Pith. sign in

REVIEW 3 major objections 3 minor 1 cited by

The Progenitors of Calcium-Strong Transients

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

Pith's one-line read This paper argues that calcium-strong transients come from rare binaries forged and then ejected by globular clusters.

desk verdict This paper makes a real contribution by constructing the local-universe globular cluster radial distribution and arguing that dynamical formation plus hardening/ejection in GCs can explain the CaST population, but the central formation-rate assumption is still unquantified and the scenario is a plausible framework, not a demonstrated solution. read the letter →

arxiv 1908.08056 v2 pith:5WCKSNPL submitted 2019-08-21 astro-ph.HE astro-ph.GAastro-ph.SR

classification astro-ph.HEastro-ph.GAastro-ph.SR
keywords calcium-strongtransientscalcium-richsupernovaeglobularclusterswhitedwarfmergerstidaldisruptionbinaryhardeningnuclearstartransientastronomy
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

Calcium-strong transients (CaSTs) are faint, fast explosions with unusually high calcium-to-oxygen nebular line ratios, and they appear tens of kiloparsecs from their host galaxies far more often than ordinary supernovae. This paper argues that their extreme locations and relatively high rate point to a production site inside globular clusters: rare binaries -- helium white dwarfs merging with oxygen/neon white dwarfs, helium white dwarfs tidally disrupted by neutron stars, or low-mass helium-burning stars dumping material onto white dwarfs -- are formed dynamically in dense clusters and then ejected by binary-hardening recoil before they explode. The ejected binaries inherit the globular cluster radial distribution, explaining both the large offsets and the absence of any cluster at the explosion site. The paper shows that old, metal-poor stars also match the distribution, but no concrete progenitor scenario exists for that alternative. If the cluster scenario is correct, CaSTs should also be produced near the centers of galaxies in nuclear star clusters, a prediction that future surveys can test.

What carries the argument

The load-bearing object is the globular cluster itself, treated as a dynamical factory: its high stellar density creates rare hard binaries through captures and exchanges, and the same environment then hardens them. The quantitative machinery is the balance between the binary-hardening recoil and the cluster's gravitational pull. Repeated encounters shrink a hard binary's orbit and give the binary a growing recoil velocity; once that velocity exceeds the cluster escape speed, the binary is ejected while its orbit is still wide enough that gravitational-wave inspiral has not yet brought the components into contact. The paper estimates that the ejection separation and the gravitational-wave-dominated separation are comparable for its three candidate channels, so ejection before interaction is plausible for at least some systems. The other load-bearing component is the mass budget: combining the observed volumetric CaST rate with the local mass density of globular clusters requires roughly one CaST per 8.4 solar masses of cluster mass if production has been steady for a Hubble time, or one per 120 solar masses if it has been active for only the last gigayear.

What would settle it

A search capable of finding faint transients in the bright cores of galaxies that finds no nuclear-star-cluster CaST population at a rate comparable to the observed outskirt rate would falsify the dynamical-production scenario. A direct dynamical calculation showing that the three channels form in globular clusters far too slowly to meet the required mass budget would do the same.

Watch

Extended reading notes

Core claim

The central claim is that the observed population of calcium-strong transients is best understood as the product of dynamically formed binaries that are ejected from globular clusters before interacting. The paper matches the projected galactocentric radial distribution of the observed CaSTs to the theoretical radial distribution of globular clusters in the local universe, built from the halo mass function and a power-law relation between cluster system size and halo mass. It then identifies three binary channels whose field rates are too low but whose formation and interaction rates could be enhanced in dense cluster environments: He plus O/Ne white dwarf mergers, tidal disruption of He white dwarfs by neutron stars, and stable accretion from low-mass He-burning stars onto white dwarfs. Binary hardening simultaneously shrinks the orbits, raising the interaction rate, and eventually gives recoil kicks that exceed the cluster escape speed, ejecting the binary before mass transfer or merger. That is why no globular cluster is seen at a CaST site despite the cluster origin. The paper explicitly flags that the required production efficiency is high: if CaSTs have been produced at a constant rate for a Hubble time, nearly half of all white dwarfs in globular clusters must participate, and this budget appears to rule out the neutron-star channel because few neutron stars are retained in clusters.

Load-bearing premise

The assumption that the three candidate binaries are actually formed dynamically inside globular clusters at rates at least competitive with field formation is not quantified in the paper, and without it the radial-distribution match is only a coincidence.

Editorial extensions

If this is right

  • CaSTs should continue to appear far from their hosts, tracing the globular cluster radial distribution; the observed sample should converge toward the broader silver-sample distribution rather than the gold-sample one as surveys improve.
  • Deep imaging at CaST sites should usually reveal no host globular cluster, because the progenitors are ejected before exploding, though events born in clusters with unusually high escape velocities may still be found inside clusters.
  • Nuclear star clusters should produce CaSTs at a rate comparable to the observed outskirt rate, and the current lack of such detections is a selection effect that core-sensitive searches can test.
  • The helium-white-dwarf plus neutron-star channel is unlikely to be the main route, because the number of neutron stars retained in globular clusters is too small to provide the required event rate.
  • Explosion models of the remaining two channels should produce low radioactive yields and ejecta dominated by intermediate-mass elements, matching the faint, calcium-dominated spectra of CaSTs.

