Pith. sign in

REVIEW 3 major objections 7 minor 54 references

Efficacy of Galaxy Catalogues for following up gravitational wave events

T0 review · 3 major / 7 minor · reviewed 2026-08-06 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read This paper tests four telescope-pointing strategies for gravitational-wave follow-up and finds that a 3D galaxy-mass-weighted search beats plain 2D sky-map tiling for events closer than about 300–400 Mpc, while the simple 2D probability…

desk verdict Useful O4-era simulation showing galaxy-catalogue pointing helps mainly below ~300 Mpc, with a clear but acknowledged circularity in the mass-filling metric and a uniform-sky assumption that may shift the crossover. read the letter →

arxiv 2507.11635 v1 pith:A76IKDE4 submitted 2025-07-15 astro-ph.HE

Tamojeet Roychowdhury , Harsh Choudhary , Varun Bhalerao , David O. Cook , Viraj Karambelkar , Mansi M. Kasliwal , Harsh Kumar , Surhud More
show 1 more author
Gaurav Waratkar
This is my paper · ORCID
classification astro-ph.HE
keywords gravitationalwaveselectromagneticcounterpartsgalaxycataloguesfollow-upstrategiesmass-fillingO4observingrunmulti-messengerastronomykilonova
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

The paper asks whether galaxy-catalogue-targeted follow-up of gravitational-wave events is still worthwhile in the LIGO-Virgo-KAGRA O4 run, when localisation volumes contain thousands of galaxies and galaxy catalogues are incomplete beyond a few hundred megaparsecs. Using 329 simulated binary-neutron-star and neutron-star–black-hole events, the authors compare four tile-ranking strategies for small-field telescopes. They find that ranking by 2D sky-map probability alone covers more of the mass-weighted source probability than a 3D galaxy-mass ranking for events beyond about 300 Mpc, while the galaxy-based ranking wins for nearer events. Filling in the unobserved galaxy mass uniformly raises the measured coverage by a few percent and transitions smoothly between the two methods. The practical output is a distance-based recommendation: point at galaxies for nearby events, and fall back to plain sky-map tiling for distant ones.

What carries the argument

The machinery is a set of tile-ranking weights applied to a fixed healpix grid and evaluated over the top 100 tiles. $S_{2DP}$ ranks by the marginalised 2D GW probability; $S_M$ ranks by the sum of galaxy stellar masses in each tile; $S_{3DPM}$ multiplies each galaxy's mass by the 3D GW probability at its position; and $S_{3DMF}$ replaces galaxy mass with a corrected mass that adds uniformly distributed missing mass per 20 Mpc shell, so each empty voxel carries the mean missing mass of its shell. The evaluation metric is itself the total $p_{3D}\times\hat{m}$ covered by the top tiles, which makes the mass-filling model the ground truth that every strategy is measured against.

What would settle it

Run the same simulated follow-up using a realistic mock galaxy catalogue built from a large-scale structure simulation, with galaxies placed along filaments and voids, as the ground truth, and recompute the per-strategy coverage; if the mass-filling strategy's advantage shrinks or the crossover distance moves, the uniform-filling assumption is the cause.

Watch

Extended reading notes

Core claim

The central discovery is a crossover in follow-up strategy driven by catalogue completeness, not by telescope field of view. For events with median distance below about 300 Mpc, weighting telescope tiles by the 3D gravitational-wave probability times galaxy mass ($S_{3DPM}$) gives higher $p_{3D}\times\hat{m}$ coverage than tiling by the marginalised 2D probability ($S_{2DP}$). Beyond 300–400 Mpc, where the NED-LVS galaxy catalogue is only about 70 percent complete, the plain 2D probability search outperforms the galaxy-based search by a few percent. A mass-filling scheme ($S_{3DMF}$) that distributes the missing galaxy mass uniformly within 20 Mpc shells achieves the highest coverage of all, a few percent above the best conventional method, and approaches the 2D-probability map at large distances where most mass is uncatalogued. A mass-only ranking ($S_M$) performs poorly except for nearby, well-localised events. The same qualitative trends hold for a wider-field telescope, with all ratios closer to unity.

