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arxiv: 2503.15313 · v2 · submitted 2025-03-19 · 🌌 astro-ph.GA

Euclid Quick Data Release (Q1): The evolution of the passive-density and morphology-density relations between z=0.25 and z=1

Euclid Collaboration: C. Cleland , S. Mei , G. De Lucia , F. Fontanot , H. Fu , C. C. Lovell , M. Magliocchetti , N. Mai
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D. Roberts F. Shankar J. G. Sorce M. Baes P. Corcho-Caballero S. Eales C. Tortora N. Aghanim B. Altieri A. Amara S. Andreon N. Auricchio H. Aussel C. Baccigalupi M. Baldi A. Balestra S. Bardelli P. Battaglia A. Biviano A. Bonchi D. Bonino E. Branchini M. Brescia J. Brinchmann S. Camera G. Ca\~nas-Herrera V. Capobianco C. Carbone J. Carretero S. Casas F. J. Castander M. Castellano G. Castignani S. Cavuoti K. C. Chambers A. Cimatti C. Colodro-Conde G. Congedo C. J. Conselice L. Conversi Y. Copin F. Courbin H. M. Courtois M. Cropper A. Da Silva H. Degaudenzi A. M. Di Giorgio C. Dolding H. Dole F. Dubath X. Dupac A. Ealet S. Escoffier M. Farina R. Farinelli F. Faustini S. Ferriol F. Finelli S. Fotopoulou M. Frailis E. Franceschi M. Fumana S. Galeotta K. George B. Gillis C. Giocoli J. Gracia-Carpio B. R. Granett A. Grazian F. Grupp S. Gwyn S. V. H. Haugan J. Hoar W. Holmes F. Hormuth A. Hornstrup P. Hudelot K. Jahnke M. Jhabvala B. Joachimi E. Keih\"anen S. Kermiche A. Kiessling B. Kubik M. K\"ummel M. Kunz H. Kurki-Suonio O. Lahav Q. Le Boulc'h A. M. C. Le Brun D. Le Mignant S. Ligori P. B. Lilje V. Lindholm I. Lloro G. Mainetti D. Maino E. Maiorano O. Mansutti S. Marcin O. Marggraf M. Martinelli N. Martinet F. Marulli R. Massey S. Maurogordato E. Medinaceli Y. Mellier M. Meneghetti E. Merlin G. Meylan A. Mora M. Moresco L. Moscardini R. Nakajima C. Neissner S.-M. Niemi J. W. Nightingale C. Padilla S. Paltani F. Pasian K. Pedersen W. J. Percival V. Pettorino S. Pires G. Polenta M. Poncet L. A. Popa L. Pozzetti F. Raison R. Rebolo A. Renzi J. Rhodes G. Riccio E. Romelli M. Roncarelli R. Saglia Z. Sakr D. Sapone B. Sartoris J. A. Schewtschenko P. Schneider M. Scodeggio A. Secroun G. Seidel S. Serrano P. Simon C. Sirignano G. Sirri L. Stanco J. Steinwagner P. Tallada-Cresp\'i A. N. Taylor H. I. Teplitz I. Tereno N. Tessore S. Toft R. Toledo-Moreo F. Torradeflot I. Tutusaus L. Valenziano J. Valiviita T. Vassallo G. Verdoes Kleijn A. Veropalumbo Y. Wang J. Weller A. Zacchei G. Zamorani F. M. Zerbi I. A. Zinchenko E. Zucca V. Allevato M. Ballardini M. Bolzonella E. Bozzo C. Burigana R. Cabanac A. Cappi D. Di Ferdinando J. A. Escartin Vigo L. Gabarra J. Mart\'in-Fleitas S. Matthew M. Maturi N. Mauri R. B. Metcalf A. Pezzotta M. P\"ontinen C. Porciani I. Risso V. Scottez M. Sereno M. Tenti M. Viel M. Wiesmann Y. Akrami S. Alvi I. T. Andika S. Anselmi M. Archidiacono F. Atrio-Barandela C. Benoist K. Benson D. Bertacca M. Bethermin A. Blanchard L. Blot H. B\"ohringer S. Borgani M. L. Brown S. Bruton A. Calabro F. Caro C. S. Carvalho T. Castro F. Cogato A. R. Cooray O. Cucciati S. Davini F. De Paolis G. Desprez A. D\'iaz-S\'anchez J. J. Diaz S. Di Domizio J. M. Diego P.-A. Duc A. Enia Y. Fang A. G. Ferrari P. G. Ferreira A. Finoguenov A. Fontana A. Franco K. Ganga J. Garc\'ia-Bellido T. Gasparetto V. Gautard E. Gaztanaga F. Giacomini F. Gianotti A. H. Gonzalez G. Gozaliasl M. Guidi C. M. Gutierrez A. Hall W. G. Hartley C. Hern\'andez-Monteagudo H. Hildebrandt J. Hjorth J. J. E. Kajava Y. Kang V. Kansal D. Karagiannis K. Kiiveri C. C. Kirkpatrick S. Kruk L. Legrand M. Lembo F. Lepori G. Leroy G. F. Lesci J. Lesgourgues L. Leuzzi T. I. Liaudat A. Loureiro J. Macias-Perez G. Maggio E. A. Magnier F. Mannucci R. Maoli C. J. A. P. Martins L. Maurin M. Miluzio P. Monaco C. Moretti G. Morgante K. Naidoo A. Navarro-Alsina S. Nesseris F. Passalacqua K. Paterson L. Patrizii A. Pisani D. Potter S. Quai M. Radovich P.-F. Rocci G. Rodighiero S. Sacquegna M. Sahl\'en D. B. Sanders E. Sarpa C. Scarlata J. Schaye A. Schneider M. Schultheis D. Sciotti E. Sellentin L. C. Smith S. A. Stanford K. Tanidis G. Testera R. Teyssier S. Tosi A. Troja M. Tucci C. Valieri A. Venhola D. Vergani G. Verza P. Vielzeuf N. A. Walton D. Scott
This is my paper

