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arXiv 2023年

作者： Islam, Tousif Vajpeyi, Avi Shaik, Feroz H. Haster, Carl-Johan Varma, Vijay Field, Scott E. Lange, Jacob O’Shaughnessy, Richard Smith, Rory Department of Mathematics University of Massachusetts DartmouthMA02747 United States Center for Scientific Computing and Data Science Research University of Massachusetts DartmouthMA02747 United States Department of Statistics The University of Auckland New Zealand School of Physics and Astronomy Monash University VIC3800 Australia OzGrav The ARC Centre of Excellence for Gravitational Wave Discovery ClaytonVIC3800 Australia Department of Physics and Astronomy University of Nevada Las Vegas 4505 South Maryland Parkway Las VegasNV89154 United States Nevada Center for Astrophysics University of Nevada Las VegasNV89154 United States LIGO Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology 77 Massachusetts Ave CambridgeMA02139 United States Max Planck Institute for Gravitational Physics Albert Einstein Institute PotsdamD-14476 Germany Center for Computational Relativity and Gravitation Rochester Institute of Technology RochesterNY14623 United States University of Texas AustinTX78712 United States

The third Gravitational-Wave Transient Catalog (GWTC-3) contains 90 binary coalescence candidates detected by the LIGO-Virgo-KAGRA Collaboration (LVK). We provide a re-analysis of binary black hole (BBH) events using a recently developed numerical relativity (NR) waveform surrogate model, NRSur7dq4, that includes all ≤ 4 spin-weighted spherical harmonic modes as well as the complete physical effects of precession. Properties of the remnant black holes’ (BH’s) mass, spin vector, and kick vector are found using an associated remnant surrogate model NRSur7dq4Remnant. Both NRSur7dq4 and NRSur7dq4Remnant models have errors comparable to numerical relativity simulations and allow for high-accuracy parameter estimates. We restrict our analysis to 47 BBH events that fall within the regime of validity of NRSur7dq4 (mass ratios greater than 1/6 and total masses greater than 60M☉). While for most of these events our results match the LVK analyses that were obtained using the semi-analytical models such as IMRPhenomXPHM and SEOBNRv4PHM, we find that for more than 20% of events the NRSur7dq4 model recovers noticeably different measurements of black hole properties like the masses and spins, as well as extrinsic properties like the binary inclination and distance. For instance, GW150914_095045 exhibits noticeable differences in spin precession and spin magnitude measurements. Other notable findings include one event (GW191109_010717) that constrains the effective spin χeff to be negative at a 99.3% credible level and two events (GW191109_010717 and GW200129_065458) with well-constrained kick velocities. Furthermore, compared to the models used in the LVK analyses, NRSur7dq4 recovers a larger signal-to-noise ratio and/or Bayes factors for several events. While these findings have important astrophysical implications, some of the more interesting events are affected by transient detector noise, which can be challenging to remove from short-duration signals. Copyright © 2023, The Au

关键词： Black holes

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Exploration of Differentiability in a Proton Computed Tomography Simulation Framework

arXiv

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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

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Multiscale Modelling of the Antiferromagnet Mn2Au: From ab-initio to Micromagnetics

arXiv

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arXiv 2022年

作者： Hirst, Joel Atxitia, Unai Ruta, Sergiu Jackson, Jerome Petit, Leon Ostler, Thomas Materials & Engineering Research Institute Sheffield Hallam University Howard Street SheffieldS1 1WB United Kingdom Dahlem Center for Complex Quantum Systems and Fachbereich Physik Freie Universitat Berlin Berlin14195 Germany Instituto de Ciencia de Materiales de Madrid CSIC Cantoblanco Madrid28049 Spain Scientific Computing Department STFC Daresbury Laboratory Warrington WA4 4AD United Kingdom Department of Physics & Mathematics University of Hull HullHU6 7RX United Kingdom Department of Engineering and Mathematics Sheffield Hallam University Howard Street SheffieldS1 1WB United Kingdom