Load-bearing premise

Coverage is measured against the paper's own mass-filling model, which assumes the missing galaxy mass is spread uniformly across the sky within every 20 Mpc shell; if missing galaxies are actually clustered, the ranking of the strategies—and the 300–400 Mpc crossover—could change.

Editorial extensions

If this is right

  • For O4-era follow-up with small-field telescopes, observers should use galaxy catalogues for events with median distance below about 300 Mpc and plain 2D sky-map tiling beyond that.
  • Mass-filling the catalogue recovers a few percent more probability coverage than either conventional method, making it a low-cost improvement worth including in scheduling.
  • The crossover distance is set by catalogue completeness, so as deeper catalogues become available the galaxy-based strategies will remain competitive at larger distances.
  • Galaxy catalogues remain essential for vetting candidate transients found in tiled surveys, even when the tiling itself does not use them.

Reading between the lines

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

  • If the missing mass is in reality clustered along filaments, a direction-dependent mass-filling scheme would likely make galaxy-based strategies perform better at larger distances than the uniform-filling assumption suggests, and the 300 Mpc crossover would shift.
  • The same methodology could be applied to future observing runs, where poorer localisation and larger distances will push more events into the regime where the 2D probability search is preferred.
  • Comparing strategies against a realistic large-scale structure mock catalogue would provide an independent ground truth that avoids evaluating each method with its own assumption.
  • The most massive galaxies are nearly 100 percent complete to about 450 Mpc, so a mass-weighted catalogue search may remain effective for the hosts most likely to harbour mergers even when total catalogue completeness is modest.
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 / 7 minor

Summary. This paper evaluates galaxy-catalogue-based optical follow-up strategies for gravitational-wave events in the O4 era, using the NED-LVS catalogue, 329 simulated BNS/NSBH events from Kiendrebeogo et al., and realistic tile grids for GIT and WINTER. Four ranking schemes are compared (2D probability tiling S_2DP, mass-only S_M, 3D probability times catalogued mass S_3DPM, and 3D probability times completeness-corrected mass S_3DMF), and performance is scored by the summed p_3D times margin over the top 100 tiles. The main empirical claims are that S_3DPM outperforms S_2DP for events within roughly 300-400 Mpc, that S_2DP is better beyond that, and that S_3DMF yields a few percent higher coverage than both. The paper recommends using galaxy catalogues for nearby events and 2D tiling for distant ones, and emphasizes the role of galaxy catalogues in candidate vetting.

Significance. If the central comparison were robust, this would be a practically useful result for planning electromagnetic follow-up in O4/O5, and the paper's use of a realistic public catalogue and telescope-specific tiling is a strength. The authors are transparent in stating the mass-filling assumption and the guaranteed superiority of S_3DMF. The main limitation is that the crossover distance between S_3DPM and S_2DP is evaluated against a ground-truth model that assumes missing mass is uniformly distributed on the sky; because the real missing mass is likely clustered, the headline number is not yet established. The paper also does not quantify the statistical uncertainty of the crossover. With a sensitivity analysis, the work could be a solid contribution.

