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Dark-matter-induced transients over cosmic time: The role of star formation history profiles

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read This paper derives a closed-form delayed-tau approximation for the star formation history of any galactocentric radial shell, as a function of galaxy stellar mass and cosmic time, accurate to a few tens of per cent.

desk verdict Useful and honest fitting formula for radial-shell SFHs, but the shell inversion conflates structural growth with star formation, so the radial accuracy claim is not established. read the letter →

arxiv 2505.21260 v2 pith:I4SJ46UO submitted 2025-05-27 astro-ph.GA astro-ph.COastro-ph.HEhep-phhep-th

Heinrich Steigerwald This is my paper
classification astro-ph.GAastro-ph.COastro-ph.HEhep-phhep-th
keywords darkmatterstarformationhistorygalactocentricradialshellsdelayed-taumodelgalaxyscalingrelationshost-offsetdistributionwhitedwarfprogenitorstypeIasupernovae
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

Star formation does not proceed evenly inside a galaxy: centers form early, outskirts late, and this radial history matters when a dark-matter-induced transient destroys its host star, because the destroyed population is only replenished where stars keep forming. This paper builds a framework, from empirical galaxy size-mass-redshift relations and two published average star formation history models, that predicts the star formation history inside any galactocentric radial shell for galaxies of a given present-day stellar mass across cosmic time. The output is a closed-form delayed-tau formula with 21 fitted coefficients, accurate to a few tens of per cent against the input models. A companion application uses it to predict where primordial-black-hole-white-dwarf collisions would ignite type Ia supernovae, and in particular their host-offset distribution.

What carries the argument

The carrying object is the delayed-tau SFH parameterization, a one-peak functional form in which star formation begins at formation time $t_f$, rises linearly, peaks at $\tau$, and decays exponentially, here adapted to radial shells. The argument runs through four linked steps: a S\'ersic mass profile deprojected to 3D, a size-mass-redshift scaling relation that fixes radius histories, a point-like galaxy mass assembly equation whose stellar mass loss is delayed by the IMF-dependent returned-mass fraction, and the key assumption that this same equation holds independently for each radial shell with zero net stellar migration across shell boundaries. Combining these steps yields shell mass histories, which are then fitted to the delayed-tau form; the fitting coefficients are the deliverable.

What would settle it

Use integral-field spectroscopic surveys of nearby and intermediate-redshift disk galaxies to measure the star formation history in annuli around the half-mass radius, and compare the peak time of each annulus with the prediction of the fitting formula; if the observed center-to-outside formation time lag is substantially smaller than predicted, with outer radii forming stars earlier than the model's formation time, the per-shell mass-assembly assumption would be falsified.

Watch

Extended reading notes

Core claim

The paper claims that the differential star formation history in a radial shell, $\partial\Psi/\partial r (t; r, M_\star)$, is well approximated by the delayed-tau form $k\,(t-t_f)/\tau\,\exp[-(t-t_f)/\tau]$, with $k$, $\tau$, and $t_f$ functions of radius and present-day stellar mass given by the fitting expansions (37)-(39) and the 21 coefficients in Table I. This holds for both the self-consistent mass-assembly SFH model and a simulation-calibrated average SFH model, and it reproduces the input mass histories, size histories, and cosmic star formation rate density to within a few tens of per cent for most masses and redshifts. The same per-shell logic, combined with a metallicity- and star-formation-rate-dependent stellar IMF and initial-final mass relation, yields Eq. (A.23) for the white dwarf formation history in a shell, the starting point for dark-matter-ignition rate calculations.

Load-bearing premise

The load-bearing premise is that each radial shell evolves like an isolated galaxy: the mass-assembly equation applies shell by shell, with no net stellar migration across shell boundaries and no contribution from elliptical galaxies, so stars formed in a shell stay in that shell over cosmic time.

