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265 results on '"José A. Font"'

1. Gravitational-Wave Parameter Inference with the Newman-Penrose Scalar

Author

Juan Calderón Bustillo, Isaac C. F. Wong, Nicolas Sanchis-Gual, Samson H. W. Leong, Alejandro Torres-Forné, Koustav Chandra, José A. Font, Carlos Herdeiro, Eugen Radu, and Tjonnie G. F. Li

Subjects
Physics, QC1-999
Abstract

Detection and parameter inference of gravitational-wave signals from compact mergers rely on the comparison of the incoming detector strain data d(t) to waveform templates for the gravitational-wave strain h(t) that ultimately rely on the resolution of Einstein’s equations via numerical relativity simulations. These, however, commonly output a quantity known as the Newman-Penrose scalar ψ_{4}(t) which, under the Bondi gauge, is related to the gravitational-wave strain by ψ_{4}(t)=d^{2}h(t)/dt^{2}. Therefore, obtaining strain templates involves an integration process that introduces artifacts that need to be treated in a rather manual way. By taking second-order finite differences on the detector data and inferring the corresponding background noise distribution, we develop a framework to perform gravitational-wave data analysis directly using ψ_{4}(t) templates. We first demonstrate this formalism, and the impact of integration artifacts in strain templates, through the recovery of numerically simulated signals from head-on collisions of Proca stars injected in Advanced LIGO noise. Next, we reanalyze the event GW190521 under the hypothesis of a Proca-star merger, obtaining results equivalent to those previously published [Phys. Rev. Lett. 126, 081101 (2021)PRLTAO0031-900710.1103/PhysRevLett.126.081101], where we used the classical strain framework. We find, however, that integration errors would strongly impact our analysis if GW190521 was 4 times louder. Finally, we show that our framework fixes significant biases in the interpretation of the high-mass gravitational-wave trigger S200114f arising from the usage of strain templates. We remove the need to obtain strain waveforms from numerical relativity simulations, avoiding the associated systematic errors.

Published
2023
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2. Evaluation of the Minimum Segment Width and Fluence Smoothing Tools for Intensity-modulated Techniques in Monaco Treatment Planning System

Author

Sara Jiménez-Puertas, Andrea González Rodríguez, Sergio Lozares Cordero, Tomás González González, Javier Díez Chamarro, Mónica Hernández Hernández, Raquel Castro Moreno, Marta Sánchez Casi, David Carlos Villa Gazulla, Almudena Gandía Martínez, Arantxa Campos Bonel, Maria del Mar Puertas Valiño, and José Antonio Font Gómez

Subjects
minimum segment width, monitor units, radiosurgery, volumetric-modulated arc therapy, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Purpose: This study aims to minimize monitor units (MUs) of intensity-modulated treatments in the Monaco treatment planning system while preserving plan quality by optimizing the “Minimum Segment Width” (MSW) and “Fluence Smoothing” parameters. Materials and Methods: We retrospectively analyzed 30 prostate, 30 gynecological, 15 breast cancer, 10 head and neck tumor, 11 radiosurgery, and 10 hypo-fractionated plans. Original prostate plans employed “Fluence Smoothing” = Off and were reoptimized with Low, Medium, and High settings. The remaining pathologies initially used MSW = 0.5 cm and were reoptimized with MSW = 1.0 cm. Plan quality, including total MU, delivery time, and dosimetric constraints, was statistically analyzed with a paired t-test. Results: Prostate plans exhibited the highest MU variation when changing “Fluence Smoothing” from Off to High (average ΔMU = −5.1%; P < 0.001). However, a High setting may increase overall MU when MSW = 0.5 cm. Gynecological plans changed substantially when MSW increased from 0.5 cm to 1.0 cm (average ΔMU = −29%; P < 0.001). Organs at risk sparing and planning target volumes remained within 1.2% differences. Replanning other pathologies with MSW = 1.0 cm affected breast and head and neck tumor plans (average ΔMU = −168.38, average Δt = −11.74 s, and average ΔMU = −256.56, average Δt = −15.05 s, respectively; all with P < 0.004). Radiosurgery and hypofractioned highly modulated plans did not yield statistically significant results. Conclusions: In breast, pelvis, head and neck, and prostate plans, starting with MSW = 1.0 cm optimally reduces MU and treatment time without compromising plan quality. MSW has a greater impact on MU than the “Fluence Smoothing” parameter. Plans with high modulation might present divergent behavior, requiring a case-specific analysis with MSW values higher than 0.5 cm.

