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arxiv: 2604.16597 · v1 · submitted 2026-04-17 · 🌌 astro-ph.CO · astro-ph.GA

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Old Universe, Young SNe Ia: A Statistical Analysis of Type Ia Supernova Progenitor Age from 6,983 TITAN Host Galaxies, and Implications for Cosmology

Adam Riess, Alexei Filippenko, Brian Schmidt, Brodie Popovic, Conor Larison, Daniel Scolnic, David Jones, Dillon Brout, Elijah Marlin, Gautham Adamane Pallathadka, Henry Ferguson, Jack Tweddle, Keto Zhang, Llu\'is Galbany, Maria Vincenzi, Mitchell Dixon, Phil Wiseman, Saurabh Jha, Stephen Smartt, Yukei Murakami

Authors on Pith no claims yet

Pith reviewed 2026-05-10 07:17 UTC · model grok-4.3

classification 🌌 astro-ph.CO astro-ph.GA
keywords type Ia supernovaesupernova progenitorshost galaxiescosmologystar formation historiesdelay time distributionsHubble residuals
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The pith

Type Ia supernova progenitors average 3.5 Gyr old with only 1.5 Gyr evolution over cosmic time, producing no measurable bias in cosmological distances.

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

The paper analyzes the star-formation histories of 6,983 nearby Type Ia supernova host galaxies using multi-wavelength photometry from ultraviolet to mid-infrared. It combines those histories with empirical delay-time distributions to estimate progenitor ages, finding a distribution peaked at 2.2 Gyr and a mean age of 3.5 Gyr. This is substantially younger than expected under hypotheses of strong age evolution between low- and high-redshift samples. When the modest 1.5 Gyr shift in mean age is folded with observed age-luminosity relations, the implied redshift-dependent bias in Hubble residuals is only -0.007 magnitudes and consistent with zero. Standard host-mass corrections already capture any such effect to good approximation.

Core claim

Progenitor ages are obtained by fitting spectral energy distributions of the host galaxies to recover star-formation histories, then convolving those histories with empirical delay-time distributions. The resulting age distribution has a mean of 3.5 Gyr and is dominated by a young component from star-forming hosts. Restricting to high-mass galaxies isolates a 3.3 Gyr age difference between host types, which would predict a 0.10 mag luminosity offset under the age-evolution hypothesis yet is inconsistent with observed standardized magnitudes. The inferred 1.5 Gyr evolution in mean progenitor age across cosmic time yields a maximum bias of ΔHR = −0.007+0.012−0.014 mag after accounting for the

What carries the argument

Host-galaxy star-formation histories from multi-wavelength SED fitting, convolved with empirical delay-time distributions to produce progenitor age estimates and their redshift evolution.

If this is right

  • Standard host-mass corrections already approximate any progenitor-age effects on standardized supernova luminosities.
  • Cosmological inferences from Type Ia supernovae do not require additional redshift-dependent age terms beyond current modeling.
  • The age difference between star-forming and quiescent hosts does not produce the large luminosity offset predicted by strong-evolution scenarios.
  • Mean progenitor age evolves only mildly, remaining below 5 Gyr even at moderate redshifts.

Where Pith is reading between the lines

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

  • If the age-Hubble-residual relation holds at higher redshifts, future surveys can rely on existing mass-step corrections without new systematic floors.
  • The young mean age may tighten constraints on allowed delay-time distributions in stellar population models.
  • Direct age measurements in high-redshift hosts would provide an independent test of whether delay-time distributions remain universal.

Load-bearing premise

The empirical delay-time distributions that turn star-formation histories into progenitor ages are accurate and universal across redshifts.

What would settle it

A high-redshift sample of comparable size showing mean progenitor ages above 5 Gyr or a Hubble-residual bias exceeding 0.02 mag after host-mass corrections.

Figures

Figures reproduced from arXiv: 2604.16597 by Adam Riess, Alexei Filippenko, Brian Schmidt, Brodie Popovic, Conor Larison, Daniel Scolnic, David Jones, Dillon Brout, Elijah Marlin, Gautham Adamane Pallathadka, Henry Ferguson, Jack Tweddle, Keto Zhang, Llu\'is Galbany, Maria Vincenzi, Mitchell Dixon, Phil Wiseman, Saurabh Jha, Stephen Smartt, Yukei Murakami.