Editorial extensions

If this is right

  • Dark-matter-induced transient rates can now be evaluated per radial shell without hydrodynamical galaxy simulations, making parameter-space scans of dark matter candidates cheap.
  • Host-offset distributions of dark-matter-induced transients will reflect the inside-out buildup of galaxies: dense central regions that deplete their compact-star populations are also the least replenished, so offsets should not simply trace the dark matter density profile.
  • The closed-form coefficients can be integrated over galaxy stellar mass functions to give volumetric transient rates at any redshift, with an uncertainty of a few tens of per cent inherited from the input SFH models.
  • The companion white-dwarf formation history lets supernova Ia progenitor formation be predicted per shell under metallicity- and star-formation-rate-dependent IMFs, so dark-matter-ignition models can be tested against observed rates and host offsets.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Because the framework is calibrated to average scaling relations, applying it to individual galaxies or extreme environments would need a re-fit; the paper itself notes ultra-massive galaxies are more compact in the model than the input scaling relations, which biases outer host-offset predictions at low redshift.
  • The zero-migration assumption is the axis on which the whole shell-by-shell construction turns. A straightforward stress test would be to insert a radial-migration prescription from simulations and see whether the outer-shell $\tau$ and $t_f$ change by more than the claimed few-tens-of-per-cent accuracy.
  • The delayed-tau shape will fail for galaxies with a late secondary burst or significant late-time star formation, and the paper notes the fit underestimates late-time star formation in supermassive galaxies. For transients hosted preferentially by massive, quiescent galaxies, a user should add a residual late-time term rather than trusting the tails of the fit.
  • Because the framework is modular, new resolved surveys or JWST-era size-mass relations could be fed through the same pipeline to produce updated coefficients without redesigning the method.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. The paper constructs a semi-empirical framework to estimate star formation histories (SFHs) in galactocentric radial shells as a function of present-day galaxy stellar mass and cosmic time. It combines Sersic-profile deprojection, empirical size-mass-redshift relations, and two models of galaxy-wide mass assembly (a fine-tuned 'mass assembly' model and UniverseMachine) to compute shell mass histories, then inverts the shell mass-conservation equation to infer differential SFHs. The main result is the closed-form delayed-tau approximation of Eq. (33) with the 21 fitting coefficients of Table I, intended for use in predicting dark-matter-induced transient rates and host-offset distributions. The appendix adds a metallicity- and SFR-dependent IMF/IFMR framework for white-dwarf mass functions. Validation consists of (1) reproducing input mass histories, sizes, and cosmic SFRD, and (2) a qualitative comparison to CALIFA resolved SFRD data.

Significance. If the radial-shell SFH framework is correct, it would fill a genuine gap: most DM-induced transient rate calculations use either galaxy-wide SFHs or crude density-weighting, whereas host-offset predictions require resolved radial SFHs. The paper is transparent in its construction, provides explicit fitting formulae and coefficients, and makes a useful attempt to connect to observed scaling relations and to local WD mass-function data. The inclusion of two SFH models and the explicit acknowledgement of several limitations are strengths. However, the central radial inference step is currently not physically validated: the inversion in Eq. (31) absorbs a structural size-evolution term into the inferred star formation, and the consistency tests largely reproduce the inputs rather than testing against independent radial-SFH data. The claimed few-tens-of-per-cent accuracy therefore applies to the fit to model inputs, not to the true radial SFH. The paper is valuable as a methods contribution, but the radial dimension needs a corrected treatment or a quantitative demonstration that the structural term is negligible before the results can support DM transient host-offset predictions.