Antiferromagnets (AFMs) are strong candidates for the future spintronic and memory applications largely because of their inherently fast dynamics and lack of stray fields, with Mn2Au being one of the most promising. For the numerical modelling of magnetic material properties, it is common to use ab-initio methods, atomistic models and micromagnetics. However, each method alone describes the physics within certain limits. Multiscale methods bridging the gap between these three approaches have been already proposed for ferromagnetic materials. Here, we present a complete multiscale model of the AFM Mn2Au as an exemplar material, starting with results from ab-initio methods going via atomistic spin dynamics (ASD) to an AFM Landau-Lifshitz-Bloch (AFM-LLB) model. Firstly, bulk Mn2Au is modelled using a classical spin Hamiltonian constructed based on earlier first-principles calculations. Secondly, this spin model is used in the stochastic Landau-Lifshitz-Gilbert (LLG) to calculate temperature-dependent equilibrium properties, such as magnetization and magnetic susceptibilities. Thirdly, the temperature dependent micromagnetic parameters are used in the AFM-LLB. We validate our approach by comparing the ASD and AFM-LLB models for three paradigmatic cases;(i) Damped magnetic oscillations, (ii) magnetization dynamics following a heat pulse resembling pump-probe experiments, (iii) magnetic domain wall motion under thermal gradients. © 2022, CC BY.

关键词： Magnetization

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Extending black-hole remnant surrogate models to extreme mass ratios

引用

Physical Review D 2023年第8期108卷 084015-084015页

作者： Matteo Boschini Davide Gerosa Vijay Varma Cristóbal Armaza Michael Boyle Marceline S. Bonilla Andrea Ceja Yitian Chen Nils Deppe Matthew Giesler Lawrence E. Kidder Prayush Kumar Guillermo Lara Oliver Long Sizheng Ma Keefe Mitman Peter James Nee Harald P. Pfeiffer Antoni Ramos-Buades Mark A. Scheel Nils L. Vu Jooheon Yoo Dipartimento di Fisica “G. Occhialini ” Universitá degli Studi di Milano-Bicocca Piazza della Scienza 3 20126 Milano Italy Max Planck Institute for Gravitational Physics (Albert Einstein Institute) Am Mühlenberg 1 Potsdam 14476 Germany INFN Sezione di Milano-Bicocca Piazza della Scienza 3 20126 Milano Italy School of Physics and Astronomy & Institute for Gravitational Wave Astronomy University of Birmingham Birmingham B15 2TT United Kingdom Department of Mathematics Center for Scientific Computing and Data Science Research University of Massachusetts Dartmouth Massachusetts 02747 USA Cornell Center for Astrophysics and Planetary Science Cornell University Ithaca New York 14853 USA Nicholas and Lee Begovich Center for Gravitational-Wave Physics and Astronomy California State University Fullerton Fullerton California 92831 USA TAPIR 350-17 California Institute of Technology 1200 E California Boulevard Pasadena California 91125 USA Department of Physics Cornell University Ithaca New York 14853 USA International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bangalore 560089 India

Numerical-relativity surrogate models for both black-hole merger waveforms and remnants have emerged as important tools in gravitational-wave astronomy. While producing very accurate predictions, their applicability is limited to the region of the parameter space where numerical-relativity simulations are available and computationally feasible. Notably, this excludes extreme mass ratios. We present a machine-learning approach to extend the validity of existing and future numerical-relativity surrogate models toward the test-particle limit, targeting in particular the mass and spin of postmerger black-hole remnants. Our model is trained on both numerical-relativity simulations at comparable masses and analytical predictions at extreme mass ratios. We extend the gaussian-process-regression model NRSur7dq4Remnant, validate its performance via cross validation, and test its accuracy against additional numerical-relativity runs. Our fit, which we dub NRSur7dq4EmriRemnant, reaches an accuracy that is comparable to or higher than that of existing remnant models while providing robust predictions for arbitrary mass ratios.

