Parameter estimation for compact binary coalescence signals with the first generation gravitational-wave detector network

Aasi, J.; Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Accadia, T.; Acernese, F.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Ajith, P.; Allen, B.; Allocca, A.; Ceron, E. Amador; Amariutei, D.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Ast, S.; Aston, S. M.; Astone, P.; Atkinson, D.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P. T.; Ballardin, G.; Ballmer, S. W.; Bao, Yiliang; Barayoga, J. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; Basti, A.; Batch, J. C.; Bauchrowitz, J.; Bauer, Th.; Bebronne, M.; Beck, D.; Behnke, B.; Bejger, M.; Beker, M. G.; Bell, A. S.; Bell, C.; Belopolski, Ilya; Benacquista, M.; Berliner, J. M.; Bertolini, A.; Betzwieser, J.; Beveridge, N.; Beyersdorf, P. T.; Bhadbade, T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biswas, R.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, David; Bland, B.; Blom, M.; Böck, O.; Bodiya, T. P.; Bogan, C.; Bond, C.; Bondarescu, Ruxandra; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, S.; Bosi, L.; Bouhou, B.; Braccini, S.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burguet–Castell, J.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannon, K. C.; Canuel, B.; Cao, Junwei; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chalermsongsak, T.; Charlton, P.; Chassande–Mottin, E.; Chen, W.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J. H.; Christensen, N.; Chua, S.; Chung, C. T.Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D.; Clark, J. A.; Clayton, J. H.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colacino, C. N.; Colla, A.; Colombini, M.; Conte, A.; Conte, R.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M. W.; Coulon, J.‐P.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Creighton, J. D. E.; Creighton, T. D.; Cruise, A. M.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, R. M.; Dahl, K.; Damjanic, M.; Danilishin, S. L.; D’Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Daw, E. J.; Dayanga, T.; Rosa, R. De; DeBra, D.; Debreczeni, G.; Degallaix, J.; Pozzo, W. Del; Dent, T.; Dergachev, V.; DeRosa, R. T.; Dhurandhar, S.; Fiore, L. Di; Lieto, A. Di; Palma, I. Di; Emilio, M. Di Paolo; Virgilio, A. Di; Díaz, M. C.; Dietz, A.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorsher, S.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J. C.; Dwyer, S. 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doi:10.1103/physrevd.88.062001

Cited by 147 publications

(130 citation statements)

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“…Inaccuracies in the waveform models could be a source of systematic error in the parameter estimates [224][225][226]. However, an alternative analysis of GW150914 using a set of waveforms from numerical-relativity simulations yielded results consistent with those using the EOBNR and IMRPhenom approximants [227].…”

Section: Appendix B: Parameter-estimation Descriptionmentioning

confidence: 54%

“…Parameters that characterize GW150914, GW151226, and LVT151012. For model parameters, we report the median value with the range of the symmetric 90% credible interval [214]; we also quote selected 90% credible bounds. For the logarithm of the Bayes factor for a signal compared to Gaussian noise, we report the mean and its 90% standard error from four parallel runs with a nested sampling algorithm [215], and for the deviance information criterion, we report the mean and its 90% standard error from a Markov-chain Monte Carlo and a nested sampling run.…”

Section: Appendix B: Parameter-estimation Descriptionmentioning

confidence: 99%

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Binary Black Hole Mergers in the First Advanced LIGO Observing Run

Abbott¹,

Abbott²,

Abbott³

et al. 2016

Phys. Rev. X

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1,191

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the first detections of gravitational waves from binary black hole mergers. In this paper, we present full results from a search for binary black hole merger signals with total masses up to 100M ⊙ and detailed implications from our observations of these systems. Our search, based on general-relativistic * Full author list given at the end of the article. † Deceased.Published by the American Physical Society under the terms of the Creative Commons Attribution 3.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. BINARY BLACK HOLE MERGERS IN THE FIRST …PHYS. REV. X 6, 041015 (2016) 041015-5 models of gravitational-wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than 5σ over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance and with an 87% probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and we place improved empirical bounds on several highorder post-Newtonian coefficients. From our observations, we infer stellar-mass binary black hole merger rates lying in the range 9-240 Gpc −3 yr −1 . These observations are beginning to inform astrophysical predictions of binary black hole formation rates and indicate that future observing runs of the Advanced detector network will yield many more gravitational-wave detections.

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Section: Appendix B: Parameter-estimation Descriptionmentioning

confidence: 54%

Section: Appendix B: Parameter-estimation Descriptionmentioning

confidence: 99%

Binary Black Hole Mergers in the First Advanced LIGO Observing Run

Abbott¹,

Abbott²,

Abbott³

et al. 2016

Phys. Rev. X

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show abstract

“…For this work, we use LALINFERENCE_MCMC, which is included in the LALINFERENCE LSC Algorithm Library [6], as our parameter estimation pipeline. It is a Markov Chain Monte Carlo (MCMC) sampler designed to efficiently explore the full waveform parameter space in order to make reliable and meaningful statements about CBC source parameters [7][8][9]. This paper's focus is on measuring the effect of tidal influence on BNS GW signals with advanced detectors.…”