major comments (3)
  1. [§4.4 and §5] The evaluation metric for all strategies is p_3D times margin, where margin is constructed by spreading the completeness-corrected missing mass uniformly over each 20 Mpc shell. Since the missing mass carries no directional information in this model, the comparison S_3DPM vs S_2DP at large distances is effectively a test of how much information the incomplete catalogue adds relative to the isotropic fill; the conclusion that S_2DP overtakes S_3DPM beyond roughly 300-400 Mpc is therefore a direct consequence of this assumption. In reality, uncatalogued galaxies trace the same large-scale structure as catalogued ones, so an incomplete catalogue still contains directional information about the missing mass; under a clustered missing-mass model, the crossover could shift to larger distances or disappear. The authors acknowledge the assumption in §4.4 and defer direction-dependent modelling to future work, but the central claim should be tested with an alternative missing-mass distribution (e.g., assigning missing mass in proportion to the angular density of catalogued galaxies, or using a lognormal mock) before the crossover is stated as a robust recommendation.
  2. [§5 and Tables 2–3] Because S_3DMF's ranking weight is exactly the figure of merit p_3D times margin used to score every strategy, the statement in §5 that 'S_3DMF will always give the highest probability coverage' is a mathematical identity. The paper explicitly acknowledges this, but the abstract and discussion still present the few-percent advantage of S_3DMF as a substantive result. For example, Table 2's median coverage of 0.530 for S_3DMF versus 0.504 for S_3DPM is guaranteed by construction. I recommend reframing S_3DMF as the upper envelope of the mass-filling model rather than an independently validated strategy, and making clear that the only non-circular comparison in the paper is S_3DPM versus S_2DP (which is nevertheless scored against the same assumed margin model).
  3. [§5.2 and Figure 4] The crossover distance of roughly 300-400 Mpc is inferred from bin-wise medians of R = p(S_3DPM)/p(S_2DP) and from the colours of scattered points, but no uncertainty or significance level is attached to this number. The sample has 329 events with wide scatter (the violin plots show substantial spread in every distance bin), so the crossover is not well constrained. A confidence interval on the crossover, or a distance-dependent fraction of events in which S_3DPM wins, would make the headline claim in the abstract and §6 quantifiable and would also help assess whether the difference between S_3DPM and S_2DP is practically meaningful given the few-percent size of the effect.
minor comments (7)
  1. [Table 1 and §5] The text says 'five methods' (e.g., §5, first paragraph) and Table 1 claims 'five follow-up schemes', but only four schemes (S_2DP, S_M, S_3DPM, S_3DMF) are defined in §4 and listed in the table. Please correct the count.
  2. [§4.4] In the mass-filling prescription, the mass of a voxel is set to the catalogued galaxy mass if the voxel is occupied, and to the mean missing mass if empty; the mean missing mass is computed per shell. This means the total filled mass is not equal to the completeness-corrected total mass, because occupied voxels do not receive their share of the unobserved mass. The authors should clarify whether this is intentional and quantify the effect on the normalisation and ranking.
  3. [§3.3] The statement that the results are 'not highly sensitive' to the 3600 deg^2 99%-area cutoff is not supported by any figure or table. A supplementary test with a different cutoff (e.g., 2000 and 5000 deg^2) would be helpful.
  4. [Figure 2 caption] The caption uses the notation S_3DMF before it has been introduced in the text (the inset captions refer to S_3DPM and S_3DMF); consider either defining the abbreviations in the caption or reordering the caption.
  5. [§2] There is a typo in the first paragraph of §2: 'the catalogue should be as as complete as possible' should read 'as complete as possible'.
  6. [Table 3] In Table 3, the number '0,892' in the S_2DP column for d_GW<302 Mpc uses a comma as the decimal separator, inconsistent with the rest of the table (which uses periods).
  7. [§4.1] The sentence 'This method (hereafter S_2DP), which completely ignores galaxy catalogue information.' is missing a main verb; consider removing the comma and the period, e.g., 'This method (hereafter S_2DP) completely ignores galaxy catalogue information.'

Circularity Check

1 steps flagged · score 6.0 of 10

The S_3DMF 'gain' is a tautology: the coverage metric is p×\hat m and S_3DMF is defined by ranking with p×\hat m, so its few-percent advantage is guaranteed by construction.

  1. self definitional [Section 5 ('Comparing with baseline observing strategies'), page 8; also Section 4.4 and Figure 5 caption]
    "Among our five methods, the “mass filled” mock catalogue (§4.4) is the closest to such an ideal catalogue, and we assume that it represents the true mass distribution in the local universe. ... A consequence of this choice is that S_3DMF will always give the highest probability coverage in this work."

    The evaluation metric for every strategy is p_3D × \hat m, where \hat m is the mass-filled 'corrected mass' constructed in §4.4 by spreading missing galaxy mass uniformly over each 20 Mpc shell. S_3DMF is defined by ranking tiles according to exactly this p_3D × \hat m product. Measuring coverage by summing the same weight over a greedy top-100 selection guarantees that S_3DMF scores highest; its few-percent advantage over S_2DP and S_3DPM is therefore a consequence of the metric choice, not an empirical result. The paper labels this a 'consequence of this choice' but still presents the mass-filling gain as a finding in the abstract and conclusion ('accounting for the catalogue incompleteness by spreading out the “missing mass” gives non–trivial gains'), which is the circular step.

