Pith. sign in

REVIEW 3 major objections 6 minor 5 cited by

LFBOT host galaxies favor mergers of compact objects with Wolf-Rayet stars over tidal disruptions or ordinary core-collapse deaths.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

T0 review · grok-4.5

2026-07-13 19:30 UTC pith:EE6VDFE4

load-bearing objection Solid first uniform host study of all 11 LFBOTs; the WR-merger preference is a fair ranking of existing models, not a unique exclusion. the 3 major comments →

arxiv 2603.23597 v2 pith:EE6VDFE4 submitted 2026-03-24 astro-ph.HE astro-ph.GA

The Environments of Luminous Fast Blue Optical Transients: Evidence for a Compact Object and Wolf-Rayet Star Merger Origin

classification astro-ph.HE astro-ph.GA
keywords luminous fast blue optical transientshost galaxiesWolf-Rayet starscompact-object mergersstellar populationscore-collapse supernovaelong gamma-ray burstsfractional flux
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

Luminous fast blue optical transients (LFBOTs) rise and fade in days, outshine ordinary supernovae, and need a central engine, yet their origin is unsettled. This paper measures the host galaxies of all 11 confirmed events with uniform stellar-population modeling and maps where the explosions sit inside those galaxies. The hosts are star-forming systems of intermediate mass and metallicity that recently experienced star-formation bursts, yet a large fraction of the transients explode in the faintest pixels or outside the host light. That combination is hard to reconcile with central black-hole tidal disruptions, with ordinary core-collapse supernovae, or with the extremely metal-poor environments of superluminous supernovae and long gamma-ray bursts. The authors therefore favor a delayed merger between a stellar-mass black hole or neutron star and a Wolf-Rayet companion: the system can be kicked out of its birth site while still forming inside a moderately metal-poor, actively star-forming galaxy. A larger sample from the Rubin Observatory will test whether the pattern holds.

Core claim

Uniform Prospector modeling of the hosts of 11 LFBOTs shows they are actively star-forming galaxies with recent bursts, median log(M*/M☉)≈9.6, and intermediate gas-phase metallicity 12+log(O/H)≈8.7. More than 30 percent of the events occur in the host's faintest pixel or outside its light, a fractional-flux distribution shared with SLSNe-I but not with ordinary CCSNe or LGRBs. These environmental facts together favor a compact-object + Wolf-Rayet star merger over IMBH/stellar-mass TDEs, PPISNe, failed supernovae, or magnetar-powered core-collapse.

What carries the argument

Uniform Prospector SED and emission-line fits that deliver stellar mass, present-day SFR, non-parametric SFHs, gas-phase metallicity, galactocentric offsets, and fractional flux for every host; these quantities are then compared statistically (AD/KS tests, SFMS weighting) to the host populations of SLSNe-I, CCSNe subtypes, and LGRBs.

Load-bearing premise

That the high fraction of events in the faintest host pixels, combined with intermediate metallicity, uniquely selects the compact-object–Wolf-Rayet merger channel rather than a kicked binary failed-supernova or magnetar channel, even though the present sample contains only eleven events.

What would settle it

A substantially larger LFBOT sample (tens of events from Rubin) whose hosts are either systematically more metal-poor and intensely star-forming than the current median, or whose fractional-flux distribution collapses to that of ordinary CCSNe, would undermine the merger preference.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 6 minor

Summary. The paper presents a uniform Prospector analysis of photometry and spectroscopy for the host galaxies of 11 LFBOTs, deriving stellar masses, SFHs, present-day SFRs/sSFRs, stellar and gas-phase metallicities (including 12+log(O/H) via R23 and [NII]/Hα), and BPT line ratios. It compares these distributions (via Monte-Carlo CDFs and AD tests) to SLSNe-I, SNe II/Ibc/Ibn, LGRBs, and field galaxies, and measures galactocentric offsets and fractional fluxes. The hosts are actively star-forming with recent bursts, intermediate mass and metallicity, and a high fraction of events in the faintest host pixels or outside the light. From this environmental ranking the authors favor a compact-object + Wolf-Rayet star merger progenitor over IMBH/stellar-mass TDEs, PPISNe, failed SNe, and magnetar-powered CCSNe.