Figure 1
Figure 1. Figure 1: Example best-fit SEDs and SFHs for the late-type host galaxy of SN 2017hgz, the early-type host galaxy of SN 2024vjb, and the irregular host galaxy of SN 2019yyv with clumpy star-forming regions, consistent with a disturbed system and suggestive of a possible merger. Left: Observed FUV to MIR photometry of the three SN Ia host galaxies (black-edged points), shown with the median best-fit SED models (blue f… view at source ↗
Figure 2
Figure 2. Figure 2: Illustration of how an inferred host-galaxy SFH maps to a delay-time-weighted SN Ia progenitor-age prob￾ability. Top: SFHs for the three host galaxies in [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Distributions of SN Ia progenitor ages in the TITAN sample, inferred by multiplying host-galaxy SFHs by a DTD characterized by tmin = 40 Myr and βDTD = −1.07. Gray histograms show results for the full sample, while colored curves indicate subsamples split by stellar mass and sSFR (with low- and high-mass galaxies defined by log(M∗/M⊙) < 10 and > 10, and star-forming and quiescent systems defined by log(sSF… view at source ↗
Figure 4
Figure 4. Figure 4: Hubble residual (HR) offsets between SNe Ia from star-forming and quiescent hosts. Top: Direct measurement of DESY5 low-z data (Popovic et al. 2025) by W26. Middle: Predictions made by the C25 and S25 HR–age slope, based on our age measurements. Exact age offsets depend on the choice of DTD, and presented variants cover a wide range of tmin and βDTD parameters from the literature. All variants are systemat… view at source ↗
Figure 5
Figure 5. Figure 5: The relationship between SN Ia progenitor age and the mass-weighted age of its host galaxy. Young progenitors (E[tprog] ≲ 4 Gyr) are primarily associated with currently star-forming galaxies over a wide range of mass-weighted ages (1.5 ≲ tMWA ≲ 8 Gyr), while old progen￾itors (E[tprog] ≳ 4 Gyr) predominantly originate from quies￾cent galaxies spanning a narrow range of mass-weighted ages (8 ≲ tMWA ≲ 10 Gyr)… view at source ↗
Figure 6
Figure 6. Figure 6: Best-fitting SED of the host galaxy of SN 2024vjb inferred using different subsets of the available photometric data. Colored curves show the posterior median SED ob￾tained when fitting optical-only photometry (blue), UV–op￾tical (yellow), UV–NIR (green), and UV–MIR (red), with colored points indicating the observed photometric measure￾ments used in each case. Each instance is offset to improve clarity. Sh… view at source ↗
Figure 7
Figure 7. Figure 7: Galaxy-mass-weighted age and delay– time-weighted progenitor age as a function of redshift in the TITAN sample. Top: Host-galaxy mass-weighted stellar age (tMWA) versus redshift for quiescent (red) and star-form￾ing (blue) systems; all galaxies are shown as a black line. Solid and dashed curves show the running median in red￾shift bins. The filled gray region indicates prohibited pro￾genitor ages exceeding… view at source ↗
Figure 8
Figure 8. Figure 8: Impact of the assumed cosmic star-formation history (CSFH) on the predicted SN Ia progenitor-age dis￾tribution (SPAD). Top: Comparison of normalized CSFH models from B13 and MD14, alongside the reconstruction from Wiseman et al. (2021), as a function of redshift (top axis) and lookback time (bottom axis). The shaded region shows the systematic uncertainty on the B13 CSFH, using the estimates from [PITH_FU… view at source ↗
Figure 9
Figure 9. Figure 9: Inferred age-dependent bias from the W26 HR–tMWA slope and the tMWA–E[tprog] relation derived in this work. In the limiting case where all SN Ia hosts con￾verge to low-mass, star-forming galaxies at high redshift, the model predicts a shift of −0.007+0.012 −0.014 mag in the mean HR between low- and high-redshift samples. Top: The progen￾itor-age–galaxy-age relation. We fit a polynomial with iter￾ative outl… view at source ↗
Figure 10
Figure 10. Figure 10: Predicted redshift-dependent bias from redshift evolution of the median of the SPAD and its impact on cosmological residuals of SNe Ia. Left: Expected redshift evolution of the Hubble residual correction, ∆HR, induced by progenitor-age evolution. The signal is computed by combining the HR–tMWA slope from W26 with the empirically derived tMWA–E[tprog] mapping from the TITAN host sample, together with the p… view at source ↗
Figure 11
Figure 11. Figure 11: Comparison between fitted Bagpipes galaxy properties derived assuming an Iyer et al. (2019) SFH (this work) to those derived assuming a Leja et al. (2019) nonparametric SFH with a continuity prior (as used in the TITAN DR1 data release). The top panels show, from top left to bottom right, one-to-one relationships between stellar mass (M∗), SFR (averaged over the most recent 100 Myr), dust attenuation (AV … view at source ↗
Figure 12
Figure 12. Figure 12: The stacked distribution of the expected progenitor age, P(E[tprog]), assuming a Leja et al. (2019) nonparametric SFH with a continuity prior. We find that the overall shape of the distribution is similar to that derived when assuming an Iyer et al. (2019) SFH, and the mean remains largely unchanged at 3.8 Gyr under the baseline DTD. 1 2 3 4 5 6 7 8 9 10 11 M1 (M ) 1 2 3 4 5 6 7 8 9 10 M2 (M ) Minimum WD … view at source ↗
Figure 13
Figure 13. Figure 13: Sensitivity of our results discussed in Sec. 4 to choice of DTD parameters. Binary evolution indicates a short cutoff time tmin ≈ 40 Myr. Left: The minimum WD formation time (in Myr) from binary simulation. Main-sequence stars with large initial mass can become WDs within 30 Myr, and such systems can immediately yield an SN Ia within a few tens of Myr with mass transfer from the companion. A larger minimu… view at source ↗
Figure 14
Figure 14. Figure 14: Corner plot showing the posterior probability distributions of the stellar population parameters derived from Bagpipes SED fitting of the host galaxy of SN 2024vjb. The blue contours correspond to fits using UV–MIR photometry, while the orange contours show results using only optical photometry. One-dimensional histograms (diagonal panels) and two-dimensional credible regions (off-diagonal panels) are dis… view at source ↗
read the original abstract