Pith reviewed 2026-05-22 23:38 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords galaxy environmentpassive galaxiesmorphology density relationquenchingEuclid Q1redshift evolutionstellar mass
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The pith

At fixed stellar mass, local density increases the quenched and early-type galaxy fractions up to z=1.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper examines how local environment shapes galaxy star formation and morphology using initial Euclid observations from redshift 0.25 to 1. It finds that at fixed stellar mass, galaxies in denser regions are more likely to be quenched and to have early-type shapes. This points to environment acting separately from mass in driving galaxy evolution over the last half of cosmic time. Understanding these relations helps explain why some galaxies stop forming stars while others do not, even when they have similar masses.

Core claim

The paper establishes that the quenched fraction increases with local environmental density at fixed stellar mass up to z=1, indicating separability of mass and environment effects. Similarly, the early-type galaxy fraction increases with density at fixed mass for galaxies below 10^10.8 solar masses. For more massive galaxies, nearly all are early-types regardless of environment. Above z=0.75, morphology is largely set by stellar mass alone except for low-mass systems.

What carries the argument

The Nth-nearest neighbour estimator of local density, specific star formation rate to identify passive galaxies, and Sersic index combined with u-r colour to classify early-type morphologies.

If this is right

  • The stellar mass and environmental effects on quenching are separable up to redshift 1.
  • Environment transforms morphology independently of mass for systems below 10^10.8 solar masses.
  • Above 10^10.8 solar masses, environment has little additional effect on morphology.
  • At redshifts greater than 0.75, stellar mass dominates over environment in setting galaxy morphology.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • These trends imply that semi-analytic models need to include environmental quenching and morphological transformation mechanisms that function separately from mass quenching up to z=1.
  • Future releases with improved morphology classification free of color bias could test whether the morphology-density relation persists without the noted caution.
  • The separability suggests that processes like ram-pressure stripping or galaxy harassment operate across this redshift range in a mass-independent way for lower-mass galaxies.

Load-bearing premise

The u-r colour reliably indicates galaxy morphology without being strongly influenced by the galaxy's current star formation rate.

What would settle it

A study using morphology measurements that do not rely on u-r colours finding no density dependence in the early-type fraction at fixed mass would show the claimed morphology-density relation does not hold.