Published
2024
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37. Prospects for the inference of inertial modes from hypermassive neutron stars with future gravitational-wave detectors

Author

Miquel Miravet-Tenés, Florencia L. Castillo, Roberto De Pietri, Pablo Cerdá-Durán, and José A. Font

Subjects
High Energy Astrophysical Phenomena (astro-ph.HE), FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

Some recent, long-term numerical simulations of binary neutron star mergers have shown that the long-lived remnants produced in such mergers might be affected by convective instabilities. Those would trigger the excitation of inertial modes, providing a potential method to improve our understanding of the rotational and thermal properties of neutron stars through the analysis of the modes' imprint in the late post-merger gravitational-wave signal. In this paper we assess the detectability of those modes by injecting numerically generated post-merger waveforms into colored Gaussian noise of second-generation and future detectors. Signals are recovered using BayesWave, a Bayesian data-analysis algorithm that reconstructs them through a morphology-independent approach using series of sine-Gaussian wavelets. Our study reveals that current interferometers (i.e. the Handford-Livingston-Virgo network) recover the peak frequency of inertial modes only if the merger occurs at distances of up to 1 Mpc. For future detectors such as the Einstein Telescope, the range of detection increases by about a factor 10.

Published
2023

38. Inference of proto-neutron star properties in core-collapse supernovae from a gravitational-wave detector network

Author

Tristan Bruel, Marie-Anne Bizouard, Martin Obergaulinger, Patricio Maturana-Russel, Alejandro Torres-Forné, Pablo Cerdá-Durán, Nelson Christensen, José A. Font, and Renate Meyer

Subjects
High Energy Astrophysical Phenomena (astro-ph.HE), FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

The next Galactic core-collapse supernova (CCSN) will be a unique opportunity to study within a fully multi-messenger approach the explosion mechanism responsible for the formation of neutron stars and stellar-mass black holes. State-of-the-art numerical simulations of those events reveal the complexity of the gravitational-wave emission which is highly stochastic. This challenges the possibility to infer the properties of the compact remnant and of its progenitor using the information encoded in the waveforms. In this paper we take further steps in a program we recently initiated to overcome those difficulties. In particular we show how oscillation modes of the proto-neutron star, highly visible in the gravitational-wave signal, can be used to reconstruct the time evolution of their physical properties. Extending our previous work where only the information from a single detector was used we here describe a new data-analysis pipeline that coherently combines gravitational-wave detectors' data and infers the time evolution of a combination of the mass and radius of the compact remnant. The performance of the method is estimated employing waveforms from 2D and 3D CCSN simulations covering a progenitor mass range between 11$\mathrm{M_{\odot}}$\, and 40$\mathrm{M_{\odot}}$\, and different equations of state for both a network of up to five second-generation detectors and the proposed third-generation detectors Einstein Telescope and Cosmic Explorer. Our study shows that it will be possible to infer PNS properties for CCSN events occurring in the vicinity of the Milky Way, up to the Large Magellanic Cloud, with the current generation of gravitational-wave detectors.

Published
2023
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41. Classification of core-collapse supernova explosions with learned dictionaries

Author

Ainara Saiz-Pérez, Alejandro Torres-Forné, and José A Font

Subjects
Space and Planetary Science, Astronomy and Astrophysics
Abstract

Core-collapse supernovae (CCSNs) are a prime source of gravitational waves. Estimations of their typical frequencies make them perfect targets for the current network of advanced, ground-based detectors. A successful detection could potentially reveal the underlying explosion mechanism through the analysis of the waveform. This has been illustrated using the Supernova Model Evidence Extractor (SMEE), an algorithm based on principal component analysis and Bayesian model selection. Here, we present a complementary approach to SMEE based on (supervised) dictionary-learning and show that it is able to reconstruct and classify CCSN signals according to their morphology. Our waveform signals are obtained from (a) two publicly available catalogues built from numerical simulations of neutrino-driven (Mur) and magneto-rotational (Dim) CCSN explosions and (b) from a third ‘mock’ catalogue of simulated sine-Gaussian (SG) waveforms. All of these signals are injected into coloured Gaussian noise to simulate the background noise of Advanced LIGO in its broad-band configuration and scaled to a freely specifiable signal-to-noise ratio (SNR). We show that our approach correctly classifies signals from all three dictionaries. In particular, for SNR = 15–20, we obtain perfect matches for both Dim and SG signals and about 85 per cent true classifications for Mur signals. These results are comparable to those reported by SMEE for the same CCSN signals when those are injected in only one LIGO detector. We discuss the main limitations of our approach as well as possible improvements.