Reading between the lines

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

  • If the globular cluster origin is right, the CaST rate should scale with the total globular cluster mass of a galaxy or halo, so more massive clustered environments should contribute disproportionately; this could be tested by comparing host halo masses of future CaST samples.
  • The tight mass budget hints that globular clusters may have been more massive in the past or that only a subpopulation of dense, core-collapsed clusters produces most CaSTs; identifying which clusters contribute could sharpen predictions for the nuclear-star-cluster rate.
  • The same ejection mechanism may apply to other compact-object transients with anomalously extended radial distributions, so a systematic search for hostless explosions tracing globular-cluster halos could reveal whether CaSTs are one example of a broader dynamical channel.
  • A direct N-body calculation of the three binary channels in realistic cluster models would turn the currently assumed formation-rate enhancement into a measured rate; if it comes out below field rates, the old-metal-poor-star alternative would need a concrete progenitor to remain viable.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 3 minor

Summary. The paper studies calcium-strong transients (CaSTs), a class of faint, spectroscopically peculiar explosions with high nebular Ca/O ratios, large galactocentric offsets, and a relatively high volumetric rate. The authors first show that the CaST radial distribution is qualitatively similar to the radial distribution of globular clusters (GCs) and of old, metal-poor stars. They then propose that CaSTs originate from one of three binary channels—He+O/Ne white dwarf mergers, He white dwarf disruptions by neutron stars, or accretion from low-mass He-burning stars onto white dwarfs—that are rare in the field but can be formed dynamically in GCs. Binary hardening both raises the interaction rate and ejects the binaries before explosion, explaining the absence of GCs at transient sites. The paper also quantifies the required CaST production efficiency from GC mass and derives a falsifiable prediction of a comparable CaST rate in nuclear star clusters. The central claim is conditional on an assumed, uncalculated dynamical formation rate, and the paper is transparent about this limitation.

Significance. If the GC-production scenario is correct, the paper would connect CaSTs to dynamical binary formation in dense stellar systems and provide a new, testable prediction for nuclear star clusters. The paper makes several useful contributions: it assembles the observational constraints on CaSTs, derives a theoretical GC radial distribution from independent empirical scaling relations, identifies three specific progenitor channels that warrant further study, and explicitly quantifies the rate-efficiency tension that any GC scenario must overcome. The falsifiable NSC prediction and the honesty about the missing dynamical calculation are strengths. The main significance is as a hypothesis-shaping paper rather than a demonstrated progenitor model; the central claim rests on an assumption that the authors themselves defer to future work.

major comments (3)
  1. [Section 3.3] The central assumption of the GC scenario is not quantified. The paper states that "we proceed under the assumption that CaST progenitors are formed dynamically in GCs as hard binaries at a rate larger than, or at least competitive with, that in the field" and defers the calculation to future N-body and population-synthesis work. This is load-bearing because §2.4 quotes field WD+NS merger rates of only 3e-16 to 3e-15 yr^-1 Msun^-1, so the required GC enhancement is not a small factor. As written, the paper demonstrates that the GC scenario is consistent with the radial distribution only if an uncalculated formation rate happens to be favorable; it does not demonstrate that the proposed channels supply the observed CaST rate. A quantitative requirement on the dynamical birth rate for each channel, or a reframing of the claim as a strictly conditional hypothesis, is needed.
  2. [Section 3.4, Eq. (6)] The rate-efficiency budget derived in §3.4 is severe and, as the authors acknowledge, not resolved by the paper. The constant-Hubble-time case requires η ≈ 1 CaST per 8.4 Msun of GC mass, which with 0.3 WDs per Msun implies roughly half of all GC white dwarfs participating; the 1-Gyr-delay case gives about 3% before applying the 2–7× mass-segregation boost and the restriction to the subset of GCs with densities near 10^7 pc^-3 needed for rapid hardening. Since the hardening timescale in Eq. (3) is evaluated at n = 10^7 pc^-3, typical GCs will be much less efficient, so the required per-cluster efficiency is even higher. This budget should be converted into a required dynamical formation rate for each candidate channel and compared with existing constraints from cataclysmic variables, X-ray binaries, and double-WD populations, rather than left as a caveat.
  3. [Section 3.1, Figure 1] The claimed consistency between the GC radial distribution and the CaST distribution is assessed only by visual comparison of cumulative distributions. No significance test (e.g., Kolmogorov–Smirnov) is given, the gold sample contains only eight objects, and the paper itself notes in §3.1 that the Palomar Transient Factory is biased against recovering CaSTs close to their hosts, making the gold distribution an upper limit. With these issues, the visual agreement is suggestive but not a quantitative empirical constraint. The paper should either provide a test statistic or explicitly label the match as qualitative for both Figure 1 and Figure 2.
minor comments (3)
  1. [Section 3.1] The uncertainty in the GC system effective radius–halo mass relation, including the alternative slope from Hudson & Robison (2018) noted in the footnote, is not propagated into the cumulative distributions in Figures 1 and 2; showing a range of Sérsic indices and scaling-relation parameters would make the robustness of the conclusion clearer.
  2. [Section 3.4] The quoted Frohmaier et al. rate is asymmetric (+1.13/-0.39), but the derived efficiency η is presented as a single value; reporting the corresponding range in η would help the reader see how sensitive the mass-budget argument is to the uncertain rate.
  3. [Section 4] The statement that overall TNG100 stellar density profiles match observed stacked galaxies is used to support the reliability of age and metallicity binning, but this is a weaker validation than a direct comparison of halo stellar populations; the sentence should be phrased as a modeling assumption.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the GC radial distribution and rate-efficiency constraints use independent empirical inputs, and the unquantified GC dynamical-formation rate is an openly stated assumption, not a fitted prediction.

