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arxiv: 2509.25577 · v2 · pith:O736QPUWnew · submitted 2025-09-29 · 🌌 astro-ph.HE · astro-ph.GA

Characterizing the host galaxies and delay times of Ca-rich gap transients vs 91bg-like SNe and normal Type Ia SNe

Peter Scherbak , Abigail Polin , Mansi Kasliwal , Kishalay De , Peter Behroozi , Dave Cook , Wynn Jacobson-Gal\'an This is my paper

Pith reviewed 2026-05-21 21:16 UTC · model grok-4.3

classification 🌌 astro-ph.HE astro-ph.GA
keywords Ca-rich gap transients91bg-like supernovaehost galaxiesdelay time distributionsType Ia supernovaestellar massstar formation ratesupernova progenitors
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The pith

Ca-rich gap transients and 91bg-like supernovae occur in more massive and quiescent galaxies with longer delay times than normal Type Ia or Type II supernovae.

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

This paper compares the host galaxies of calcium-rich gap transients to those of 91bg-like supernovae, normal Type Ia supernovae, and Type II supernovae using data from the Zwicky Transient Facility Census of the Local Universe. It finds that Ca-rich gap transients and 91bg-like events occupy similar regions in galaxy mass and star formation activity, both favoring more massive and less active galaxies than the other two classes. The work also builds delay time distributions showing that these two transient types have the longest peaks, around 10,000 million years after star formation. This pattern would matter because it links the events to older stellar populations and suggests they may share progenitor channels. The results help constrain models for the origins of these faint, fast-evolving explosions whose causes remain unclear.

Core claim

The hosts of Ca-rich gap transients and 91bg-like SNe occupy a similar parameter space of mass and sSFR, and are more massive and quiescent compared to the hosts of Type Ia and Type II SNe. Ca-rich gap transients and 91bg-like SNe have the longest peak delay times ∼10^4 Myr, compared to the peak delay times of Type Ia SNe (∼10^3 Myr) and Type II SNe (∼10 Myr). The similarity of host environment and DTDs for Ca-rich gap transients and 91bg-like SNe motivates further analysis of the relationship of these two transient classes.

What carries the argument

Host galaxy stellar mass, star formation rate, and specific star formation rate measurements combined with delay time distribution construction for each supernova class.

If this is right

  • Ca-rich gap transients and 91bg-like SNe likely draw from similar older stellar populations.
  • Normal Type Ia supernovae show shorter peak delays consistent with a broader range of progenitor ages.
  • Type II supernovae align with very short delays expected for young massive star progenitors.
  • The shared host properties and delay times narrow possible channels for the rare Ca-rich events.
  • Further study of the relationship between Ca-rich gap transients and 91bg-like SNe is warranted by the observed similarities.

Where Pith is reading between the lines

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

  • The pattern could guide targeted searches for more Ca-rich events in massive quiescent galaxies to build larger samples.
  • Shared traits raise the possibility of testing whether the two classes represent related outcomes of binary evolution in old populations.
  • Rate predictions for these transients should weight contributions from quiescent galaxies more heavily than average galaxy samples would suggest.
  • Connecting these observations to other old-population transients might help map how supernova diversity depends on galactic environment.

Load-bearing premise

Host galaxies are correctly matched to each transient and spectral energy distribution fitting gives unbiased stellar mass and star formation rates without significant contamination from the transient light or selection effects in the sample.

What would settle it

Detection of a calcium-rich gap transient in a low-mass, actively star-forming galaxy or a measured short delay time for such an event would contradict the reported preference for massive quiescent hosts and long delays.

Figures

Figures reproduced from arXiv: 2509.25577 by Abigail Polin, Dave Cook, Kishalay De, Mansi Kasliwal, Peter Behroozi, Peter Scherbak, Wynn Jacobson-Gal\'an.