Figures

Figures reproduced from arXiv: 2503.15313 by A. Amara, A. Balestra, A. Biviano, A. Blanchard, A. Bonchi, A. Calabro, A. Cappi, A. Cimatti, A. Da Silva, A. D\'iaz-S\'anchez, A. Ealet, A. Enia, A. Finoguenov, A. Fontana, A. Franco, A. G. Ferrari, A. Grazian, A. Hall, A. H. Gonzalez, A. Hornstrup, A. Kiessling, A. Loureiro, A. M. C. Le Brun, A. M. Di Giorgio, A. Mora, A. Navarro-Alsina, A. N. Taylor, A. Pezzotta, A. Pisani, A. R. Cooray, A. Renzi, A. Schneider, A. Secroun, A. Troja, A. Venhola, A. Veropalumbo, A. Zacchei, B. Altieri, B. Gillis, B. Joachimi, B. Kubik, B. R. Granett, B. Sartoris, C. Baccigalupi, C. Benoist, C. Burigana, C. Carbone, C. C. Kirkpatrick, C. C. Lovell, C. Colodro-Conde, C. Dolding, C. Giocoli, C. Hern\'andez-Monteagudo, C. J. A. P. Martins, C. J. Conselice, C. M. Gutierrez, C. Moretti, C. Neissner, C. Padilla, C. Porciani, C. Scarlata, C. S. Carvalho, C. Sirignano, C. Tortora, C. Valieri, D. Bertacca, D. Bonino, D. B. Sanders, D. Di Ferdinando, D. Karagiannis, D. Le Mignant, D. Maino, D. Potter, D. Roberts, D. Sapone, D. Sciotti, D. Scott, D. Vergani, E. A. Magnier, E. Bozzo, E. Branchini, E. Franceschi, E. Gaztanaga, E. Keih\"anen, E. Maiorano, E. Medinaceli, E. Merlin, E. Romelli, E. Sarpa, E. Sellentin, Euclid Collaboration: C. Cleland, E. Zucca, F. Atrio-Barandela, F. Caro, F. Cogato, F. Courbin, F. De Paolis, F. Dubath, F. Faustini, F. Finelli, F. Fontanot, F. Giacomini, F. Gianotti, F. Grupp, F. Hormuth, F. J. Castander, F. Lepori, F. Mannucci, F. Marulli, F. M. Zerbi, F. Pasian, F. Passalacqua, F. Raison, F. Shankar, F. Torradeflot, G. Ca\~nas-Herrera, G. Castignani, G. Congedo, G. De Lucia, G. Desprez, G. F. Lesci, G. Gozaliasl, G. Leroy, G. Maggio, G. Mainetti, G. Meylan, G. Morgante, G. Polenta, G. Riccio, G. Rodighiero, G. Seidel, G. Sirri, G. Testera, G. Verdoes Kleijn, G. Verza, G. Zamorani, H. Aussel, H. B\"ohringer, H. Degaudenzi, H. Dole, H. Fu, H. Hildebrandt, H. I. Teplitz, H. Kurki-Suonio, H. M. Courtois, I. A. Zinchenko, I. Lloro, I. Risso, I. T. Andika, I. Tereno, I. Tutusaus, J. A. Escartin Vigo, J. A. Schewtschenko, J. Brinchmann, J. Carretero, J. Garc\'ia-Bellido, J. Gracia-Carpio, J. G. Sorce, J. Hjorth, J. Hoar, J. J. Diaz, J. J. E. Kajava, J. Lesgourgues, J. Macias-Perez, J. Mart\'in-Fleitas, J. M. Diego, J. Rhodes, J. Schaye, J. Steinwagner, J. Valiviita, J. Weller, J. W. Nightingale, K. Benson, K. C. Chambers, K. Ganga, K. George, K. Jahnke, K. Kiiveri, K. Naidoo, K. Paterson, K. Pedersen, K. Tanidis, L. A. Popa, L. Blot, L. Conversi, L. C. Smith, L. Gabarra, L. Legrand, L. Leuzzi, L. Maurin, L. Moscardini, L. Patrizii, L. Pozzetti, L. Stanco, L. Valenziano, M. Archidiacono, M. Baes, M. Baldi, M. Ballardini, M. Bethermin, M. Bolzonella, M. Brescia, M. Castellano, M. Cropper, M. Farina, M. Frailis, M. Fumana, M. Guidi, M. Jhabvala, M. K\"ummel, M. Kunz, M. L. Brown, M. Lembo, M. Magliocchetti, M. Martinelli, M. Maturi, M. Meneghetti, M. Miluzio, M. Moresco, M. Poncet, M. P\"ontinen, M. Radovich, M. Roncarelli, M. Sahl\'en, M. Schultheis, M. Scodeggio, M. Sereno, M. Tenti, M. Tucci, M. Viel, M. Wiesmann, N. Aghanim, N. Auricchio, N. A. Walton, N. Mai, N. Martinet, N. Mauri, N. Tessore, O. Cucciati, O. Lahav, O. Mansutti, O. Marggraf, P.-A. Duc, P. Battaglia, P. B. Lilje, P. Corcho-Caballero, P.-F. Rocci, P. G. Ferreira, P. Hudelot, P. Monaco, P. Schneider, P. Simon, P. Tallada-Cresp\'i, P. Vielzeuf, Q. Le Boulc'h, R. B. Metcalf, R. Cabanac, R. Farinelli, R. Maoli, R. Massey, R. Nakajima, R. Rebolo, R. Saglia, R. Teyssier, R. Toledo-Moreo, S. Alvi, S. Andreon, S. Anselmi, S. A. Stanford, S. Bardelli, S. Borgani, S. Bruton, S. Camera, S. Casas, S. Cavuoti, S. Davini, S. Di Domizio, S. Eales, S. Escoffier, S. Ferriol, S. Fotopoulou, S. Galeotta, S. Gwyn, S. Kermiche, S. Kruk, S. Ligori, S. Marcin, S. Matthew, S. Maurogordato, S. Mei, S.-M. Niemi, S. Nesseris, S. Paltani, S. Pires, S. Quai, S. Sacquegna, S. Serrano, S. Toft, S. Tosi, S. V. H. Haugan, T. Castro, T. Gasparetto, T. I. Liaudat, T. Vassallo, V. Allevato, V. Capobianco, V. Gautard, V. Kansal, V. Lindholm, V. Pettorino, V. Scottez, W. G. Hartley, W. Holmes, W. J. Percival, X. Dupac, Y. Akrami, Y. Copin, Y. Fang, Y. Kang, Y. Mellier, Y. Wang, Z. Sakr.