full rationale

The paper's central comparison is not circular. In Section 3.1, the predicted GC radial distribution is built from independent inputs: the observed M_GCs/M_halo relation, the Tinker et al. (2008) halo mass function, and Forbes (2017)'s empirically calibrated Re-halo mass relation. This cumulative distribution is then compared with, not fitted to, the observed CaST offsets in Figure 1. Section 3.4 similarly treats the observed volumetric CaST rate (Frohmaier et al. 2018) and the independently integrated GC mass density (rho_GCs = 1.4e6 Msun/Mpc3) as inputs, and the resulting efficiency eta ~ 1 CaST per 8.4 Msun is explicitly an 'implied production efficiency' — a constraint used to test the scenario (e.g., ruling out He WD + NS progenitors), not a fitted parameter relabeled as a prediction. The load-bearing dynamical-formation rate in GCs is admittedly not quantified: Section 3.3 states, 'We do not conduct a quantitative estimate of the birth rates... Instead, we proceed under the assumption that CaST progenitors are formed dynamically in GCs as hard binaries at a rate larger than, or at least competitive with, that in the field.' That is an acknowledged unverified assumption and a correctness risk, but it is not circularity because the paper does not pretend to derive it. The Section 3.5 nuclear-star-cluster prediction is a conditional, falsifiable corollary ('if CaSTs are indeed dynamically formed in GCs, they should also explode in nuclear star clusters'), not an output forced by construction. The self-citations present (e.g., Shen & Bildsten 2014 for O/Ne WD core behavior, Shen 2015 for double-WD mass-transfer instability) support ancillary physics subclaims about candidate explosion channels; they are not the basis for the GC-production scenario, and the paper imports no 'uniqueness theorem' from the authors' prior work. Overall, the derivation chain is self-contained against external benchmarks; the central weakness is an unquantified rate assumption, which belongs to scientific plausibility, not circular reasoning.

Assumptions & free parameters 5 free parameters · 7 assumptions · 0 invented entities

The paper's quantitative case rests on a chain of empirical calibrations (MGCs/Mhalo ~ 3e-5, Forbes 2017 Re-halo relation, Sersic index n=2-4, Tinker HMF) to build the GC radial distribution, and on an explicitly unverified assumption that dynamical formation rates in GCs are competitive with the field. The efficiency calculation in Section 3.4 converts the observed CaST rate and the derived GC mass density into a required production efficiency; that conversion is sound but exposes a demanding constraint. No new physical entities are introduced.

free parameters (5)
  • Sersic index n for GC surface density profiles = n = 2 and n = 4 (representative values)
    Chosen by hand to bracket GC system profiles; enters Eq. (2) and sets the shape of the model GC radial distribution in Figure 1.
  • GC system mass fraction MGCs/Mhalo = 3e-5
    Empirical scaling from Blakeslee et al. (1997), Harris et al. (2015), Choksi & Gnedin (2019); sets the normalization of rho_GCs = 1.4e6 Msun/Mpc^3 and thus the required CaST production efficiency eta in Section 3.4.
  • GC effective radius-halo mass relation Re = 22 kpc (Mhalo/1e13 Msun)^(1/3) = Normalization 22 kpc, slope 1/3
    Forbes (2017) correlation used to map halo mass to GC system size; Hudson & Robison (2018) find a slope near 0.74 with ultradiffuse galaxies removed, which would alter the predicted distribution. The paper does not explore that alternative.
  • Duration of CaST production from GCs = Constant over Hubble time vs. only last 1 Gyr
    The efficiency eta (1 per 8.4 Msun vs. 1 per 120 Msun) is computed under two assumed production histories; neither is constrained by data.
  • Binary hardening fiducial parameters (xi=0.3, n=1e7 pc^-3, sigma=10 km/s, vesc=50 km/s) = Fiducial values for core-collapsed GC
    Used in Eqs. (3)-(5) to argue that binaries can be ejected before merging; the conclusion that at least some CaSTs occur outside their birth clusters depends on these choices.
assumptions (7)
  • domain assumption GC total mass is linearly proportional to host halo mass (MGCs/Mhalo ~ 3e-5) across five orders of magnitude
    Invoked in Sections 3.1 and 3.2 to build the mass-weighted GC radial distribution from the halo mass function; if the scaling breaks down at low halo masses, the derived GC distribution and rho_GCs could be biased.
  • standard math The Tinker et al. (2008) halo mass function at z=0 describes local universe halos and HMFcalc implements it correctly
    Used in Section 3.1 to compute the mass-weighted halo CDF; standard tool in the field.
  • domain assumption GC systems are described by Sersic surface density profiles with index n=2 to 4
    Equation (2) in Section 3.1; representative values are chosen, not derived from CaST data.
  • standard math Hardening of a binary in a GC follows the Heggie-Hills law with timescale Eq. (3), and ejection occurs when recoil velocity reaches the GC escape velocity Eq. (4)
    Standard three-body dynamical results (Heggie 1975; Hills 1983; Spitzer 1987; Sigurdsson & Phinney 1993) invoked in Section 3.3.
  • ad hoc to paper CaST progenitors (He+O/Ne WD, He WD+NS, or He-burning star+WD binaries) are formed dynamically in GCs at a rate at least competitive with the field
    Explicit assumption in Section 3.3: the paper proceeds under this assumption and declines to compute the rate, deferring to future N-body and population synthesis work.
  • domain assumption IllustrisTNG100 stellar populations binned by age and metallicity accurately represent the true radial distributions of old, metal-poor stars in the local universe
    Section 4 uses TNG100 because observational stellar halo metallicities and ages are not generally available; authors cite D'Souza et al. (2014) agreement of total stellar density profiles as validation.
  • domain assumption The retained neutron star fraction in globular clusters is about 1 per 800-900 Msun (Ivanova et al. 2008)
    Section 3.4 uses this literature value to rule out He WD+NS progenitors; if the retention fraction were much larger, that channel could be viable.