major comments (3)
  1. [§IV.1, Eqs. (8), (14), (31)] The central inversion assumes that dM_shell/dt equals local star formation minus local mass loss, with no stellar flux across shell boundaries. But the shell mass history is evaluated from Eq. (14) using the time-dependent half-mass radius R1/2(t; Mstar) of Eq. (8). For fixed physical radii r1 and r2, dM_shell/dt contains a structural term (∂M_shell/∂R1/2)(dR1/2/dt) that describes the redistribution of pre-existing stars across the fixed boundaries as the galaxy grows in size, not new star formation. Eq. (31) has no separate term for this effect and will absorb it into the inferred ΔΨ. The assumption of zero net radial migration, discussed in §IV.1, concerns the motion of stellar populations and does not remove this boundary-crossing term. The bias is largest for passive galaxies and for outer shells, where the empirical size-mass relation evolves rapidly even at roughly fixed stellar mass; these are precisely the regions that dominate host-offset predictions. The manuscript should either add the structural flux term explicitly, redefine the shells in a Lagrangian way, or demonstrate quantitatively that the term is negligible for the mass and redshift ranges of interest.
  2. [§IV.2, Figs. 10–12; §III.3, Fig. 7] The validation does not establish that the inferred radial ΔΨ is the true star formation history. Tests 1–3 reproduce the input mass histories, size histories, and SFRD; they therefore verify only that the fitting formula of Eq. (33) accurately represents the outputs of the model, not that the model's radial decomposition is physically correct. In particular, the SFRD comparison in Fig. 12 is partly circular, because the mass-assembly SFH parameters in §III.3 were fine-tuned to reproduce the observed SFRD, and the same SFRD is then used as a validation target; the author explicitly states the model reproduces it 'by construction'. The CALIFA comparison in Fig. 12 is qualitative and mixed by projection effects, and it does not test the outer shells (beyond 2 R1/2) or the redshift range where the structural term matters most. The claim that Eq. (33) is accurate 'to within a few tens of per cent' should be restricted to the fit to the model inputs until an independent test of the radial dimension is provided.
  3. [§II.1, Eq. (6); Figs. 2, 11] The size-mass-redshift relation of Eq. (6) is fitted to CANDELS data covering 0 < z < 3 and log(Mstar/Msun) in [9, 12], but the framework applies it over the full cosmic history and over the range log(Mstar/Msun) in [8, 12], including the dotted extrapolations shown in Fig. 11. For the most massive galaxies (Mstar = 10^12 Msun), the test in Fig. 11 already shows up to 40% error in R1/2, and the author notes this will bias the outermost host-offset predictions. Since the radial shells are expressed in units of present-day R1/2 and the offset distribution is sensitive to the outer profile, the extrapolated size evolution contributes an additional, unquantified uncertainty to the main product. Please quantify the sensitivity of Eq. (33) to the choice of size-mass relation and to the extrapolation, or explicitly restrict the claimed validity range.
minor comments (4)
  1. [§I, first paragraph] 'to test weather or not' should be 'to test whether or not'.
  2. [Fig. 15 caption] 'fitted by eq. (A.17) (flue full lines)' should read '(blue full lines)'.
  3. [Appendix A, Eq. (A.18)] The list of coefficients after Eq. (A.18) assigns c8 twice; the last coefficient should be c9 = −0.325.
  4. [§IV.2, Fig. 12] The red and cyan curves are defined in the text as 'three-dimensional galactocentric spheres' but the figure and caption should state explicitly that the model curves are volume-integrated within spherical shells while the CALIFA data are sky-projected cylinders/donuts; this distinction is mentioned in the text but would be clearer in the caption.

Circularity Check

3 steps flagged · score 4.0 of 10

The SFRD validation is circular by the paper's own wording, and the per-shell SFH inversion folds time-dependent size growth into the inferred star formation, making the radial 'prediction' partly a constructed residual.

  1. fitted input called prediction [§ III.1 (eq. 17) and § III.3 (Fig. 7)]
    "values Ψsf,0 = 0.62M⊙ yr−1, α = 0.62 and β = 2.9, that we adopted pragmatically (fine-tuned) in order to reproduce the observed star formation rate density (SFRD, see § III 3). ... while, by construction, the mass assembly SFHs (blue lines) best reproduce the observed SFRD with that of Ref. [29] (full blue line)."

    The free parameters of the mass-assembly SFH are explicitly fine-tuned to match the observed SFRD, and then the same observed SFRD is used in Figure 7 as the validating comparison. The match is therefore forced by the calibration and is not an independent confirmation. The paper even labels it 'by construction.' This affects one of the two SFH inputs feeding the radial-shell model, so it is a genuine but partial circularity.

  2. self definitional [§ II.1 (after eq. 14) and § IV.1 (eqs. 30-31)]
    "the integrated mass history, M⋆(t; r1, r2, M⋆), between radii r1 and r2 ... is obtained by simply replacing in the right-hand side of eq. (14), R1/2 → R1/2(t; M⋆), the half-mass radius history (see eq. 8). ... Now, restricting eq. (30) to a radial shell within r1 → r2, we have dM⋆/dt(t; r1, r2, M⋆) = ∆Ψ(t; r1, r2, M⋆) − ... where M⋆(r; , r1, r2, M⋆) is the integrated stellar mass history defined immediately after eq. (14), and is already known."