Significance. If the environmental ranking holds, this is the largest uniform LFBOT host study to date and supplies a concrete observational filter on progenitor models that have been hard to distinguish from light curves and spectra alone. Strengths include non-parametric SFH modeling with nebular marginalization, joint photo+spec fits where available, redshift-limited comparison samples, Monte-Carlo AD/KS tests, Rice-distributed offsets, and an explicit Horowicz–Margalit SFR–M* weighting test. The work is timely for Rubin-era LFBOT samples and usefully connects LFBOTs to SNe Ibn/Icn and ultra-long GRBs as possible related channels. The central claim is an interpretive ranking of existing models rather than a quantitative exclusion; that is still a valuable contribution if the caveats are stated clearly.

major comments (3)
  1. Abstract, §6.4 and §7: The claim that intermediate metallicity (12+log(O/H)≈8.71) plus a high zero-fractional-flux fraction (>30%, §5.2, Fig. 7) favor the compact-object–WR merger over kicked binary failed-SN or magnetar channels is not supported by a quantitative uniqueness test. The paper itself notes that binary interactions can displace ordinary CCSNe (§6.3.2–6.3.3) and that N=11 is small (§7). No predicted zero-fractional-flux fraction or metallicity distribution is given for a kicked binary failed-SN/magnetar model versus the WR-merger model. The AD tests and Horowicz–Margalit weights (§4.1–4.2) establish that LFBOT hosts differ from ordinary CCSN and SLSN-I hosts, but do not show that only the WR-merger channel can produce those differences. Soften the language from “favor … over” / “strongest support” to an explicit ranking of consistency, and state that binary-kick CCSN variants
  2. §4.1 and comparison to SLSN-I/LGRB hosts: The paper correctly flags that Schulze et al. (2021) used delayed-τ SFHs (which can under-estimate M* by 25–100% relative to non-parametric models) and that LGRB hosts come from heterogeneous methods. The AD tests still report 100% of PAD<0.05 for both M* and sSFR versus SLSNe-I. Because the SLSN distinction is load-bearing for ranking progenitors, either re-derive a subset of SLSN-I hosts with the same non-parametric Prospector setup used here, or quantify the systematic shift and show that the AD rejection survives a plausible 0.3–0.5 dex M* offset. Without that, the claimed statistical distinction from SLSNe-I is not fully robust.
  3. §4.2, Table 2 and oxygen abundances: R23 is used only above 12+log(O/H)=8.53 and [NII]/Hα below that, with Ugas fixed at the Prospector median. For CSS161010 the Prospector [OIII]/Hβ fit is discarded and replaced by a manual Gaussian residual fit. The population median 12+log(O/H)=8.71+0.17−0.40 and the AD tests versus SNe Ibc/II and SLSNe-I/LGRBs depend on these choices. Provide a sensitivity check (e.g., all hosts on a single calibration, or Ugas sampled from the posterior) and state how the AD rejection fractions change. Also clarify why AT2020xnd and AT2023vth are excluded from the metallicity CDF while still appearing in the stellar-mass/sSFR analyses.
minor comments (6)
  1. Abstract vs Table 1 / §4: Abstract quotes SFR=0.99+14.85−0.95 and 12+log(O/H)=8.59+0.18−0.22; Table 1 and §4 give SFR=0.95+18.37−0.91 and 12+log(O/H)=8.71+0.17−0.40. Align all summary numbers.
  2. Fig. 1 caption and text: Caption says LFBOT hosts are “more massive than those of SLSNe-I and have statistically similar stellar mass distributions to SNe Ibc, Ibn, II and LGRB hosts”; ensure the AD percentages quoted in the text match the figure narrative for every comparison.
  3. Table 3 / §5.1: For AT2020mrf, AT2022tsd, and AT2023vth, re is measured with SEP and assigned a 1% uncertainty. State whether that 1% is validated against DECaLS hosts with both measurements, or adopt a more conservative floor.
  4. §5.2 fractional flux: Two events (AT2020xnd, AT2023fhn) lie outside the Kron radius and are assigned fractional flux 0. Note whether Kron radius choice (1σ threshold) affects the >30% zero-flux fraction if a deeper or shallower threshold is used.
  5. Typos and notation: “A2023hkw” (§2.1); “galacotocentric” (§7); inconsistent use of sSFR vs log(sSFR) units in places; “W olf-Rayet” spacing in the title block.
  6. Fig. B1: SED panels are useful; consider marking which hosts used spectrum+photometry vs photometry-only so readers can judge constraint quality at a glance.