how reviews work

0 comments
Cite this review

Pith. "Pith review of The Progenitors of Calcium-Strong Transients." pith.science (2026). https://pith.science/paper/5WCKSNPL

@misc{pith2026190808056,
  author       = {Pith},
  title        = {Pith review of: The Progenitors of Calcium-Strong Transients},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/5WCKSNPL}},
  note         = {Machine review of arXiv:1908.08056}
}
read the original abstract

A new class of faint, spectroscopically peculiar transients has emerged in the last decade. We term these events "calcium-strong transients" (CaSTs) because of their atypically high calcium-to-oxygen nebular line ratios. Previous studies have struggled to deduce the identity of their progenitors due to a combination of their extremely extended radial distributions with respect to their host galaxies and their relatively high rate of occurrence. In this work, we find that the CaST radial distribution is consistent with the radial distribution of two populations of stars: old (ages > 5 Gyr), low-metallicity (Z/Zsol < 0.3) stars and globular clusters. While no obvious progenitor scenario arises from considering old, metal-poor stars, the alternative production site of globular clusters leads us to narrow down the list of possible candidates to three binary scenarios: mergers of helium and oxygen/neon white dwarfs; tidal disruptions of helium white dwarfs by neutron stars; and stable accretion from low-mass helium-burning stars onto white dwarfs. While rare in the field, these binary systems can be formed dynamically at much higher rates in globular clusters. Subsequent binary hardening both increases their interaction rate and ejects them from their parent globular clusters prior to mass transfer contact. Their production in, and ejection from, globular clusters may explain their radial distribution and the absence of globular clusters at their explosion site. This model predicts a currently undiscovered high rate of CaSTs in nuclear star clusters. Alternatively, an undetermined progenitor scenario involving old, low-metallicity stars may instead hold the key to understanding CaSTs.

Figures

Figures reproduced from arXiv: 1908.08056 by the authors.

Figure 1
Figure 1. Projected galactocentric radial distribution func￾tions of CaSTs and GCs. The GC radial distributions assume S´ersic profiles with n = 2 (blue line) and n = 4 (red line). The yellow and gray lines show the gold- and silver-sample radial distributions of CaSTs, respectively. halo CDF, which also corresponds to the mass-weighted GC distribution function, and relate the halo mass to the effective radius of the GC syste… view at source ↗
Figure 2
Figure 2. Projected galactocentric radial distribution func￾tions of CaSTs and stellar populations of various ages and metallicities from TNG100. Red, blue, green, and purple lines show distributions of stellar populations with ages from 1 to 3, 3 to 5, 5 to 10, and 10 to 13.8 Gyr, and solid, dashed, and dotted lines show distributions of stars with metallici￾ties of Z/Z ≥ 0.3, 0.3 > Z/Z ≥ 0.1, and Z/Z < 0.1, respectively. As… view at source ↗

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Compact Objects in Globular Clusters

    astro-ph.HE 2025-08 unverdicted novelty 1.0 of 10

    Globular clusters host many stellar remnants, and their dense environments produce X-ray sources, radio pulsars, and gravitational-wave black hole mergers.

Reference graph

Works this paper leans on

112 extracted references · 12 canonical work pages · cited by 1 Pith paper

  1. [1]

    J., & Mandel, I

    Andrews, J. J., & Mandel, I. 2019, ApJL, 880, L8, doi: 10.3847/2041-8213/ab2ed1

  2. [2]

    C., Olivier, S

    Anninos, P., Fragile, P. C., Olivier, S. S., et al. 2018, ApJ, 865, 3, doi: 10.3847/1538-4357/aadad9

  3. [3]

    Antonini, F., & Rasio, F. A. 2016, ApJ, 831, 187, doi: 10.3847/0004-637X/831/2/187

  4. [4]

    2003, MNRAS, 340, 227, doi: 10.1046/j.1365-8711.2003.06286.x

    Baumgardt, H., & Makino, J. 2003, MNRAS, 340, 227, doi: 10.1046/j.1365-8711.2003.06286.x

  5. [5]

    S., Conroy, C., & Wechsler, R

    Behroozi, P. S., Conroy, C., & Wechsler, R. H. 2010, ApJ, 717, 379, doi: 10.1088/0004-637X/717/1/379

  6. [6]

    J., & Downing, J

    Benacquista, M. J., & Downing, J. M. B. 2013, Living Reviews in Relativity, 16, 4, doi: 10.12942/lrr-2013-4

  7. [7]

    J., Weinberg, N

    Bildsten, L., Shen, K. J., Weinberg, N. N., & Nelemans, G. 2007, ApJL, 662, L95, doi: 10.1086/519489

  8. [8]

    P., Tonry, J

    Blakeslee, J. P., Tonry, J. L., & Metzger, M. R. 1997, AJ, 114, 482, doi: 10.1086/118488

Show all 112 references
  1. [9]