full rationale

The paper contains one clear by-construction result: the superiority of S_3DMF is forced because the same quantity p×\hat m both defines the strategy's ranking and serves as the coverage figure of merit for all strategies. This is openly acknowledged in §5 ('A consequence of this choice is that S_3DMF will always give the highest probability coverage in this work') and in the Figure 5 caption ('By definition, S_3DMF performs better than S_2DP'). That tautology inflates the apparent benefit of mass-filling and reduces the central 'non-trivial gains' claim to a definition. The other headline comparison, S_3DPM versus S_2DP with a crossover at ~300–400 Mpc, is not circular in the same sense: it compares two concrete ranking schemes under a fixed—if assumed—truth model. However, that truth model itself is the paper's uniform missing-mass assumption, stated in §4.4 ('we assume the missing galaxy mass to be uniform all over the sky. A future work could address the case where we take the missing mass distribution to be direction–dependent'). The crossover distance is therefore contingent on an isotropy assumption about uncatalogued galaxies, and would likely shift if the missing mass traces large-scale structure. This is a significant modeling limitation, but it is not a hidden input or a fitted-parameter-as-prediction; it is an explicit assumption, so I do not count it as an additional circular step. The other parts of the paper—catalogue selection, simulated O4 events from external simulations, and telescope tiling—are externally grounded. Overall, one central result reduces by construction, warranting a score of 6 rather than a higher score, because the main practical recommendation about S_2DP versus S_3DPM retains independent content under the stated model.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

The analysis rests on a small set of explicit modeling choices: a linear mass prior, uniform sky filling of missing mass, and the use of the mass-filled model as ground truth. None are fitted to data in this paper; they are adopted from the literature or chosen for simplicity.

free parameters (4)
  • 99% localization area cutoff = 3600 deg^2
    Events with 99% area above this are excluded from the sample; the paper states results are not highly sensitive to this cutoff.
  • Max tiles observed per night = 100
    Assumed observing schedule length for both telescopes; cross-checks with 50 and 250 tiles show trends persist.
  • Distance shell width for mass filling = 20 Mpc
    Concentric shells used to compute missing mass; choice affects smoothness of the filling.
  • Distance cut for mass-only scheme = median +/- 3 sigma
    Applied to S_M only; the paper notes coverage worsens without the cut.
assumptions (6)
  • domain assumption Merger rate of BNS/NSBH traces galaxy stellar mass linearly (P(M*) proportional to M*).
    Used to weight galaxies in S_M, S_3DPM, S_3DMF. Supported by simulations cited in Section 1 (Mapelli et al. 2018, Artale et al. 2019, 2020).
  • ad hoc to paper Missing galaxy mass is distributed uniformly over the sky within each 20 Mpc shell.
    Core of the mass-filling scheme in Section 4.4. The paper states 'we assume the missing galaxy mass to be uniform all over the sky' and notes a direction-dependent distribution as future work.
  • ad hoc to paper The mass-filled catalogue represents the true mass distribution of the local universe.
    Used as the ground truth metric for evaluating all strategies in Section 5. This makes S_3DMF outperform by construction.
  • domain assumption P(I|G) is independent of G, and P(alpha, delta, z) is independent of P(M*).
    Separates the galaxy mass prior from the GW localisation probability in Appendix A; explicitly stated as assumptions in the derivation.
  • domain assumption The Kiendrebeogo et al. (2023) simulated O4 event set accurately represents real O4 events.
    The 329-event sample is the basis for all follow-up simulations (Section 3.3).
  • domain assumption GW injections are random in space and this does not affect results because localisation volumes contain many galaxies.
    Stated in Section 3.3 without quantitative demonstration.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Efficacy of Galaxy Catalogues for following up gravitational wave events." pith.science (2026). https://pith.science/paper/A76IKDE4

@misc{pith2026250711635,
  author       = {Pith},
  title        = {Pith review of: Efficacy of Galaxy Catalogues for following up gravitational wave events},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/A76IKDE4}},
  note         = {Machine review of arXiv:2507.11635}
}
read the original abstract