Circularity Check

1 steps flagged

No derivation-by-construction circularity: host properties are measured independently and used to rank prior progenitor models; only minor non-load-bearing self-citation of a comparison sample.

specific steps
  1. self citation load bearing [§4.1 (comparison samples); also Abstract/§6 ranking]
    "We obtain host galaxy sSFRs and M∗ for SNe II, Ibc, and Ibn in Nugent et al. (2026)… We note that Nugent et al. (2026) employed the same Prospector model as used in this work… thus their results are complementary to the ones derived here."

    Minor only: the CCSN comparison sample is drawn from overlapping-author work using the same SED model. That improves methodological consistency but does not define LFBOT host properties or force the WR-merger preference; LFBOT M*, SFR, Z, offsets, and fractional fluxes are measured independently, and SLSN-I/LGRB comparisons come from external literature. Not load-bearing for the central claim.

full rationale

The paper’s chain is observational, not a closed derivation. Host stellar masses, SFRs, metallicities, offsets, and fractional fluxes are obtained from photometry/spectroscopy via Prospector and standard aperture/offset methods; those quantities are then compared to external (and one same-method) transient-host samples and used to rank pre-existing progenitor scenarios. The favored compact-object–WR merger is prior theory (Metzger 2022; Klencki & Metzger 2025), not a model fitted to these 11 hosts, and the paper states a preference rather than a uniqueness theorem that forbids alternatives. There is no self-definitional step, no fitted parameter re-labeled as a prediction, and no equation that reduces to its own input. The only mild self-citation is Nugent et al. (2026) for CCSN host M*/sSFR under the same Prospector setup—useful for consistency, not required to force the LFBOT conclusion, which rests on the LFBOT measurements themselves plus literature SLSN/LGRB/CCSN comparisons. Co-authorship with Metzger does not make the ranking circular under the stated rules: the environmental data remain independent of the model. Score 1 reflects that minor self-citation only.

Axiom & Free-Parameter Ledger

4 free parameters · 6 axioms · 0 invented entities

The central inference rests on standard stellar-population modeling assumptions, literature comparison samples, and the theoretical expectations of the Metzger/Klencki merger model. No new free parameters are fitted to force the progenitor conclusion; the free parameters are those internal to Prospector SED fits. No new physical entities are invented.

free parameters (4)
  • Prospector SFH bin ratios and mass-weighted age
    Seven-bin non-parametric continuity SFH; ratios and derived present-day SFR/age are fitted per host and enter the population medians used for comparisons.
  • Dust attenuation offsets (τV,1/τV,2) and q_pah
    Kriek & Conroy dust model parameters sampled per host; affect derived AV and can shift SFR/M* posteriors.
  • Gas-phase metallicity and ionization parameter (Zgas, Ugas)
    Nebular emission-line marginalization parameters; used to compute 12+log(O/H) via R23 or [NII]/Hα calibrations.
  • 5% photometric error floor
    Ad-hoc floor imposed to avoid overfitting single bands; affects posterior widths.
axioms (6)
  • domain assumption Non-parametric continuity SFH with fixed age bins (0–30 Myr, 30–100 Myr, then log-spaced) and constant SFR within bins is an adequate description of LFBOT hosts.
    §3; choice affects M* and SFR relative to parametric delayed-τ models used in some comparison samples.
  • domain assumption Gallazzi et al. (2005) mass–metallicity relation as a prior on (MF, Z*).
    §3; couples mass and metallicity posteriors.
  • domain assumption R23 and [NII]/Hα calibrations of Kewley et al. (2019) correctly convert line ratios to 12+log(O/H).
    §4.2; used for the metallicity CDF comparisons.
  • domain assumption Comparison host samples (SLSNe-I, LGRBs, CCSNe) are sufficiently homogeneous and redshift-matched (z<0.5) for AD/KS tests to be meaningful.
    §4.1; paper notes residual SFH-model and selection differences.
  • domain assumption Fractional flux measured in the bluest available band traces recent star formation and birth sites of massive progenitors.
    §5.2; standard Fruchter et al. (2006) interpretation.
  • domain assumption Theoretical expectations of the compact-object–WR merger channel (mild metallicity bias, few-Myr delay after CCSN kick, tens-of-Myr total delay) correctly predict the observed host and offset properties.
    §6.4 citing Metzger (2022) and Klencki & Metzger (2025).

