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From the far-ultraviolet to the far-infrared -- galaxy emission at $0\le z \le 10$ in the Shark semi-analytic model

T0 review · 3 major / 5 minor · reviewed 2026-08-14 · deepseek-v4-flash

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Pith's one-line read The Shark galaxy-formation model reproduces observed UV-to-FIR galaxy emission from z=0 to z=10 without changing the stellar initial mass function.

desk verdict A serious, broad panchromatic SAM validation that mostly delivers, with the high-z agreement resting on an unproven dust-to-metal scaling that the authors themselves flag. read the letter →

arxiv 1908.03423 v3 pith:LNII5PB4 submitted 2019-08-09 astro-ph.GA

Claudia del P. Lagos (ICRAR/UWA) , Aaron S. G. Robotham , James W. Trayford , Rodrigo Tobar , Matías Bravo , Sabine Bellstedt , Luke J. M. Davies , Simon P. Driver
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Pascal J. Elahi Danail Obreschkow Chris Power
This is my paper · ORCID
classification astro-ph.GA
keywords galaxyformationsemi-analyticmodelspectralenergydistributionsdustattenuationluminosityfunctionsubmillimetregalaxiescosmicSEDfar-infrared
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

This paper claims that a state-of-the-art semi-analytic model of galaxy formation, Shark, can reproduce observed galaxy emission across the whole far-ultraviolet to far-infrared range and across cosmic time, from z=0 to z=10, in one go. The matching is done by attaching to each simulated galaxy a spectral energy distribution built from its star-formation and metal-enrichment history, then applying dust attenuation scaled by galaxy dust surface density and re-emitting absorbed light in the infrared. The authors report simultaneous agreement with z=0 luminosity functions in 27 bands, rest-frame K-band luminosity functions to z=3, rest-frame UV luminosity functions to z=10, UV slopes to z=8, number counts including the disputed 850-micron counts, the redshift distribution of bright submillimetre galaxies, and the z=0 to z=1 cosmic SED. The central point is that this is achieved with a universal Chabrier initial mass function and with no redshift-dependent adjustments to the dust-to-metal ratio. If right, it means earlier models that required a top-heavy IMF in starbursts to fit the far-infrared were resolving a tension specific to their assumptions, not a universal feature of galaxy formation.

What carries the argument

The load-bearing object is the attenuation chain that maps a simulated Shark galaxy's physical state to an SED. Dust masses come from the local dust-to-metal vs metallicity scaling of Remy-Ruyer et al. (2014), assumed to hold to z=10. Diffuse ISM optical depth and power-law index, tau_ISM and eta_ISM, are sampled from the EAGLE radiative-transfer parametrisation of Trayford et al. (2019) as functions of dust surface density, separately for disks and bulges; birth-cloud optical depth scales with the dust surface density of molecular clouds following Lacey et al. (2016). The absorbed light is re-emitted using Dale et al. (2014) templates at fixed effective temperatures for diffuse ISM and birth clouds, ensuring energy balance. This machinery produces attenuation that grows with stellar mass, peaks at z~1-2, and declines at high redshift as galaxies become metal poor, which is what allows the UV and FIR to fit simultaneously.

What would settle it

Measure the dust-to-metal mass ratio of galaxies at z=4-8 using ALMA dust-continuum observations and JWST/NIRSpec gas metallicities; if the ratio falls roughly 1.5 dex below the local Remy-Ruyer relation at fixed metallicity, as some dust-formation models predict, the model's high-redshift UV slopes and 850-micron counts would not be reproduced with the assumed invariant scaling.