The detection of gravitational waves (GW) by the LIGO-Virgo-KAGRA (LVK) network has opened up a new era in astrophysics. The identification of the electromagnetic counterparts of GW sources is crucial for multi-messenger astronomy, one way of which is to use galaxy catalogues to guide optical follow-up observations. In this paper, we test the utility of galaxy-targeted approach with mass prioritised galaxy ranking for the ongoing LIGO O4 run. We have used the simulated results for the expected LIGO O4 events and the NED-LVS galaxy catalogue and based our study for small field of view telescopes, specifically the GROWTH-India Telescope (GIT). With the increase in sensitivity of LIGO/Virgo in the ongoing observing run O4, the expected number of total detections have gone up but most of these are also now poorly localised. We show that a larger volume covered in the same field-of-view (FoV) on the sky results in a large increase in the total number of galaxies in each FoV. A significant top-heaviness is observed in the mass-ranked list of galaxies, which still number to a few thousand in most cases. At larger distances, such high numbers of deep follow-up observations are infeasible in most cases rendering galaxy catalogues useful in limited cases, but these are still useful at lower distances where LVK detectors are currently sensitive and where galaxy completeness is higher. We also explore the effect of mass-filling to account for galaxy catalogue incompleteness at large distances. If mass-filled probabilities are considered as the metric for ranking and coverage, we find that the conventional 2D probability search performs better than a 3D galaxy catalogue (without mass-filling) based search at distances larger than 300 Mpc (upto which NED-LVS is ~70% complete), and using 3D mass times probability in each tile performs better for nearby events.

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

54 extracted references · 52 canonical work pages

  1. [1]

    P., Abbott, R., Abbott, T

    Abbott, B. P., Abbott, R., Abbott, T. D.,et al. 2020, Living Reviews in Relativity, 23, 3

    work page 2020

  2. [2]

    2015, Classical and Quantum Gravity, 32, 024001

    Acernese, F., Agathos, M., Agatsuma, K.,et al. 2015, Classical and Quantum Gravity, 32, 024001

    work page 2015

  3. [3]

    W.,et al

    Ahumada, T., Anand, S., Coughlin, M. W.,et al. 2024, arXiv e-prints, arXiv:2405.12403

    arXiv 2024

  4. [4]

    2018, Phys

    Annala, E., Gorda, T., Kurkela, A., & Vuorinen, A. 2018, Phys. Rev. Lett., 120, 172703

    2018

  5. [5]

    2020, MN- RAS, 497, 5518

    Antier, S., Agayeva, S., Almualla, M.,et al. 2020, MN- RAS, 497, 5518

    work page 2020

  6. [6]

    C., Mapelli, M., Bouffanais, Y .,et al

    Artale, M. C., Mapelli, M., Bouffanais, Y .,et al. 2020, Monthly Notices of the Royal Astronomical Society, 491, 3419

    work page 2020

  7. [7]

    C., Mapelli, M., Giacobbo, N.,et al

    Artale, M. C., Mapelli, M., Giacobbo, N.,et al. 2019, Monthly Notices of the Royal Astronomical Society, 487, 1675

    work page 2019

  8. [8]

    2013, Phys- ical Review D, 88, 043007

    Aso, Y ., Michimura, Y ., Somiya, K.,et al. 2013, Phys- ical Review D, 88, 043007

    work page 2013

Show all 54 references
  1. [9]

    C., Kulkarni, S

    Bellm, E. C., Kulkarni, S. R., Barlow, T.,et al. 2019, PASP, 131, 068003

    2019

  2. [10]

    2014, Annual Review of Astronomy and As- trophysics, 52, 43

    Berger, E. 2014, Annual Review of Astronomy and As- trophysics, 52, 43

    2014

  3. [11]

    O., Kasliwal, M

    Cook, D. O., Kasliwal, M. M., Van Sistine, A.,et al. 2019, The Astrophysical Journal, 880, 7

    2019

  4. [12]

    O., Mazzarella, J

    Cook, D. O., Mazzarella, J. M., Helou, G.,et al. 2023, The Astrophysical Journal Supplement Series, 268, 14

    2023

  5. [13]

    W., Antier, S., Corre, D.,et al

    Coughlin, M. W., Antier, S., Corre, D.,et al. 2019, Monthly Notices of the Royal Astronomical Society, 489, 5775–5783

    2019

  6. [14]

    A., Foley, R

    Coulter, D. A., Foley, R. J., Kilpatrick, C. D.,et al. 2017, Science, 358, 1556 Dálya, G., Galgóczi, G., Dobos, L.,et al. 2018, Monthly Notices of the Royal Astronomical Society, 479, 2374 Dálya, G., Díaz, R., Bouchet, F. R.,et al. 2022, Monthly Notices of the Royal Astronomic...

