标题
Massively parallel Bayesian inference for transient gravitational-wave astronomy
作者
关键词
-
出版物
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 498, Issue 3, Pages 4492-4502
出版商
Oxford University Press (OUP)
发表日期
2020-08-18
DOI
10.1093/mnras/staa2483
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- The UTMOST pulsar timing programme II: Timing noise across the pulsar population
- (2020) M E Lower et al. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
- dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences
- (2020) Joshua S Speagle MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
- Science case for the Einstein telescope
- (2020) Michele Maggiore et al. JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS
- PyCBC Inference: A Python-based Parameter Estimation Toolkit for Compact Binary Coalescence Signals
- (2019) C. M. Biwer et al. PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC
- Properties of the Binary Neutron Star Merger GW170817
- (2019) B. P. Abbott et al. Physical Review X
- Tests of General Relativity with GW170817
- (2019) B. P. Abbott et al. PHYSICAL REVIEW LETTERS
- Optimal Search for an Astrophysical Gravitational-Wave Background
- (2018) Rory Smith et al. Physical Review X
- GW170817: Measurements of Neutron Star Radii and Equation of State
- (2018) B. P. Abbott et al. PHYSICAL REVIEW LETTERS
- Detection methods for stochastic gravitational-wave backgrounds: a unified treatment
- (2017) Joseph D. Romano et al. Living Reviews in Relativity
- Tests of General Relativity with GW150914
- (2016) B. P. Abbott et al. PHYSICAL REVIEW LETTERS
- Bayeswave: Bayesian inference for gravitational wave bursts and instrument glitches
- (2015) Neil J Cornish et al. CLASSICAL AND QUANTUM GRAVITY
- polychord: next-generation nested sampling
- (2015) W. J. Handley et al. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
- Novel scheme for rapid parallel parameter estimation of gravitational waves from compact binary coalescences
- (2015) C. Pankow et al. PHYSICAL REVIEW D
- Parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library
- (2015) J. Veitch et al. PHYSICAL REVIEW D
- Accelerated Gravitational Wave Parameter Estimation with Reduced Order Modeling
- (2015) Priscilla Canizares et al. PHYSICAL REVIEW LETTERS
- Frequency-domain reduced order models for gravitational waves from aligned-spin compact binaries
- (2014) Michael Pürrer CLASSICAL AND QUANTUM GRAVITY
- Inspiral-merger-ringdown waveforms of spinning, precessing black-hole binaries in the effective-one-body formalism
- (2014) Yi Pan et al. PHYSICAL REVIEW D
- Simple Model of Complete Precessing Black-Hole-Binary Gravitational Waveforms
- (2014) Mark Hannam et al. PHYSICAL REVIEW LETTERS
- Fast Prediction and Evaluation of Gravitational Waveforms Using Surrogate Models
- (2014) Scott E. Field et al. Physical Review X
- Comparison of sampling techniques for Bayesian parameter estimation
- (2013) Rupert Allison et al. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
- Low-frequency gravitational-wave science with eLISA/NGO
- (2012) Pau Amaro-Seoane et al. CLASSICAL AND QUANTUM GRAVITY
- Scientific objectives of Einstein Telescope
- (2012) B Sathyaprakash et al. CLASSICAL AND QUANTUM GRAVITY
- Parallel distributed computing using Python
- (2011) Lisandro D. Dalcin et al. ADVANCES IN WATER RESOURCES
- Properties of nested sampling
- (2010) N. Chopin et al. BIOMETRIKA
- Bayesian coherent analysis of in-spiral gravitational wave signals with a detector network
- (2010) J. Veitch et al. PHYSICAL REVIEW D
- MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics
- (2009) F. Feroz et al. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
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