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Extended reading notes

Core claim

The paper's central claim is that Shark, a semi-analytic galaxy formation model with a universal Chabrier IMF, is capable of reproducing the observed panchromatic emission of galaxies from the FUV to the FIR across 0<=z<=10 without retuning or changing physical assumptions. The authors construct SEDs from simulated star formation and metallicity histories, compute dust masses from a local empirical relation between dust-to-metal ratio and gas metallicity (Remy-Ruyer et al. 2014), derive diffuse-ISM attenuation parameters from radiative transfer calculations of EAGLE galaxies (Trayford et al. 2019), and re-emit attenuated light in the infrared using energy-conserving Dale et al. (2014) templates. They find the model matches observed luminosity functions, number counts, UV slopes, the redshift distribution of bright 850-micron galaxies, and the cosmic SED. Their key discovery is that the long-standing tension between simultaneously reproducing UV-optical and FIR emission, which earlier models resolved by invoking a top-heavy IMF in starbursts, is not required here; the answer is model dependent. They attribute the difference to the combination of realistic gas metallicities, galaxy sizes, dust surface densities, attenuation curves, and dust temperatures in Shark.

Load-bearing premise

The model assumes that the relation between dust mass, gas metals, and gas metallicity measured in nearby galaxies holds unchanged out to redshift 10; if dust production or destruction changes that ratio with time, the claimed joint fit to ultraviolet and 850-micron observations could be an artifact of the assumed scaling.

Editorial extensions

If this is right

  • The model can be used to build panchromatic lightcones for upcoming surveys, since the SED machinery requires no retuning when new bands or redshifts are considered.
  • The 850-micron number counts and the redshift distribution of bright submillimetre galaxies are reproduced without a top-heavy IMF, so current and future submm surveys can be interpreted within a universal-IMF galaxy formation model.
  • Predicted cosmic SEDs at z>1 are genuine predictions awaiting observation; if JWST and ALMA confirm the steep UV slopes and FIR dominance by starbursts, the model's attenuation prescriptions will be validated.
  • The observed cosmic SEDs at z<=1 are matched within about 0.1-0.15 dex, providing a benchmark for interpreting the extragalactic background light.
  • The model demonstrates that complex, non-parametric star-formation histories from a semi-analytic model can be used directly for SED generation, rather than assuming simple analytic forms.

Reading between the lines

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

  • If the local dust-to-metal scaling is truly invariant, then high-redshift UV-selected galaxies should be nearly dust-free at fixed stellar mass, a prediction that can be tested with ALMA dust-continuum observations of z~6-8 galaxies.
  • The model's success suggests the earlier need for a top-heavy IMF in other models was partly due to those models' gas metallicities and sizes, not an intrinsic constraint; applying the same attenuation prescription across different galaxy-formation models would isolate the cause.
  • The fixed dust temperatures adopted for re-emission mean the model's 850-micron counts are sensitive to the assumed dust SED, so allowing a redshift-dependent dust temperature would sharpen the claim of a simultaneous fit.
  • A direct extension is to use the same machinery to generate mock catalogues for JWST and Euclid to predict colour-selection biases and photometric-redshift systematics.
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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 / 5 minor

Summary. The paper combines the Shark semi-analytic model of galaxy formation with the ProSpect SED generation code to predict galaxy emission from the FUV to the FIR over 0 ≤ z ≤ 10. Dust attenuation is built from radiative-transfer-derived Charlot & Fall parameters calibrated on EAGLE galaxies, dust masses are computed from gas mass and metallicity using local empirical relations (Rémy-Ruyer et al. 2014), and absorbed light is re-emitted with Dale et al. (2014) templates under energy balance. The authors compare four attenuation variants against a wide set of observations: z=0 FUV-to-FIR luminosity functions, rest-frame K-band and FUV luminosity functions out to z=3 and z=10, UV slopes, number counts from the NUV to 850 µm, the redshift distribution of bright 850 µm galaxies, and the cosmic SED. The central claim is that Shark reproduces these observations simultaneously with a universal Chabrier IMF, without retuning to SED data and without invoking a varying IMF or a redshift-dependent dust-to-metal scaling.