pith-pipeline@v1.1.0-grok45 · 47321 in / 3405 out tokens · 30850 ms · 2026-07-13T19:30:15.929915+00:00 · methodology

0 comments
read the original abstract

We present a comprehensive analysis of the host galaxies of 11 luminous fast blue optical transients (LFBOTs). We model new and archival host photometry and spectroscopy with Prospector. We determine that all LFBOT hosts are actively star-forming with recent bursts of star formation and have a median stellar mass of $\log(M_*/M_\odot)=9.61^{+0.74}_{-1.61}$, present-day star formation rate SFR=$0.99^{+14.85}_{-0.95}$~$M_\odot$~yr$^{-1}$, and gas-phase oxygen abundance metallicity 12+log(O/H)=$8.59^{+0.18}_{-0.22}$. To contextualize these results, we compare them to the host properties of Hydrogen-poor superluminous supernovae (SLSNe-I), several core-collapse supernova subtypes (CCSN; SNe Ibc, II, and Ibn) and long gamma-ray bursts (LGRBs). We find that LFBOT hosts are more star-forming than CCSN hosts, but less star-forming than SLSN-I hosts. We further show that LFBOT hosts are more metal-poor than SN Ibc and II hosts, but more metal-rich than SLSN-I and LGRB hosts. Finally, we find that, similar to SLSNe-I and unlike CCSNe and LGRBs, a large fraction of LFBOTs occur in their hosts' faintest pixel or outside their host galaxy's light. Our results indicate that LFBOTs have a massive stellar origin that do not trace active star-forming regions within their hosts and have a weaker metallicity-dependence than other extreme transients. For these reasons, we favor a compact-object and Wolf-Rayet star merger progenitor scenario over other previously proposed models, such as tidal disruption events and failed or successful CCSN. Future discoveries of LFBOTs with the Rubin observatory will help to increase their sample size and place firmer constraints on their environments and progenitors.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. A spectacular multi-wavelength transient associated with an off-axis relativistic jet

    astro-ph.HE 2026-07 conditional novelty 8.0

    AT 2019ijn is an off-axis jetted transient (E~2e52 erg) with a fast-rising, slowly-declining optical flare from a z=0.273 dwarf galaxy, most consistent with a low-mass BH TDE.

  2. Hyperaccreting Neutron Stars inside Massive Envelopes: The Implausibility of Thorne-\.Zytkow Objects

    astro-ph.HE 2026-04 unverdicted novelty 7.0

    Hypercritical accretion onto neutron stars embedded in massive envelopes leads to rapid collapse into black holes rather than stable Thorne-Zytkow objects.

  3. Hyperaccreting Neutron Stars inside Massive Envelopes: The Implausibility of Thorne-\.Zytkow Objects

    astro-ph.HE 2026-04 unverdicted novelty 7.0

    First coupled GRHD simulations with M1 neutrino transport and alpha-chain network show hyperaccreting NSs in envelopes collapse to BHs without forming stable TZOs or unbound ejecta.

  4. Implications of the UV/optical Plateau of AT2018cow

    astro-ph.HE 2026-07 conditional novelty 6.0

    A wind-and-irradiation disk model fits the AT2018cow UV plateau with accretor masses from 1.4 to ~100 solar masses, removing the need for a >200 solar-mass black hole.

  5. Compact Objects Merging with Stars as an Origin of Ultra-Long Gamma-Ray Bursts and Luminous Fast Blue Optical Transients

    astro-ph.HE 2026-07 conditional novelty 6.0

    SN 2011kl is broadly consistent with an LFBOT light-curve model and ULGRB hosts match LFBOT/LGRB environments, supporting a shared He-CO merger progenitor for a subset of both classes.

