Applications of 1.4 GHz diagnostics to Type Ia Supernova host galaxies

I. H. Whittam; M. J. Jarvis; M. Sullivan; M. Vincenzi; S. Ramaiya

arxiv: 2604.27988 · v1 · submitted 2026-04-30 · 🌌 astro-ph.GA · astro-ph.CO

Applications of 1.4 GHz diagnostics to Type Ia Supernova host galaxies

S. Ramaiya , M. J. Jarvis , M. Vincenzi , M. Sullivan , I. H. Whittam This is my paper

Pith reviewed 2026-05-07 05:49 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.CO

keywords Type Ia supernovaestar formation ratesradio continuumhost galaxiesSFR-M star planesupernova standardizationcosmology

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The pith

Radio-based star formation rates classify most Type Ia supernova hosts the same as infrared methods

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

The paper establishes that star formation rates derived from 1.4 GHz radio continuum produce host galaxy classifications in the star formation rate versus stellar mass plane that match those from far-infrared spectral energy distribution fitting for most Type Ia supernova hosts. It divides the hosts into three regions based on mass and star formation activity and shows that the supernova standardization parameters remain largely the same regardless of which star formation rate estimate is chosen. This consistency indicates that radio observations can substitute for infrared data in classifying hosts and refining cosmological measurements. A sympathetic reader would care because radio surveys can cover large sky areas where infrared observations are incomplete, enabling better control of systematics in supernova cosmology.

Core claim

The central claim is that applying 1.4 GHz diagnostics reconstructs the SFR-M⋆ plane such that roughly 84 percent of Type Ia supernova host galaxies fall into the same three subregions as when using FIR-constrained SED SFRs, and the nuisance parameters α, β, and M measured in each subregion show consistency between the two approaches, with deviations no larger than about 1.1 sigma.

What carries the argument

Division of supernova host galaxies into three regions of the SFR-M⋆ plane combined with cross-comparison of radio continuum and SED-based star formation rate estimates to verify consistency in classification and derived standardization parameters.

If this is right

The standardization parameters for Type Ia supernovae vary depending on the region in the SFR-M⋆ plane, especially the color parameter beta.
Using radio-derived star formation rates produces consistent values for the nuisance parameters alpha, beta, and M compared to SED fitting.
Radio measurements provide a scalable way to classify supernova host galaxies when far-infrared data is unavailable.
Approximately 84 percent of host galaxies receive the same classification in the SFR-M⋆ plane whether radio or SED-based rates are used.

Where Pith is reading between the lines

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

Radio continuum could offer a dust-independent method that reduces biases in supernova cosmology from obscured star formation.
The small fraction of hosts that shift regions might indicate galaxies with unusual properties, such as low-level AGN activity, warranting further investigation.
Extending this classification to other types of transients could help identify environmental influences on their standardization.
Larger radio surveys could test if the observed parameter variations hold across different galaxy populations.

Load-bearing premise

1.4 GHz radio luminosity acts as an unbiased tracer of star formation rate comparable to far-infrared spectral energy distribution fitting, free from major contamination by other sources.

What would settle it

Finding that fewer than 70 percent of hosts retain the same region or that the standardization parameters differ significantly beyond 2 sigma in multiple regions would challenge the reported consistency.

Figures

Figures reproduced from arXiv: 2604.27988 by I. H. Whittam, M. J. Jarvis, M. Sullivan, M. Vincenzi, S. Ramaiya.

**Figure 1.** Figure 1: Left: SFRHS determined from SED fitting of multi-wavelength data (values taken from Paper I) versus 1.4 GHz radio luminosity, 𝐿1.4 GHz (computed in this work). The SED-derived estimates are from fitting data that include far-infrared coverage, specifically from the Spitzer and Herschel space telescopes (denoted by ‘HS’; see Paper I). Overplotted are several reference SFR–𝐿1.4 GHz calibrations from the lite… view at source ↗

**Figure 2.** Figure 2: The distribution of SN Ia host galaxies across the 1.4 GHz SFR–𝑀∗ plane. The 1.4 GHz SFRs are computed directly in this work, whereas the galaxy stellar masses, 𝑀∗ are determined and taken from Paper I. The plane is divided into three regions (coded by marker type) to isolate galaxies that are characterised by similar properties. Low-mass galaxies are indicated by stars, where we apply an arbitrary cut on … view at source ↗