Significance. If the central claim holds, this is a significant advance: it would show that a full cosmological galaxy formation model can simultaneously match UV-to-optical and FIR observations without a varying IMF, and it would provide a generative, panchromatic tool for interpreting upcoming surveys. The paper's strengths include the open-source software infrastructure (Shark, ProSpect, Viperfish), the systematic comparison in 27 bands, the explicit decomposition into disk, merger-driven bulge, and disk-instability-driven bulge contributions, and the unusually candid discussion of model limitations, including the dust-to-metal scaling and dust temperature assumptions. The claim of being 'unprecedented' is plausible but needs sharper qualification because some comparisons (K-band, near-IR) partly inherit the model's tuning to the stellar mass function, and because the headline high-redshift result is obtained with a specific steep variant of the local dust-to-metal relation.

major comments (3)
  1. [§2.2, §6, Figs. 14–15] The central conclusion that no redshift-dependent dust-to-metal scaling is needed is not fully established. The attenuation chain assumes the local Rémy-Ruyer et al. (2014) dust-to-metal ratio versus gas metallicity relation is invariant out to z=10, as the paper itself states in §6. The manuscript also cites Vijayan et al. (2019), who predict a dust-to-metal ratio about 1.5 dex lower at z=8–10 at fixed stellar mass, while Popping et al. (2017) find little evolution. Because the high-redshift UV LFs and UV slopes are the main probes of this regime, the claimed simultaneous match could be an artifact of the assumed redshift-invariant scaling rather than a success of Shark's baryon physics. Please add a sensitivity test in which the dust-to-metal ratio evolves with redshift within the published range and re-evaluate the UV LFs, the 850 µm counts, and the SMG redshift distribution; if the conclusions survive, state this explicitly, and otherwise soften the abstract and conclusion claims accordingly.
  2. [§4.3, Fig. 14] The high-redshift agreement is obtained with the EAGLE-τ RR14-steep variant, not with the model labelled as the default (EAGLE-τ RR14). At z=3–6 the default RR14 and fdust-const models over-attenuate bright galaxies, with differences of up to ~1.5 mag at z=3 and ~2 mag at z=6 in the disk contribution to the UV LF. The paper is transparent about this in the text and captions, but the abstract and conclusions present the high-z match without saying that it depends on selecting one particular steep variant within the local scatter of the Rémy-Ruyer relation. This makes the 'without retuning' claim less clean: choosing among variants after inspecting the comparisons is a mild form of model selection even if no parameter is re-fit. Please clarify throughout that the headline high-redshift result refers to a specified steep variant, and discuss the extent to which that choice is motivated a priori by De Vis et al. (2019) versus selected after comparing with the observed LFs.
  3. [§3.2, §5.1, Figs. 16–17] The FIR predictions that support the 'no varying IMF' conclusion assume a fixed Dale et al. (2014) dust SED with two constant effective dust temperatures (≈20–25 K for the diffuse ISM and ≈50–60 K for birth clouds) at all redshifts. The 850 µm number counts and the redshift distribution of bright 850 µm galaxies are temperature-sensitive, and the paper itself notes that GALFORM's self-consistently computed dust temperature evolves with redshift. Please quantify how much the predicted 850 µm counts and N(z) change if the dust temperature or the αSF parameters evolve with redshift within a plausible range, or explicitly restrict the claim of no varying IMF to the fixed-temperature model adopted here. As written, the FIR side of the headline claim contains an additional untested invariance assumption beyond the dust-to-metal scaling.
minor comments (5)
  1. [§5.1, Fig. 16] The lightcone area is printed as '107 deg2' and the caption says '107 deg2 deep lightcone'. If this is meant to be 10^7 deg2, it exceeds the whole sky (~4.1×10^4 deg2) and is unphysical; if it is meant to be 10^7 arcmin2 or another value, please state the correct units explicitly.
  2. [Abstract, §4.2, §4.3] The near-infrared and K-band luminosity function agreement is partly inherited from tuning Shark to the z=0, 1, and 2 stellar mass functions and to the mass-size relations; the text acknowledges this ('not necessarily surprising'), but the abstract's broad 'without retuning' claim should be qualified so readers can see which comparisons are truly independent of the tuning.
  3. [Figs. 10–17] The comparisons are assessed visually, with qualitative statements such as 'excellent' and 'very good'. Adding a quantitative goodness-of-fit measure (including model cosmic variance and observed systematic uncertainties) would make the 'unprecedented agreement' claim easier to evaluate.
  4. [Fig. 1] The caption should define the 'Remy-Ruyer14 - XCO Z' and 'Remy-Ruyer14 - XCO MW' variants, since these labels are not self-explanatory without going to the Rémy-Ruyer et al. paper.
  5. [Fig. 8 caption and figure] The y-axis of the GALEX UV LFs is presented without normalization by bin size, while later figures normalize by bin size; this inconsistency should be flagged in the caption to avoid confusion.

