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Accelerated parameter estimation in Bilby with relative binning

Published 10 Dec 2023 in gr-qc and astro-ph.IM | (2312.06009v1)

Abstract: We describe an implementation of the relative binning technique to speed up parameter estimation of gravitational-wave signals. We first give a pedagogical overview of relative binning, discussing also the expressions for the likelihood marginalized over phase and distance. Then, we describe the details of the code in \texttt{Bilby}, an open-source software package commonly used for parameter estimation of gravitational-wave sources. Our code is able to reproduce the parameters of GW170817 in 14 hours on a single-core CPU, performs well on simulated signals, and passes the percentile-percentile (p-p) tests. We also illustrate that relative binning is an ideal technique to estimate the parameters of signals in next-generation gravitational wave detectors.

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References (77)
  1. J. Aasi et al. (LIGO Scientific), “Advanced LIGO,” Class. Quant. Grav. 32, 074001 (2015), arXiv:1411.4547 [gr-qc] .
  2. F. Acernese et al. (VIRGO), “Advanced Virgo: a second-generation interferometric gravitational wave detector,” Class. Quant. Grav. 32, 024001 (2015), arXiv:1408.3978 [gr-qc] .
  3. Kentaro Somiya (KAGRA), “Detector configuration of KAGRA: The Japanese cryogenic gravitational-wave detector,” Class. Quant. Grav. 29, 124007 (2012), arXiv:1111.7185 [gr-qc] .
  4. Yoichi Aso, Yuta Michimura, Kentaro Somiya, Masaki Ando, Osamu Miyakawa, Takanori Sekiguchi, Daisuke Tatsumi,  and Hiroaki Yamamoto (KAGRA), “Interferometer design of the KAGRA gravitational wave detector,” Phys. Rev. D 88, 043007 (2013), arXiv:1306.6747 [gr-qc] .
  5. T. Akutsu et al. (KAGRA), “Overview of KAGRA: Detector design and construction history,” PTEP 2021, 05A101 (2021), arXiv:2005.05574 [physics.ins-det] .
  6. B. P. Abbott et al., “Multi-messenger Observations of a Binary Neutron Star Merger,” Astrophys. J. Lett. 848, L12 (2017a), arXiv:1710.05833 [astro-ph.HE] .
  7. B. P. Abbott et al. (LIGO Scientific, Virgo), “Properties of the binary neutron star merger GW170817,” Phys. Rev. X 9, 011001 (2019a), arXiv:1805.11579 [gr-qc] .
  8. B. P. Abbott et al. (LIGO Scientific, Virgo), “GW170817: Measurements of neutron star radii and equation of state,” Phys. Rev. Lett. 121, 161101 (2018a), arXiv:1805.11581 [gr-qc] .
  9. R. Abbott et al. (LIGO Scientific, Virgo), “Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog,” Astrophys. J. Lett. 913, L7 (2021a), arXiv:2010.14533 [astro-ph.HE] .
  10. R. Abbott et al. (KAGRA, VIRGO, LIGO Scientific), “Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3,” Phys. Rev. X 13, 011048 (2023a), arXiv:2111.03634 [astro-ph.HE] .
  11. R. Abbott et al. (LIGO Scientific, Virgo), “Tests of general relativity with binary black holes from the second LIGO-Virgo gravitational-wave transient catalog,” Phys. Rev. D 103, 122002 (2021b), arXiv:2010.14529 [gr-qc] .
  12. R. Abbott et al. (LIGO Scientific, Virgo, KAGRA), “Constraints on the Cosmic Expansion History from GWTC–3,” Astrophys. J. 949, 76 (2023b), arXiv:2111.03604 [astro-ph.CO] .
  13. John Miller, Lisa Barsotti, Salvatore Vitale, Peter Fritschel, Matthew Evans,  and Daniel Sigg, “Prospects for doubling the range of Advanced LIGO,” Phys. Rev. D 91, 062005 (2015), arXiv:1410.5882 [gr-qc] .
  14. B. P. Abbott et al. (KAGRA, LIGO Scientific, Virgo, VIRGO), “Prospects for observing and localizing gravitational-wave transients with Advanced LIGO, Advanced Virgo and KAGRA,” Living Rev. Rel. 21, 3 (2018b), arXiv:1304.0670 [gr-qc] .
