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arxiv: 1304.0670 · v11 · submitted 2013-04-02 · 🌀 gr-qc · astro-ph.HE

Recognition: 2 theorem links

· Lean Theorem

Prospects for Observing and Localizing Gravitational-Wave Transients with Advanced LIGO, Advanced Virgo and KAGRA

The LIGO Scientific Collaboration , the Virgo Collaboration , the KAGRA Collaboration: B. P. Abbott , R. Abbott , T. D. Abbott , S. Abraham , F. Acernese , K. Ackley
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C. Adams V. B. Adya C. Affeldt M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith T. Akutsu G. Allen A. Allocca M. A. Aloy P. A. Altin A. Amato A. Ananyeva S. B. Anderson W. G. Anderson M. Ando S. V. Angelova S. Antier S. Appert K. Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Ar\`ene N. Aritomi N. Arnaud K. G. Arun S. Ascenzi G. Ashton Y. Aso S. M. Aston P. Astone F. Aubin P. Aufmuth K. AultONeal C. Austin V. Avendano A. Avila-Alvarez S. Babak P. Bacon F. Badaracco M. K. M. Bader S. W. Bae Y. B. Bae L. Baiotti R. Bajpai P. T. Baker F. Baldaccini G. Ballardin S. W. Ballmer S. Banagiri J. C. Barayoga S. E. Barclay B. C. Barish D. Barker K. Barkett S. Barnum F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley M. Bazzan B. B\'ecsy M. Bejger I. Belahcene A. S. Bell D. Beniwal B. K. Berger G. Bergmann S. Bernuzzi J. J. Bero C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser R. Bhandare J. Bidler I. A. Bilenko S. A. Bilgili G. Billingsley J. Birch R. Birney O. Birnholtz S. Biscans S. Biscoveanu A. Bisht M. Bitossi M. A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair S. Bloemen N. Bode M. Boer Y. Boetzel G. Bogaert F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom C. D. Booth R. Bork V. Boschi S. Bose K. Bossie V. Bossilkov J. Bosveld Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley M. Branchesi J. E. Brau T. Briant J. H. Briggs F. Brighenti A. Brillet M. Brinkmann V. Brisson P. Brockill A. F. Brooks D. A. Brown D. D. Brown S. Brunett A. Buikema T. Bulik H. J. Bulten A. Buonanno D. Buskulic C. Buy R. L. Byer M. Cabero L. Cadonati G. Cagnoli C. Cahillane J. Calder\'on Bustillo T. A. Callister E. Calloni J. B. Camp W. A. Campbell M. Canepa K. Cannon K. C. Cannon H. Cao J. Cao E. Capocasa F. Carbognani S. Caride M. F. Carney G. Carullo J. Casanueva Diaz C. Casentini S. Caudill M. Cavagli\`a F. Cavalier R. Cavalieri G. Cella P. Cerd\'a-Dur\'an G. Cerretani E. Cesarini O. Chaibi K. Chakravarti S. J. Chamberlin M. Chan M. L. Chan S. Chao P. Charlton E. A. Chase E. Chassande-Mottin D. Chatterjee M. Chaturvedi K. Chatziioannou B. D. Cheeseboro C. S. Chen H. Y. Chen K. H. Chen X. Chen Y. Chen Y. R. Chen H.-P. Cheng C. K. Cheong H. Y. Chia A. Chincarini A. Chiummo G. Cho H. S. Cho M. Cho N. Christensen H. Y. Chu Q. Chu Y. K. Chu S. Chua K. W. Chung S. Chung G. Ciani A. A. Ciobanu R. Ciolfi F. Cipriano A. Cirone F. Clara J. A. Clark P. Clearwater F. Cleva C. Cocchieri E. Coccia P.