Figure 1
Figure 1. Figure 1: Fraction of galaxies classes as quenched as a function of stellar mass, binned by redshift. Shaded regions show 68 % confidence intervals. Only bins where the total number of galaxies is greater than 10 are plotted. ORELSE quenched fractions (Lemaux et al. 2019) are plotted in coloured squares. Their fractions are higher on average, likely because they purposely probe areas with larger galaxy densities tha… view at source ↗
Figure 2
Figure 2. Figure 2: Fraction of galaxies classed as quenched as a function of galaxy density, binned by stellar mass and redshift. The stellar mass bins listed in the legend are in units of log10(M∗/M⊙). The grey shaded regions in the background refer to the three density bins used in Lemaux et al. (2019), see text for details. The colour shaded regions show 68 % confidence intervals. Dashed lines indicate density bins where … view at source ↗
Figure 3
Figure 3. Figure 3: Distribution of the quenched fraction as a function of both stellar mass and galaxy density, in bins of increasing redshift from left to right. The colour-bar indicates the mean quenched fraction in each bin. The separability of the impact of stellar mass and the environment on the quenched fractions is clearly visible up to z = 0.75, after which the stellar mass dominates the quenching effects. forming ga… view at source ↗
Figure 4
Figure 4. Figure 4: Fractions of galaxies classed as ETGs as a function of stellar mass, binned by redshift. Shaded regions show 68 % confidence inter￾vals. Only bins where the total number of galaxies is greater than 10 are plotted. The quenched fractions from [PITH_FULL_IMAGE:figures/full_fig_p007_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Fraction of galaxies classed as ETGs as a function of galaxy density, binned by stellar mass and redshift. Shaded regions show 68 % confidence intervals. Dashed lines indicate density bins where the total number of galaxies is less than 5. Up to z ∼ 0.75, there is a significant increase in the ETG fraction of galaxies from low density environments to high density environments, for low-mass galaxies. Howeve… view at source ↗
Figure 6
Figure 6. Figure 6: Fraction of ETGs as a function of galaxy density, in the high￾est redshift bin 0.75 < z < 1. The stellar mass range is shown in the top right corner. The ETG fractions from the entire cluster sample of Postman et al. (2005) are plotted in black dots. The two samples are comparable, as they are selected at roughly the same depth, however photometric redshift uncertainties in the Euclid sample are larger, an… view at source ↗
Figure 7
Figure 7. Figure 7: Distribution of the ETG fraction as a function of both stellar mass and galaxy density, in increasing redshift bins from left to right. The colour-bar indicates the mean ETG fraction in each bin. Similar to in [PITH_FULL_IMAGE:figures/full_fig_p009_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Top: Quenched fractions as in [PITH_FULL_IMAGE:figures/full_fig_p010_8.png] view at source ↗
read the original abstract

The extent to which the environment affects galaxy evolution has been under scrutiny by researchers for decades. With the first data from Euclid, we can begin to systematically study a wide range of environments and their effects as a function of redshift, using 63 deg2 of space-based data. In this paper, we present results from Euclid Q1, where we measured the passive-density and morphology-density relations in the redshift range z=0.25--1. We determined if a galaxy is passive using the specific star formation rate, and we classified the morphologies of galaxies using the Sersic index n and the u-r colours. We measured the local environmental density of each galaxy using the Nth-nearest neighbour method. We find that at a fixed stellar mass, the quenched fraction (the fraction of galaxies that have ceased star formation) increases with increasing local environmental density up to $z=1$. This result is indicative of the separability of the effects from the stellar mass and the environment. Similarly, at all redshifts in this work, the early-type galaxy fraction increases with increasing density at fixed stellar mass, meaning the environment also transforms the morphology of the galaxy independently of stellar mass, up to M_* < 10^10.8 Msol$. For M* > 10^10.8 Msol, almost all galaxies are early-types, with minimal impact from the environment. At z>0.75, the morphology depends mostly on stellar mass, with only low-mass galaxies being affected by the environment. Given that the morphology classifications use u-r colours, these are correlated to the star formation rate, and as such our morphology results should be taken with caution, yet future morphology classifications should help verify these results. To summarise, we successfully identify the passive-density and morphology-density relations at 0.25<z<1. Future Euclid data releases are key to confirm these trends at higher redshifts.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper uses Euclid Q1 data over 63 deg² to measure the passive-density and morphology-density relations from z=0.25 to z=1. Passive galaxies are identified via sSFR threshold; morphologies are classified via Sersic index n combined with u-r colour cuts. Local density is estimated with the Nth-nearest-neighbour method. At fixed stellar mass the quenched fraction rises with density up to z=1, and the early-type fraction likewise rises with density up to M* < 10^10.8 M⊙, which the authors interpret as evidence that environment affects both quenching and morphology independently of stellar mass. The abstract explicitly cautions that u-r colours correlate with SFR and that the morphology results should be viewed with care.