Published
2022

43. Assessment of a new sub-grid model for magneto-hydrodynamical turbulence. I. Magnetorotational instability

Author

Miquel Miravet-Tenés, Pablo Cerdá-Durán, Martin Obergaulinger, and José A Font

Subjects
High Energy Astrophysical Phenomena (astro-ph.HE), Astrophysics - Solar and Stellar Astrophysics, Space and Planetary Science, Fluid Dynamics (physics.flu-dyn), FOS: Physical sciences, Astronomy and Astrophysics, Physics - Fluid Dynamics, Astrophysics - High Energy Astrophysical Phenomena, Solar and Stellar Astrophysics (astro-ph.SR)
Abstract

Insufficient numerical resolution of grid-based, direct numerical simulations (DNS) hampers the development of instabilitydriven turbulence at small (unresolved) scales. As an alternative to DNS, sub-grid models can potentially reproduce the effects of turbulence at small scales in terms of the resolved scales, and hence can capture physical effects with less computational resources. We present a new sub-grid model, the MHD-instability-induced-turbulence (MInIT) mean-field model. MInIT is a physically motivated model based on the evolution of the turbulent (Maxwell, Reynolds, and Faraday) stress tensors and their relation with the turbulent energy densities of the magneto-rotational (MRI) and parasitic instabilities, modeled with two partial differential evolution equations with stiff source terms. Their solution allows obtaining the turbulent stress tensors through the constant coefficients that link them to the energy densities. The model is assessed using data from MRI in-box DNS and applying a filtering operation to compare the filtered data with that from the model. Using the $L_2$-norm as the metric for the comparison, we find less than one order-of-magnitude difference between the two sets of data. No dependence on filter size or length scale of unresolved scales is found, as opposed to results using the gradient model (which we also use to contrast our model) in which the $L_2$-norm of some of the stresses increases with filter size. We conclude that MInIT can help DNS by properly capturing small-scale turbulent stresses which has potential implications on the dynamics of highly-magnetized rotating compact objects, such as those formed during binary neutron star mergers., 20 pages, 15 figures

Published
2022

48. Erratum: Searches for continuous gravitational waves from 15 supernova remnants and fomalhaut b with advanced LIGO (2019, ApJ, 875, 122)*