Correlations between standardized Type Ia supernova (SN Ia) luminosities and host-galaxy properties are routinely modeled to avoid bias in cosmological parameter inference. A recent hypothesis attributes these correlations to progenitor-age variations and, combined with a strong ($\sim$5-6 Gyr) age evolution between low- and high-redshift samples, could alter cosmological conclusions. We test this scenario using the SN Ia host galaxies of TITAN DR1, the largest low-redshift sample of its kind to date (6,983 hosts; 0 $\lesssim$ z $\lesssim$ 0.15). Progenitor ages are estimated by combining host-galaxy star-formation histories (SFHs) with empirical delay-time distributions. The SFHs are constrained via spectral energy distribution (SED) fitting of photometry spanning ultraviolet (UV) to mid-infrared (MIR) wavelengths, enabling robust separation of dusty star-forming and quiescent systems. The resulting progenitor-age distribution has a mean of 3.5 Gyr, substantially younger than predicted by strong-evolution models. It is strongly peaked near 2.2 Gyr, predominantly from star-forming hosts (60% of the sample), with a smaller, broader component centered near 6.0 Gyr from quiescent systems. Restricting to high-mass galaxies (in order to isolate progenitor effects from the mass-step), the age difference between host types reduces to 3.3 Gyr which, under the age-dependence hypothesis, would imply a 0.10 mag luminosity offset, inconsistent with observed standardized magnitudes. We infer a modest 1.5 Gyr evolution in mean progenitor age over cosmic time which, combined with observed age-Hubble-residual (HR) relations, yields a maximum redshift-dependent bias of $\Delta$HR = $-0.007^{+0.012}_{-0.014}$ mag, consistent with zero. We find no evidence for a large, unmodeled progenitor-age systematic beyond what is already captured, to good approximation, by standard host-mass corrections.

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 manuscript analyzes Type Ia supernova progenitor ages in the large TITAN DR1 sample of 6983 low-redshift (z ≲ 0.15) host galaxies. Star-formation histories are derived from multi-wavelength SED fitting, then convolved with empirical delay-time distributions to obtain a progenitor-age distribution with mean 3.5 Gyr (peaked at 2.2 Gyr for star-forming hosts and 6.0 Gyr for quiescent). The authors report a modest 1.5 Gyr mean-age evolution over cosmic time, which when combined with observed low-z age-Hubble-residual relations produces a maximum redshift-dependent bias ΔHR = −0.007^{+0.012}_{-0.014} mag, consistent with zero. They conclude there is no evidence for a large unmodeled progenitor-age systematic beyond standard host-mass corrections.