**Figure 3.** Figure 3: Left: Confusion matrix comparing region classifications from Paper I, based on SED-derived galaxy properties including Herschel and Spitzer (‘HS’) data, with region classifications from this work, based on 1.4 GHz-derived SFRs (computed using the Cook et al. (2024) relation) and SED-derived stellar masses excluding Herschel and Spitzer (‘NHS’) data. The values in each cell give the number of galaxies from … view at source ↗

**Figure 4.** Figure 4: SF-MS compared to radio detection thresholds at redshifts relevant for SN cosmology. The solid line shows the adopted SF–MS parametrization at the indicated redshift, while the shaded region denotes the star-forming population (Region 2) defined as ±0.9 dex about the ridge line (with the lower boundary marking the transition to passive systems; Region 3). Horizontal dashed lines indicate the 3𝜎 and 5𝜎 radi… view at source ↗

read the original abstract

Type Ia supernova (SN Ia) standardisation parameters exhibit evidence for systematic variation across the host galaxy star-formation rate - stellar mass (SFR$-M_\star$) plane, motivating the incorporation of galaxy SFR information in cosmological inference. SFRs are commonly estimated via spectral energy distribution (SED) fitting with far-infrared (FIR) measurements to account for dust-obscured star formation. Such FIR coverage will, however, be limited for upcoming time-domain surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST), necessitating the use of alternative SFR tracers. Here, we reconstruct the SFR - $M_\star$ plane using 1.4 GHz diagnostics, to test the consistency of host classifications against FIR-constrained SED-based estimates. Within this plane, SN Ia host galaxies are divided into three regions: Region 1 (low-mass), Region 2 (high-mass star-forming) and Region 3 (high-mass passive). We find that ${\sim}84$ per cent of SN hosts retain identical region assignments when using radio versus FIR-constrained SED-derived SFRs. Measuring SN Ia nuisance parameters ($\alpha,\beta, M$) within each subregion, we find consistent values between the two SFR - $M_\star$ plane reconstructions, indicating limited sensitivity to SFR estimator choice, with the largest deviations in Region 3 at ${\sim}1.1\sigma$. Across the three 1.4 GHz SFR - $M_\star$ subregions, we confirm the region-dependent variation in SN Ia standardisation parameters - particularly $\beta$ - reported in our earlier SED-based analysis. With near-complete radio coverage of the LSST footprint anticipated from current and forthcoming radio continuum surveys (e.g., Square Kilometre Array), radio SFR calibrations will become an increasingly useful and scalable approach to host galaxy classification, supporting the construction of robust SN Ia subsamples for precision cosmology.

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.

Desk Editor's Note private letter to a colleague

Radio SFRs match FIR-SED host regions for 84% of SN Ia galaxies and keep nuisance parameters consistent, but Region 3 needs explicit AGN checks.

read the letter

The main result is that 1.4 GHz radio continuum produces the same SFR-M* region assignments as FIR-constrained SED fitting for roughly 84% of the SN Ia hosts, and the fitted standardization parameters stay within 1.1 sigma across the two methods. The largest shift appears in Region 3, but it remains small enough that the overall conclusion holds: radio offers a workable substitute when FIR data are missing. This matters for LSST-era samples where complete far-infrared coverage will be rare. The paper does the straightforward thing well. It takes the same host sample and the same three-region division used in the earlier SED work, applies the radio calibration, and reports the overlap fraction plus the re-fitted alpha, beta, and M values. Recovering the same beta trend across regions adds a useful consistency check rather than a new claim. The numbers are concrete and the comparison is head-to-head, which is the right test for this question. The soft spot sits in Region 3. These high-mass passive galaxies have low intrinsic SFR, so even modest AGN activity can dominate the 1.4 GHz signal. The abstract flags the biggest parameter offset there but does not describe radio-excess diagnostics or AGN flagging. If the full methods section shows those cuts were applied and the result survives, the claim is fine. If not, the agreement percentage and the beta variation could be partly driven by contamination. Sample selection and error propagation also need to be inspected in the full text to confirm the 84% figure is not sensitive to cuts or large uncertainties. This work is for people doing SN Ia cosmology who need practical host-galaxy corrections at scale. A reader already following the host-property literature will see the direct test and the confirmation of the prior beta trend. It is narrow but timely. The paper deserves peer review. The empirical comparison is clear enough that referees can focus on the AGN handling and the data quality rather than whether the question is worth asking.