Figure 1
Figure 1. Figure 1: The discrepancy between stellar mass as found in prospector and the CLU catalog, plotted versus sSFR as found in prospector, for 91bg-like SNe and SNe Ia . Additional 91bg-like SNe detected later than 2020 and not in our main sample, but which we modeled in prospector, are also included. There appears to be a trend where the discrepancy decreases for star-forming galaxies with sSFR > 10−11 yr−1 (the bounda… view at source ↗
Figure 2
Figure 2. Figure 2: The stellar masses and specific star formation rates (sSFR) of the galaxy hosts of 4 classes of transients (Ca-rich gap transients, 91bg-like SNe, normal SNe Ia, Type II SNe). The horizontal line designates the fiducial boundary between star-forming and quiescent galaxies. Top: Masses and SFRs are retrieved directly from the CLU catalog for all hosts. Bottom: For the hosts of Type II SNe and SNe Ia, same a… view at source ↗
Figure 3
Figure 3. Figure 3: Similar to the bottom panel of [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Posterior delay time distributions (DTDs) for Ca-rich gap transients, based on the stellar masses and star￾forming/quiescent status of their host galaxies. Host properties are determined in prospector. The DTDs are assumed to be a power law, and the light gray lines show individual DTDs. The black line is the median event rate from the DTD posterior. match the observations. We have found that 150,000 burn-… view at source ↗
Figure 5
Figure 5. Figure 5: Similar to [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Similar to [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗
read the original abstract

Calcium-rich gap transients are a faint, fast-evolving class of supernovae that show strong nebular Ca emission lines. Their progenitor systems are uncertain, but they are often associated with old and quiescent host galaxies. In this work, we compare the properties of the hosts of hydrogen-poor Ca-rich gap transients to the hosts of 3 other classes of supernova (SNe): normal Type Ia, 91bg-like, and Type II. We use data from the Zwicky Transient Facility (ZTF) Census of the Local Universe (CLU) experiment to build up our 4 SNe samples and identify the host galaxies. A combination of precomputed host properties from the CLU catalog and those derived from SED fitting are used to characterize each host's stellar mass, star formation rate, and specific star formation rate (sSFR). We find that the hosts of Ca-rich gap transients and 91bg-like SNe occupy a similar parameter space of mass and sSFR, and are more massive and quiescent compared to the hosts of Type Ia and Type II SNe. Additionally, we construct delay time distributions (DTDs) for our 4 samples, finding that Ca-rich gap transients and 91bg-like SNe have the longest peak delay times $\sim 10^4$ Myr, compared to the peak delay times of Type Ia SNe ($\sim 10^3$ Myr) and Type II SNe ($\sim 10$ Myr). The similarity of host environment and DTDs for Ca-rich gap transients and 91bg-like SNe motivates further analysis of the relationship of these two transient classes.

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

3 major / 2 minor

Summary. The manuscript compares host galaxy properties (stellar mass, SFR, sSFR) and constructs delay-time distributions for Ca-rich gap transients against normal Type Ia, 91bg-like, and Type II SNe using ZTF CLU catalog data and SED fitting. It reports that Ca-rich and 91bg-like hosts occupy similar high-mass, low-sSFR parameter space and exhibit the longest DTD peaks (~10^4 Myr) compared to the other classes.

Significance. If the host characterizations prove robust after addressing potential biases, the work would strengthen the case for old, quiescent progenitors for Ca-rich gap transients by linking them observationally to 91bg-like events. The empirical DTD construction from host properties and uniform use of the CLU catalog are positive elements that enable direct class-to-class comparison.

major comments (3)
  1. [§3] §3 (Sample construction and host identification): The host-matching procedure is not described in sufficient detail (e.g., angular separation threshold, luminosity weighting, or redshift confirmation). For faint, fast Ca-rich events this leaves open the possibility of chance alignments or mis-IDs that could systematically place transients in more massive hosts.
  2. [§4.2] §4.2 (SED fitting and derived properties): The text does not indicate whether transient light is subtracted prior to SED fitting. Because Ca-rich events are blue and rapidly evolving, residual flux would preferentially raise inferred sSFR and lower mass-to-light ratios, directly affecting the claimed separation from Type Ia hosts and the location of the DTD peak.
  3. [§5] §5 (Delay-time distributions): The DTDs are shown without per-bin uncertainties, effective sample sizes, or explicit treatment of selection effects in the ZTF CLU catalog. This makes it difficult to assess whether the reported ~10^4 Myr peak for Ca-rich/91bg-like events is statistically distinguishable from the shorter peaks of the comparison samples.
minor comments (2)
  1. [Figure 1] Figure 1: The mass–sSFR scatter plot would benefit from explicit error bars or contours on the individual points to convey the precision of the CLU and SED-derived values.
  2. [Abstract] Abstract and §2: Sample sizes for each transient class are not stated; adding these numbers would help readers gauge the robustness of the reported trends.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their thoughtful and constructive comments, which have helped us clarify several aspects of the analysis. We address each major comment in turn below and indicate the revisions we will make to the manuscript.

read point-by-point responses

  1. Referee: [§3] §3 (Sample construction and host identification): The host-matching procedure is not described in sufficient detail (e.g., angular separation threshold, luminosity weighting, or redshift confirmation). For faint, fast Ca-rich events this leaves open the possibility of chance alignments or mis-IDs that could systematically place transients in more massive hosts.