Author

A. Parida, S. S. Eikenberry, F. Frasconi, Chris A. Collins, R. Flaminio, Marcus E. Lower, Rosa Poggiani, V. Frey, E. K. Wessel, Nikhil Sarin, Odylio D. Aguiar, I. W. Martin, S. Farinon, P. Raffai, Andrew Matas, C. F. Da Silva Costa, M. A. Okada, G. Rutins, Graham Woan, Sebastiano Bernuzzi, D. Passuello, A. Cirone, H. S. Chen, Hyun Lee, J. D. Lough, K. Mason, S. A. Bilgili, E. C. Ferreira, Robert L. Byer, J. Calderón Bustillo, Sanjeev Dhurandhar, O. Halim, N. A. Robertson, Stuart Reid, F. J. Hayes, Patrick Godwin, N. Sennett, P. Kumar, Jacob Scheuer, B. R. Hall, J. Hanks, R. M. Martin, David A. Nichols, Edward K. Porter, J. G. Bartlett, Márton Tápai, K. W. Tsang, C. Horst, W. A. Campbell, Andreas Freise, C. V. Kalaghatgi, M. Rakhmanov, G. Pagano, Paul D. Lasky, J. W. Westhouse, M. C. Araya, Srishti Tiwari, C. Lazzaro, Patricia Schmidt, V. Brisson, Bernard F. Schutz, Li Ju, Matthew Pitkin, D. Cohen, Kiran Prasai, P. J. Veitch, S. A. Usman, C. Messenger, Liam Cunningham, E. A. M. Muniz, Daniel A. Shaddock, P. Gruning, Brittany Kamai, Riccardo Ciolfi, Alberto Vecchio, Geoffrey Mo, J. M. Fishner, Roman Schnabel, J. Hanson, M. Wade, M. Montani, P. Sharma, Héctor Estellés, N. Letendre, F. Ricci, A. Lenon, J. E. Brau, A. A. van Veggel, Richard Gray, Efim A. Khazanov, Peter T. H. Pang, C. Affeldt, G. Ballardin, Moritz Mehmet, A. A. Ciobanu, M. Granata, Minchuan Zhou, F. Marion, P. Brockill, Nancy Aggarwal, Hang Yu, P. G. Murray, Fabien Kéfélian, J. H. Hough, P. W. F. Forsyth, S. R. Thondapu, J. R. Palamos, Michele Zanolin, S. Mukherjee, T. J. Massinger, T. Vo, V. Kalogera, N. Leroy, G. D. Hammond, Javed Rana, H. Fong, G. Greco, M. Haney, T. A. Callister, Alec Mishkin, R. Cavalieri, S. R. P. Mohapatra, G. Giordano, K. Toland, A. K. Srivastava, A. E. Pace, H. Ohta, Vuk Mandic, B. Bécsy, M. Kasprzack, I. Dave, B. D. Lackey, R. L. Ward, Scott Coughlin, A.J. Weinstein, K. H. Lai, M. Phelps, H. S. Cho, L. Kuo, H. Yamamoto, E. Capocasa, M. Chan, S. Walsh, D. J. McManus, A. Schönbeck, B. Rajbhandari, Andrew Mehta, S. D. Linker, R. Robie, M. Fletcher, B. Hughey, R. D. Kennedy, José A. Font, Gregorio Carullo, S. Kumar, J. Prasad, H. K. Gulati, V. Raymond, Steven Bloemen, H. J. Bulten, Shiuh Chao, P. J. Sutton, N. Singh, C. Buy, Samuele Cortese, J. McIver, Vivishek Sudhir, P. A. Altin, A. Basti, N. A. Lockerbie, E. Schreiber, Charalampos Markakis, P. Grassia, Kipp Cannon, M. Steinke, P.H. Nguyen, Ryan N. Lang, Z. Doctor, Alyssa Garcia, J. H. Romie, Carlos O. Lousto, S. Sitmukhambetov, Alejandro Torres-Forné, A. Samajdar, D. M. Wysocki, T. Mistry, Mark A. Scheel, Charlie Hoy, F. Clara, M. A. Aloy, T. M. Evans, C. North, Thomas Dent, P. Corban, P. Ajith, B. Mours, Mandar Patil, Abhirup Ghosh, J. Neilson, Bala R. Iyer, Y. K. Lecoeuche, M. Muratore, Karsten Danzmann, Fabrizio Barone, N. Mukund, P. B. Covas, M. C. Edwards, T. Hinderer, Marta Colleoni, J. A. Giaime, Michael Pürrer, R. Pedurand, Benno Willke, A. Grado, D. C. Vander-Hyde, S. S. Y. Chua, J. Eichholz, J.