    R., & Moustakas, J

    Blanton, M. R., & Moustakas, J. 2009, ARA&A, 47, 159, doi: 10.1146/annurev-astro-082708-101734

  2. [10]

    B., & Church, R

    Bobrick, A., Davies, M. B., & Church, R. P. 2017, MNRAS, 467, 3556, doi: 10.1093/mnras/stx312

  3. [11]

    C., et al

    Branch, D., Baron, E., Thomas, R. C., et al. 2004, PASP, 116, 903, doi: 10.1086/425081

  4. [12]

    D., & Kocsis, B

    Brandt, T. D., & Kocsis, B. 2015, ApJ, 812, 15, doi: 10.1088/0004-637X/812/1/15

  5. [13]

    R., Kilic, M., Kenyon, S

    Brown, W. R., Kilic, M., Kenyon, S. J., & Gianninas, A. 2016, ApJ, 824, 46, doi: 10.3847/0004-637X/824/1/46

  6. [14]

    J., Marsh, T

    Carter, P. J., Marsh, T. R., Steeghs, D., et al. 2013, MNRAS, 429, 2143, doi: 10.1093/mnras/sts485

  7. [15]

    D., et al

    Chen, P., Dong, S., Stritzinger, M. D., et al. 2019, ApJL, submitted (arXiv:1905.02205)

  8. [16]

    Choksi, N., & Gnedin, O. Y. 2019, MNRAS, 488, 5409, doi: 10.1093/mnras/stz2097

  9. [17]

    2007, CBET, 1084, 1

    Chu, J., & Li, W. 2007, CBET, 1084, 1

  10. [18]

    Clayton, G. C. 1996, PASP, 108, 225, doi: 10.1086/133715

  11. [19]

    R., Darbha, S., Kasen, D., & Quataert, E

    Coughlin, E. R., Darbha, S., Kasen, D., & Quataert, E. 2018, ApJL, 863, L24, doi: 10.3847/2041-8213/aad7bd

  12. [20]

    M., Cantwell, T., et al

    De, K., Kasliwal, M. M., Cantwell, T., et al. 2018a, ApJ, 866, 72, doi: 10.3847/1538-4357/aadf8e

  13. [21]

    M., Ofek, E

    De, K., Kasliwal, M. M., Ofek, E. O., et al. 2018b, Science, 362, 201, doi: 10.1126/science.aas8693 de Plaa, J., Werner, N., Bleeker, J. A. M., et al. 2007, A&A, 465, 345, doi: 10.1051/0004-6361:20066382

  14. [22]

    Dessart, L., & Hillier, D. J. 2015, MNRAS, 447, 1370, doi: 10.1093/mnras/stu2520 D’Souza, R., Kauffman, G., Wang, J., & Vegetti, S. 2014, MNRAS, 443, 1433, doi: 10.1093/mnras/stu1194

  15. [23]

    V., & Fedorova, A

    Ergma, E. V., & Fedorova, A. V. 1990, Ap&SS, 163, 143, doi: 10.1007/BF00639983 Fern´ andez, R., Margalit, B., & Metzger, B. D. 2019, MNRAS, 488, 259, doi: 10.1093/mnras/stz1701 Fern´ andez, R., & Metzger, B. D. 2013, ApJ, 763, 108, doi: 10.1088/0004-637X/763/2/108

  16. [24]

    Filippenko, A. V. 1997, ARA&A, 35, 309, doi: 10.1146/annurev.astro.35.1.309

  17. [25]

    V., Chornock, R., Swift, B., et al

    Filippenko, A. V., Chornock, R., Swift, B., et al. 2003, IAUC, 8159, 2

  18. [26]

    Fink, M., Hillebrandt, W., & R¨ opke, F. K. 2007, A&A, 476, 1133, doi: 10.1051/0004-6361:20078438

  19. [27]

    K., Hillebrandt, W., et al

    Fink, M., R¨ opke, F. K., Hillebrandt, W., et al. 2010, A&A, 514, A53, doi: 10.1051/0004-6361/200913892 12 Shen, Quataert, & Pakmor

  20. [28]

    R., et al

    Fink, M., Kromer, M., Seitenzahl, I. R., et al. 2014, MNRAS, 438, 1762, doi: 10.1093/mnras/stt2315

  21. [29]

    Foley, R. J. 2015, MNRAS, 452, 2463, doi: 10.1093/mnras/stv789

  22. [30]

    Forbes, D. A. 2017, MNRAS, 472, L104, doi: 10.1093/mnrasl/slx148

  23. [31]

    A., Read, J

    Forbes, D. A., Read, J. I., Gieles, M., & Collins, M. L. M. 2018, MNRAS, 481, 5592, doi: 10.1093/mnras/sty2584

  24. [32]

    Fragione, G., Antonini, F., & Gnedin, O. Y. 2018, MNRAS, 475, 5313, doi: 10.1093/mnras/sty183

  25. [33]

    2018, ApJ, 858, 50, doi: 10.3847/1538-4357/aabc0b

    Frohmaier, C., Sullivan, M., Maguire, K., & Nugent, P. 2018, ApJ, 858, 50, doi: 10.3847/1538-4357/aabc0b

  26. [34]

    R., Wang, B., et al

    Geier, S., Marsh, T. R., Wang, B., et al. 2013, A&A, 554, A54, doi: 10.1051/0004-6361/201321395

  27. [35]

    Y., Ostriker, J

    Gnedin, O. Y., Ostriker, J. P., & Tremaine, S. 2014, ApJ, 785, 71, doi: 10.1088/0004-637X/785/1/71