Significance. If the passive-density trend is robust, the work supplies one of the first wide-area, space-based constraints on the redshift evolution of environment-driven quenching out to z=1. The morphology-density result, while tentative, would extend the separability argument to structural transformation if the colour-SFR degeneracy can be controlled. The data volume and redshift baseline are strengths for an early-release paper.

major comments (2)
  1. [Abstract] Abstract: the morphology-density claim asserts that environment transforms galaxy morphology independently of stellar mass. However, the classification combines Sersic n with u-r colour, and the text states that u-r is correlated with SFR (the same quantity used to define the passive sample). This correlation means any density trend in the u-r component can be driven by the quenching signal rather than a distinct morphological process, weakening the separability interpretation for morphology while leaving the sSFR-based passive-density result intact.
  2. [Abstract] Abstract and methods description: the manuscript does not present the explicit sSFR threshold, the precise u-r and n cuts, the adopted N for the nearest-neighbour estimator, or the completeness corrections applied to the density and fraction measurements. These choices are free parameters that directly affect the reported trends and must be shown to be robust before the separability conclusions can be considered load-bearing.
minor comments (2)
  1. The mass threshold M* = 10^10.8 M⊙ is stated without reference to the underlying stellar-mass completeness limit or the redshift-dependent selection function.
  2. [Abstract] The abstract would benefit from a brief statement of the typical uncertainties on the reported fractions and whether the trends remain significant after accounting for cosmic variance across the 63 deg² field.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which help clarify the presentation of our results. We address each major comment below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the morphology-density claim asserts that environment transforms galaxy morphology independently of stellar mass. However, the classification combines Sersic n with u-r colour, and the text states that u-r is correlated with SFR (the same quantity used to define the passive sample). This correlation means any density trend in the u-r component can be driven by the quenching signal rather than a distinct morphological process, weakening the separability interpretation for morphology while leaving the sSFR-based passive-density result intact.

    Authors: We agree that the u-r colour correlation with SFR introduces a potential degeneracy for the morphology classification. This is precisely why the abstract already states that 'our morphology results should be taken with caution' and notes the correlation with star formation rate. The passive-density relation relies solely on the sSFR threshold and remains robust. We will revise the abstract and discussion sections to more explicitly distinguish the two relations, framing the morphology-density result as tentative and secondary while preserving the separability claim only for the sSFR-based quenching. revision: partial

  2. Referee: [Abstract] Abstract and methods description: the manuscript does not present the explicit sSFR threshold, the precise u-r and n cuts, the adopted N for the nearest-neighbour estimator, or the completeness corrections applied to the density and fraction measurements. These choices are free parameters that directly affect the reported trends and must be shown to be robust before the separability conclusions can be considered load-bearing.

    Authors: We agree these parameters must be stated explicitly for reproducibility. The full methods section of the manuscript describes the approaches, but we will add the specific numerical values (sSFR threshold, u-r and n cuts, adopted N, and completeness corrections) to the revised text. We will also include a brief robustness section or appendix demonstrating that the reported trends persist under reasonable variations of these choices. revision: yes

Circularity Check

0 steps flagged

No circularity: direct observational measurements from Euclid Q1 data

full rationale

This paper reports measured quenched fractions and early-type fractions as functions of local density and stellar mass using Euclid Q1 observations. Passive galaxies are identified via sSFR thresholds and morphologies via Sersic n plus u-r colour, with the paper explicitly cautioning that u-r correlates with SFR. No equations, fits, or self-citations reduce the reported relations to inputs by construction; the results are empirical counts in bins. The morphology-density claim is presented alongside the stated caution rather than derived from a self-referential premise. This is a standard observational analysis with no load-bearing self-definition or fitted-input-as-prediction steps.