Circularity Check

1 steps flagged · score 3.0 of 10

K-band LF agreement is self-admittedly inherited from SMF tuning; the central FUV-to-FIR chain otherwise rests on independent inputs.

  1. fitted input called prediction [Section 4.3, after Fig. 13 (rest-frame K-band LF comparison)]
    "This is not necessarily surprising as the free parameters in Shark are chosen to provide a good fit to the z = 0, 1, 2 stellar mass functions, which are strongly correlated with the rest-frame K-band luminosity."

    Shark's default parameters were tuned to the z=0,1,2 stellar mass functions (Section 2). Rest-frame K-band luminosity is essentially stellar mass times a mass-to-light ratio, so the K-band LF is not an independent prediction: at the masses that dominate the SMF fit it is largely forced by the same tuning inputs. The paper concedes this explicitly. Since the abstract lists the 0<=z<=3 rest-frame K-band LF among the reproduced observables, that specific comparison partially reduces to the fitted input rather than to the new SED/attenuation modelling.

full rationale

The central FUV-to-FIR derivation is not circular. The attenuation parameters come from radiative transfer on the independent EAGLE hydrodynamical simulation suite (Trayford et al. 2019), not from Shark or from the observed luminosity functions being compared; the dust masses come from the local Remy-Ruyer et al. (2014) scaling; and the FIR re-emission uses energy balance with fixed Dale et al. (2014) templates. No free parameter of the SED pipeline is fitted to the target LFs or number counts. The paper also honestly flags the redshift-invariance of the dust-to-metal relation as an assumption, noting that competing models disagree by about 1.5 dex at z=8-10. The only in-sample element is the underlying Shark tuning to the z=0,1,2 stellar mass functions, which the paper itself identifies as making the K-band LF agreement unsurprising; that specific 'prediction' is therefore partly forced by construction. The selection of the RR14-steep variant as the best-performing attenuation model is a model-choice caveat but not a definitional reduction, since its parameters still come from local data. Overall, the central simultaneous UV-to-FIR claim has independent content, with one admitted tuning-correlated comparison.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

The paper introduces no new particles or physical entities. All ingredients are existing models and empirical relations. The free parameters are mostly carried from Shark or from the CF00/Dale/Trayford/Remy-Ruyer frameworks. The central modeling burden is the assumed transferability of local dust scalings and EAGLE attenuation curves to all redshifts, plus the fixed FIR template shapes.