  28. [36]

    G., Carretta, E., & Bragaglia, A

    Gratton, R. G., Carretta, E., & Bragaglia, A. 2012, A&A Rv, 20, 50, doi: 10.1007/s00159-012-0050-3

  29. [37]

    2010, ApJL, 709, L64, doi: 10.1088/2041-8205/709/1/L64

    Guillochon, J., Dan, M., Ramirez-Ruiz, E., & Rosswog, S. 2010, ApJL, 709, L64, doi: 10.1088/2041-8205/709/1/L64

  30. [38]

    E., Harris, G

    Harris, W. E., Harris, G. L., & Hudson, M. J. 2015, ApJ, 806, 36, doi: 10.1088/0004-637X/806/1/36

  31. [39]

    Heggie, D. C. 1975, MNRAS, 173, 729, doi: 10.1093/mnras/173.3.729

  32. [40]

    Hills, J. G. 1983, AJ, 88, 1269, doi: 10.1086/113418

  33. [41]

    J., & Robison, B

    Hudson, M. J., & Robison, B. 2018, MNRAS, 477, 3869, doi: 10.1093/mnras/sty844

  34. [42]

    Fregeau, J. M. 2008, MNRAS, 386, 553, doi: 10.1111/j.1365-2966.2008.13064.x

  35. [43]

    O., Rasio, F

    Ivanova, N., Heinke, C. O., Rasio, F. A., et al. 2006, MNRAS, 372, 1043, doi: 10.1111/j.1365-2966.2006.10876.x

  36. [44]

    M., Kulkarni, S

    Kasliwal, M. M., Kulkarni, S. R., Gal-Yam, A., et al. 2012, ApJ, 755, 161, doi: 10.1088/0004-637X/755/2/161

  37. [45]

    S., Maeda, K., Nomoto, K., et al

    Kawabata, K. S., Maeda, K., Nomoto, K., et al. 2010, Nature, 465, 326, doi: 10.1038/nature09055

  38. [46]

    2018, MNRAS, 477, 3449, doi: 10.1093/mnras/sty842

    Kawana, K., Tanikawa, A., & Yoshida, N. 2018, MNRAS, 477, 3449, doi: 10.1093/mnras/sty842

  39. [47]

    Khokhlov, A. M. 1991, A&A, 245, 114

  40. [48]

    Kravtsov, A. V. 2013, ApJL, 764, L31, doi: 10.1088/2041-8205/764/2/L31

  41. [49]

    C., van Rossum, D

    Long, M., Jordan, IV, G. C., van Rossum, D. R., et al. 2014, ApJ, 789, 103, doi: 10.1088/0004-637X/789/2/103

  42. [50]

    M., Cao, Y., et al

    Lunnan, R., Kasliwal, M. M., Cao, Y., et al. 2017, ApJ, 836, 60, doi: 10.3847/1538-4357/836/1/60

  43. [51]

    D., Bersier, D., James, P

    Lyman, J. D., Bersier, D., James, P. A., et al. 2016a, MNRAS, 457, 328, doi: 10.1093/mnras/stv2983

  44. [52]

    D., James, P

    Lyman, J. D., James, P. A., Perets, H. B., et al. 2013, MNRAS, 434, 527, doi: 10.1093/mnras/stt1038

  45. [53]

    Tanvir, N. R. 2014, MNRAS, 444, 2157, doi: 10.1093/mnras/stu1574

  46. [54]

    D., Levan, A

    Lyman, J. D., Levan, A. J., James, P. A., et al. 2016b, MNRAS, 458, 1768, doi: 10.1093/mnras/stw477

  47. [55]

    2016, ApJ, 819, 3, doi: 10.3847/0004-637X/819/1/3

    MacLeod, M., Guillochon, J., Ramirez-Ruiz, E., Kasen, D., & Rosswog, S. 2016, ApJ, 819, 3, doi: 10.3847/0004-637X/819/1/3

  48. [56]

    2018, MNRAS, 476, 2584, doi: 10.1093/mnras/sty339

    Maoz, D., Hallakoun, N., & Badenes, C. 2018, MNRAS, 476, 2584, doi: 10.1093/mnras/sty339

  49. [57]

    Margalit, B., & Metzger, B. D. 2016, MNRAS, 461, 1154, doi: 10.1093/mnras/stw1410

  50. [58]

    2018, MNRAS, 480, 5113, doi: 10.1093/mnras/sty2206

    Marinacci, F., Vogelsberger, M., Pakmor, R., et al. 2018, MNRAS, 480, 5113, doi: 10.1093/mnras/sty2206

  51. [59]

    2015, A&A, 573, A57, doi: 10.1051/0004-6361/201424562

    Meng, X., & Han, Z. 2015, A&A, 573, A57, doi: 10.1051/0004-6361/201424562

  52. [60]

    2016, A&A, 595, A126, doi: 10.1051/0004-6361/201628765

    Mernier, F., de Plaa, J., Pinto, C., et al. 2016, A&A, 595, A126, doi: 10.1051/0004-6361/201628765

  53. [62]

    J., Raymond, J

    Milisavljevic, D., Patnaude, D. J., Raymond, J. C., et al. 2017, ApJ, 846, 50, doi: 10.3847/1538-4357/aa7d9f

  54. [63]

    M., & Badenes, C

    Moe, M., Kratter, K. M., & Badenes, C. 2019, ApJ, 875, 61, doi: 10.3847/1538-4357/ab0d88