关键词： Classical black holes Gravitational wave sources Gravitational waves Astronomical black holes Numerical relativity

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Improved Fitness Dependent Optimizer for Solving Economic Load Dispatch Problem

arXiv

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arXiv 2022年

作者： Tahir, Barzan Hussein Rashid, Tarik A. Rauf, Hafiz Tayyab Bacanin, Nebojsa Chhabra, Amit Vimal, S. Yaseen, Zaher Mundher Department of Computer Science and Engineering University of Kurdistan Helwer Erbil Iraq Centre for Smart Systems AI and Cybersecurity Staffordshire University Stoke-on-Trent United Kingdom Singidunum University Danijelova 32 Belgrade11000 Serbia Department of Computer Engineering and Technology Guru Nanak Dev University Amritsar India Department of Artificial Intelligence and Data Science Ramco Institute of Technology North Venganallur Village Virudhunagar District Tamilnadu Rajapalayam626 117 India Department of Earth Sciences and Environment Faculty of Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia USQ's Advanced Data Analytics Research Group School of Mathematics Physics and Computing University of Southern Queensland QLD4350 Australia New era and Development in Civil Engineering Research Group Scientific Research Center Al-Ayen University Thi-Qar64001 Iraq

Economic Load Dispatch depicts a fundamental role in the operation of power systems, as it decreases the environmental load, minimizes the operating cost, and preserves energy resources. The optimal solution to Economic Load Dispatch problems and various constraints can be obtained by evolving several evolutionary and swarm-based algorithms. The major drawback to swarm-based algorithms is premature convergence towards an optimal solution. Fitness Dependent Optimizer is a novel optimization algorithm stimulated by the decision-making and reproductive process of bee swarming. Fitness Dependent Optimizer (FDO) examines the search spaces based on the searching approach of Particle Swarm Optimization. To calculate the pace, the fitness function is utilized to generate weights that direct the search agents in the phases of exploitation and exploration. In this research, the authors have carried out Fitness Dependent Optimizer to solve the Economic Load Dispatch problem by reducing fuel cost, emission allocation, and transmission loss. Moreover, the authors have enhanced a novel variant of Fitness Dependent Optimizer, which incorporates novel population initialization techniques and dynamically employed sine maps to select the weight factor for Fitness Dependent Optimizer. The enhanced population initialization approach incorporates a quasi-random Sabol sequence to generate the initial solution in the multi-dimensional search space. A standard 24-unit system is employed for experimental evaluation with different power demands. Empirical results obtained using the enhanced variant of the Fitness Dependent Optimizer demonstrate superior performance in terms of low transmission loss, low fuel cost, and low emission allocation compared to the conventional Fitness Dependent Optimizer. The experimental study obtained 7.94E-12, the lowest transmission loss using the enhanced Fitness Dependent Optimizer. Correspondingly, various standard estimations are used to prove the stability

关键词： Decision making

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A computational model for investigating the evolution of colonic crypts during Lynch syndrome carcinogenesis

Computational and Systems Oncology

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Computational and Systems Oncology 2021年第2期1卷

作者： Haupt, Saskia Gleim, Nils Ahadova, Aysel Bläker, Hendrik von Knebel Doeberitz, Magnus Kloor, Matthias Heuveline, Vincent Engineering Mathematics and Computing Lab (EMCL) Interdisciplinary Center for Scientific Computing (IWR) Heidelberg University Heidelberg Germany Data Mining and Uncertainty Quantification (DMQ) Heidelberg Institute for Theoretical Studies (HITS) Heidelberg Germany Department of Applied Tumor Biology (ATB) Institute of Pathology University Hospital Heidelberg Heidelberg Germany Clinical Cooperation Unit Applied Tumor Biology German Cancer Research Center Heidelberg Germany Institute of Pathology University Hospital Leipzig Leipzig Germany