free parameters (4)
  • epsilon_disk (disk instability threshold) = 0.8
    Taken from the default Shark model; treated as a free parameter in Lagos et al. (2018), and it controls the abundance of disk-instability starbursts that contribute to the FIR at high redshift.
  • tau_BC,z0 (birth cloud optical depth normalization) = 1.0
    Eq. 6: tau_BC = tau_BC,0 [fdust Zgas Sigma_gas,cl / (fdust,MW Zsun Sigma_MW,cl)]. The normalization tau_BC,0 = 1 and the local cloud surface density Sigma_MW,cl = 85 Msun/pc^2 are adopted from Charlot and Fall (2000) and Lacey et al. (2016); they set the overall scale of birth-cloud attenuation.
  • Dale et al. (2014) alpha_SF parameters = alpha_SF = 3 (diffuse ISM), 1 (birth clouds)
    These set the FIR template shapes and effective dust temperatures (about 20-25 K and 50-60 K). They are fixed values chosen from the literature, but they are not derived from the target observations covered in this paper.
  • Remy-Ruyer et al. (2014) dust-to-metal versus Zgas relation and its steep variant = RR14 best fit; RR14-steep variant
    The dust-to-metal ratio is taken from a local empirical fit (Remy-Ruyer et al. 2014), with a steeper variant, RR14-steep, used as the best-performing model for high-redshift UV LFs and UV slopes. The choice of RR14-steep over RR14 is motivated partly by agreement with the UV LF and UV slope data, which is a mild model-selection effect.
assumptions (6)
  • domain assumption Charlot and Fall (2000) two-phase dust attenuation model with power-law optical depths (Eqs. 4-5) applies to all Shark galaxies at all redshifts.
    The paper adopts the CF00 parametric form for the attenuation curve and only varies tau_ISM, eta_ISM, tau_BC with galaxy properties. This is an assumed functional form for the dust-star geometry, motivated by EAGLE RT but still an approximation.
  • domain assumption Dale et al. (2014) IR templates with two fixed alpha_SF values represent dust re-emission at all redshifts.
    The paper assumes fixed effective dust temperatures for the diffuse ISM and birth clouds, about 20-25 K and 50-60 K, at all redshifts (Section 3.2 and Conclusions). The paper notes GALFORM computes a dust temperature that weakly increases with redshift, which would weaken the 850 micron emission at fixed FIR luminosity.
  • domain assumption The Trayford et al. (2019) parametrization of EAGLE attenuation curves, tau_ISM and eta_ISM as functions of dust surface density, is transferable to Shark galaxies.
    The parametrization is derived from EAGLE hydrodynamic simulations and applied to Shark galaxies with different sizes, gas fractions, and ISM structure. The paper acknowledges the sub-grid ISM model in EAGLE impacts clumpiness and attenuation.
  • domain assumption The local dust-to-metal ratio versus gas metallicity relation holds at all redshifts out to z=10.
    This is the weakest assumption. The paper applies Remy-Ruyer et al. (2014) out to z=10 and explicitly acknowledges competing models predict a strongly evolving dust-to-metal ratio, with about 1.5 dex differences at z=8-10 (Section 4.3).
  • domain assumption Dust surface density of disks and bulges is computed using the half-gas mass radius and an assumed disk scaleheight ratio of 7.3 (Eqs. 2-3).
    The 7.3 comes from Kregel et al. (2002) local disk observations and is assumed redshift-independent. Bulges are assumed spherical. These geometric choices directly set the dust column densities used to derive optical depths.
  • domain assumption Shark's default baryon physics model, as tuned in Lagos et al. (2018), provides the correct star formation histories, gas masses, metallicities, and sizes.
    All SED predictions inherit the Shark galaxy properties. The paper relies on the published successes of Shark but the tuning targets (z=0,1,2 SMFs, BH-host relations, size relations) do not guarantee the SFHs that drive UV and FIR emission are correct.

