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Divergences in gravitational-wave emission and absorption from extreme mass ratio binaries

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Physical Review D 2021年第6期104卷 064031-064031页

作者： Enrico Barausse Emanuele Berti Vitor Cardoso Scott A. Hughes Gaurav Khanna SISSA Via Bonomea 265 34136 Trieste Italy and INFN Sezione di Trieste IFPU—Institute for Fundamental Physics of the Universe Via Beirut 2 34014 Trieste Italy Department of Physics and Astronomy Johns Hopkins University 3400 North Charles Street Baltimore Maryland 21218 USA CENTRA Departamento de Física Instituto Superior Técnico—IST Universidade de Lisboa—UL Avenida Rovisco Pais 1 1049 Lisboa Portugal Department of Physics and MIT Kavli Institute Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics University of Rhode Island Kingston Rhode Island 02881 USA Center for Scientific Computing and Visualization Research and Physics Department University of Massachusetts Dartmouth Massachusetts 02747 USA

A powerful technique to calculate gravitational radiation from binary systems involves a perturbative expansion: if the masses of the two bodies are very different, the “small” body is treated as a point particle of mass mp moving in the gravitational field generated by the large mass M, and one keeps only linear terms in the small mass ratio mp/M. This technique usually yields finite answers, which are often in good agreement with fully nonlinear numerical relativity results, even when extrapolated to nearly comparable mass ratios. Here we study two situations in which the point-particle approximation yields a divergent result: the instantaneous flux emitted by a small body as it orbits the light ring of a black hole, and the total energy absorbed by the horizon when a small body plunges into a black hole. By integrating the Teukolsky (or Zerilli/Regge-Wheeler) equations in the frequency and time domains we show that both of these quantities diverge. We find that these divergences are an artifact of the point-particle idealization, and are able to interpret and regularize this behavior by introducing a finite size for the point particle. These divergences do not play a role in black-hole imaging, e.g., by the Event Horizon Telescope.

关键词： Classical black holes Gravitational wave sources

High precision source characterization of intermediate mass-ratio black hole coalescences with gravitational waves: The importance of higher order multipoles

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Physical Review D 2021年第8期104卷 084068-084068页

作者： Tousif Islam Scott E. Field Carl-Johan Haster Rory Smith Department of Physics University of Massachusetts Dartmouth Massachusetts 02747 USA Department of Mathematics University of Massachusetts Dartmouth Massachusetts 02747 USA Center for Scientific Computing and Visualization Research University of Massachusetts Dartmouth Massachusetts 02747 USA Kavli Institute for Theoretical Physics University of California Santa Barbara California 93106 USA LIGO Laboratory Massachusetts Institute of Technology 185 Albany Street Cambridge Massachusetts 02139 USA Department of Physics and Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge Massachusetts 02139 USA School of Physics and Astronomy Monash University Melbourne VIC 3800 Australia OzGrav: The ARC Centre of Excellence for Gravitational Wave Discovery Clayton VIC 3800 Australia

Intermediate mass-ratio inspiral (IMRI) binaries—containing stellar-mass black holes coalescing into intermediate-mass black holes (M>100 M⊙)—are a highly anticipated source of gravitational waves (GWs) for Advanced LIGO/Virgo. Their detection and source characterization would provide a unique probe of strong-field gravity and stellar evolution. Because of the asymmetric component masses and the large primary, these systems generically excite subdominant modes while reducing the importance of the dominant quadrupole mode. Including higher order harmonics can also result in a 10%–25% increase in signal-to-noise ratio for IMRIs, which may help to detect these systems. We show that by including subdominant gravitational-wave modes into the analysis we can achieve a precise characterization of IMRI source properties. For example, we find that the source properties for IMRIs can be measured to within 2%–15% accuracy at a fiducial signal-to-noise ratio of 25 if subdominant modes are included. When subdominant modes are neglected, the accuracy degrades to 9%–44% and significant biases are seen in chirp mass, mass ratio, primary spin, and luminosity distances. We further demonstrate that including subdominant modes in the waveform model can enable an informative measurement of both individual spin components and improve the source localization by a factor of ∼10. We discuss some important astrophysical implications of high precision source characterization enabled by subdominant modes such as constraining the mass gap and probing formation channels.