Lynch syndrome (LS), the most common inherited colorectal cancer (CRC) syndrome, increases the cancer risk in affected individuals. LS is caused by pathogenic germline variants in one of the DNA mismatch repair (MMR) genes, complete inactivation of which causes numerous mutations in affected cells. As CRC is believed to originate in colonic crypts, understanding the intra-crypt dynamics caused by mutational processes is essential for a complete picture of LS CRC and may have significant implications for cancer prevention. We propose a computational model describing the evolution of colonic crypts during LS carcinogenesis. Extending existing modeling approaches for the non-Lynch scenario, we incorporated MMR deficiency and implemented recent experimental data demonstrating that somatic CTNNB1 mutations are common drivers of LS-associated CRCs, if affecting both alleles of the gene. Further, we simulated the effect of different mutations on the entire crypt, distinguishing non-transforming and transforming mutations. As an example, we analyzed the spread of mutations in the genes APC and CTNNB1, which are frequently mutated in LS tumors, as well as of MMR deficiency itself. We quantified each mutation's potential for monoclonal conversion and investigated the influence of the cell location and of stem cell dynamics on mutation spread. The in silico experiments underline the importance of stem cell dynamics for the overall crypt evolution. Further, simulating different mutational processes is essential in LS since mutations without survival advantages (the MMR deficiency-inducing second hit) play a key role. The effect of other mutations can be simulated with the proposed model. Our results provide first mathematical clues towards more effective surveillance protocols for LS carriers. © 2021 The Authors. Computational and Systems Oncology published by Wiley Periodicals LLC.

关键词： Carcinogenesis Colonic Crypts Colorectal Cancer Computational Modeling Lynch Syndrome Monoclonal Conversion Voronoi Tessellation Model

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An aggregation-based nonlinear multigrid solver for two-phase flow and transport in porous media

arXiv

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arXiv 2021年

作者： Lee, Chak Shing Hamon, François P. Castelletto, Nicola Vassilevski, Panayot S. White, Joshua A. Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 United States TotalEnergies E&P Research and Technology HoustonTX77002 United States Atmospheric Earth and Energy Division Lawrence Livermore National Laboratory LivermoreCA94550 United States Fariborz Maseeh Department of Mathematics and Statistics Portland State University PortlandOR97201 United States

MSC Codes 65M55, 65M08A nonlinear multigrid solver for two-phase flow and transport in a mixed fractional-flow velocity-pressure-saturation formulation is proposed. The solver, which is under the framework of the full approximation scheme (FAS), extends our previous work on nonlinear multigrid for heterogeneous diffusion problems. The coarse spaces in the multigrid hierarchy are constructed by first aggregating degrees of freedom, and then solving some local flow problems. The mixed formulation and the choice of coarse spaces allow us to assemble the coarse problems without visiting finer levels during the solving phase, which is crucial for the scalability of multigrid methods. Specifically, a natural generalization of the upwind flux can be evaluated directly on coarse levels using the precomputed coarse flux basis vectors. The resulting solver is applicable to problems discretized on general unstructured grids. The performance of the proposed nonlinear multigrid solver in comparison with the standard single level Newton's method is demonstrated through challenging numerical examples. It is observed that the proposed solver is robust for highly nonlinear problems and clearly outperforms Newton's method in the case of high Courant-Friedrichs-Lewy (CFL) numbers. Copyright © 2021, The Authors. All rights reserved.

关键词： Two phase flow

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A coupling strategy for a 3D-1D model of the cardiovascular system to study the effects of pulse wave propagation on cardiac function

arXiv

引用

arXiv 2021年

作者： Caforio, Federica Augustin, Christoph M. Alastruey, Jordi Gsell, Matthias A.F. Plank, Gernot Institute of Mathematics and Scientific Computing NAWI Graz University of Graz Graz Austria Gottfried Schatz Research Center Division of Biophysics Medical University of Graz Graz Austria Department of Biomedical Engineering Division of Imaging Sciences and Biomedical Engineering King’s College London King’s Health Partners St. Thomas’ Hospital LondonSE1 7EH United Kingdom World-Class Research Center "Digital Biodesign and Personalized Healthcare" Sechenov University Moscow Russia