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Cite this review

Pith. "Pith review of From the far-ultraviolet to the far-infrared -- galaxy emission at $0\le z \le 10$ in the Shark semi-analytic model." pith.science (2026). https://pith.science/paper/LNII5PB4

@misc{pith2026190803423,
  author       = {Pith},
  title        = {Pith review of: From the far-ultraviolet to the far-infrared -- galaxy emission at $0\le z \le 10$ in the Shark semi-analytic model},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/LNII5PB4}},
  note         = {Machine review of arXiv:1908.03423}
}
abstract

We combine the Shark semi-analytic model of galaxy formation with the ProSpect software tool for spectral energy distribution (SED) generation to study the multi-wavelength emission of galaxies from the far-ultraviolet (FUV) to the far-infrared (FIR) at $0\le z\le 10$. We produce a physical model for the attenuation of galaxies across cosmic time by combining a local Universe empirical relation to compute the dust mass of galaxies from their gas metallicity and mass, attenuation curves derived from radiative transfer calculations of galaxies in the EAGLE hydrodynamic simulation suite, and the properties of Shark galaxies. We are able to produce a wide range of galaxies, from the $z=8$ star-forming galaxies with almost no extinction, $z=2$ submillimeter galaxies, down to the normal star-forming and red sequence galaxies at $z=0$. Quantitatively, we find that Shark reproduces the observed (i) the $z=0$ FUV-to-FIR, (ii) $0\le z\le 3$ rest-frame $K$-band, and (iii) $0\le z\le 10$ rest-frame FUV luminosity functions, (iv) $z\le 8$ UV slopes, (v) the FUV-to-FIR number counts (including the widely disputed 850$\mu$m), (vi) redshift distribution of bright $850\mu$m galaxies and (vii) the integrated cosmic SED from $z=0$ to $z=1$ to an unprecedented level. This is achieved without the need to invoke changes in the stellar initial mass function, dust-to-metal mass ratio, or metal enrichment timescales. Our model predicts star formation in galaxy disks to dominate in the FUV-to-optical, while bulges dominate at the NIR at all redshifts. The FIR sees a strong evolution in which disks dominate at $z\le 1$ and starbursts (triggered by both galaxy mergers and disk instabilities, in an even mix) dominate at higher redshifts, even out to $z=10$.

Figures

Figures reproduced from arXiv: 1908.03423 by the authors.