-F. Cohadon D. Cohen R. Colgan M. Colleoni C. G. Collette C. Collins L. R. Cominsky M. Constancio Jr. L. Conti S. J. Cooper P. Corban T. R. Corbitt I. Cordero-Carri\'on K. R. Corley N. Cornish A. Corsi S. Cortese C. A. Costa R. Cotesta M. W. Coughlin S. B. Coughlin J.-P. Coulon S. T. Countryman P. Couvares P. B. Covas E. E. Cowan D. M. Coward M. J. Cowart D. C. Coyne R. Coyne J. D. E. Creighton T. D. Creighton J. Cripe M. Croquette S. G. Crowder T. J. Cullen A. Cumming L. Cunningham E. Cuoco T. Dal Canton G. D\'alya S. L. Danilishin S. D'Antonio K. Danzmann A. Dasgupta C. F. Da Silva Costa L. E. H. Datrier V. Dattilo I. Dave M. Davier D. Davis E. J. Daw D. DeBra M. Deenadayalan J. Degallaix M. De Laurentis S. Del\'eglise W. Del Pozzo L. M. DeMarchi N. Demos T. Dent R. De Pietri J. Derby R. De Rosa C. De Rossi R. DeSalvo O. de Varona S. Dhurandhar M. C. D\'iaz T. Dietrich L. Di Fiore M. Di Giovanni T. Di Girolamo A. Di Lieto B. Ding S. Di Pace I. Di Palma F. Di Renzo A. Dmitriev Z. Doctor K. Doi F. Donovan K. L. Dooley S. Doravari I. Dorrington T. P. Downes M. Drago J. C. Driggers Z. Du J.-G. Ducoin P. Dupej S. E. Dwyer P. J. Easter T. B. Edo M. C. Edwards A. Effler S. Eguchi P. Ehrens J. Eichholz S. S. Eikenberry M. Eisenmann R. A. Eisenstein Y. Enomoto R. C. Essick H. Estelles D. Estevez Z. B. Etienne T. Etzel M. Evans T. M. Evans V. Fafone H. Fair S. Fairhurst X. Fan S. Farinon B. Farr W. M. Farr E. J. Fauchon-Jones M. Favata M. Fays M. Fazio C. Fee J. Feicht M. M. Fejer F. Feng A. Fernandez-Galiana I. Ferrante E. C. Ferreira T. A. Ferreira F. Ferrini F. Fidecaro I. Fiori D. Fiorucci M. Fishbach R. P. Fisher J. M. Fishner M. Fitz-Axen R. Flaminio M. Fletcher E. Flynn H. Fong J. A. Font P. W. F. Forsyth J.-D. Fournier S. Frasca F. Frasconi Z. Frei A. Freise R. Frey V. Frey P. Fritschel V. V. Frolov Y. Fujii M. Fukunaga M. Fukushima P. Fulda M. Fyffe H. A. Gabbard B. U. Gadre S. M. Gaebel J. R. Gair L. Gammaitoni M. R. Ganija S. G. Gaonkar A. Garcia C. Garc\'ia-Quir\'os F. Garufi B. Gateley S. Gaudio G. Gaur V. Gayathri G. G. Ge G. Gemme E. Genin A. Gennai D. George J. George L. Gergely V. Germain S. Ghonge Abhirup Ghosh Archisman Ghosh S. Ghosh B. Giacomazzo J. A. Giaime K. D. Giardina A. Giazotto K. Gill G. Giordano L. Glover P. Godwin E. Goetz R. Goetz B. Goncharov G. Gonz\'alez J. M. Gonzalez Castro A. Gopakumar M. L. Gorodetsky S. E. Gossan M. Gosselin R. Gouaty A. Grado C. 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W. Luo R. Lynch Y. Ma R. Macas S. Macfoy M. MacInnis D. M. Macleod A. Macquet F. Maga\~na-Sandoval L. Maga\~na Zertuche R. M. Magee E. Majorana I. Maksimovic A. Malik N. Man V. Mandic V. Mangano G. L. Mansell M. Manske M. Mantovani F. Marchesoni M. Marchio F. Marion S. M\'arka Z. M\'arka C. Markakis A. S. Markosyan A. Markowitz E. Maros A. Marquina S. Marsat F. Martelli I. W. Martin R. M. Martin D. V. Martynov K. Mason E. Massera A. Masserot T. J. Massinger M. Masso-Reid S. Mastrogiovanni