    The shell-mass history input to eq. (31) is computed with the time-dependent half-mass radius R1/2(t), so dM_shell/dt contains a structural term (∂M_shell/∂R1/2)(dR1/2/dt) that redistributes existing stars across fixed physical radii. Eq. (31) has no stellar-migration or flux term and is solved for ΔΨ, so ΔΨ is forced to absorb this size-growth term. A passive galaxy with zero star formation in a shell can therefore acquire a nonzero inferred ΔΨ. The outer-shell 'star formation histories' are thus, by construction, residuals of the assumed size evolution rather than independent estimates of star formation.

1 more flagged steps
  1. fitted input called prediction [§ IV.2, Consistency testing (Figs. 10-12)]
    "Since, to our knowledge, SFH models in galactocentric radial shells are still missing in the literature, testing ∂Ψ/∂r consists here in trivially reproducing the input physics."

    The paper explicitly states that the radial tests are not independent checks: they reproduce the same input mass histories, size histories, and SFRD from which the 21 coefficients of Table I were derived. The agreement shown in Figures 10-12 therefore measures fitting accuracy, not predictive power. This is acknowledged by the author, which lessens the severity, but it means the 'few tens of per cent' accuracy claim refers to interpolation of the training data rather than to external validation.

full rationale

The paper is largely an honest emulator: Eq. (33) with Table I is a fitting function trained on two existing SFH models (the mass-assembly model and UniverseMachine), and the author openly labels the radial consistency tests as reproducing input. That part is not itself circular. The score of 4 reflects two genuine circular or self-definitional elements. First, the mass-assembly SFH parameters are explicitly 'fine-tuned' to the observed SFRD, and the same SFRD is then presented as a successful test 'by construction'; this is a fitted-input-called-prediction loop for one of the two model inputs. Second, the radial-shell inversion of eq. (31) uses shell-mass histories computed with a time-dependent half-mass radius R1/2(t), so the solved ΔΨ necessarily absorbs the structural size-growth term; the inferred outer-shell SFH is therefore at least partly constructed from the assumed size evolution rather than independently predicted. The CALIFA comparison is qualitative and projection-mixed, as the paper concedes, so it does not resolve this. There is no load-bearing self-citation chain or imported uniqueness theorem; the companion-paper citations are motivational rather than argumentative. Overall, the central radial formula has independent content as a compact fit to two SFH models, but its validation is partly circular and its radial dimension is contaminated by construction, giving a moderate circularity score of 4.

Assumptions & free parameters 10 free parameters · 7 assumptions · 0 invented entities

The central claim depends on a chain of empirical fits, both from this paper and from prior literature. The main deliverable is itself a 21-coefficient fit to the author's simulations, so the free parameter count is high. No new physical entities are introduced; the axioms are domain assumptions about average galaxy evolution and about the validity of extrapolating empirical scaling relations. The dominant uncertainty is not a missing particle or force, but the reliability of the fitted galaxy evolution inputs.