Axiom & Free-Parameter Ledger

3 free parameters · 2 axioms · 0 invented entities

The central measurements rest on standard observational definitions (Nth-nearest-neighbour density estimator, sSFR cut for quenching, Sersic index plus u-r colour for morphology) whose precise numerical thresholds are not stated in the abstract and are treated as given by prior literature.

free parameters (3)
  • N in Nth-nearest-neighbour density
    Choice of neighbour count that defines local density; not numerically specified in abstract.
  • sSFR threshold for passive classification
    Specific star-formation-rate cut that separates quenched from star-forming galaxies; value not given.
  • Sersic index and u-r colour cuts for early-type classification
    Numerical boundaries used to label morphologies; not provided.
axioms (2)
  • domain assumption Local density measured by projected Nth-nearest neighbour accurately traces the true three-dimensional environment relevant to galaxy evolution.
    Invoked when interpreting the measured density trends as environmental effects.
  • domain assumption Stellar-mass estimates and photometric redshifts from Euclid data are sufficiently accurate for the fixed-mass slicing performed.
    Required to claim trends are at fixed stellar mass.

pith-pipeline@v0.9.0 · 7700 in / 1597 out tokens · 32043 ms · 2026-05-22T23:38:21.851667+00:00 · methodology

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Works this paper leans on

66 extracted references · 66 canonical work pages

  1. [1]

    L., Navarro, J

    Balogh, M. L., Navarro, J. F., & Morris, S. L. 2000, ApJ, 540, 113

    work page 2000

  2. [2]

    C., Cooper, M

    Baxter, D. C., Cooper, M. C., Balogh, M. L., et al. 2023, MNRAS, 526, 3716

    work page 2023

  3. [3]

    2020, in Astronomical Society of the Pacific Conference Series, V ol

    Bertin, E., Schefer, M., Apostolakos, N., et al. 2020, in Astronomical Society of the Pacific Conference Series, V ol. 527, Astronomical Data Analysis Soft- ware and Systems XXIX, ed. R. Pizzo, E. R. Deul, J. D. Mol, J. de Plaa, & H. Verkouter, 461

    work page 2020

  4. [4]

    C., et al

    Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682

    work page 2000

  5. [5]

    C., Cullen, F., McLure, R

    Carnall, A. C., Cullen, F., McLure, R. J., et al. 2024, arXiv e-prints, arXiv:2405.02242

    work page arXiv 2024

  6. [6]

    C., McLeod, D

    Carnall, A. C., McLeod, D. J., McLure, R. J., et al. 2023, MNRAS, 520, 3974

    work page 2023

  7. [7]

    2013, ApJ, 779, 127

    Chiang, Y .-K., Overzier, R., & Gebhardt, K. 2013, ApJ, 779, 127

    work page 2013

  8. [8]

    A., Gebhardt, K., & Henriques, B

    Chiang, Y .-K., Overzier, R. A., Gebhardt, K., & Henriques, B. 2017, ApJ, 844, L23

    work page 2017

  9. [9]

    & McGee, S

    Cleland, C. & McGee, S. L. 2021, MNRAS, 500, 590

    work page 2021

  10. [10]

    2023, MNRAS, 524, 3692

    Corcho-Caballero, P., Ascasibar, Y ., Cortese, L., et al. 2023, MNRAS, 524, 3692

    work page 2023

  11. [11]

    J., Noble, A

    Cramer, W. J., Noble, A. G., Rudnick, G., et al. 2024, arXiv e-prints, arXiv:2404.07355

    work page arXiv 2024

  12. [12]

    2017, A&A, 602, A15

    Cucciati, O., Davidzon, I., Bolzonella, M., et al. 2017, A&A, 602, A15

    work page 2017

  13. [13]

    2010, A&A, 524, A2

    Cucciati, O., Iovino, A., Kovaˇc, K., et al. 2010, A&A, 524, A2

    work page 2010

  14. [14]

    C., et al

    Darvish, B., Mobasher, B., Martin, D. C., et al. 2017, ApJ, 837, 16

    work page 2017

  15. [15]

    2015, ApJ, 805, 121

    Darvish, B., Mobasher, B., Sobral, D., Scoville, N., & Aragon-Calvo, M. 2015, ApJ, 805, 121

    work page 2015

  16. [16]

    2016, A&A, 586, A23 De Lucia, G

    Davidzon, I., Cucciati, O., Bolzonella, M., et al. 2016, A&A, 586, A23 De Lucia, G. & Blaizot, J. 2007, MNRAS, 375, 2 De Lucia, G., Fontanot, F., Xie, L., & Hirschmann, M. 2024, A&A, 687, A68 Domínguez Sánchez, H., Margalef, B., Bernardi, M., & Huertas-Company, M. 2022, MNRAS, 509, 4024

    work page 2016

  17. [17]

    1980, ApJ, 236, 351

    Dressler, A. 1980, ApJ, 236, 351

    work page 1980

  18. [18]

    H., Balogh, M

    Edward, A. H., Balogh, M. L., Bahé, Y . M., et al. 2024, MNRAS, 527, 8598

    work page 2024

  19. [19]

    2007, A&A, 468, 33 Euclid Collaboration: Aussel, H., Tereno, I., Schirmer, M., et al