Reference graph

Works this paper leans on

160 extracted references · 14 canonical work pages · cited by 4 Pith papers · 1 internal anchor

  1. [1]

    N., Adelman-McCarthy, J

    Abazajian, K. N., Adelman-McCarthy, J. K., Ag¨ ueros, M. A., et al. 2009, ApJS, 182, 543, doi: 10.1088/0067-0049/182/2/543

  2. [2]

    P., Abbott, R., Abbott, T

    Abbott, B. P., Abbott, R., Abbott, T. D., et al. 2017, ApJL, 848, L13, doi: 10.3847/2041-8213/aa920c

  3. [3]

    W., Smith, N., & Hloˇ zek, R

    Aghakhanloo, M., Murphy, J. W., Smith, N., & Hloˇ zek, R. 2017, MNRAS, 472, 591, doi: 10.1093/mnras/stx2050

  4. [4]

    2018, PASJ, 70, S4, doi: 10.1093/pasj/psx066

    Aihara, H., Arimoto, N., Armstrong, R., et al. 2018, PASJ, 70, S4, doi: 10.1093/pasj/psx066

  5. [5]

    2019, PASJ, 71, 114, doi: 10.1093/pasj/psz103

    Aihara, H., AlSayyad, Y., Ando, M., et al. 2019, PASJ, 71, 114, doi: 10.1093/pasj/psz103

  6. [6]

    P., Covarrubias, R

    Anderson, J. P., Covarrubias, R. A., James, P. A., Hamuy, M., & Habergham, S. M. 2010, MNRAS, 407, 2660, doi: 10.1111/j.1365-2966.2010.17118.x

  7. [7]

    P., & James, P

    Anderson, J. P., & James, P. A. 2009, MNRAS, 399, 559, doi: 10.1111/j.1365-2966.2009.15324.x

  8. [8]

    R., Levan, A

    Angus, C. R., Levan, A. J., Perley, D. A., et al. 2016, MNRAS, 458, 84, doi: 10.1093/mnras/stw063

  9. [9]

    2022, MNRAS, 511, 176, doi: 10.1093/mnras/stab3776

    Antoni, A., & Quataert, E. 2022, MNRAS, 511, 176, doi: 10.1093/mnras/stab3776

  10. [10]

    M., et al

    Arcavi, I., Gal-Yam, A., Kasliwal, M. M., et al. 2010, ApJ, 721, 777, doi: 10.1088/0004-637X/721/1/777

  11. [11]

    2026, arXiv e-prints, arXiv:2602.20775, doi: 10.48550/arXiv.2602.20775

    Aster, C., Inserra, C., Pastorello, A., et al. 2026, arXiv e-prints, arXiv:2602.20775, doi: 10.48550/arXiv.2602.20775

  12. [12]

    A., Phillips, M

    Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5, doi: 10.1086/130766

  13. [13]

    2016, Journal of Open Source Software, 1, 58, doi: 10.21105/joss.00058

    Barbary, K. 2016, Journal of Open Source Software, 1, 58, doi: 10.21105/joss.00058

  14. [14]

    2016, kbarbary/sep: v1.0.0, v1.0.0, Zenodo, doi: 10.5281/zenodo.159035

    Barbary, K., Boone, K., McCully, C., et al. 2016, kbarbary/sep: v1.0.0, v1.0.0, Zenodo, doi: 10.5281/zenodo.159035

  15. [15]

    C., Kulkarni, S

    Bellm, E. C., Kulkarni, S. R., Graham, M. J., et al. 2019, PASP, 131, 018002, doi: 10.1088/1538-3873/aaecbe

  16. [16]

    M., Governato, F., Quinn, T

    Bellovary, J. M., Governato, F., Quinn, T. R., et al. 2010, ApJL, 721, L148, doi: 10.1088/2041-8205/721/2/L148

  17. [17]

    L., Larson, D., Weiland, J

    Bennett, C. L., Larson, D., Weiland, J. L., & Hinshaw, G. 2014, ApJ, 794, 135, doi: 10.1088/0004-637X/794/2/135

  18. [18]

    1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

  19. [19]

    K., Berger, E., & Fong, W.-f

    Blanchard, P. K., Berger, E., & Fong, W.-f. 2016, ApJ, 817, 144, doi: 10.3847/0004-637X/817/2/144

  20. [20]

    K., Berger, E., Nicholl, M., & Villar, V

    Blanchard, P. K., Berger, E., Nicholl, M., & Villar, V. A. 2020, ApJ, 897, 114, doi: 10.3847/1538-4357/ab9638

  21. [21]

    Bouquin, A. Y. K., Gil de Paz, A., Mu˜ noz-Mateos, J. C., et al. 2018, ApJS, 234, 18, doi: 10.3847/1538-4365/aaa384

  22. [22]