-P. Coulon, Hua Wang, E. A. Chase, J. Betzwieser, G. Kang, L. R. Cominsky, O. A. Hannuksela, Z. Frei, A. Pal-Singh, S. Caride, Kevin Barkett, N. Bode, S. E. Gossan, Tristan Briant, R. Gustafson, Antoine Heidmann, Rana X. Adhikari, S. McCormick, C. Casentini, Slawomir Gras, D. Töyrä, H. Overmier, S. W. S. Ng, G. Wang, M. C. Heintze, J. S. Areeda, I. Belahcene, B. B. Lane, N. Mazumder, Maher Yazback, F. Donovan, J. Bosveld, N. A. Holland, N. V. Keerthana, M.L. Walker, C. Cahillane, L. Sun, M. C. Milovich-Goff, Dániel Barta, J. D. E. Creighton, V. Gayathri, P. Puppo, J.-D. Fournier, S. J. Kapadia, A. L. Stuver, A. S. Sengupta, H. W. Lee, I. Di Palma, S. T. Countryman, Francesco Pannarale, E. A. Huerta, J. L. Wright, Alessandra Corsi, B. W. Schulte, A. Rocchi, J. P. Zendri, R. Kashyap, Chandra Kant Mishra, R. Bhandare, Sylvain Marsat, Lee McCuller, T. Bulik, T. D. Abbott, O. Puncken, J. M. Gonzalez Castro, Philip F. Hopkins, C. Cocchieri, B. Goncharov, R. Birney, M. Kinley-Hanlon, I. Fiori, Shawn Rosofsky, Jun Liu, S. Raja, S. E. Strigin, D. Sellers, J. Meidam, Jeff R. Powell, Riccardo Sturani, D. Hoak, Stefan L. Danilishin, Patrick Brady, L. Matone, Haocun Yu, M. Landry, R. M. S. Schofield, Surabhi Sachdev, Christopher J. Moore, V. Avendano, R. Mittleman, Nelson Christensen, Geoffrey Lovelace, Soichiro Morisaki, John Worden, P. Couvares, Carl-Johan Haster, O. J. Piccinni, L. Rolland, C. L. Romel, Miriam Cabero, Alessandra Buonanno, L. Wallace, S. Biscoveanu, M. B. Shaner, Benjamin J. Owen, Alexander Urban, Antoni Ramos-Buades, V. V. Frolov, A. Singhal, F. Carbognani, Jordan Camp, R. L. Savage, A. S. Bell, M. Laxen, Anchal Gupta, A. Królak, B. D. Cheeseboro, G. Cerretani, P. J. Easter, J. F. J. van den Brand, M. J. Szczepańczyk, L. Di Fiore, E. Bonilla, S. Sunil, M. Tacca, Jessica Steinlechner, A. Neunzert, P.-F. Cohadon, M. Heurs, Irina Kowalska, E. Katsavounidis, Xiuling Li, C. I. Torrie, Jan Harms, Kazuhiro Agatsuma, Kin Sing Stephen Lee, Frank Ohme, M. Tonelli, R. De Rosa, Kwan-Lok Li, I. Nardecchia, Reed Essick, Martin Hendry, Cecilio García-Quirós, S. Kandhasamy, M. Fishbach, B. Sorazu, Christopher Wipf, Archisman Ghosh, A. P. Lundgren, Gabrielle Allen, E. J. Daw, M. Punturo, F. Garufi, Antonio Marquina, Surendra Nadh Somala, I. Dorrington, Robert J. McCarthy, T. A. Ferreira, R. Frey, Joseph Smith, S. Brunett, J. Zweizig, A. W. Heptonstall, E. L. Merilh, D. Barker, K. D. Giardina, Denis Martynov, Marco Bazzan, C. Ingram, L. Pinard, L. Naticchioni, Salvatore Vitale, R. Kirchhoff, B. L. Pearlstone, N. Man, Antonios Kontos, D. Moffa, J. J. McCann, J.-M. Isac, D. Hofman, Linqing Wen, A. Bisht, A. Kutynia, M. A. Page, Tyson Littenberg, Z. Tornasi, Junwei Cao, Sebastian Steinlechner, T. J. Slaven-Blair, S. ShyamSundar, C. Stachie, Hongyu Shen, O. de Varona, J. B. Kanner, Federico Ferrini, Lijing Shao, G. Vajente, S. M. Gaebel, Christopher P. L. Berry, S. H. Huttner, G. M. Harry, Andrea Chincarini, K. Venkateswara, Yuri Levin, C. Austin, C.D. Booth, M. Barsuglia, S. Appert, A. Giazotto, P. Shawhan, I. Ferrante, T. Z. Summerscales, A. Viceré, T. Huynh-Dinh, Fabio Hernandez, H. Cao, Ashok Kumar, D. J. Vine, W. Katzman, Alena Ananyeva, D. C. Coyne, Stanislav Babak, Rico K. L. Lo, Kendall Ackley, R. K. Nayak, F. Y. Khalili, Ken K. Y. Ng, A. Hreibi, M. Thomas, D. Fiorucci, Manuela