    Elbaz, D., Daddi, E., Le Borgne, D., et al. 2007, A&A, 468, 33 Euclid Collaboration: Aussel, H., Tereno, I., Schirmer, M., et al. 2025, A&A, submitted Euclid Collaboration: Corcho-Caballero, P., Ascasibar, Y ., Verdoes Kleijn, G., et al. 2025, A&A, submitted Euclid Collaboration: Cropper, M., Al Bahlawan, A., Amiaux, J., et al. 2024, A&A, accepted, arXiv:...

    work page doi:10.57780/esa-2853f3b 2007

  20. [20]

    2020, MNRAS, 496, 3943

    Fontanot, F., De Lucia, G., Hirschmann, M., et al. 2020, MNRAS, 496, 3943

    work page 2020

  21. [21]

    G., Förster Schreiber, N

    Franx, M., van Dokkum, P. G., Förster Schreiber, N. M., et al. 2008, ApJ, 688, 770

    work page 2008

  22. [22]

    K., & Sugahara, Y

    Fudamoto, Y ., Inoue, A. K., & Sugahara, Y . 2022, ApJ, 938, L24

    work page 2022

  23. [23]

    2017, A&A, 598, A45

    George, K. 2017, A&A, 598, A45

    work page 2017

  24. [24]

    & Zingade, K

    George, K. & Zingade, K. 2015, A&A, 583, A103

    work page 2015

  25. [25]

    Gunn, J. E. & Gott, III, J. R. 1972, ApJ, 176, 1

    work page 1972

  26. [26]

    2016, MNRAS, 461, 1760

    Hirschmann, M., De Lucia, G., & Fontanot, F. 2016, MNRAS, 461, 1760

    work page 2016

  27. [27]

    M., White, S

    Kauffmann, G., Heckman, T. M., White, S. D. M., et al. 2003, MNRAS, 341, 54

    work page 2003

  28. [28]

    2022, arXiv e-prints, arXiv:2212.02428

    Kroupa, P. 2001, MNRAS, 322, 231 Kümmel, M., Álvarez-Ayllón, A., Bertin, E., et al. 2022, arXiv e-prints, arXiv:2212.02428

    work page arXiv 2001

  29. [29]

    B., Tinsley, B

    Larson, R. B., Tinsley, B. M., & Caldwell, C. N. 1980, ApJ, 237, 692

    work page 1980

  30. [30]

    C., Tomczak, A

    Lemaux, B. C., Tomczak, A. R., Lubin, L. M., et al. 2019, MNRAS, 490, 1231

    work page 2019

  31. [31]

    C., Thomas, P

    Lovell, C. C., Thomas, P. A., & Wilkins, S. M. 2018, MNRAS, 474, 4612

    work page 2018

  32. [32]

    M., Gal, R

    Lubin, L. M., Gal, R. R., Lemaux, B. C., Kocevski, D. D., & Squires, G. K. 2009, AJ, 137, 4867

    work page 2009

  33. [33]

    L., Mosleh, M., Romer, A

    Masters, K. L., Mosleh, M., Romer, A. K., et al. 2010, MNRAS, 405, 783

    work page 2010

  34. [34]

    H., Wagner, C., Cooper, A., et al

    McIntosh, D. H., Wagner, C., Cooper, A., et al. 2014, MNRAS, 442, 533

    work page 2014

  35. [35]

    P., Stanford, S

    Mei, S., Blakeslee, J. P., Stanford, S. A., et al. 2006, ApJ, 639, 81

    work page 2006

  36. [36]

    A., Amodeo, S., et al

    Mei, S., Hatch, N. A., Amodeo, S., et al. 2023, A&A, 670, A58

    work page 2023

  37. [37]

    2015, ApJ, 804, 117

    Mei, S., Scarlata, C., Pentericci, L., et al. 2015, ApJ, 804, 117

    work page 2015

  38. [38]

    2018, MNRAS, 473, 2098

    Merlin, E., Fontana, A., Castellano, M., et al. 2018, MNRAS, 473, 2098

    work page 2018

  39. [39]

    2019, MNRAS, 490, 3309

    Merlin, E., Fortuni, F., Torelli, M., et al. 2019, MNRAS, 490, 3309

    work page 2019

  40. [40]

    1996, Nature, 379, 613

    Moore, B., Katz, N., Lake, G., Dressler, A., & Oemler, A. 1996, Nature, 379, 613

    work page 1996

  41. [41]

    Overzier, R. A. 2016, A&A Rev., 24, 14

    work page 2016

  42. [42]

    M., et al

    Paccagnella, A., Vulcani, B., Poggianti, B. M., et al. 2016, ApJ, 816, L25

    work page 2016

  43. [43]

    J., Kovaˇc, K., et al

    Peng, Y .-j., Lilly, S. J., Kovaˇc, K., et al. 2010, ApJ, 721, 193 Pérez-Martínez, J. M., Dannerbauer, H., Kodama, T., et al. 2023, MNRAS, 518, 1707 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13

    work page 2010

  44. [44]