    2025, astropy/photutils: 2.2.0, 2.2.0, Zenodo, doi: 10.5281/zenodo.596036

    Bradley, L., Sip˝ ocz, B., Robitaille, T., et al. 2025, astropy/photutils: 2.2.0, 2.2.0, Zenodo, doi: 10.5281/zenodo.596036

  23. [23]

    S., Margutti, R., Matthews, D., et al

    Bright, J. S., Margutti, R., Matthews, D., et al. 2022, ApJ, 926, 112, doi: 10.3847/1538-4357/ac4506

  24. [24]

    2008, MNRAS, 385, 769, doi: 10.1111/j.1365-2966.2008.12914.x

    Brinchmann, J., Pettini, M., & Charlot, S. 2008, MNRAS, 385, 769, doi: 10.1111/j.1365-2966.2008.12914.x

  25. [25]

    C., et al

    Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682, doi: 10.1086/308692

  26. [26]

    A., Clayton, G

    Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245, doi: 10.1086/167900

  27. [27]

    2003, PASP, 115, 763, doi: 10.1086/376392

    Chabrier, G. 2003, PASP, 115, 763, doi: 10.1086/376392

  28. [28]

    C., Magnier, E

    Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560, doi: 10.48550/arXiv.1612.05560

  29. [29]

    J., Bresolin, F., et al

    Chen, T.-W., Smartt, S. J., Bresolin, F., et al. 2013, ApJL, 763, L28, doi: 10.1088/2041-8205/763/2/L28

  30. [30]

    R., Piro, A

    Chen, Y., Drout, M. R., Piro, A. L., et al. 2023, ApJ, 955, 42, doi: 10.3847/1538-4357/ace965

  31. [31]

    2012, MNRAS, 424, 1925, doi: 10.1111/j.1365-2966.2012.21317.x

    Zinnecker, H. 2012, MNRAS, 424, 1925, doi: 10.1111/j.1365-2966.2012.21317.x

  32. [32]

    A., Coppejans, D

    Chrimes, A. A., Coppejans, D. L., Jonker, P. G., et al. 2024a, A&A, 691, A329, doi: 10.1051/0004-6361/202451172

  33. [33]

    A., Jonker, P

    Chrimes, A. A., Jonker, P. G., Levan, A. J., et al. 2024b, MNRAS, 527, L47, doi: 10.1093/mnrasl/slad145 24Nugent et al. Cid Fernandes, R., Stasi´ nska, G., Schlickmann, M. S., et al. 2010, MNRAS, 403, 1036, doi: 10.1111/j.1365-2966.2009.16185.x

  34. [34]

    Conroy, C., & Gunn, J. E. 2010, ApJ, 712, 833, doi: 10.1088/0004-637X/712/2/833

  35. [35]

    E., & White, M

    Conroy, C., Gunn, J. E., & White, M. 2009, ApJ, 699, 486, doi: 10.1088/0004-637X/699/1/486

  36. [36]

    L., Margutti, R., Terreran, G., et al

    Coppejans, D. L., Margutti, R., Terreran, G., et al. 2020, ApJL, 895, L23, doi: 10.3847/2041-8213/ab8cc7

  37. [37]

    J., Lang, D., et al

    Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168, doi: 10.3847/1538-3881/ab089d

  38. [38]

    A., Nugent, A., et al

    Dong, Y., Villar, V. A., Nugent, A., et al. 2025, arXiv e-prints, arXiv:2511.03926, doi: 10.48550/arXiv.2511.03926

  39. [39]

    T., & Li, A

    Draine, B. T., & Li, A. 2007, ApJ, 657, 810, doi: 10.1086/511055

  40. [40]

    R., Chornock, R., Soderberg, A

    Drout, M. R., Chornock, R., Soderberg, A. M., et al. 2014, ApJ, 794, 23, doi: 10.1088/0004-637X/794/1/23

  41. [41]

    R., Dufton, P

    Dunstall, P. R., Dufton, P. L., Sana, H., et al. 2015, A&A, 580, A93, doi: 10.1051/0004-6361/201526192 Falc´ on-Barroso, J., S´ anchez-Bl´ azquez, P., Vazdekis, A., et al. 2011, A&A, 532, A95, doi: 10.1051/0004-6361/201116842

  42. [42]

    E., Dong, Y., et al

    Fong, W.-f., Nugent, A. E., Dong, Y., et al. 2022, ApJ, 940, 56, doi: 10.3847/1538-4357/ac91d0

