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arXiv 2024年

作者： Zertuche, Lorena Magaña Stein, Leo C. Mitman, Keefe Field, Scott E. Varma, Vijay Boyle, Michael Deppe, Nils Kidder, Lawrence E. Moxon, Jordan Pfeiffer, Harald P. Scheel, Mark A. Nelli, Kyle C. Throwe, William Vu, Nils L. Department of Physics and Astronomy University of Mississippi UniversityMS38677 United States Theoretical Astrophysics 350-17 California Institute of Technology PasadenaCA91125 United States Department of Mathematics Center for Scientific Computing & Visualization Research University of Massachusetts DartmouthMA02747 United States Department of Physics Center for Computational Research East Hall University of Rhode Island KingstonRI02881 United States Cornell Center for Astrophysics and Planetary Science Cornell University IthacaNY14853 United States Laboratory for Elementary Particle Physics Cornell University IthacaNY14853 United States Department of Physics Cornell University IthacaNY14853 United States Am Mühlenberg 1 Potsdam14476 Germany

Highly precise and robust waveform models are required as improvements in detector sensitivity enable us to test general relativity with more precision than ever before. In this work, we introduce a spin-aligned surrogate ringdown model. This ringdown surrogate, NRSur3dq8_RD, is built with numerical waveforms produced using Cauchy-characteristic evolution. In addition, these waveforms are in the superrest frame of the remnant black hole allowing us to do a correct analysis of the ringdown spectrum. The novel prediction of our surrogate model is complex-valued quasinormal mode (QNM) amplitudes, with median relative errors of 10−2 − 10−3 over the parameter space. Like previous remnant surrogates, we also predict the remnant black hole’s mass and spin. The QNM mode amplitude errors translate into median errors on ringdown waveforms of ∼ 10−4. The high accuracy and QNM mode content provided by our surrogate will enable high-precision ringdown analyses such as tests of general relativity. Our ringdown model is publicly available through the python package surfinBH. Copyright © 2024, The Authors. All rights reserved.

关键词： Relativity

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Surrogate model for gravitational wave signals from nonspinning, comparable-to large-mass-ratio black hole binaries built on black hole perturbation theory waveforms calibrated to numerical relativity

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Physical Review D 2022年第10期106卷 104025-104025页

作者： Tousif Islam Scott E. Field Scott A. Hughes Gaurav Khanna Vijay Varma Matthew Giesler Mark A. Scheel Lawrence E. Kidder Harald P. Pfeiffer 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 of Theoretical Physics University of California Santa Barbara Santa Barbara California 93106 USA 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 Max Planck Institute for Gravitational Physics (Albert Einstein Institute) Am Mühlenberg 1 Potsdam 14476 Germany Cornell Center for Astrophysics and Planetary Science Cornell University Ithaca New York 14853 USA Theoretical Astrophysics Walter Burke Institute for Theoretical Physics California Institute of Technology Pasadena California 91125 USA

We present a reduced-order surrogate model of gravitational waveforms from nonspinning binary black hole systems with comparable to large mass-ratio configurations. This surrogate model, BHPTNRSur1dq1e4, is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT) with mass ratios varying from 2.5 to 10,000. BHPTNRSur1dq1e4 extends an earlier waveform model, EMRISur1dq1e4, by using an updated transition-to-plunge model, covering longer durations up to 30,500m1 (where m1 is the mass of the primary black hole), includes several more spherical harmonic modes up to ℓ=10, and calibrates subdominant modes to numerical relativity (NR) data. In the comparable mass-ratio regime, including mass ratios as low as 2.5, the gravitational waveforms generated through ppBHPT agree surprisingly well with those from NR after this simple calibration step. We also compare our model to recent SXS and RIT NR simulations at mass ratios ranging from 15 to 32, and find the dominant quadrupolar modes agree to better than ≈10−3. We expect our model to be useful to study intermediate-mass-ratio binary systems in current and future gravitational-wave detectors.