A. Matas F. Matichard L. Matone N. Mavalvala N. Mazumder J. J. McCann R. McCarthy D. E. McClelland S. McCormick L. McCuller S. C. McGuire J. McIver D. J. McManus T. McRae S. T. McWilliams D. Meacher G. D. Meadors M. Mehmet A. K. Mehta J. Meidam A. Melatos G. Mendell R. A. Mercer L. Mereni E. L. Merilh M. Merzougui S. Meshkov C. Messenger C. Messick R. Metzdorff P. M. Meyers H. Miao C. Michel Y. Michimura H. Middleton E. E. Mikhailov L. Milano A. L. Miller A. Miller M. Millhouse J. C. Mills M. C. 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Sekiguchi Y. Sekiguchi D. Sellers A. S. Sengupta N. Sennett D. Sentenac V. Sequino A. Sergeev Y. Setyawati D. A. Shaddock T. Shaffer M. S. Shahriar M. B. Shaner L. Shao P. Sharma P. Shawhan H. Shen S. Shibagaki R. Shimizu T. Shimoda K. Shimode R. Shink H. Shinkai T. Shishido A. Shoda D. H. Shoemaker D. M. Shoemaker S. ShyamSundar K. Siellez M. Sieniawska D. Sigg A. D. Silva L. P. Singer N. Singh A. Singhal A. M. Sintes S. Sitmukhambetov V. Skliris B. J. J. Slagmolen T. J. Slaven-Blair J. R. Smith R. J. E. Smith S. Somala K. Somiya E. J. Son B. Sorazu F. Sorrentino H. Sotani T. Souradeep E. Sowell A. P. Spencer A. K. Srivastava V. Srivastava K. Staats C. Stachie M. Standke D. A. Steer M. Steinke J. Steinlechner S. Steinlechner D. Steinmeyer S. P. Stevenson D. Stocks R. Stone D. J. Stops K. A. Strain G. Stratta S. E. Strigin A. Strunk R. Sturani A. L. Stuver V. Sudhir R. Sugimoto T. Z. Summerscales L. Sun S. Sunil J. Suresh P. J. Sutton Takamasa Suzuki Toshikazu Suzuki B. L. Swinkels M. 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V. van Heijningen M. H. P. M. van Putten A. A. van Veggel M. Vardaro V. Varma S. Vass M. Vas\'uth A. Vecchio G. Vedovato J. Veitch P. J. Veitch K. Venkateswara G. Venugopalan D. Verkindt F. Vetrano A. Vicer\'e A. D. Viets D. J. Vine J.-Y. Vinet S. Vitale Francisco Hernandez Vivanco T. Vo H. Vocca C. Vorvick S. P. Vyatchanin A. R. Wade L. E. Wade M. Wade R. Walet M. Walker L. Wallace S. Walsh G. Wang H. Wang J. Wang J. Z. Wang W. H. Wang Y. F. Wang R. L. Ward Z. A. Warden J. Warner M. Was J. Watchi B. Weaver L.-W. Wei M. Weinert A. J. Weinstein R. Weiss F. Wellmann L. Wen E. K. Wessel P. We{\ss}els J. W. Westhouse K. Wette J. T. Whelan B. F. Whiting C. Whittle D. M. Wilken D. Williams A. R. Williamson J. L. Willis B. Willke M. H. Wimmer W. Winkler C. C. Wipf H. Wittel G. Woan J. Woehler J. K. Wofford J. Worden J. L. Wright C. M. Wu D. S. Wu H. C. Wu S. R. Wu D. M. Wysocki L. Xiao W. R. Xu T. Yamada H. Yamamoto Kazuhiro Yamamoto Kohei Yamamoto T. Yamamoto C. C. Yancey L. Yang M. J. Yap M. Yazback D. W. Yeeles K. Yokogawa J. Yokoyama T. Yokozawa T. Yoshioka Hang Yu Haocun Yu S. H. R. Yuen H. Yuzurihara M. Yvert A. K. Zadro\.zny M. Zanolin S. Zeidler T. Zelenova J.-P. Zendri M. Zevin J. Zhang L. Zhang T. Zhang C. Zhao Y. Zhao M. Zhou Z. Zhou X. J. Zhu Z. H. Zhu A. B. Zimmerman M. E. Zucker J. Zweizig
Authors on Pith no claims yet