free parameters (10)
  • Sersic index transition mass and width (log(Mn/Msun), sigma_n) = 10.77, 0.81
    Fitted to median PS1 Sersic index data, eq. (5), Fig. 1. Determines the shape of the stellar density profile and hence the radial mass distribution.
  • Size-mass-redshift relation constants (a1/2,0, alpha, beta) = 4.506 kpc, 0.17, -0.55
    Fitted to combined CANDELS data, eq. (6), Fig. 2. Sets the physical scale of all radial shells.
  • Star-forming main sequence parameters (Psi_sf,0, alpha, beta) = 0.62 Msun/yr, 0.62, 2.9
    Fine-tuned by the author to reproduce the observed cosmic star formation rate density, eq. (17), Section III.1. This is the input SFR law for the mass assembly model.
  • Quenching penalty parameters (sigma_Q, M_Q(z) relation) = sigma_Q=1.5; log(M_Q/Msun)=10.077+0.636z
    Adopted from Childress et al. and used in eqs. (19)-(20). Controls the passive fraction and is load-bearing for massive galaxy star formation histories.
  • Galaxy-wide delayed-tau fitting parameters (Psi_0, tau, tf as functions of Mstar) = Second-order fits shown in Fig. 6
    Fitted to the author's mass assembly SFHs to represent Psi(t; Mstar), eq. (24). These intermediate fits feed the radial construction.
  • Radial delayed-tau coefficients in Table I (21 values) = Table I, e.g. log(k)_00=-5.161, log(k)_01=0.0368, log(tau)_00=0.426
    The main free parameters. Fitted to the simulated radial-shell SFHs via eqs. (37)-(39). These coefficients are the paper's central deliverable.
  • IFMR fitting coefficients (c1..c6 for eq. A.17) = 0.003689, -0.06585, 0.4637, -0.1956, 50.6603, -0.1714
    Fitted to Umeda et al. stellar evolution grids to map zero-age main sequence mass to white dwarf mass. Alternative coefficients in eq. (A.18) are also listed.
  • IMF slope and normalization coefficients in eqs. (A.1)-(A.14) = c1..c9 in eq. (A.2); slope coefficients c1..c5 in eqs. (A.11)-(A.14)
    Adopted from Yan et al. and Fontanot et al. These modulate the IMF with metallicity and SFR, strongly affecting the appendix white dwarf mass function.
  • White dwarf formation delay fractions = 0.65 single-star, 0.35 binary-merger with 4x delay
    Chosen by hand based on binary population synthesis average merger delay, eq. (A.24). Simplifies the convolution for white dwarf formation.
  • Radial grid truncation at 5 R1/2 = 5 present-day half-mass radii
    Arbitrary cutoff chosen by the author. All predictions are limited to this radius, and the outer host-offset distribution is affected by the truncation.
assumptions (7)
  • domain assumption The galaxy-wide mass assembly equation (15) also holds independently in each radial shell, with no net stellar migration across shell boundaries.
    Invoked in Section IV.1 to write eq. (31) and to convert integrated mass histories into shell SFHs. The author cites literature for near-zero net migration but acknowledges outward migration at r greater than about R1/2 and neglects ellipticals.
  • domain assumption The stellar component can be treated as spherically symmetric for the purpose of DM-stellar encounter rates.
    Stated in Sections I and II.2. The disk and bulge are approximated with spherical Sersic deprojection, which smears angular structure.
  • domain assumption Empirical scaling relations for Sersic index and size versus mass and redshift hold for individual galaxies and can be extrapolated beyond their fitted ranges and beyond z=3.
    Used throughout Section II. The paper itself flags extrapolations in Fig. 11 dotted lines and for ultra-massive galaxies.
  • domain assumption The stellar IMF depends on metallicity and SFR according to literature parametrizations, and the IFMR fitting can be extrapolated beyond Z=0.03.
    Used in Appendix Sections 1 and 2. The author notes that IMF choice feeds back into the SFH via eq. (16), and that the IFMR extrapolation is an assumption.
  • domain assumption The white dwarf mass function from single-star evolution, computed as a pullback of the IMF through the IFMR, is a good approximation even though roughly 35% of white dwarfs form in binary mergers, because the mass function shape is insensitive to mergers.
    Invoked in Appendix Section 3 around eq. (A.19), relying on binary population synthesis results from Temmink et al. and generalized to all environments.
  • standard math The Prugniel-Simien Sersic deprojection approximation is accurate enough for the calculation.
    Eq. (10) and Ref. [26] quoted as accurate to a few per cent for n in [1,5.5] and radii in [0.1,100] half-mass radii.
  • standard math A fixed flat matter-plus-cosmological-constant cosmology with Omega_m=0.3, Omega_Lambda=0.7, and H0=70 km/s/Mpc is assumed.
    Used to map redshift and cosmic time, eq. (2).