关键词： Gravitational waves

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IDEAS: Immersive dome experiences for accelerating science

arXiv

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arXiv 2019年

作者： Faherty, Jacqueline K. SubbaRao, Mark Wyatt, Ryan Ynnerman, Anders deGrasse Tyson, Neil Geller, Aaron Weber, Maria Rosenfield, Philip Stoeckle, Gabriel Weiskopf, Daniel Magnor, Marcus Williams, Peter K.G. Abbott, Brian Marchetti, Lucia Jarrrett, Thomas Fay, Jonathan Peek, Joshua Graur, Or Durrell, Patrick Homeier, Derek Preston, Heather Müller, Thomas Vos, Johanna M. Brown, David Godfrey, Paige Giorla Rice, Emily Gagliuffi, Daniella Bardalez Bock, Alexander American Museum of Natural History Hayden Planetarium Adler Planetarium International Planetarium Society California Academy of Sciences Linköping University Adler Planetarium University of Chicago AAS WorldWide Telescope Instituto de Astronomiá UNAM Natural History Museum Vienna Austria Visualization Research Center University of Stuttgart Computer Graphics Lab TU Braunschweig Center for Astrophysics | Harvard & Smithsonian American Astronomical Society American Museum of Natural History Hayden Planetarium University of Cape Town Iziko Planetarium & Digital Dome Space Telescope Science Institute Johns Hopkins University Youngstown State University Ward Beecher Planetarium Förderkreis Planetarium Göttingen Germany Calusa Nature Center & Planetarium Haus der Astronomie MPIA Microsoft Research Slooh CUNY Macaulay Honors College Scientific Computing and Imaging Institute University of Utah

Astrophysics lies at the crossroads of big datasets (such as the Large Synoptic Survey Telescope and Gaia), open source software to visualize and interpret high dimensional datasets (such as Glue, WorldWide Telescope, and OpenSpace), and uniquely skilled software engineers who bridge data science and research fields. At the same time, more than 4,000 planetariums across the globe immerse millions of visitors in scientific data. We have identified the potential for critical synergy across data, software, hardware, locations, and content that-if prioritized over the next decade-will drive discovery in astronomical research. Planetariums can and should be used for the advancement of scientific research. Current facilities such as the Hayden Planetarium in New York City, Adler Planetarium in Chicago, Morrison Planetarium in San Francisco, the Iziko Planetarium & Digital Dome Research Consortium in Cape Town, and visualization center C in Norrköping are already developing software which ingests catalogs of astronomical and multi-disciplinary data critical for exploration research primarily for the purpose of creating scientific storylines for the general public. We propose a transformative model whereby scientists become the audience and explorers in planetariums, utilizing software for their own investigative purposes. In this manner, research benefits from the authentic and unique experience of data immersion contained in an environment bathed in context and equipped for collaboration. Consequently, in this white paper we argue that over the next decade the research astronomy community should partner with planetariums to create visualization-based research opportunities for the field. Realizing this vision will require new investments in software and human capital. Copyright © 2019, The Authors. All rights reserved.

关键词： Planetariums

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Probability-turbulence divergence: A tunable allotaxonometric instrument for comparing heavy-tailed categorical distributions

arXiv

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arXiv 2020年

作者： Dodds, Peter Sheridan Minot, Joshua R. Arnold, Michael V. Alshaabi, Thayer Adams, Jane Lydia Reagan, Andrew J. Danforth, Christopher M. Computational Story Lab Vermont Complex Systems Center MassMutual Center of Excellence for Complex Systems and Data Science University of Vermont BurlingtonVT05401 United States Vermont Advanced Computing Center University of Vermont BurlingtonVT05401 United States Department of Computer Science University of Vermont BurlingtonVT05401 United States Santa Fe Institute 1399 Hyde Park Rd Santa FeNM87501 United States MassMutual Data Science AmherstMA01002 United States Howard Hughes Medical Institute University of California Berkeley BerkeleyCA94720 United States Data Visualization Lab Khoury College of Computer Sciences Northeastern University BostonMA United States Department of Mathematics & Statistics University of Vermont BurlingtonVT05401 United States