The impact of increased stiffness and pulsatile load on the circulation and their influence on heart performance have been documented not only for cardiovascular events but also for ventricular dysfunctions. For this reason, computer models of cardiac electromechanics (EM) have to integrate effects of the circulatory system on heart function to be relevant for clinical applications. Currently it is not feasible to consider three-dimensional (3D) models of the entire circulation. Instead, simplified representations of the circulation are used, ensuring a satisfactory trade-off between accuracy and computational cost. In this work, we propose a novel and stable strategy to couple a 3D EM model of the heart to a one-dimensional (1D) model of blood flow in the arterial system. A personalised coupled 3D-1D model of LV and arterial system is built and used in a numerical benchmark to demonstrate robustness and accuracy of our scheme over a range of time steps. Validation of the coupled model is performed by investigating the coupled system’s physiological response to variations in the arterial system affecting pulse wave propagation, comprising aortic stiffening, aortic stenosis or bifurcations causing wave reflections. Our results show that the coupled 3D-1D model is robust, stable and correctly replicates known physiology. In comparison with standard coupled 3D-0D models, additional computational costs are negligible, thus facilitating the use of our coupled 3D-1D model as a key methodology in studies where wave propagation effects are under investigation. © 2021, CC BY-NC-ND.

关键词： Heart

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Extending black-hole remnant surrogate models to extreme mass ratios

arXiv

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arXiv 2023年

作者： Boschini, Matteo Gerosa, Davide Varma, Vijay Armaza, Cristóbal Boyle, Michael Bonilla, Marceline S. Ceja, Andrea Chen, Yitian Deppe, Nils Giesler, Matthew Kidder, Lawrence E. Kumar, Prayush Lara, Guillermo Long, Oliver Ma, Sizheng Mitman, Keefe Nee, Peter James Pfeiffer, Harald P. Ramos-Buades, Antoni Scheel, Mark A. Vu, Nils L. Yoo, Jooheon Dipartimento di Fisica "G. Occhialini" Universitá degli Studi di Milano-Bicocca Piazza della Scienza 3 Milano20126 Italy Am Mühlenberg 1 Potsdam14476 Germany INFN Sezione di Milano-Bicocca Piazza della Scienza 3 Milano20126 Italy School of Physics and Astronomy Institute for Gravitational Wave Astronomy University of Birmingham BirminghamB15 2TT United Kingdom Department of Mathematics Center for Scientific Computing and Data Science Research University of Massachusetts DartmouthMA02747 United States Cornell Center for Astrophysics and Planetary Science Cornell University IthacaNY14853 United States Nicholas and Lee Begovich Center for Gravitational-Wave Physics and Astronomy California State University FullertonCA92831 United States TAPIR 350-17 California Institute of Technology 1200 E California Boulevard PasadenaCA91125 United States Department of Physics Cornell University IthacaNY14853 United States International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bangalore560089 India

Numerical-relativity surrogate models for both black-hole merger waveforms and remnants have emerged as important tools in gravitational-wave astronomy. While producing very accurate predictions, their applicability is limited to the region of the parameter space where numerical-relativity simulations are available and computationally feasible. Notably, this excludes extreme mass ratios. We present a machine-learning approach to extend the validity of existing and future numerical-relativity surrogate models toward the test-particle limit, targeting in particular the mass and spin of post-merger black-hole remnants. Our model is trained on both numerical-relativity simulations at comparable masses and analytical predictions at extreme mass ratios. We extend the gaussian-process-regression model NRSur7dq4Remnant, validate its performance via cross validation, and test its accuracy against additional numerical-relativity runs. Our fit, which we dub NRSur7dq4EmriRemnant, reaches an accuracy that is comparable to or higher than that of existing remnant models while providing robust predictions for arbitrary mass ratios. Copyright © 2023, The Authors. All rights reserved.

关键词： Black holes

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

arXiv

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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

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