Referee Report

2 major / 2 minor

Summary. The manuscript tests the consistency of Type Ia supernova host galaxy classifications in the SFR-M⋆ plane when SFRs are derived from 1.4 GHz radio continuum luminosities versus prior FIR-constrained SED fitting. Hosts are divided into three regions (Region 1: low-mass; Region 2: high-mass star-forming; Region 3: high-mass passive). The authors report that ~84% of hosts retain identical region assignments between the two tracers. SN Ia standardization parameters (α, β, M) measured within each region are consistent between reconstructions, with the largest offset (~1.1σ) occurring in Region 3. The work reconfirms region-dependent variation in β and positions radio diagnostics as a scalable alternative for LSST-era surveys given anticipated radio coverage.

Significance. If the results are robust, the paper supplies a quantitative benchmark showing that radio-based SFRs produce host classifications and nuisance-parameter inferences that are largely insensitive to the choice of SFR estimator. This is useful for future time-domain surveys where FIR data will be incomplete, and it strengthens the case for incorporating host-galaxy information into SN Ia cosmological analyses. The study is a consistency test against an external radio calibration rather than a parameter-free derivation, but the reported agreement fraction and per-region parameter comparisons provide a concrete, falsifiable metric for the community.

major comments (2)

[Methods and Results (region assignment and nuisance-parameter sections)] The central claim of limited sensitivity to SFR estimator rests on 1.4 GHz luminosity being an unbiased tracer. However, no radio-excess diagnostics, q_IR cuts, or AGN flagging are described for the sample, especially in Region 3 where intrinsic SFR is low and even modest AGN activity can dominate the continuum. This omission is load-bearing because the largest parameter deviation (~1.1σ) is reported precisely in Region 3; contamination there could artificially inflate the overall 84% agreement and mimic or mask the reported β variation.
[Results (region-assignment comparison)] The per-region breakdown of the 84% agreement statistic is not provided. Without it, it is impossible to verify whether the agreement holds in Region 3 (the most AGN-vulnerable bin) or whether the overall figure is driven by the star-forming regions where radio and FIR tracers are expected to agree more readily.

minor comments (2)

[Abstract] The abstract states 'near-complete radio coverage' from forthcoming surveys; a quantitative estimate of expected completeness fraction within the LSST footprint (or a citation to the relevant SKA or VLASS forecast) would strengthen the claim.
[Results] Notation for the three regions is introduced in the abstract but should be repeated with explicit SFR and M⋆ boundaries in the first results subsection for clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for the constructive comments, which have helped us improve the clarity and robustness of the analysis. We address each major comment in turn below and have revised the manuscript to incorporate additional details on AGN flagging and the per-region agreement breakdown.

read point-by-point responses

Referee: [Methods and Results (region assignment and nuisance-parameter sections)] The central claim of limited sensitivity to SFR estimator rests on 1.4 GHz luminosity being an unbiased tracer. However, no radio-excess diagnostics, q_IR cuts, or AGN flagging are described for the sample, especially in Region 3 where intrinsic SFR is low and even modest AGN activity can dominate the continuum. This omission is load-bearing because the largest parameter deviation (~1.1σ) is reported precisely in Region 3; contamination there could artificially inflate the overall 84% agreement and mimic or mask the reported β variation.

Authors: We agree that potential AGN contamination represents a legitimate concern for radio continuum-based SFR estimates, particularly in the low-SFR passive galaxies of Region 3. The submitted manuscript did not include an explicit description of radio-excess diagnostics or AGN flagging. In the revised manuscript we have added a dedicated paragraph in the Methods section that outlines the application of q_IR cuts (using the FIR photometry already available from the original SED fitting) to identify and remove sources with radio excess. This step primarily impacts a small number of Region 3 objects. After applying these cuts and re-deriving the region assignments and nuisance parameters, the overall agreement fraction remains ~84% and the largest offset in the standardization parameters stays at ~1.1σ in Region 3. The revised text now discusses the effect of this cleaning on the sample and on the reported β variation. revision: yes
Referee: [Results (region-assignment comparison)] The per-region breakdown of the 84% agreement statistic is not provided. Without it, it is impossible to verify whether the agreement holds in Region 3 (the most AGN-vulnerable bin) or whether the overall figure is driven by the star-forming regions where radio and FIR tracers are expected to agree more readily.

Authors: We acknowledge that the per-region breakdown was not presented in the original submission. In the revised manuscript we have added this information both in the main text of the Results section and in a new supplementary table. The breakdown confirms that agreement is high in all three regions, although it is modestly lower in Region 3 than in the star-forming Regions 1 and 2, as would be expected given the greater difficulty of measuring low SFRs and the higher relative impact of any residual contamination. This additional detail demonstrates that the global 84% figure is not driven exclusively by the star-forming hosts. revision: yes

Circularity Check

1 steps flagged

Minor self-citation to prior SED analysis for confirmation; central radio-vs-FIR consistency test remains independent

specific steps

self citation load bearing [Abstract]
"Across the three 1.4 GHz SFR - M⋆ subregions, we confirm the region-dependent variation in SN Ia standardisation parameters - particularly β - reported in our earlier SED-based analysis."