Pith reviewed 2026-05-16 00:28 UTC · model grok-4.3

classification 🌀 gr-qc astro-ph.HE
keywords gravitational wavessky localizationLIGOVirgoKAGRAbinary mergersobserving runsmulti-messenger astronomy
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The pith

Advanced LIGO, Virgo and KAGRA will localize most binary merger sources to a few tens of square degrees once KAGRA joins the network.

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

The paper estimates the sensitivity and sky-localization performance of the Advanced LIGO, Advanced Virgo and KAGRA detectors across the third, fourth and fifth observing runs. It models the response of the three- and four-detector networks to gravitational-wave signals from binary neutron-star, neutron-star-black-hole and binary-black-hole inspirals. The central projection is that the median 90-percent credible sky area will be a few hundred square degrees in the three-detector configuration and will shrink to a few tens of square degrees after KAGRA is added. These figures are intended to help astronomers plan electromagnetic follow-up observations and to guide expectations for multi-messenger detections.

Core claim

The authors' simulations show that the median sky localization area (90 percent credible region) for all three classes of compact-binary signals is expected to be a few hundred square degrees during the third observing run with the LIGO-Virgo network and will improve to a few tens of square degrees during the fourth run with the full LIGO-Virgo-KAGRA network. Comparable estimates are given for luminosity distance and comoving volume reach, together with sensitivity expectations for unmodeled transient searches including intermediate-mass black-hole binary mergers.

What carries the argument

Monte Carlo injections of compact-binary waveforms into simulated detector noise, followed by coherent network analysis to extract sky-area probability distributions, luminosity distances and comoving volumes.

If this is right

  • Astronomers can design follow-up campaigns that cover a few hundred square degrees during O3 and a few tens of square degrees during O4.
  • The addition of KAGRA is expected to increase the number of events with sufficiently precise localizations for host-galaxy identification.
  • Volume reach will grow with each run, allowing detection of more distant mergers.
  • Similar localization statistics are projected for unmodeled searches such as intermediate-mass black-hole binaries.

Where Pith is reading between the lines

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

  • If the quoted areas are achieved, routine association of gravitational-wave events with specific galaxies or electromagnetic transients becomes feasible for a larger fraction of detections.
  • Delays in reaching design sensitivity would directly postpone the improvement from hundreds to tens of square degrees.
  • The same simulation framework could be reused to test the benefit of adding further detectors or upgrading existing ones beyond O5.

Load-bearing premise

The detectors will reach their planned sensitivity curves on schedule and the noise properties and signal models used in the simulations will match actual performance.