关键词： Gravitation Gravitational waves

Exploration of Differentiability in a Proton Computed Tomography Simulation Framework

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arXiv 2022年

作者： Aehle, Max Alme, Johan Barnaföldi, Gergely Gábor Blühdorn, Johannes Bodova, Tea Borshchov, Vyacheslav van den Brink, Anthony Eikeland, Viljar Feofilov, Gregory Garth, Christoph Gauger, Nicolas R. Grøttvik, Ola Helstrup, Håvard Igolkin, Sergey Keidel, Ralf Kobdaj, Chinorat Kortus, Tobias Kusch, Lisa Leonhardt, Viktor Mehendale, Shruti Mulawade, Raju Ningappa Odland, Odd Harald O’Neill, George Papp, Gábor Peitzmann, Thomas Pettersen, Helge Egil Seime Piersimoni, Pierluigi Pochampalli, Rohit Protsenko, Maksym Rauch, Max Rehman, Attiq Ur Richter, Matthias Röhrich, Dieter Sagebaum, Max Santana, Joshua Schilling, Alexander Seco, Joao Songmoolnak, Arnon Sudár, Ákos Tambave, Ganesh Tymchuk, Ihor Ullaland, Kjetil Varga-Kofarago, Monika Volz, Lennart Wagner, Boris Wendzel, Steffen Wiebel, Alexander Xiao, RenZheng Yang, Shiming Zillien, Sebastian Chair for Scientific Computing University of Kaiserslautern-Landau Kaiserslautern67663 Germany Department of Physics and Technology University of Bergen Bergen5007 Norway Wigner Research Centre for Physics Budapest Hungary Kharkiv Ukraine Institute for Subatomic Physics Utrecht University/Nikhef Utrecht Netherlands St. Petersburg University St. Petersburg Russia Scientific Visualization Lab University of Kaiserslautern-Landau Kaiserslautern67663 Germany Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen5020 Norway University of Applied Sciences Worms Worms Germany Institute of Science Suranaree University of Technology Nakhon Ratchasima Thailand Department of Oncology and Medical Physics Haukeland University Hospital Bergen5021 Norway Institute for Physics Eötvös Loránd University 1/A Pázmány P. Sétány BudapestH-1117 Hungary FSN Department ENEA Frascati Research Center Frascati00044 Italy Department of Physics University of Oslo Oslo0371 Norway Department of Biomedical Physics in Radiation Oncology DKFZ—German Cancer Research Center Heidelberg Germany Department of Physics and Astronomy Heidelberg University Heidelberg Germany Bhubaneswar India Biophysics GSI Helmholtz Center for Heavy Ion Research GmbH Darmstadt Germany Department of Medical Physics and Biomedical Engineering University College London London United Kingdom College of Mechanical & Power Engineering China Three Gorges University Yichang China

Objective. Algorithmic differentiation (AD) can be a useful technique to numerically optimize design and algorithmic parameters by, and quantify uncertainties in, computer simulations. However, the effectiveness of AD depends on how "well-linearizable" the software is. In this study, we assess how promising derivative information of a typical proton computed tomography (pCT) scan computer simulation is for the aforementioned applications. Approach. This study is mainly based on numerical experiments, in which we repeatedly evaluate three representative computational steps with perturbed input values. We support our observations with a review of the algorithmic steps and arithmetic operations performed by the software, using debugging techniques. Main results. The model-based iterative reconstruction (MBIR) subprocedure (at the end of the software pipeline) and the Monte Carlo (MC) simulation (at the beginning) were piecewise differentiable. Jumps in the MBIR function arose from the discrete computation of the set of voxels intersected by a proton path. Jumps in the MC function likely arose from changes in the control flow that affect the amount of consumed random numbers. The tracking algorithm solves an inherently non-differentiable problem. Significance. The MC and MBIR codes are ready for the integration of AD, and further research on surrogate models for the tracking subprocedure is necessary. Copyright © 2022, The Authors. All rights reserved.