    2017

  7. [15]

    2020, Monthly Notices of the Royal Astronomical Society, 492, 4768

    Ducoin, J.-G., Corre, D., Leroy, N., & Le Floch, E. 2020, Monthly Notices of the Royal Astronomical Society, 492, 4768

    2020

  8. [16]

    2021, Journal of Cosmology and As- troparticle Physics, 2021, 026

    Mancarella, M. 2021, Journal of Cosmology and As- troparticle Physics, 2021, 026

    2021

  9. [17]

    2024, ApJ, 964, 149

    Fletcher, C., Wood, J., Hamburg, R.,et al. 2024, ApJ, 964, 149

    2024

  10. [18]

    E., Dong, Y .,et al

    Fong, W.-f., Nugent, A. E., Dong, Y .,et al. 2022, The Astrophysical Journal, 940, 56

    2022

  11. [19]

    2022, The Astrophysical Journal, 926, 152

    Frostig, D., Biscoveanu, S., Mo, G.,et al. 2022, The Astrophysical Journal, 926, 152

    2022

  12. [20]

    K., Kanner, J.,et al

    Gehrels, N., Cannizzo, J. K., Kanner, J.,et al. 2016, The Astrophysical Journal, 820, 136

    2016

  13. [21]

    M., Hivon, E., Banday, A

    Gorski, K. M., Hivon, E., Banday, A. J.,et al. 2005, The Astrophysical Journal, 622, 759–771

    2005

  14. [22]

    J., McKernan, B., Ford, K

    Graham, M. J., McKernan, B., Ford, K. E. S.,et al. 2023, ApJ, 942, 99

    2023

  15. [23]

    2014, The As- trophysical Journal, 784, 8

    Hanna, C., Mandel, I., & V ousden, W. 2014, The As- trophysical Journal, 784, 8

    2014

  16. [24]

    2012, The Astrophysical Journal, 759, 22

    Kanner, J., Camp, J., Racusin, J., Gehrels, N., & White, D. 2012, The Astrophysical Journal, 759, 22

    2012

  17. [25]

    2017, Nature, 551, 80 Page 14 of 13J

    Ramirez-Ruiz, E. 2017, Nature, 551, 80 Page 14 of 13J. Astrophys. Astr .(0000)000:

    2017

  18. [26]

    2017, Sci- ence, 358, 1559

    Kasliwal, M., Nakar, E., Singer, L.,et al. 2017, Sci- ence, 358, 1559

    2017

  19. [27]

    Kasliwal, M. M. 2011, PhD thesis, California Institute of Technology

    2011

  20. [28]

    M., & Nissanke, S

    Kasliwal, M. M., & Nissanke, S. 2014, The Astrophys- ical Journall, 789, L5

    2014

  21. [29]

    M., Anand, S., Ahumada, T.,et al

    Kasliwal, M. M., Anand, S., Ahumada, T.,et al. 2020, ApJ, 905, 145

    2020

  22. [30]

    W., Farah, A

    Kiendrebeogo, R. W., Farah, A. M., Foley, E. M.,et al. 2023, The Astrophysical Journal, 958, 158

    2023

  23. [31]

    K., Hanna, C., Kalogera, V .,et al

    Kopparapu, R. K., Hanna, C., Kalogera, V .,et al. 2008, The Astrophysical Journal, 675, 1459

    2008

  24. [32]

    J.,et al

    Kovlakas, K., Zezas, A., Andrews, J. J.,et al. 2021, Monthly Notices of the Royal Astronomical Society, 506, 1896

    2021

  25. [33]

    C.,et al

    Kumar, H., Bhalerao, V ., Anupama, G. C.,et al. 2022, MNRAS, 516, 4517

    2022

  26. [34]

    C.,et al

    Kumar, H., Bhalerao, V ., Anupama, G. C.,et al. 2022, The Astronomical Journal, 164, 90

    2022

  27. [35]

    Lampoudi, S., Saunders, E., & Eastman, J. 2015, in Proceedings of the International Conference on Op- erations Research and Enterprise Systems - V olume 1: ICORES„ INSTICC (SciTePress), 331–337 LIGO Scientific Collaboration, Aasi, J., Abbott, B. P., et al. 2015, Classical and ...