Rizzo, H. Radkins, A. Bozzi, A. K. Prajapati, A. R. Wade, M. Agathos, M. Brinkmann, R. Quitzow-James, N. N. Janthalur, B. Sassolas, K. Izumi, L. Xiao, J. S. Lange, H. Y. Chia, M. C. Díaz, W. S. Kim, M. H. Wimmer, K. Haughian, S. Hochheim, M. Yvert, M. Nery, Marc Favata, L. E. Wade, Roger Jones, V. J. Roma, A. P. Spencer, G. Kuehn, C. M. Mow-Lowry, Sergey P. Vyatchanin, Andrew Melatos, M. Lorenzini, A. Masserot, M. Khursheed, Ettore Majorana, Robert Stone, Alessandro Nagar, D. D. Brown, Anthony A. Amato, N. van Bakel, Sebastien Biscans, P. Fulda, P. Charlton, F. Magaña-Sandoval, L. Aiello, M. Gosselin, A. R. Williamson, D. Huet, R. Green, M. Was, M. C. Tringali, A. K. Zadrożny, E. E. Cowan, V. Boschi, L. Zhang, J. H. Klika, M. Bawaj, J. Junker, M. van Beuzekom, K. W. Chung, David Coward, T. Hardwick, D. Steinmeyer, F. Travasso, M. Constancio, A. Allocca, Sascha Husa, G. Venugopalan, D.B. DeBra, Mikhail L. Gorodetsky, C. Whittle, Z. Khan, P. Ehrens, Paul M. Ricker, Y. Setyawati, H. Khan, S. E. Barclay, B. F. Whiting, F. Brighenti, C. Talbot, J. H. Briggs, J. Casanueva Diaz, D. H. Reitze, A. F. Brooks, P. J. Quinonez, V. Kringel, J. L. Willis, Ofek Birnholtz, M. F. Carney, P. Schale, R. Bonnand, Mariana Fazio, H. Vocca, C. Van Den Broeck, E. Sowell, Albrecht Rüdiger, Xing-Jiang Zhu, Jochen Kissel, Felice Sorrentino, V. Srivastava, D. Talukder, Michał Bejger, M. Standke, M. Croquette, David A. Williams, A. Effler, I. W. Harry, D. Mukherjee, Y. R. Chen, J. Jiang, Alessandro Bertolini, M. Fays, D. Moraru, J. C. Driggers, Matthew Evans, M. Bitossi, G. Bergmann, K. Wette, M. M. Hanke, Leo Singer, E. Cesarini, M. Hulko, T. D. Creighton, Eugeniy E. Mikhailov, Jörg Hennig, Eric Howell, A. Strunk, G. Vedovato, L. E. H. Datrier, D. B. Kozak, D. Stocks, C. Vorvick, P. Thomas, M. Arène, S. B. Anderson, Tim Dietrich, A. Perreca, G. Gemme, A. Di Lieto, R. A. Eisenstein, S. J. Chamberlin, Jishnu Suresh, G. D. Meadors, Z. A. Warden, R. Gouaty, T. Zelenova, Riccardo Bassiri, John J. Oh, M. Vasúth, Jonathan Cripe, N. Kijbunchoo, E. Cuoco, Sheelu Abraham, K. Kawabe, S. M. Aston, Michael W. Coughlin, G. D. O'Dea, Bruno Giacomazzo, Giuseppe Intini, M. Drago, Guenakh Mitselmakher, B. A. Boom, A. M. Sergeev, T. Etzel, J.-G. Ducoin, M. Eisenmann, A. Dmitriev, S. Leavey, Hai-Ping Cheng, A. Iess, L. K. Nuttall, D. Wilken, S. Katsanevas, R. Goetz, C. Adams, R. M. Blair, D. Sigg, S. W. Ballmer, D. M. Shoemaker, Binlei Ding, V. Bossilkov, Lindsay DeMarchi, I. Khan, K. Siellez, D. Sentenac, R. Macas, G. Billingsley, S. Macfoy, Sergio Gaudio, D. B. Tanner, A. Trovato, Olivier Minazzoli, Magnus Manske, M. Razzano, C. C. Yancey, F. Vetrano, Zachariah B. Etienne, Jennifer Watchi, E. Maros, R. C. Walet, V. P. Mitrofanov, R. Colgan, C. S. Unnikrishnan, G. Moreno, V. Kondrashov, P. Leaci, S. Meshkov, Seog Oh, S. P. Stevenson, Achamveedu Gopakumar, R. Inta, C. J. Richardson, S. Klimenko, M. J. Yap, C. Palomba, W. G. Anderson, G. Cella, F.L. Linde, P. Booker, L. Milano, S. C. Tait, N. V. Krishnendu, A. Pasqualetti, W. Del Pozzo, W. M. Farr, A. C. Green, Fausto Acernese, M. Korobko, B. C. Pant, C. Messick, J. Derby, J. Healy, K. A. Thorne, A. Cumming, M. Denys, M. Tse, S. Ascenzi, S. E. Dwyer, R. M. Magee, David Keitel, V. Germain, S. J. Cooper, Giacomo Ciani, K. Rao, Yongjung Kim, Peter