

3. Morphology and Bulge Fraction:

The sample is predominantly disc-dominated, with bulge-to-total stellar mass ratios (B/T) generally below 0.2, a trend consistent across all redshifts and environments. However, galaxies closer to void centers possess lower B/T ratios than those in denser regions. This distinction remains significant up to z about 1.15, implying that morphological transformations—the transition towards more bulge-dominated systems—are more frequently driven by environmental processes in higher-density settings over cosmic time.

4. Halo and Central Galaxy Fractions:

The fraction of central galaxies increases toward lower redshifts and closer proximity to void centers, with regions closest to void centers hosting between 70% to 80% centrals at low redshift and high redshift, respectively. Furthermore, satellite galaxies found near void centers are preferentially hosted in less massive dark matter haloes compared to their counterparts in high-density environments.

5. Delayed Stellar Mass Assembly:

A crucial finding concerns the assembly timeline: galaxies in low-density regions assemble their stellar mass more slowly. They reach 50% and 90% of their observed stellar mass approximately ** 0.5–1 Gyr later** than galaxies in denser environments. This delay is statistically significant (pKS 10-5), providing strong evidence for a coherent picture of gradual, extended stellar mass growth in underdense regions.

**6.

Improvements for AI systems

Here are the potential improvements for AI systems, based on this scientific paper, along with what those improved systems could achieve:

)Improved System: Environment-Aware Galaxy Evolution Predictor (EAGEP)

This system would integrate the findings from Section 4 (Galaxy Properties in Voids) and Section 6.1 (Parametrisation of Environment).

Improvements:

  1. Multi-Parametric Environmental Classification: Instead of relying solely on void-centric distance, the system should incorporate a two-parameter framework combining normalized void-centric distance and local galaxy density contrast (as suggested in Section 6.1). This would allow for a more nuanced classification of environments, explicitly identifying tendrils (voids with high local density) and bubbles (low-density peripheral substructures).
  1. Redshift-Dependent Trend Modeling: The system must model how environmental trends change over cosmic time, specifically incorporating the finding that the separation between environments weakens at higher redshifts (Section 4.2). This requires fitting models with redshift as a key variable to accurately predict property evolution in different epochs.
  1. Mass-Matched Property Isolation: The system should implement the mass-matching procedure (Section 4.1) to isolate the effect of environment from stellar mass dependence when predicting other properties like specific star formation rate (sSFR) or bulge-to-total ratio (B/T).

What the Improved System Can Do:

The EAGEP system can accurately predict and categorize galaxy properties across different cosmic epochs based on their local large-scale environment. Specifically, it can:

  1. Identify if a galaxy's observed properties (mass, sSFR, morphology) are systematically influenced by its specific location within the cosmic web structure (e.g., is it in a true void core vs. a dense filament?).
  1. Predict the expected star formation activity of galaxies at any given redshift based on their environment, accounting for the weakening environmental signal at high redshifts.
  1. Determine if observed morphological transformations (like changes in B/T ratio) are more likely to occur in dense environments versus voids, providing a quantitative tool to probe the role of isolation in galaxy quenching or disc preservation.

)Improved System: Merger History Assembly Modeler (MHAM)

This system would utilize the results from Section 5 (Merger histories of galaxies in voids), specifically focusing on timing and type.

Improvements:

  1. Delayed Merger Timing Prediction: The system must be trained to predict the lookback times for major, minor, and mini mergers based on the galaxy's environment and redshift. It should learn that while major mergers are early in all environments, minor/mini mergers are significantly delayed (by 0.5–1 Gyr) in low-density regions (Section 7).
  1. Merger Type Specificity: The system should distinguish between merger types, learning that the late-time assembly of void galaxies is dominated by minor and mini mergers, not major ones.
  1. Selection Bias Correction Module: An internal module must be developed to account for the selection bias (Hα-selected sample) by comparing its predictions against a Ground Truth catalogue (Section 2.2), ensuring that the predicted merger frequency is representative of the full galaxy population, not just star-forming ones.

Abstract

The evolution of galaxies is profoundly influenced by the environment in which they reside. Cosmic voids serve as pristine laboratories for studying galaxy evolution in the relative absence of the complex physical processes that dominate denser environments. In this study, we investigate galaxy properties and merger histories as a function of environment using the GAlaxy Evolution and Assembly (GAEA) mock-observation lightcone replicating the Euclid Deep Survey as foreseen for the first Euclid data release. The H α-selected galaxy sample spans the redshift range 0.4 < z < 1.8, corresponding to the interval over which H α is accessible to Euclid slitless spectroscopy. We classify galaxies based on their void-centric distance and local density contrast, and compare their stellar mass, specific star formation rate, bulge-to-total stellar mass ratio, and halo mass across different environments. We further analyse the merger histories of these galaxies to study their assembly evolution. We find that galaxies located closer to void centres (d cc 0.7 R v) are less massive, more actively star-forming, and more disc-dominated than galaxies in denser regions. Merger histories indicate that void galaxies do not experience fewer mergers, but rather that mergers occur later relative to galaxies in high-density regions. These results support a scenario in which the environment regulates the timing and nature of mergers rather than their overall frequency, producing a slower evolutionary path in low-density regions. We conclude by discussing the extent to which these trends are shaped by environmental parametrisation methods and observational selection effects. Our analysis provides a framework for interpreting forthcoming Euclid data and demonstrates Euclid's potential to identify cosmic voids and probe environmental effects on galaxy evolution.

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