    2015

  28. [36]

    2018, Monthly Notices of the Royal Astronomical Society

    Mapelli, M., Giacobbo, N., Toffano, M.,et al. 2018, Monthly Notices of the Royal Astronomical Society

    2018

  29. [37]

    Margalit, B., & Metzger, B. D. 2017, ApJ, 850, L19

    2017

  30. [38]

    M., Tollerud, E., Sip˝ocz, B.,et al

    Morris, B. M., Tollerud, E., Sip˝ocz, B.,et al. 2018, The Astronomical Journal, 155, 128

    2018

  31. [39]

    2025, Philosophical Trans- actions of the Royal Society of London Series A, 383, 20240126

    Nicholl, M., & Andreoni, I. 2025, Philosophical Trans- actions of the Royal Society of London Series A, 383, 20240126

    2025

  32. [40]

    2013, The Astrophysical Journal, 767, 124

    Nissanke, S., Kasliwal, M., & Georgieva, A. 2013, The Astrophysical Journal, 767, 124

    2013

  33. [41]

    E., Fong, W.-F., Dong, Y .,et al

    Nugent, A. E., Fong, W.-F., Dong, Y .,et al. 2022, ApJ, 940, 57

    2022

  34. [42]

    J., Rastinejad, J

    Paterson, K., Lundquist, M. J., Rastinejad, J. C.,et al. 2021, ApJ, 912, 128

    2021

  35. [43]

    2017, Nature, 551, 67

    Pian, E., D’Avanzo, P., Benetti, S.,et al. 2017, Nature, 551, 67

    2017

  36. [44]

    2025, ApJ, 980, 207

    Raman, G., Ronchini, S., Delaunay, J.,et al. 2025, ApJ, 980, 207

    2025

  37. [45]

    2017, The Astrophysical Journal, 838, 108

    Rana, J., Singhal, A., Gadre, B., Bhalerao, V ., & Bose, S. 2017, The Astrophysical Journal, 838, 108

    2017

  38. [46]

    2017, ApJ, 848, L15

    Savchenko, V ., Ferrigno, C., Kuulkers, E.,et al. 2017, ApJ, 848, L15

    2017

  39. [47]

    P., Chen, H.-Y ., Holz, D

    Singer, L. P., Chen, H.-Y ., Holz, D. E.,et al. 2016, ApJS, 226, 10

    2016

  40. [48]

    P., Criswell, A

    Singer, L. P., Criswell, A. W., Leggio, S. C.,et al. 2025, arXiv e-prints, arXiv:2502.17560

    2025 arXiv

  41. [49]

    2016, Astronomy and Computing, 15, 90

    Solar, M., Michelon, P., Avarias, J., & Garces, M. 2016, Astronomy and Computing, 15, 90

    2016

  42. [50]

    2017, Astrophysical Journal, 838, 46

    Bose, S. 2017, Astrophysical Journal, 838, 46

    2017

  43. [51]

    2017, Nature, 551, 71

    Troja, E., Piro, L., van Eerten, H.,et al. 2017, Nature, 551, 71

    2017

  44. [52]

    2022, ApJ, 924, 80

    Ursi, A., Verrecchia, F., Piano, G.,et al. 2022, ApJ, 924, 80

    2022

  45. [53]

    2024, ApJ, 976, 123

    Waratkar, G., Bhalerao, V ., & Bhattacharya, D. 2024, ApJ, 976, 123

    2024

  46. [54]

    J., Daw, E

    White, D. J., Daw, E. J., & Dhillon, V . S. 2011, Classi- cal and Quantum Gravity, 28, 085016 APPENDIX A: Mathematical Formulation for Probability-Mass Consider a GW event was detected by a detector with strain data{x(t)}. We have a catalogue of galaxies that are potential hos...

    2011

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.