关键词： Monte Carlo methods

Towards Neural Charged Particle Tracking in Digital Tracking Calorimeters with Reinforcement Learning

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TechRxiv

TechRxiv 2022年

作者： Kortus, Tobias Keidel, Ralf Gauger, Nicolas R. Aehle, Max Alme, Johan Barnaföldi, Gergely Gábor Bodova, Tea Borshchov, Vyacheslav van den Brink, Anthony Chaar, Mamdouh Eikeland, Viljar Feofilov, Gregory Garth, Christoph Genov, Georgi Grøttvik, Ola Helstrup, Håvard Igolkin, Sergey Keidel, Ralf Kobdaj, Chinorat Leonhardt, Viktor Mehendale, Shruti Mulawade, Raju Ningappa Odland, Odd Harald O’Neill, George Papp, Gábor Peitzmann, Thomas Pettersen, Helge Egil Seime Piersimoni, Pierluigi Protsenko, Maksym Rauch, Max Rehman, Attiq Ur Richter, Matthias Röhrich, Dieter Santana, Joshua Schilling, Alexander Seco, Joao Songmoolnak, Arnon Sudár, Ákos Sølie, Jarle Rambo Tambave, Ganesh Tymchuk, Ihor Ullaland, Kjetil Varga-Kofarago, Monika Volz, Lennart Wagner, Boris Wendzel, Steffen Wiebel, Alexander Xiao, RenZheng Yang, Shiming Yokoyama, Hiroki Zillien, Sebastian University of Applied Sciences Worms Worms67549 Germany Chair for Scientific Computing TU Kaiserslautern Kaiserslautern67663 Germany Department of Physics and Technology University of Bergen Bergen5007 Norway Wigner Research Centre for Physics Budapest Hungary Kharkiv Ukraine Institute for Subatomic Physics Utrecht University/Nikhef Utrecht Netherlands St. Petersburg University St. Petersburg Russia Scientific Visualization Lab TU Kaiserslautern Kaiserslautern67663 Germany Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen5020 Norway Institute of Science Suranaree University of Technology Nakhon Ratchasima Thailand Department of Oncology and Medical Physics Haukeland University Hospital Bergen5021 Norway Institute for Physics Eötvös Loránd University 1/A Pázmány P. Sétány BudapestH-1117 Hungary UniCamillus Saint Camillus International University of Health Sciences Rome Italy Department of Physics University of Oslo Oslo0371 Norway Department of Biomedical Physics in Radiation Oncology DKFZ—German Cancer Research Center Heidelberg Germany Department of Physics and Astronomy Heidelberg University Heidelberg Germany Budapest University of Technology and Economics Budapest Hungary Department of Diagnostic Physics Division of Radiology and Nuclear Medicine Oslo University Hospital Oslo Norway Bhubaneswar India Biophysics GSI Helmholtz Center for Heavy Ion Research GmbH Darmstadt Germany Department of Medical Physics and Biomedical Engineering University College London London United Kingdom College of Mechanical & Power Engineering China Three Gorges University Yichang China

We propose a novel technique for reconstructing charged particles in digital tracking calorimeters using reinforcement learning aiming to benefit from the rapid progress and success of neural network architectures without the dependency on simulated or manually-labeled data. Here we optimize by trial-and-error a behavior policy acting as an approximation to the full combinatorial optimization problem, maximizing the physical plausibility of sampled trajectories. In modern processing pipelines used in high energy physics and related applications, tracking plays an essential role allowing to identify and follow charged particle trajectories traversing particle detectors. Due to the high multiplicity of charged particles and their physical interactions, randomly deflecting the particles, the reconstruction is a challenging undertaking, requiring fast, accurate and robust algorithms. Our approach works on graph-structured data, capturing track hypotheses through edge connections between particles in the detector layers. We demonstrate in a comprehensive study on simulated data for a particle detector used for proton computed tomography, the high potential as well as the competitiveness of our approach compared to a heuristic search algorithm and a model trained on ground truth. Finally, we point out limitations of our approach, guiding towards a robust foundation for further development of reinforcement learning based tracking. © 2022, CC BY.