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Pith. "Pith review of Dark-matter-induced transients over cosmic time: The role of star formation history profiles." pith.science (2026). https://pith.science/paper/I4SJ46UO

@misc{pith2026250521260,
  author       = {Pith},
  title        = {Pith review of: Dark-matter-induced transients over cosmic time: The role of star formation history profiles},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/I4SJ46UO}},
  note         = {Machine review of arXiv:2505.21260}
}
read the original abstract

The dark matter (DM) conundrum is one of the most intriguing due to its resistance in direct detection experiments. In recent years, attempts to identify non-gravitational signatures as the result of DM traversing or accumulating within stars have attracted a lot of attention. These calculations are usually evaluated at the order-of-magnitude level for stellar populations where the DM density is highest, such as galactic centers. However, if the signature implies the destruction of the host star, their population could have been diminished over a Hubble time in the most DM-dense regions, unless replenished by star formation. This circumstance exemplifies the need for galactic star formation history profiles when deriving DM-induced transient rates, in particular for predicting the host-offset distribution. Here, we combine theoretical and empirical scaling relations of galaxy structure, star formation, and stellar initial mass function to construct a simple and efficient framework that permits us to estimate the target population formation rate and mass function within galactocentric radial zones across galaxy stellar masses and cosmic time. In a companion paper, we apply the framework to the hypothesis that DM in the form of primordial black holes accounts for the ignition of normal type Ia supernovae when colliding with white dwarf stars.

Figures

Figures reproduced from arXiv: 2505.21260 by the authors.

Figure 1
Figure 1. FIG. 1. Median trend of the S´ersic index with stellar mass [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. Median trend of the semi-major projected half-light [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. Median SFR assumed in this work with/without [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (14 more)
Figure 4
Figure 4. Figure 4: FIG. 4. Stellar mass histories calculated with the mass as [PITH_FULL_IMAGE:figures/full_fig_p005_4.png]
Figure 6
Figure 6. Figure 6: FIG. 6. Delayed- [PITH_FULL_IMAGE:figures/full_fig_p006_6.png]
Figure 7
Figure 7. Figure 7: FIG. 7. Star formation rate density as defined by eq. ( [PITH_FULL_IMAGE:figures/full_fig_p007_7.png]
Figure 8
Figure 8. Figure 8: FIG. 8. Radial fitting of delayed- [PITH_FULL_IMAGE:figures/full_fig_p007_8.png]
Figure 9
Figure 9. Figure 9: FIG. 9. Fitting in log [PITH_FULL_IMAGE:figures/full_fig_p008_9.png]
Figure 10
Figure 10. Figure 10: FIG. 10. Total stellar mass histories within 5 [PITH_FULL_IMAGE:figures/full_fig_p010_10.png]
Figure 11
Figure 11. Figure 11: FIG. 11. Comparison of circularized sky-projected half-mass sizes of simulated galaxies with fitting formula eq. ( [PITH_FULL_IMAGE:figures/full_fig_p010_11.png]
Figure 12
Figure 12. Figure 12: FIG. 12. Same as Fig [PITH_FULL_IMAGE:figures/full_fig_p011_12.png]
Figure 14
Figure 14. Figure 14: FIG. 14. Mean gas phase metallicity evolution as a function of [PITH_FULL_IMAGE:figures/full_fig_p012_14.png]
Figure 13
Figure 13. Figure 13: FIG. 13. Galaxy-wide stellar IMF with metallicity-dependent [PITH_FULL_IMAGE:figures/full_fig_p012_13.png]
Figure 15
Figure 15. Figure 15: FIG. 15. Initial-final mass relation, i.e. WD mass as a func [PITH_FULL_IMAGE:figures/full_fig_p013_15.png]
Figure 16
Figure 16. Figure 16: FIG. 16. Differential number of WDs per solar mass of stars [PITH_FULL_IMAGE:figures/full_fig_p014_16.png]
Figure 17
Figure 17. Figure 17: FIG. 17. Same as Fig [PITH_FULL_IMAGE:figures/full_fig_p014_17.png]
Figure 18
Figure 18. Figure 18: FIG. 18. Same as Fig [PITH_FULL_IMAGE:figures/full_fig_p015_18.png]

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Reference graph

Works this paper leans on

75 extracted references · 39 canonical work pages · cited by 1 Pith paper

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    Mass-assembly framework We model the mean SFHs of galaxies following a pro- cedure elaborated by Ref. [17], see also [18–20], and the quenching prescription of Ref. [19], that we update slightly in order to be consistent with the most recent de- termination of the galaxy stellar mass function [29–31]. In this approach, the galaxy stellar mass increase rat...

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