  43. [43]

    S., Levan, A

    Fruchter, A. S., Levan, A. J., Strolger, L., et al. 2006, Nature, 441, 463, doi: 10.1038/nature04787

  44. [44]

    L., Burns, E., Ho, A

    Fryer, C. L., Burns, E., Ho, A. Y. Q., et al. 2025, ApJ, 986, 185, doi: 10.3847/1538-4357/add474

  45. [45]

    L., & Woosley, S

    Fryer, C. L., & Woosley, S. E. 1998, ApJL, 502, L9, doi: 10.1086/311493

  46. [46]

    L., Woosley, S

    Fryer, C. L., Woosley, S. E., & Hartmann, D. H. 1999, ApJ, 526, 152, doi: 10.1086/307992

  47. [47]

    P., Rosales-Ortega, F

    Galbany, L., Anderson, J. P., Rosales-Ortega, F. F., et al. 2016, MNRAS, 455, 4087, doi: 10.1093/mnras/stv2620

  48. [48]

    Gallazzi, A., Charlot, S., Brinchmann, J., White, S. D. M., & Tremonti, C. A. 2005, MNRAS, 362, 41, doi: 10.1111/j.1365-2966.2005.09321.x

  49. [49]

    F., Levan, A

    Gaspari, N., Stevance, H. F., Levan, A. J., Chrimes, A. A., & Lyman, J. D. 2024, A&A, 692, A21, doi: 10.1051/0004-6361/202450908

  50. [50]

    2017, ApJL, 848, L14, doi: 10.3847/2041-8213/aa8f41

    Goldstein, A., Veres, P., Burns, E., et al. 2017, ApJL, 848, L14, doi: 10.3847/2041-8213/aa8f41

  51. [51]

    M., & Quataert, E

    Govreen-Segal, T., Nakar, E., Hotokezaka, K., Irwin, C. M., & Quataert, E. 2026, arXiv e-prints, arXiv:2601.18887, doi: 10.48550/arXiv.2601.18887

  52. [52]

    E., Lancaster, L., Ting, Y.-S., et al

    Greene, J. E., Lancaster, L., Ting, Y.-S., et al. 2021, ApJ, 917, 17, doi: 10.3847/1538-4357/ac0896

  53. [53]

    2026, arXiv e-prints, arXiv:2602.12970, doi: 10.48550/arXiv.2602.12970

    Guolo, M. 2026, arXiv e-prints, arXiv:2602.12970, doi: 10.48550/arXiv.2602.12970

  54. [54]

    2026, arXiv e-prints, arXiv:2602.12272, doi: 10.48550/arXiv.2602.12272 Guti´ errez, C

    Guolo, M., Mummery, A., van Velzen, S., et al. 2026, arXiv e-prints, arXiv:2602.12272, doi: 10.48550/arXiv.2602.12272 Guti´ errez, C. P., Mattila, S., Lundqvist, P., et al. 2024, ApJ, 977, 162, doi: 10.3847/1538-4357/ad89a5

  55. [55]

    Hartmann, D. H. 2003, ApJ, 591, 288, doi: 10.1086/375341

  56. [56]

    2013, ApJS, 208, 19, doi: 10.1088/0067-0049/208/2/19

    Hinshaw, G., Larson, D., Komatsu, E., et al. 2013, ApJS, 208, 19, doi: 10.1088/0067-0049/208/2/19

  57. [57]

    Ho, A. Y. Q., Phinney, E. S., Ravi, V., et al. 2019, ApJ, 871, 73, doi: 10.3847/1538-4357/aaf473

  58. [58]

    Ho, A. Y. Q., Perley, D. A., Kulkarni, S. R., et al. 2020, ApJ, 895, 49, doi: 10.3847/1538-4357/ab8bcf

  59. [59]

    Ho, A. Y. Q., Margalit, B., Bremer, M., et al. 2022, ApJ, 932, 116, doi: 10.3847/1538-4357/ac4e97

  60. [60]

    Ho, A. Y. Q., Perley, D. A., Chen, P., et al. 2023a, Nature, 623, 927, doi: 10.1038/s41586-023-06673-6

  61. [61]

    Ho, A. Y. Q., Perley, D. A., Gal-Yam, A., et al. 2023b, ApJ, 949, 120, doi: 10.3847/1538-4357/acc533