关键词： Reinforcement learning

Eccentric binary black hole surrogate models for the gravitational waveform and remnant properties: Comparable mass, nonspinning case

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Physical Review D 2021年第6期103卷 064022-064022页

作者： Tousif Islam Vijay Varma Jackie Lodman Scott E. Field Gaurav Khanna Mark A. Scheel Harald P. Pfeiffer Davide Gerosa Lawrence E. Kidder Department of Physics University of Massachusetts Dartmouth Massachusetts 02747 USA Department of Mathematics University of Massachusetts Dartmouth Massachusetts 02747 USA Center for Scientific Computing and Visualization Research University of Massachusetts Dartmouth Massachusetts 02747 USA Department of Physics Cornell University Ithaca New York 14853 USA Cornell Center for Astrophysics and Planetary Science Cornell University Ithaca New York 14853 USA TAPIR 350-17 California Institute of Technology 1200 East California Boulevard Pasadena California 91125 USA Department of Physics University of Rhode Island Kingston Rhode Island 02881 USA Max Planck Institute for Gravitational Physics (Albert Einstein Institute) Am Mühlenberg 1 Potsdam 14476 Germany School of Physics and Astronomy & Institute for Gravitational Wave Astronomy University of Birmingham Birmingham B15 2TT United Kingdom

We develop new strategies to build numerical relativity surrogate models for eccentric binary black hole systems, which are expected to play an increasingly important role in current and future gravitational-wave detectors. We introduce a new surrogate waveform model, NRSur2dq1Ecc, using 47 nonspinning, equal-mass waveforms with eccentricities up to 0.2 when measured at a reference time of 5500M before merger. This is the first waveform model that is directly trained on eccentric numerical relativity simulations and does not require that the binary circularizes before merger. The model includes the (2,2), (3,2), and (4,4) spin-weighted spherical harmonic modes. We also build a final black hole model, NRSur2dq1EccRemnant, which models the mass, and spin of the remnant black hole. We show that our waveform model can accurately predict numerical relativity waveforms with mismatches ≈10−3, while the remnant model can recover the final mass and dimensionless spin with absolute errors smaller than ≈5×10−4M and ≈2×10−3 respectively. We demonstrate that the waveform model can also recover subtle effects like mode mixing in the ringdown signal without any special ad hoc modeling steps. Finally, we show that despite being trained only on equal-mass binaries, NRSur2dq1Ecc can be reasonably extended up to mass ratio q≈3 with mismatches ≃10−2 for eccentricities smaller than ∼0.05 as measured at a reference time of 2000M before merger. The methods developed here should prove useful in the building of future eccentric surrogate models over larger regions of the parameter space.

关键词： Gravitational waves

High-precision source characterization of intermediate mass-ratio black hole coalescences with gravitational waves: The importance of higher-order multipoles

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arXiv 2021年

作者： Islam, Tousif Field, Scott E. Haster, Carl-Johan Smith, Rory Department of Physics University of Massachusetts DartmouthMA02747 United States Department of Mathematics University of Massachusetts DartmouthMA02747 United States Center for Scientific Computing and Visualization Research University of Massachusetts DartmouthMA02747 United States Kavli Institute for Theoretical Physics University of California Santa BarbaraCA93106 United States LIGO Laboratory Massachusetts Institute of Technology 185 Albany St CambridgeMA02139 United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States School of Physics and Astronomy Monash University Vic3800 Australia OzGrav: The ARC Centre of Excellence for Gravitational Wave Discovery ClaytonVIC3800 Australia