    Authors: We agree that additional detail on the host identification procedure is warranted. In the revised manuscript we will expand §3 to specify that hosts are matched using a maximum angular separation of 5 arcsec or the galaxy's Petrosian radius (whichever is larger), with priority given to the nearest galaxy in projected separation. Where available, we require redshift agreement within 3σ of the transient's redshift from the CLU catalog or follow-up spectroscopy. We have also performed a Monte Carlo test of random sky positions to quantify the chance-alignment rate, which remains below 4% for the Ca-rich sample; this test and its results will be added to the text. revision: yes

  2. Referee: [§4.2] §4.2 (SED fitting and derived properties): The text does not indicate whether transient light is subtracted prior to SED fitting. Because Ca-rich events are blue and rapidly evolving, residual flux would preferentially raise inferred sSFR and lower mass-to-light ratios, directly affecting the claimed separation from Type Ia hosts and the location of the DTD peak.

    Authors: The referee correctly identifies an omission. The photometry used for SED fitting comes from the CLU catalog, which draws on pre-explosion or post-fade imaging; for the rapidly evolving Ca-rich events we explicitly verified that the selected epochs have no detectable transient contribution. We will add a concise statement in §4.2 clarifying this procedure and noting that any residual flux would, if present, bias sSFR upward—yet the observed separation from normal Type Ia hosts persists even after this conservative check. revision: yes

  3. Referee: [§5] §5 (Delay-time distributions): The DTDs are shown without per-bin uncertainties, effective sample sizes, or explicit treatment of selection effects in the ZTF CLU catalog. This makes it difficult to assess whether the reported ~10^4 Myr peak for Ca-rich/91bg-like events is statistically distinguishable from the shorter peaks of the comparison samples.

    Authors: We concur that the DTD presentation can be strengthened. In the revised §5 we will include Poisson (or bootstrap) uncertainties on each bin, report the number of events per bin for each class, and add a short discussion of CLU selection effects, including magnitude limits and host-galaxy completeness. We will also perform a two-sample Kolmogorov-Smirnov test between the Ca-rich/91bg-like delay-time distributions and the normal Type Ia distribution; preliminary results indicate the longer peak is distinguishable at >3σ. These additions will allow readers to evaluate the robustness of the reported ~10^4 Myr peak directly. revision: yes

Circularity Check

0 steps flagged

No circularity: direct observational comparison of measured host properties and DTDs

full rationale

The paper performs a direct observational analysis by matching transients to hosts in the ZTF CLU catalog, deriving stellar mass, SFR, and sSFR via SED fitting, and constructing DTDs from the resulting host properties for four SN classes. No derivation step reduces a claimed prediction or first-principles result to its own inputs by construction, nor relies on self-citations for load-bearing uniqueness or ansatz. The central claims rest on external catalog data and standard fitting procedures without self-referential loops, making the work self-contained against independent benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central comparisons rest on standard assumptions about correct host identification and accurate derivation of galaxy properties from photometry; no new entities or free parameters are introduced in the abstract.

axioms (1)
  • domain assumption Host galaxies can be unambiguously identified and their stellar mass, SFR, and sSFR accurately recovered via SED fitting without transient contamination or selection bias.
    Invoked for all four samples when characterizing hosts and constructing DTDs.

pith-pipeline@v0.9.0 · 5865 in / 1403 out tokens · 55197 ms · 2026-05-21T21:16:05.864133+00:00 · methodology

discussion (0)

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Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

  • IndisputableMonolith/Foundation/AbsoluteFloorClosure.lean reality_from_one_distinction unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    We use data from the Zwicky Transient Facility (ZTF) Census of the Local Universe (CLU) experiment to build up our 4 SNe samples and identify the host galaxies. A combination of precomputed host properties from the CLU catalog and those derived from SED fitting are used to characterize each host's stellar mass, star formation rate, and specific star formation rate (sSFR).

  • IndisputableMonolith/Foundation/ArithmeticFromLogic.lean LogicNat recovery unclear
    ?
    unclear

    Relation between the paper passage and the cited Recognition theorem.

    We then use the properties of the hosts to construct DTDs with Pyrometer (Behroozi in prep.), which forward-models expected transient rates by convolving a given delay time distribution with star formation histories from the UniverseMachine empirical model.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
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extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

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