  55. [64]

    J., Mazzali, P

    Moriya, T. J., Mazzali, P. A., Tominaga, N., et al. 2017, MNRAS, 466, 2085, doi: 10.1093/mnras/stw3225

  56. [65]

    S., Kasliwal, M

    Mulchaey, J. S., Kasliwal, M. M., & Kollmeier, J. A. 2014, ApJL, 780, L34, doi: 10.1088/2041-8205/780/2/L34

  57. [66]

    G., Power, C., & Robotham, A

    Murray, S. G., Power, C., & Robotham, A. S. G. 2013, Astronomy and Computing, 3, 23, doi: 10.1016/j.ascom.2013.11.001

  58. [67]

    P., Pillepich, A., Springel, V., et al

    Naiman, J. P., Pillepich, A., Springel, V., et al. 2018, MNRAS, 477, 1206, doi: 10.1093/mnras/sty618

  59. [68]

    Yungelson, L. R. 2001, A&A, 368, 939, doi: 10.1051/0004-6361:20010049

  60. [69]

    2018, MNRAS, 475, 624, doi: 10.1093/mnras/stx3040

    Nelson, D., Pillepich, A., Springel, V., et al. 2018, MNRAS, 475, 624, doi: 10.1093/mnras/stx3040

  61. [70]

    2019, Computational Astrophysics and Cosmology, 6, 2, doi: 10.1186/s40668-019-0028-x

    Nelson, D., Springel, V., Pillepich, A., et al. 2019, Computational Astrophysics and Cosmology, 6, 2, doi: 10.1186/s40668-019-0028-x

  62. [71]

    1982, ApJ, 257, 780, doi: 10.1086/160031

    Nomoto, K. 1982, ApJ, 257, 780, doi: 10.1086/160031

  63. [72]

    2013, ApJL, 770, L8, doi: 10.1088/2041-8205/770/1/L8

    Pakmor, R., Kromer, M., Taubenberger, S., & Springel, V. 2013, ApJL, 770, L8, doi: 10.1088/2041-8205/770/1/L8

  64. [73]

    T., Etienne, Z., & Shapiro, S

    Paschalidis, V., Liu, Y. T., Etienne, Z., & Shapiro, S. L. 2011, PhRvD, 84, 104032, doi: 10.1103/PhysRevD.84.104032

  65. [74]

    Shapiro, S. L. 2009, PhRvD, 80, 024006, doi: 10.1103/PhysRevD.80.024006 13

  66. [75]

    Perets, H. B. 2014, arXiv e-prints, arXiv:1407.2254. https://arxiv.org/abs/1407.2254

  67. [76]

    B., Gal-yam, A., Crockett, R

    Perets, H. B., Gal-yam, A., Crockett, R. M., et al. 2011, ApJL, 728, L36+, doi: 10.1088/2041-8205/728/2/L36

  68. [77]

    B., Gal-Yam, A., Mazzali, P

    Perets, H. B., Gal-Yam, A., Mazzali, P. A., et al. 2010, Nature, 465, 322, doi: 10.1038/nature09056

  69. [78]

    2018, MNRAS, 475, 648, doi: 10.1093/mnras/stx3112

    Pillepich, A., Nelson, D., Hernquist, L., et al. 2018, MNRAS, 475, 648, doi: 10.1093/mnras/stx3112

  70. [79]

    2019, ApJ, 873, 84, doi: 10.3847/1538-4357/aafb6a

    Polin, A., Nugent, P., & Kasen, D. 2019, ApJ, 873, 84, doi: 10.3847/1538-4357/aafb6a

  71. [80]

    J., Maguire, K., Fl¨ ors, A., et al

    Prentice, S. J., Maguire, K., Fl¨ ors, A., et al. 2019, A&A, submitted (arXiv:1909.05567)

  72. [81]

    2000, IAUC, 7507, 2

    Puckett, T., & Dowdle, G. 2000, IAUC, 7507, 2

  73. [82]

    L., Chatterjee, S., & Rasio, F

    Rodriguez, C. L., Chatterjee, S., & Rasio, F. A. 2016, PhRvD, 93, 084029, doi: 10.1103/PhysRevD.93.084029

  74. [83]

    Rosswog, S., Ramirez-Ruiz, E., & Hix, W. R. 2008, ApJ, 679, 1385, doi: 10.1086/528738 —. 2009, ApJ, 695, 404, doi: 10.1088/0004-637X/695/1/404

  75. [84]

    2017, ApJ, 846, 36, doi: 10.3847/1538-4357/aa7e32 S´ anchez-Janssen, R., Cˆ ot´ e, P., Ferrarese, L., et al

    Samsing, J., MacLeod, M., & Ramirez-Ruiz, E. 2017, ApJ, 846, 36, doi: 10.3847/1538-4357/aa7e32 S´ anchez-Janssen, R., Cˆ ot´ e, P., Ferrarese, L., et al. 2019, ApJ, 878, 18, doi: 10.3847/1538-4357/aaf4fd

  76. [85]

    H., Arur, K., Maccarone, T

    Sell, P. H., Arur, K., Maccarone, T. J., et al. 2018, MNRAS, 475, L111, doi: 10.1093/mnrasl/sly011

  77. [86]

    Sand, D. J. 2015, MNRAS, 450, 4198, doi: 10.1093/mnras/stv902

  78. [87]

    Shen, K. J. 2015, ApJL, 805, L6, doi: 10.1088/2041-8205/805/1/L6

  79. [88]