Figure 1
Figure 1. Fraction of metals in dust as a function of gas metallic￾ity. Local Universe observations of R´emy-Ruyer et al. (2014) are shown as diamonds, while their best fit relation is shown as thick dashed line. We also show the observations of De Vis et al. (2019) as circles from the DustPedia of a large sample of local galaxies. The thin dotted lines show the 1σ uncertainty in the slope of the relation at low metallicities… view at source ↗
Figure 2
Figure 2. Dust surface density (Eqs. 2 and 3) as a function of stellar mass from z = 8 to z = 0 for disks and bulges in Shark combined with the model RR14-steep to derive dust masses from the gas metallicity and surface density information. Lines show the medians, while shaded regions show the 16th − 84th percentile ranges. fit Mdust/MZ−Zgas relation in R´emy-Ruyer et al. (2014) being quite significant and the recent observat… view at source ↗
Figure 3
Figure 3. Optical depth of dust in the diffuse ISM and birth clouds of the disks and bulges of galaxies, as labelled at the top of each panel, as a function of stellar mass from z = 0 to z = 8, as labelled, for the EAGLE-τ RR14-steep attenuation model. Lines show the medians, while shaded regions show the 16th − 84th percentile ranges. Horizontal lines show the default values adopted for the Charlot & Fall (2000) model. 6 7 8… view at source ↗
Figures from the paper (16 more)
Figure 4
Figure 4. Figure 4: Power-law index of the optical-depth dependence on wavelength in Eq. 4, for the disks (left) and bulges (right) of Shark galaxies as a function of stellar mass from z = 0 to z = 8, as labelled, for the EAGLE-τ RR14-steep attenuation model. Lines show the medians, while…
Figure 5
Figure 5. Figure 5: Examples of the star formation rate as a function of lookback time (LBT) of Shark galaxies that by z = 0 have stellar masses > 109 M and mean stellar-mass weighted ages ±0.3 Gyr from the value indicated in each panel. We show for each selection 10 random examples, and …
Figure 7
Figure 7. Figure 7: Rest-frame broadband photometry (after including the effects of dust extinction and re-radiation) in 27 bands (as in [PITH_FULL_IMAGE:figures/full_fig_p009_7.png]
Figure 6
Figure 6. Figure 6: Broadband photometry in 27 bands (in order of wave￾length: GALEX FUV and NUV, SDSS ugriz, VISTA YJHK, WISE 1, IRAC 3.6µm, IRAC 4.5µm, WISE 2, IRAC 5.8µm, IRAC 8µm, WISE 3 and 4 and Herschel PACS 70µm, 100µm, 160µm, Herschel SPIRE 250µm, 350µm JCMT 450µm, SPIRE 500µm an…
Figure 9
Figure 9. Figure 9: Luminosity functions at z = 0 for the Herschel PACS band 160µm, and SPIRE bands 250µm and 500µm. Here we show the total LF for all the galaxies in the Shark model of La￾gos et al. (2018) using the four attenuation models of [PITH_FULL_IMAGE:figures/full_fig_p010_9.png]
Figure 10
Figure 10. Figure 10: Luminosity functions at z = 0 for the GALEX FUV and NUV bands (top panels) and the SDSS u, r, g, i and z bands (middle and bottom panels), as labelled. Here, we include all galaxies in the Shark model and adopt the default extinction model EAGLEτ RR14 (see [PITH_FULL…
Figure 12
Figure 12. Figure 12: Luminosity functions at z = 0 for the Herschel PACS band 160µm, SPIRE bands 250µm, 350µm, 500µm and the JCMT 850µm, as labelled in each panel. As in [PITH_FULL_IMAGE:figures/full_fig_p013_12.png]
Figure 13
Figure 13. Figure 13: K-band LF out to z = 3, as labelled, for Shark af￾ter applying the extinction models of [PITH_FULL_IMAGE:figures/full_fig_p014_13.png]
Figure 14
Figure 14. Figure 14: Rest-frame UV LFs from z = 3 to z = 10, as labelled, showing the intrinsic emitted light in thin, solid lines, and the four attenuation models of [PITH_FULL_IMAGE:figures/full_fig_p015_14.png]
Figure 15
Figure 15. Figure 15: The UV slope evolution of Shark galaxies with a rest￾frame 1500 magnitude of [−19.7, −19.3] mags (AB), computed as ν ∝ λ 2+βUV , for the 4 attenuation models of [PITH_FULL_IMAGE:figures/full_fig_p016_15.png]
Figure 16
Figure 16. Figure 16: Number counts for out Shark 107 deg2 deep lightcone and the 4 attenuation models of [PITH_FULL_IMAGE:figures/full_fig_p017_16.png]
Figure 17
Figure 17. Figure 17: Redshift distribution of Shark 850µm galaxies with a flux ≥ 5 mJy for the 4 attenuation models of [PITH_FULL_IMAGE:figures/full_fig_p018_17.png]
Figure 18
Figure 18. Figure 18: Cosmic Spectral Energy Distribution at z = 0, z = 1, z = 3 and z = 6 for Shark using the 4 attenuation models of [PITH_FULL_IMAGE:figures/full_fig_p018_18.png]
Figure 19
Figure 19. Figure 19: The UV slope of the Shark CSED computed as ν ∝ λ 2+βUV as a function of redshift for the 4 attenuation models of [PITH_FULL_IMAGE:figures/full_fig_p019_19.png]
Figure 20
Figure 20. Figure 20: Cosmic Spectral Energy Distribution at z = 0.25, z = 0.5 and z = 1, as labelled, for Shark (small and large diamonds show the intrinsic and attenuated/remitted light, respectively) using the attenuation model EAGLE-τ RR14 (see [PITH_FULL_IMAGE:figures/full_fig_p019_20.png]
Figure 21
Figure 21. Figure 21: As in [PITH_FULL_IMAGE:figures/full_fig_p020_21.png]

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Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.