  62. [62]

    2026, ApJ, 996, 78, doi: 10.3847/1538-4357/ae1f11

    Horowicz, A., & Margalit, B. 2026, ApJ, 996, 78, doi: 10.3847/1538-4357/ae1f11

  63. [63]

    I., et al

    Hosseinzadeh, G., McCully, C., Zabludoff, A. I., et al. 2019, ApJL, 871, L9, doi: 10.3847/2041-8213/aafc61

  64. [64]

    K., Berger, E., & Gomez, S

    Hsu, B., Blanchard, P. K., Berger, E., & Gomez, S. 2024, ApJ, 961, 169, doi: 10.3847/1538-4357/ad12be

  65. [65]

    2026, arXiv e-prints, arXiv:2601.01333, doi: 10.48550/arXiv.2601.01333

    Hu, M., Yan, S., Wang, X., et al. 2026, arXiv e-prints, arXiv:2601.01333, doi: 10.48550/arXiv.2601.01333

  66. [66]

    J., Mummery, A., & Jonker, P

    Inkenhaag, A., Levan, A. J., Mummery, A., & Jonker, P. G. 2025, MNRAS, 544, L108, doi: 10.1093/mnrasl/slaf107 Ivezi´ c,ˇZ., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111, doi: 10.3847/1538-4357/ab042c

  67. [67]

    D., Leja, J., Conroy, C., & Speagle, J

    Johnson, B. D., Leja, J., Conroy, C., & Speagle, J. S. 2021, ApJS, 254, 22, doi: 10.3847/1538-4365/abef67

  68. [68]

    O., McGill, P., Manning, T

    Jones, D. O., McGill, P., Manning, T. A., et al. 2024, arXiv e-prints, arXiv:2410.17322, doi: 10.48550/arXiv.2410.17322

  69. [69]

    2018, MNRAS, 477, 5568, doi: 10.1093/mnras/sty1012

    Kaasinen, M., Kewley, L., Bian, F., et al. 2018, MNRAS, 477, 5568, doi: 10.1093/mnras/sty1012

  70. [70]

    2010, ApJ, 717, 245, doi: 10.1088/0004-637X/717/1/245

    Kasen, D., & Bildsten, L. 2010, ApJ, 717, 245, doi: 10.1088/0004-637X/717/1/245

  71. [71]

    M., Tremonti, C., et al

    Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x

  72. [72]

    L., & Kirshner, R

    Kelly, P. L., & Kirshner, R. P. 2012, ApJ, 759, 107, doi: 10.1088/0004-637X/759/2/107

  73. [73]

    L., Kirshner, R

    Kelly, P. L., Kirshner, R. P., & Pahre, M. 2008, ApJ, 687, 1201, doi: 10.1086/591925

  74. [74]

    J., & Dopita, M

    Kewley, L. J., & Dopita, M. A. 2002, ApJS, 142, 35, doi: 10.1086/341326 LFBOT Hosts25

  75. [75]

    J., Dopita, M

    Kewley, L. J., Dopita, M. A., Sutherland, R. S., Heisler, C. A., & Trevena, J. 2001, ApJ, 556, 121, doi: 10.1086/321545

  76. [76]

    J., Groves, B., Kauffmann, G., & Heckman, T

    Kewley, L. J., Groves, B., Kauffmann, G., & Heckman, T. 2006, MNRAS, 372, 961, doi: 10.1111/j.1365-2966.2006.10859.x

  77. [77]

    J., Maier, C., Yabe, K., et al

    Kewley, L. J., Maier, C., Yabe, K., et al. 2013, ApJL, 774, L10, doi: 10.1088/2041-8205/774/1/L10

  78. [78]

    J., Nicholls, D

    Kewley, L. J., Nicholls, D. C., & Sutherland, R. S. 2019, ARA&A, 57, 511, doi: 10.1146/annurev-astro-081817-051832

  79. [79]

    K., & Kasen, D

    Khatami, D. K., & Kasen, D. N. 2024, ApJ, 972, 140, doi: 10.3847/1538-4357/ad60c0

  80. [80]

    Klencki, J., & Metzger, B. D. 2025, arXiv e-prints, arXiv:2510.09745, doi: 10.48550/arXiv.2510.09745

Showing first 80 references.