    J., & Bildsten, L

    Shen, K. J., & Bildsten, L. 2009, ApJ, 699, 1365, doi: 10.1088/0004-637X/699/2/1365 —. 2014, ApJ, 785, 61, doi: 10.1088/0004-637X/785/1/61

  80. [89]

    J., Kasen, D., Miles, B

    Shen, K. J., Kasen, D., Miles, B. J., & Townsley, D. M. 2018a, ApJ, 854, 52, doi: 10.3847/1538-4357/aaa8de

  81. [90]

    2010, ApJ, 715, 767, doi: 10.1088/0004-637X/715/2/767

    Scannapieco, E. 2010, ApJ, 715, 767, doi: 10.1088/0004-637X/715/2/767

  82. [91]

    J., Boubert, D., G¨ ansicke, B

    Shen, K. J., Boubert, D., G¨ ansicke, B. T., et al. 2018b, ApJ, 865, 15, doi: 10.3847/1538-4357/aad55b

  83. [92]

    Sigurdsson, S., & Phinney, E. S. 1993, ApJ, 415, 631, doi: 10.1086/173190

  84. [93]

    A., Fink, M., Kromer, M., et al

    Sim, S. A., Fink, M., Kromer, M., et al. 2012, MNRAS, 420, 3003, doi: 10.1111/j.1365-2966.2011.20162.x

  85. [94]

    1987, Dynamical evolution of globular clusters (Princeton: Princeton University Press)

    Spitzer, L. 1987, Dynamical evolution of globular clusters (Princeton: Princeton University Press)

  86. [95]

    2018, MNRAS, 475, 676, doi: 10.1093/mnras/stx3304

    Springel, V., Pakmor, R., Pillepich, A., et al. 2018, MNRAS, 475, 676, doi: 10.1093/mnras/stx3304

  87. [96]

    M., Nugent, P

    Sullivan, M., Kasliwal, M. M., Nugent, P. E., et al. 2011, ApJ, 732, 118, doi: 10.1088/0004-637X/732/2/118

  88. [97]

    2018, ApJ, 858, 26, doi: 10.3847/1538-4357/aaba79

    Tanikawa, A. 2018, ApJ, 858, 26, doi: 10.3847/1538-4357/aaba79

  89. [98]

    2017, in Handbook of Supernovae, ed

    Taubenberger, S. 2017, in Handbook of Supernovae, ed. A. W. Alsabti & P. Murdin (New York: Springer), 317, doi: 10.1007/978-3-319-21846-5 37

  90. [99]

    M., Langer, N., Moriya, T

    Tauris, T. M., Langer, N., Moriya, T. J., et al. 2013, ApJL, 778, L23, doi: 10.1088/2041-8205/778/2/L23

  91. [100]

    V., Klypin, A., et al

    Tinker, J., Kravtsov, A. V., Klypin, A., et al. 2008, ApJ, 688, 709, doi: 10.1086/591439

  92. [101]

    2016, ATel, 9685, 1

    Tonry, J., Denneau, L., Stalder, B., et al. 2016, ATel, 9685, 1

  93. [102]

    2018, A&A, 619, A53, doi: 10.1051/0004-6361/201833164

    Zenati, Y. 2018, A&A, 619, A53, doi: 10.1051/0004-6361/201833164

  94. [103]

    M., Miles, B

    Townsley, D. M., Miles, B. J., Shen, K. J., & Kasen, D. 2019, ApJL, 878, L38, doi: 10.3847/2041-8213/ab27cd

  95. [104]

    2014, MNRAS, 437, 1519, doi: 10.1093/mnras/stt1983

    Valenti, S., Yuan, F., Taubenberger, S., et al. 2014, MNRAS, 437, 1519, doi: 10.1093/mnras/stt1983

  96. [105]

    Vesperini, E., & Heggie, D. C. 1997, MNRAS, 289, 898, doi: 10.1093/mnras/289.4.898

  97. [106]

    2011, ApJ, 738, 21, doi: 10.1088/0004-637X/738/1/21

    Waldman, R., Sauer, D., Livne, E., et al. 2011, ApJ, 738, 21, doi: 10.1088/0004-637X/738/1/21

  98. [107]

    2019, MNRAS, 482, 3206, doi: 10.1093/mnras/sty2866

    Wang, Y.-H., Leigh, N., Sesana, A., & Perna, R. 2019, MNRAS, 482, 3206, doi: 10.1093/mnras/sty2866

  99. [108]

    H., & Tinker, J

    Wechsler, R. H., & Tinker, J. L. 2018, ARA&A, 56, 435, doi: 10.1146/annurev-astro-081817-051756

  100. [109]

    E., & Kasen, D

    Woosley, S. E., & Kasen, D. 2011, ApJ, 734, 38, doi: 10.1088/0004-637X/734/1/38

  101. [110]

    P., et al

    Yuan, F., Kobayashi, C., Schmidt, B. P., et al. 2013, MNRAS, 432, 1680, doi: 10.1093/mnras/stt591

  102. [111]

    Yungelson, L. R. 2008, Astronomy Letters, 34, 620, doi: 10.1134/S1063773708090053

  103. [112]

    Zenati, Y., Bobrick, A., & Perets, H. B. 2019a, MNRAS, submitted (arXiv:1908.10866)

  104. [113]

    B., & Toonen, S

    Zenati, Y., Perets, H. B., & Toonen, S. 2019b, MNRAS, 486, 1805, doi: 10.1093/mnras/stz316

Pith tools

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