Weßels, I. A. Bilenko, L. Haegel, David J. Ottaway, B. P. Abbott, H. Vahlbruch, J. C. Mills, E. K. Gustafson, K. Riles, J. Y. Vinet, H. Middleton, S. Doravari, H. Heitmann, Piotr Jaranowski, M. S. Shahriar, P. Ruggi, M. Weinert, H. A. G. Gabbard, D. M. Macleod, Karan Jani, B. L. Swinkels, Arunava Mukherjee, S. Privitera, L. Glover, Imre Bartos, Isabel Cordero-Carrión, H. Qi, E. Genin, J. Zhang, F. Baldaccini, B. U. Gadre, A. Lartaux-Vollard, B. Irwin, R. Shink, L. Rei, Huang-Wei Pan, Gijs Nelemans, S. Vass, Kenneth A. Strain, Jimin George, R. Coyne, C. Gray, G. H. Ogin, T. J. Shaffer, M. Sieniawska, Fabrice Matichard, A. Paoli, K. A. Santiago, F. Fidecaro, G. M. Guidi, G. Cagnoli, Arnold Miller, H. N. Isa, Suvadeep Bose, V. Tiwari, V. Quetschke, Yann Bouffanais, Martin M. Fejer, L. F. Ortega, D. Lumaca, M. Pedraza, R. Bork, S. Ghonge, Y. Minenkov, P. Bacon, K. AultONeal, K. Chakravarti, E. D. Hall, L. Sammut, Lionel London, D. George, R. K. Lanza, Y. Boetzel, Alexander C. Jenkins, P. Dupej, Eric B. Flynn, Z. Márka, M. Mantovani, T. Prestegard, D. W. Yeeles, Xie Chen, A. Markowitz, Fabio Marchesoni, P. Hello, Samuel Deléglise, M. Merzougui, A. Fernandez-Galiana, S. M. Scott, M. Obergaulinger, Turlough P. Downes, F. Cavalier, A. Ain, R. J. Trudeau, K. Holt, Chunglee Kim, L. van der Schaaf, S. A. Pai, C. De Rossi, W. Parker, A. Gennai, Rahul Kumar, Harald P. Pfeiffer, Milan Gupta, G. Dálya, B. Gateley, G. Cho, J. C. Bayley, Aaron Buikema, V. Sandberg, E. J. King, M. J. Cowart, S. Koley, M. Boer, G. Mendell, S. J. Jadhav, B. Idzkowski, V. Loriette, V. Skliris, J. K. Blackburn, E. Chassande-Mottin, Shubhanshu Tiwari, G. Koekoek, L. Trozzo, C. Pankow, P. M. Meyers, Koh Ueno, Christian Pedersen, Albert Lazzarini, Kyungmin Kim, N. Koper, H. Wittel, M. Deenadayalan, B. O'Reilly, A. W. Jones, Sheila Rowan, S. G. Schwalbe, D. Pascucci, R. De Pietri, S. Mitra, T. Sadecki, W. Ren, Rocco Romano, John D. Scott, J. Z. Wang, S. Grunewald, R. Prasanna, R. Cotesta, R. G. Ormiston, S. Kaufer, Rainer Weiss, David E. McClelland, Paul J. Groot, M. Zevin, R. A. Mercer, S. Ossokine, Jinsook Kim, Rebecca Fisher, J. Li, A. M. Holgado, H. Fair, Samaya Nissanke, X. Liu, M. A. Bizouard, K. Bossie, John Veitch, J. 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Costa, Zhihui Du, Laboratoire des matériaux avancés (LMA), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Laboratoire de l'Accélérateur Linéaire (LAL), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), (Astro)-Particles Physics, Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)

Subjects
Physics, [PHYS]Physics [physics], 010504 meteorology & atmospheric sciences, Gravitational wave, Astronomy, Astronomy and Astrophysics, 01 natural sciences, LIGO, Supernova, Fomalhaut, Space and Planetary Science, 0103 physical sciences, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], 010303 astronomy & astrophysics, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract

Equation (5) of the published article?(Abbott et al. 2019) is in error; it should read (Formula Presented) The upper limits on ò presented in the published article are unaffected by this error.

Published
2021

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