Intermediate mass ratio inspiral (IMRI) binaries—containing stellar-mass black holes coalescing into intermediate-mass black holes (M > 100Mo )—are a highly anticipated source of gravitational waves (GWs) for Advanced LIGO/Virgo. Their detection and source characterization would provide a unique probe of strong-field gravity and stellar evolution. Due to the asymmetric component masses and the large primary, these systems generically excite subdominant modes while reducing the importance of the dominant quadrupole mode. Including higher order harmonics can also result in a 10% − 25% increase in signal-to-noise ratio for IMRIs, which may help to detect these systems. We show that by including subdominant GW modes into the analysis we can achieve a precise characterization of IMRI source properties. For example, we find that the source properties for IMRIs can be measured to within 2% − 15% accuracy at a fiducial signal-to-noise ratio of 25 if subdominant modes are included. When subdominant modes are neglected, the accuracy degrades to 9% − 44% and significant biases are seen in chirp mass, mass ratio, primary spin and luminosity distances. We further demonstrate that including subdominant modes in the waveform model can enable an informative measurement of both individual spin components and improve the source localization by a factor of ∼10. We discuss some important astrophysical implications of high-precision source characterization enabled by subdominant modes such as constraining the mass gap and probing formation channels. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal to noise ratio

Divergences in gravitational-wave emission and absorption from extreme mass ratio binaries

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arXiv 2021年

作者： Barausse, Enrico Berti, Emanuele Cardoso, Vitor Hughes, Scott A. Khanna, Gaurav SISSA Via Bonomea 265 Trieste34136 Italy INFN Sezione di Trieste IFPU - Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34014 Italy Department of Physics and Astronomy Johns Hopkins University 3400 N. Charles Street BaltimoreMD21218 United States CENTRA Departamento de Física Instituto Superior Técnico - IST Universidade de Lisboa - UL Avenida Rovisco Pais 1 Lisboa1049 Portugal Department of Physics MIT Kavli Institute Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics University of Rhode Island KingstonRI02881 United States Center for Scientific Computing & Visualization Research Physics Department University of Massachusetts DartmouthMA02747 United States

A powerful technique to calculate gravitational radiation from binary systems involves a perturbative expansion: if the masses of the two bodies are very different, the "small" body is treated as a point particle of mass mp moving in the gravitational field generated by the large mass M, and one keeps only linear terms in the small mass ratio mp/M. This technique usually yields finite answers, which are often in good agreement with fully nonlinear numerical relativity results, even when extrapolated to nearly comparable mass ratios. Here we study two situations in which the point-particle approximation yields a divergent result: the instantaneous flux emitted by a small body as it orbits the light ring of a black hole, and the total energy absorbed by the horizon when a small body plunges into a black hole. By integrating the Teukolsky (or Zerilli/Regge-Wheeler) equations in the frequency and time domains we show that both of these quantities diverge. We find that these divergences are an artifact of the point-particle idealization, and are able to interpret and regularize this behavior by introducing a finite size for the point particle. These divergences do not play a role in black-hole imaging, e.g. by the Event Horizon Telescope. Copyright © 2021, The Authors. All rights reserved.

关键词： Time domain analysis

Bayesian Inference for Gravitational Waves from Binary Neutron Star Mergers in Third Generation Observatories

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Physical Review Letters 2021年第8期127卷 081102-081102页

作者： Rory Smith Ssohrab Borhanian Bangalore Sathyaprakash Francisco Hernandez Vivanco Scott E. Field Paul Lasky Ilya Mandel Soichiro Morisaki David Ottaway Bram J. J. Slagmolen Eric Thrane Daniel Töyrä Salvatore Vitale School of Physics and Astronomy Monash University Victoria 3800 Australia OzGrav: The ARC Centre of Excellence for Gravitational Wave Discovery Clayton Victoria 3800 Australia Institute for Gravitation and the Cosmos Department of Physics Pennsylvania State University University Park Pennsylvania 16802 USA Department of Astronomy and Astrophysics Pennsylvania State University University Park Pennsylvania 16802 USA School of Physics and Astronomy Cardiff University Cardiff CF24 3AA United Kingdom Department of Mathematics and Center for Scientific Computing and Visualization Research University of Massachusetts Dartmouth Massachusetts 02747 USA Department of Physics University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav University of Adelaide Adelaide South Australia 5005 Australia OzGrav ANU Centre for Gravitational Astrophysics Research Schools of Physics and Astronomy and Astrophysics The Australian National University Australian Capital Territory 2601 Australia LIGO Laboratory Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge Massachusetts 02139 USA