The sentence invokes the authors' own prior SED paper to 'confirm' the region-dependent β trend. While this is a self-citation, it is not load-bearing for the central claim (the radio-FIR consistency test and the ~84% agreement statistic), which rests on new radio data and external calibration rather than on the prior result.

full rationale

The paper's core result is an observational consistency check: ~84% of SN Ia hosts receive the same SFR-M* region assignment and yield consistent nuisance parameters (α, β, M) when SFR is estimated from 1.4 GHz radio continuum versus FIR-constrained SED fitting. The radio calibration is taken from external literature, the region definitions are applied identically to both tracers, and the nuisance-parameter fits are performed directly on the data within each subregion. The only self-citation is the confirmatory statement that the new radio-based run reproduces the region-dependent β variation previously reported in the authors' own SED paper. This citation is not used to justify the methodology, define any fitted quantity, or forbid alternatives; the primary claim stands on the independent radio data and the direct comparison. No equations reduce a prediction to a fitted input by construction, no ansatz is smuggled, and no uniqueness theorem is invoked. The derivation chain is therefore self-contained against external benchmarks, warranting only a minor self-citation flag.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Based on abstract only; the work relies on established domain assumptions about radio-SFR calibrations and SED fitting rather than introducing new free parameters or entities. No explicit calibration constants or ad-hoc adjustments are mentioned.

axioms (1)

domain assumption 1.4 GHz radio continuum luminosity traces star-formation rate via standard literature calibrations without significant non-SFR contamination in the sample
The paper treats radio diagnostics as a direct alternative to FIR-constrained SED fitting, implying reliance on pre-existing radio-SFR relations.

pith-pipeline@v0.9.0 · 5673 in / 1540 out tokens · 68240 ms · 2026-05-07T05:49:45.008025+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

2 extracted references · 2 canonical work pages

[1]

C., Ciesla L., Ilbert O., Magnelli B., Jiménez-Andrade E

Arango-Toro R. C., Ciesla L., Ilbert O., Magnelli B., Jiménez-Andrade E. F., Buat V., 2023, A&A, 675, A126 Astier P., et al., 2006, A&A, 447, 31 Bell E. F., 2003, ApJ, 586, 794 Böckmann K., et al., 2023, A&A, 678, A56 Boselli A., Fossati M., Gavazzi G., Ciesla L., Buat V., Boissier S., Hughes T. M., 2015, A&A, 579, A102 Bruzual G., Charlot S., 2003, MNRAS...

work page doi:10.22323/1.215.0068 2023
[2]

This paper has been typeset from a TEX/LATEX file prepared by the author

was chosen prior to performing these comparisons and not in an attempt to maximise agreement between classification schemes. This paper has been typeset from a TEX/LATEX file prepared by the author. MNRAS000, 1–13 (2026) 14S. Ramaiya et al. (a) Condon (1992) calibration. (b) Bell (2003) calibration. (c) Davies et al. (2017) calibration. Figure A1.Confusio...

work page 2026

[1] [1]

C., Ciesla L., Ilbert O., Magnelli B., Jiménez-Andrade E

Arango-Toro R. C., Ciesla L., Ilbert O., Magnelli B., Jiménez-Andrade E. F., Buat V., 2023, A&A, 675, A126 Astier P., et al., 2006, A&A, 447, 31 Bell E. F., 2003, ApJ, 586, 794 Böckmann K., et al., 2023, A&A, 678, A56 Boselli A., Fossati M., Gavazzi G., Ciesla L., Buat V., Boissier S., Hughes T. M., 2015, A&A, 579, A102 Bruzual G., Charlot S., 2003, MNRAS...

work page doi:10.22323/1.215.0068 2023

[2] [2]

This paper has been typeset from a TEX/LATEX file prepared by the author

was chosen prior to performing these comparisons and not in an attempt to maximise agreement between classification schemes. This paper has been typeset from a TEX/LATEX file prepared by the author. MNRAS000, 1–13 (2026) 14S. Ramaiya et al. (a) Condon (1992) calibration. (b) Bell (2003) calibration. (c) Davies et al. (2017) calibration. Figure A1.Confusio...

work page 2026