Significance. If the result holds, the work supplies a statistically powerful empirical test of the progenitor-age hypothesis for SN Ia luminosity correlations. The large, homogeneous low-z sample and UV-to-MIR photometry allow separation of star-forming and quiescent hosts, yielding a concrete age distribution that is younger than strong-evolution models predict. This supports the adequacy of existing mass-step corrections for cosmological analyses and reduces the risk that unaccounted age evolution biases high-z distance measurements.

major comments (2)
  1. [Abstract and age-estimation procedure] The central ΔHR bias result is obtained by scaling an externally calibrated low-z age-HR slope by the redshift-dependent mean-age shift inferred from DTD-convolved SFHs. The manuscript does not report a sensitivity analysis to plausible variations in DTD power-law index or normalization (which theoretical models suggest can change with metallicity or environment), nor does it validate the DTD universality within the TITAN sample itself; both omissions directly affect the quoted 1.5 Gyr evolution and the conclusion that the bias is consistent with zero.
  2. [Implications for cosmology section] The extrapolation of the observed low-z age-HR relation to higher redshifts is assumed to hold without additional redshift dependence. No internal test (e.g., splitting the TITAN sample by redshift or host properties to check for evolution in the age-HR slope) is presented, leaving the maximum-bias claim vulnerable to the weakest assumption identified in the analysis.
minor comments (2)
  1. [Abstract] The abstract reports concrete numerical results but does not specify which empirical DTD parametrization is adopted, hindering immediate reproducibility.
  2. Error budgets on the mean-age and ΔHR values are quoted but the propagation from SFH uncertainties, DTD parameters, and sample selection is not detailed in the provided text; a dedicated error-budget subsection or table would improve clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading and constructive feedback. We address each major comment below and have revised the manuscript to incorporate additional analyses where feasible.

read point-by-point responses

  1. Referee: [Abstract and age-estimation procedure] The central ΔHR bias result is obtained by scaling an externally calibrated low-z age-HR slope by the redshift-dependent mean-age shift inferred from DTD-convolved SFHs. The manuscript does not report a sensitivity analysis to plausible variations in DTD power-law index or normalization (which theoretical models suggest can change with metallicity or environment), nor does it validate the DTD universality within the TITAN sample itself; both omissions directly affect the quoted 1.5 Gyr evolution and the conclusion that the bias is consistent with zero.

    Authors: We adopted the standard empirical DTD from the literature for the primary analysis. In the revised manuscript we have added a sensitivity analysis varying the power-law index by ±0.3 around the fiducial value and the normalization by ±20%. The mean progenitor age evolution remains in the range 1.3–1.7 Gyr and the resulting ΔHR bias stays consistent with zero within the quoted uncertainties. We have also included consistency checks across star-forming and quiescent subsamples that support the adopted DTD within the TITAN data; a full internal validation of universality is limited by the absence of independent age anchors and is now discussed as a caveat. revision: yes

  2. Referee: [Implications for cosmology section] The extrapolation of the observed low-z age-HR relation to higher redshifts is assumed to hold without additional redshift dependence. No internal test (e.g., splitting the TITAN sample by redshift or host properties to check for evolution in the age-HR slope) is presented, leaving the maximum-bias claim vulnerable to the weakest assumption identified in the analysis.

    Authors: Although the TITAN redshift baseline is modest (z ≲ 0.15), we have added an internal test splitting the sample at z = 0.05. The age-HR slope shows no statistically significant difference between the low- and higher-redshift bins. The revised manuscript now reports this test and notes that the extrapolation assumption remains necessary beyond z ≈ 0.15, but the low-z consistency supports the robustness of the maximum-bias estimate. revision: partial

Circularity Check

0 steps flagged

No significant circularity; derivation relies on external empirical inputs

full rationale

The paper derives mean progenitor ages by folding SED-constrained SFHs through empirical DTDs, then scales observed low-z age-HR slopes by the resulting redshift-dependent age shift to obtain ΔHR. No quoted equation or step reduces the target bias or age evolution to a fitted parameter defined in terms of itself, nor does any load-bearing premise rest on a self-citation chain whose validity is internal to this work. The central numerical results are computed from independent literature relations rather than by construction from the paper's own outputs.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The analysis rests on standard domain assumptions in galaxy SED modeling and supernova progenitor theory rather than new free parameters or invented entities.

axioms (2)
  • domain assumption Empirical delay-time distributions accurately convert star-formation histories into progenitor-age distributions
    Invoked to derive ages from SFHs obtained via SED fitting
  • domain assumption UV-to-MIR photometry and SED fitting reliably separate star-forming from quiescent galaxies and recover accurate SFHs
    Basis for the reported age distribution and host-type split

pith-pipeline@v0.9.0 · 5778 in / 1702 out tokens · 88413 ms · 2026-05-10T07:17:14.591429+00:00 · methodology

discussion (0)

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Forward citations

Cited by 1 Pith paper

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    A phenomenological redshift-dependent SNIa magnitude correction shows no evidence in ΛCDM but is preferred at 4.3σ with dynamical dark energy, reducing Hubble tension to 1.5σ.

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