Third generation (3G) gravitational-wave detectors will observe thousands of coalescing neutron star binaries with unprecedented fidelity. Extracting the highest precision science from these signals is expected to be challenging owing to both high signal-to-noise ratios and long-duration signals. We demonstrate that current Bayesian inference paradigms can be extended to the analysis of binary neutron star signals without breaking the computational bank. We construct reduced-order models for ∼90-min-long gravitational-wave signals covering the observing band (5–2048 Hz), speeding up inference by a factor of ∼1.3×104 compared to the calculation times without reduced-order models. The reduced-order models incorporate key physics including the effects of tidal deformability, amplitude modulation due to Earth’s rotation, and spin-induced orbital precession. We show how reduced-order modeling can accelerate inference on data containing multiple overlapping gravitational-wave signals, and determine the speedup as a function of the number of overlapping signals. Thus, we conclude that Bayesian inference is computationally tractable for the long-lived, overlapping, high signal-to-noise-ratio events present in 3G observatories.

关键词： Experimental studies of gravity Gravitational waves

Eccentric binary black hole surrogate models for the gravitational waveform and remnant properties: Comparable mass, nonspinning case

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arXiv 2021年

作者： Islam, Tousif Varma, Vijay Lodman, Jackie Field, Scott E. Khanna, Gaurav Scheel, Mark A. Pfeiffer, Harald P. Gerosa, Davide Kidder, Lawrence E. Department of Physics University of Massachusetts DartmouthMA02747 United States Department of Mathematics University of Massachusetts DartmouthMA02747 United States Center for Scientific Computing and Visualization Research University of Massachusetts DartmouthMA02747 United States Department of Physics Cornell University IthacaNY14853 United States Cornell Center for Astrophysics and Planetary Science Cornell University IthacaNY14853 United States TAPIR 350-17 California Institute of Technology 1200 E California Boulevard PasadenaCA91125 United States Department of Physics University of Rhode Island KingstonRI02881 United States Max Planck Institute for Gravitational Physics Albert Einstein Institute Am Mühlenberg 1 Potsdam14476 Germany School of Physics and Astronomy Institute for Gravitational Wave Astronomy University of Birmingham BirminghamB15 2TT United Kingdom

We develop new strategies to build numerical relativity surrogate models for eccentric binary black hole systems, which are expected to play an increasingly important role in current and future gravitational-wave detectors. We introduce a new surrogate waveform model, NRSur2dq1Ecc, using 47 nonspinning, equal-mass waveforms with eccentricities up to 0.2 when measured at a reference time of 5500M before merger. This is the first waveform model that is directly trained on eccentric numerical relativity simulations and does not require that the binary circularizes before merger. The model includes the (2, 2), (3, 2), and (4, 4) spin-weighted spherical harmonic modes. We also build a final black hole model, NRSur2dq1EccRemnant, which models the mass, and spin of the remnant black hole. We show that our waveform model can accurately predict numerical relativity waveforms with mismatches ≈ 10−3, while the remnant model can recover the final mass and dimensionless spin with absolute errors smaller than ≈ 5 × 10−4M and ≈ 2 × 10−3 respectively. We demonstrate that the waveform model can also recover subtle effects like mode-mixing in the ringdown signal without any special ad-hoc modeling steps. Finally, we show that despite being trained only on equal-mass binaries, NRSur2dq1Ecc can be reasonably extended up to mass ratio q ≈ 3 with mismatches ' 10−2 for eccentricities smaller than ∼ 0.05 as measured at a reference time of 2000M before merger. The methods developed here should prove useful in the building of future eccentric surrogate models over larger regions of the parameter space. © 2021, CC BY.

关键词： Merging