What would settle it

A sample of real binary-merger events whose median 90-percent credible sky areas are systematically larger than a few hundred square degrees in O3 or a few tens of square degrees in O4 would contradict the projections.

read the original abstract

We present our current best estimate of the plausible observing scenarios for the Advanced LIGO, Advanced Virgo and KAGRA gravitational-wave detectors over the next several years, with the intention of providing information to facilitate planning for multi-messenger astronomy with gravitational waves. We estimate the sensitivity of the network to transient gravitational-wave signals for the third (O3), fourth (O4) and fifth observing (O5) runs, including the planned upgrades of the Advanced LIGO and Advanced Virgo detectors. We study the capability of the network to determine the sky location of the source for gravitational-wave signals from the inspiral of binary systems of compact objects, that is BNS, NSBH, and BBH systems. The ability to localize the sources is given as a sky-area probability, luminosity distance, and comoving volume. The median sky localization area (90\% credible region) is expected to be a few hundreds of square degrees for all types of binary systems during O3 with the Advanced LIGO and Virgo (HLV) network. The median sky localization area will improve to a few tens of square degrees during O4 with the Advanced LIGO, Virgo, and KAGRA (HLVK) network. We evaluate sensitivity and localization expectations for unmodeled signal searches, including the search for intermediate mass black hole binary mergers.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. The manuscript presents projections for the sensitivity and source localization performance of the Advanced LIGO, Advanced Virgo, and KAGRA detector network during the O3, O4, and O5 observing runs. Using Monte Carlo injection studies into modeled noise, it quantifies expected median sky localization areas (90% credible regions), luminosity distances, and comoving volumes for binary neutron star, neutron star-black hole, and binary black hole systems, as well as capabilities for unmodeled transient searches. The central results are that median sky areas are a few hundred square degrees for the HLV network in O3 and improve to a few tens of square degrees for the HLVK network in O4.

Significance. If the assumed detector sensitivity curves are realized, the reported localization metrics will directly inform multi-messenger follow-up strategies by providing quantitative expectations for sky areas and distances. The work employs standard network geometry and response models without circular fitting, and the conditional framing of the projections (tied to planned upgrades) makes the results useful for observational planning.

minor comments (3)
  1. §2 (sensitivity curves): the text refers to 'planned upgrades' without a dedicated table listing the exact noise curve parameters (e.g., strain at 100 Hz) used for each run; adding such a summary table would improve reproducibility.
  2. Figure 3 (sky area distributions): the caption does not state the number of injections per binary type or the exact prior ranges on component masses; this detail is needed to assess the robustness of the reported medians.
  3. §4.2 (unmodeled searches): the discussion of intermediate-mass black hole binaries is brief; a short paragraph clarifying the waveform family and frequency band assumptions would clarify the scope.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their positive review and recommendation to accept the manuscript. The summary accurately reflects our projections for the HLV network in O3 and the HLVK network in O4, as well as the utility for multi-messenger follow-up planning.

read point-by-point responses
  1. Referee: No major comments were provided in the report.

    Authors: We appreciate the referee's assessment that the work employs standard models and provides useful conditional projections. No revisions to the manuscript are required. revision: no

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper computes projected sensitivities and median sky localization areas (hundreds of deg² for O3 HLV, tens for O4 HLVK) directly from planned detector noise curves, standard inspiral signal models for BNS/NSBH/BBH systems, and network response geometry. No parameters are fitted to the projected outputs and re-used as inputs; the results are forward simulations under explicit assumptions about future performance. Self-citations to prior LIGO/Virgo work exist but are not load-bearing for the central projections, which remain independently verifiable against external benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

The estimates rest on modeled detector sensitivities and standard binary population assumptions rather than new first-principles derivations; full details are absent from the abstract.

free parameters (2)
  • O3/O4/O5 detector noise curves
    Assumed values based on planned upgrades; not derived within the paper.
  • binary merger population parameters
    Standard rates and mass distributions for BNS, NSBH, BBH systems used in injections.
axioms (2)
  • domain assumption Gaussian stationary noise in each detector
    Standard assumption for sensitivity and localization calculations.
  • standard math Post-Newtonian inspiral waveforms for compact binaries
    Used to generate injected signals.

pith-pipeline@v0.9.0 · 12995 in / 1284 out tokens · 94092 ms · 2026-05-16T00:28:38.604732+00:00 · methodology

discussion (0)

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Reference graph

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