Real-world complex systems often comprise many distinct types of elements as well as many more types of networked interactions between elements. When the relative abundances of types can be measured well, we further observe heavy-tailed categorical distributions for type frequencies. For the comparison of type frequency distributions of two systems or a system with itself at different time points in time—a facet of allotaxonometry—a great range of probability divergences are available. Here, we introduce and explore ‘probability-turbulence divergence’, a tunable, straightforward, and interpretable instrument for comparing normalizable categorical frequency distributions. We model probability-turbulence divergence (PTD) after rank-turbulence divergence (RTD). While probability-turbulence divergence is more limited in application than rank-turbulence divergence, it is more sensitive to changes in type frequency. We build allotaxonographs to display probability turbulence, incorporating a way to visually accommodate zero probabilities for ‘exclusive types’ which are types that appear in only one system. We explore comparisons of example distributions taken from literature, social media, and ecology. We show how probability-turbulence divergence either explicitly or functionally generalizes many existing kinds of distances and measures, including, as special cases, L(p) norms, the Sørensen-Dice coefficient (the F1 statistic), and the Hellinger distance. We discuss similarities with the generalized entropies of Rényi and Tsallis, and the diversity indices (or Hill numbers) from ecology. We close with thoughts on open problems concerning the optimization of the tuning of rank- and probability-turbulence divergence. Copyright © 2020, The Authors. All rights reserved.

关键词： Normal distribution

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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

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Disentangling Alzheimer’s disease neurodegeneration from typical brain aging using machine learning

arXiv

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arXiv 2021年

作者： Hwang, Gyujoon Abdulkadir, Ahmed Erus, Guray Habes, Mohamad Pomponio, Raymond Shou, Haochang Doshi, Jimit Mamourian, Elizabeth Rashid, Tanweer Bilgel, Murat Fan, Yong Sotiras, Aristeidis Srinivasan, Dhivya Morris, John C. Marcus, Daniel Albert, Marilyn S. Bryan, Nick R. Resnick, Susan M. Nasrallah, Ilya M. Davatzikos, Christos Wolk, David A. Center for Biomedical Image Computing and Analytics University of Pennsylvania Philadelphia United States Department of Radiology University of Pennsylvania Philadelphia United States Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases University of Texas Health Science Center at San Antonio San Antonio United States Penn Statistics in Imaging and Visualization Center Department of Biostatistics Epidemiology and Informatics Perelman School of Medicine University of Pennsylvania Philadelphia United States Laboratory of Behavioral Neuroscience National Institute on Aging Baltimore United States Department of Radiology Washington University in St. Louis St. Louis United States Department of Neurology Washington University in St. Louis St. Louis United States Department of Neurology Johns Hopkins University School of Medicine United States Department of Diagnostic Medicine University of Texas AustinAustin United States Department of Neurology Penn Memory Center University of Pennsylvania Philadelphia United States

Neuroimaging biomarkers that distinguish between changes due to typical brain aging and Alzheimer’s disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multi-variate patterns of brain change related to the two processes (including the SPARE-AD [Spatial Patterns of Atrophy for Recognition of Alzheimer’s Disease] and SPARE-BA [of Brain Aging] scores investigated herein). However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, toward disentangling the two. T1-weighted MRI images of 4,054 participants (48–95 years) with Alzheimer’s disease, mild cognitive impairment, or cognitively normal diagnoses from the iSTAGING (Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases) consortium were analyzed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically- or molecularly-defined sub-cohorts. First, a subset of clinical Alzheimer’s disease patients (n = 718) and age- and sex-matched cognitively normal adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using cognitively normal individuals) and SPARE-AD1 (classification of cognitively normal versus Alzheimer’s disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer’s disease continuum group (n = 718;consisting of amyloid-positive Alzheimer’s disease, amyloid-positive mild cognitive impairment, and amyloid- and tau-positive cognitively normal individuals) and amyloid-negative cognitively normal group (n = 718). Finally, the combined group of the Alzheimer’s disease continuum and amyloid-negative cognitively normal individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regar