Section: Background and Motivationmentioning

confidence: 99%

Systematic and statistical errors in a Bayesian approach to the estimation of the neutron-star equation of state using advanced gravitational wave detectors

et al. 2014

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Advanced ground-based gravitational-wave detectors are capable of measuring tidal influences in binary neutron-star systems. In this work, we report on the statistical uncertainties in measuring tidal deformability with a full Bayesian parameter estimation implementation. We show how simultaneous measurements of chirp mass and tidal deformability can be used to constrain the neutron-star equation of state. We also study the effects of waveform modeling bias and individual instances of detector noise on these measurements. We notably find that systematic error between post-Newtonian waveform families can significantly bias the estimation of tidal parameters, thus motivating the continued development of waveform models that are more reliable at high frequencies. DOI: 10.1103/PhysRevD.89.103012 PACS numbers: 95.85.Sz, 26.60.Kp I. BACKGROUND AND MOTIVATIONAdvanced interferometric gravitational-wave (GW) detectors currently under construction are expected to begin operating in the next few years. Advanced LIGO [1] is expected to achieve its design sensitivity c. 2019 [2], at which time the detection rate of binary neutron-star (BNS) events in a single detector is expected to be ∼40 yr −1 , though this value is quite uncertain and ranges from 0.4 − 400 yr −1 [3]. When a compact binary coalescence (CBC) signal is detected [4,5], the corresponding interferometer data stream segment is sent through a parameter estimation pipeline to determine the source parameters of the system. Some of these source parameters include the binary component masses and spins, the sky location, distance, and orientation of the system. Bayesian inference is used to explore the probability distribution of the CBC's source parameters by comparing model waveform templates, whose form depends on these source parameters, to the data stream segment containing the GW. For this work, we use LALINFERENCE_MCMC, which is included in the LALINFERENCE LSC Algorithm Library [6], as our parameter estimation pipeline. It is a Markov Chain Monte Carlo (MCMC) sampler designed to efficiently explore the full waveform parameter space in order to make reliable and meaningful statements about CBC source parameters [7][8][9]. This paper's focus is on measuring the effect of tidal influence on BNS GW signals with advanced detectors. Neutron stars (NSs) in merging CBC systems will be tidally deformed by the gravitational gradient of their companion across their finite diameter. This effect is insignificant at large separations but becomes increasingly significant as the NSs near each other [10]. The internal structure of a NS, which is characterized by its equation of state (EOS), determines how much each star will deform. The amount that a NS deforms will affect the orbital decay rate, which is encoded in the observed gravitational waveform. Therefore, if a gravitational signal from a BNS system is detected, then such a detection could provide insight into the NS EOS [10][11][12][13].In order to make meaningful statements regarding the recoverability of tidal param...

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“…LALInference has been extensively used both on real 55 and simulated data. Unlike BAYESTAR, it does not assume that masses are known, and instead performs a full Markov Chain Monte Carlo exploration of the parameter space.…”

Section: Refined Sky Maps and Subsequential Updatesmentioning

confidence: 99%

Prospects and challenges in the electromagnetic follow-up of LIGO-Virgo gravitational wave transients

Vitale

2014

SPIE Proceedings

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The kilometer-scale ground based gravitational wave (GW) detectors, LIGO and Virgo, are being upgraded to their advanced configurations. We expect the two LIGO observatories to undertake a 3 month science run in 2015 with a limited sensitivity. Virgo should come online in 2016, and join LIGO for a 6 month science run. Through a sequence of science runs and commissioning periods, the final sensitivity should be reached by ∼ 2019. LIGO and Virgo are expected to deliver the first direct detection of gravitational wave transients in the next few years. Most of the known sources of GWs targeted by LIGO and Virgo will likely be luminous in the electromagnetic (EM) spectrum as well. Compact binary coalescences are thought to be progenitors of short gamma-ray bursts, while long gamma-ray bursts are likely to be associated with core collapse supernova. A joint detection of gravitational and EM radiation may help confirm these associations, and expand our understanding of those astrophysical systems. Due to the transient nature, a search for the EM counterparts to GW events should be done with the shortest latency. In this paper we describe the EM follow-up program of Advanced LIGO and Virgo, from the search for GWs to the production of sky maps. Furthermore, we quantify the expected sky localization errors in the first two years of operation of the advanced detectors network. INTRODUCTIONThe advanced version of the ground based gravitational wave observatories LIGO 1 will start collecting data in 2015, followed shortly after by Advanced Virgo.2 Through a sequence of commissioning periods, they will reach their design sensitivity at the end of this decade, when they will probe a volume of the Universe a factor of 10 3 larger than the initial detectors. The Japanese detector KAGRA, 3 and LIGO-India 4 are also expected to join this global network in the early 2020s, further increasing the sensitivity, and dramatically improving sky localization of gravitational wave (GW) sources. Ground based detectors are thus expected to make the first direct detection of gravitational radiation, and start gravitational wave astronomy.Beside the obvious interest that a direct GW detection deserves on its own, there is much interest in the possibility of joint electromagnetic -gravitational detections. In fact GW detectors target several classes of astrophysical sources, some of which are also expected to be luminous in the electromagnetic (EM) spectrum. 5-8The most promising sources of GWs are compact binary systems (CBC) consisting of neutron stars and/or black holes, which are also the best theoretically understood. Loss of energy through gravitational wave emission makes the orbit to shrink (inspiral phase), until the two objects merge to form a single black hole. This releases the excess of energy "ringing-down" to equilibrium. The inspiral part can be described well using Post-Newtonian theory (see.9 for a review), while effective one body (EOB) models 10 and Inspiral-Merger-Ringdown (IMR) phenomenological models 11 can descr...

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Parameter estimation for compact binary coalescence signals with the first generation gravitational-wave detector network

Cited by 147 publications

References 62 publications

Binary Black Hole Mergers in the First Advanced LIGO Observing Run

Binary Black Hole Mergers in the First Advanced LIGO Observing Run

Systematic and statistical errors in a Bayesian approach to the estimation of the neutron-star equation of state using advanced gravitational wave detectors

Prospects and challenges in the electromagnetic follow-up of LIGO-Virgo gravitational wave transients

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