    Postman, M., Franx, M., Cross, N. J. G., et al. 2005, ApJ, 623, 721

    work page 2005

  45. [45]

    2010, A&A, 523, A13

    Pozzetti, L., Bolzonella, M., Zucca, E., et al. 2010, A&A, 523, A13

    work page 2010

  46. [46]

    L., Lequeux, J., Maurice, E., Prevot, L., & Rocca-V olmerange, B

    Prevot, M. L., Lequeux, J., Maurice, E., Prevot, L., & Rocca-V olmerange, B. 1984, A&A, 132, 389

    work page 1984

  47. [47]

    C., Aubourg, É., et al

    Rhodes, J., Nichol, R. C., Aubourg, É., et al. 2017, ApJS, 233, 21

    work page 2017

  48. [48]

    2012, MNRAS, 419, 2545

    Rowlands, K., Dunne, L., Maddox, S., et al. 2012, MNRAS, 419, 2545

    work page 2012

  49. [49]

    2020, ApJ, 899, 85

    Sazonova, E., Alatalo, K., Lotz, J., et al. 2020, ApJ, 899, 85

    work page 2020

  50. [50]

    2024, ApJ, 961, 39

    Shi, K., Malavasi, N., Toshikawa, J., & Zheng, X. 2024, ApJ, 961, 39

    work page 2024

  51. [51]

    Shimakawa, R., Koyama, Y ., Röttgering, H. J. A., et al. 2018, MNRAS, 481, 5630

    work page 2018

  52. [52]

    S., Steinhardt, C

    Speagle, J. S., Steinhardt, C. L., Capak, P. L., & Silverman, J. D. 2014, ApJS, 214, 15

    work page 2014

  53. [53]

    Straatman, C. M. S., Spitler, L. R., Quadri, R. F., et al. 2016, ApJ, 830, 51

    work page 2016

  54. [54]

    J., et al

    Strazzullo, V ., Pannella, M., Mohr, J. J., et al. 2019, A&A, 622, A117

    work page 2019

  55. [55]

    2024, ApJ, 966, 18

    Taamoli, S., Mobasher, B., Chartab, N., et al. 2024, ApJ, 966, 18

    work page 2024

  56. [56]

    L., Richards, J., et al

    Tojeiro, R., Masters, K. L., Richards, J., et al. 2013, MNRAS, 432, 359

    work page 2013

  57. [57]

    R., Lemaux, B

    Tomczak, A. R., Lemaux, B. C., Lubin, L. M., et al. 2017, MNRAS, 472, 3512

    work page 2017

  58. [58]

    & Toomre, J

    Toomre, A. & Toomre, J. 1972, ApJ, 178, 623

    work page 1972

  59. [59]

    H., Thongkham, K., et al

    Trudeau, A., Gonzalez, A. H., Thongkham, K., et al. 2024, ApJ, 972, 27 van der Burg, R. F. J., Rudnick, G., Balogh, M. L., et al. 2020, A&A, 638, A112

    work page 2024

  60. [60]

    M., Finn, R

    Vulcani, B., Poggianti, B. M., Finn, R. A., et al. 2010, ApJ, 710, L1

    work page 2010

  61. [61]

    2016, ApJ, 828, 56

    Wang, T., Elbaz, D., Daddi, E., et al. 2016, ApJ, 828, 56

    work page 2016

  62. [62]

    R., Davidzon, I., Toft, S., et al

    Weaver, J. R., Davidzon, I., Toft, S., et al. 2023, A&A, 677, A184

    work page 2023

  63. [63]

    R., Tinker, J

    Wetzel, A. R., Tinker, J. L., & Conroy, C. 2012, MNRAS, 424, 232

    work page 2012

  64. [64]

    2020, MNRAS, 498, 4327

    Xie, L., De Lucia, G., Hirschmann, M., & Fontanot, F. 2020, MNRAS, 498, 4327

    work page 2020

  65. [65]

    2017, MN- RAS, 469, 968 1 Université Paris Cité, CNRS, Astroparticule et Cosmologie, 75013

    Xie, L., De Lucia, G., Hirschmann, M., Fontanot, F., & Zoldan, A. 2017, MN- RAS, 469, 968 1 Université Paris Cité, CNRS, Astroparticule et Cosmologie, 75013

    work page 2017

  66. [66]

    Padova, Via Marzolo 8, 35131 Padova, Italy 104 INFN-Padova, Via Marzolo 8, 35131 Padova, Italy 105 Institut für Theoretische Physik, University of Heidelberg, Philosophenweg 16, 69120 Heidelberg, Germany 106 Institut de Recherche en Astrophysique et Planétologie (IRAP), Université de Toulouse, CNRS, UPS, CNES, 14 Av. Edouard Belin, 31400 Toulouse, France ...

    work page 2008