关键词： Magnetic resonance imaging

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A MULTIGRID REDUCTION FRAMEWORK FOR DOMAINS WITH SYMMETRIES

arXiv

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arXiv 2024年

作者： Alsalti-Baldellou, Àdel Janna, Carlo Álvarez-Farré, Xavier Xavier Trias, F. Department of Information Engineering University of Padova Via Giovanni Gradenigo 6b Padova PD35131 Italy Heat and Mass Transfer Technological Center Universitat Politècnica de Catalunya BarcelonaTech Carrer de Colom 11 Terrassa08222 Spain Department of Civil Environmental and Architectural Engineering University of Padova Via Francesco Marzolo 9 Padova PD35131 Italy M3E S.r.l. Via Giambellino 7 Padova PD35129 Italy High-Performance Computing and Visualization Team SURF Science Park 140 Amsterdam1098 XG Netherlands

Divergence constraints are present in the governing equations of numerous physical phenomena, and they usually lead to a Poisson equation whose solution represents a bottleneck in many simulation codes. Algebraic Multigrid (AMG) is arguably the most powerful preconditioner for Poisson’s equation, and its effectiveness results from the complementary roles played by the smoother, responsible for damping high-frequency error components, and the coarse-grid correction, which in turn reduces low-frequency modes. This work presents several strategies to make AMG more compute-intensive by leveraging reflection, translational and rotational symmetries. AMGR, our final proposal, does not require boundary conditions to be symmetric, therefore applying to a broad range of academic and industrial configurations. It is based on a multigrid reduction framework that introduces an aggressive coarsening to the multigrid hierarchy, reducing the memory footprint, setup and application costs of the top-level smoother. While preserving AMG’s excellent convergence, AMGR allows replacing the standard sparse matrix-vector product with the more compute-intensive sparse matrix-matrix product, yielding significant accelerations. Numerical experiments on industrial CFD applications demonstrated up to 70% speed-ups when solving Poisson’s equation with AMGR instead of AMG. Additionally, strong and weak scalability analyses revealed no significant *** Codes 65F08, 65F50, 65N55, 65Y05 © 2024, CC BY-NC-ND.

关键词： Poisson equation

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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

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Removing degeneracy and multimodality in gravitational wave source parameters

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Physical Review D 2022年第12期106卷 123015-123015页

作者： Javier Roulet Seth Olsen Jonathan Mushkin Tousif Islam Tejaswi Venumadhav Barak Zackay Matias Zaldarriaga Kavli Institute for Theoretical Physics University of California at Santa Barbara Santa Barbara California 93106 USA Department of Physics Princeton University Princeton New Jersey 08540 USA Department of Particle Physics and Astrophysics Weizmann Institute of Science Rehovot 76100 Israel 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 University of California at Santa Barbara Santa Barbara California 93106 USA International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bangalore 560089 India School of Natural Sciences Institute for Advanced Study 1 Einstein Drive Princeton New Jersey 08540 USA

Quasicircular binary black hole mergers are described by 15 parameters, of which gravitational wave observations can typically constrain only ∼10 independent combinations to varying degree. In this work, we devise coordinates that remove correlations, and disentangle well- and poorly-measured quantities. Additionally, we identify approximate discrete symmetries in the posterior as the primary cause of multimodality, and design a method to tackle this type of multimodality. The resulting posteriors have little structure and can be sampled efficiently and robustly. We provide a python package for parameter estimation, cogwheel, that implements these methods together with other algorithms for accelerating the inference process. One of the coordinates we introduce is a spin azimuth that is measured remarkably well in several events. We suggest this might be a sensitive indicator of orbital precession, and we anticipate that it will shed light on the occurrence of spin-orbit misalignment in nature.

关键词： Gravitational waves Astronomical black holes

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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

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