  15. Benjamin P Abbott et al. (LIGO Scientific), “Exploring the Sensitivity of Next Generation Gravitational Wave Detectors,” Class. Quant. Grav. 34, 044001 (2017b), arXiv:1607.08697 [astro-ph.IM] .
  16. M. Punturo et al., “The Einstein Telescope: A third-generation gravitational wave observatory,” Class. Quant. Grav. 27, 194002 (2010).
  17. Priscilla Canizares, Scott E. Field, Jonathan Gair, Vivien Raymond, Rory Smith,  and Manuel Tiglio, “Accelerated gravitational-wave parameter estimation with reduced order modeling,” Phys. Rev. Lett. 114, 071104 (2015), arXiv:1404.6284 [gr-qc] .
  18. Soichiro Morisaki and Vivien Raymond, “Rapid Parameter Estimation of Gravitational Waves from Binary Neutron Star Coalescence using Focused Reduced Order Quadrature,” Phys. Rev. D 102, 104020 (2020), arXiv:2007.09108 [gr-qc] .
  19. Soichiro Morisaki, Rory Smith, Leo Tsukada, Surabhi Sachdev, Simon Stevenson, Colm Talbot,  and Aaron Zimmerman, “Rapid localization and inference on compact binary coalescences with the Advanced LIGO-Virgo-KAGRA gravitational-wave detector network,”  (2023), arXiv:2307.13380 [gr-qc] .
  20. Serena Vinciguerra, John Veitch,  and Ilya Mandel, “Accelerating gravitational wave parameter estimation with multi-band template interpolation,” Class. Quant. Grav. 34, 115006 (2017), arXiv:1703.02062 [gr-qc] .
  21. Soichiro Morisaki, “Accelerating parameter estimation of gravitational waves from compact binary coalescence using adaptive frequency resolutions,” Phys. Rev. D 104, 044062 (2021), arXiv:2104.07813 [gr-qc] .
  22. Lalit Pathak, Amit Reza,  and Anand S. Sengupta, “Fast likelihood evaluation using meshfree approximations for reconstructing compact binary sources,” Phys. Rev. D 108, 064055 (2023), arXiv:2210.02706 [gr-qc] .
  23. Lalit Pathak, Sanket Munishwar, Amit Reza,  and Anand S. Sengupta, “Prompt sky localization of compact binary sources using meshfree approximation,”   (2023), arXiv:2309.07012 [gr-qc] .
  24. C. Pankow, P. Brady, E. Ochsner,  and R. O’Shaughnessy, “Novel scheme for rapid parallel parameter estimation of gravitational waves from compact binary coalescences,” Phys. Rev. D 92, 023002 (2015), arXiv:1502.04370 [gr-qc] .
  25. Jacob Lange, Richard O’Shaughnessy,  and Monica Rizzo, “Rapid and accurate parameter inference for coalescing, precessing compact binaries,”   (2018), arXiv:1805.10457 [gr-qc] .
  26. Rory J. E. Smith, Gregory Ashton, Avi Vajpeyi,  and Colm Talbot, “Massively parallel Bayesian inference for transient gravitational-wave astronomy,” Mon. Not. Roy. Astron. Soc. 498, 4492–4502 (2020), arXiv:1909.11873 [gr-qc] .
  27. Colm Talbot, Rory Smith, Eric Thrane,  and Gregory B. Poole, “Parallelized Inference for Gravitational-Wave Astronomy,” Phys. Rev. D 100, 043030 (2019), arXiv:1904.02863 [astro-ph.IM] .
  28. Vaibhav Tiwari, Charlie Hoy, Stephen Fairhurst,  and Duncan MacLeod, “Fast non-Markovian sampler for estimating gravitational-wave posteriors,” Phys. Rev. D 108, 023001 (2023), arXiv:2303.01463 [astro-ph.HE] .
  29. Michael J. Williams, John Veitch,  and Chris Messenger, “Nested sampling with normalizing flows for gravitational-wave inference,” Phys. Rev. D 103, 103006 (2021), arXiv:2102.11056 [gr-qc] .
  30. Stephen R. Green, Christine Simpson,  and Jonathan Gair, “Gravitational-wave parameter estimation with autoregressive neural network flows,” Phys. Rev. D 102, 104057 (2020), arXiv:2002.07656 [astro-ph.IM] .
  31. Thomas D. P. Edwards, Kaze W. K. Wong, Kelvin K. H. Lam, Adam Coogan, Daniel Foreman-Mackey, Maximiliano Isi,  and Aaron Zimmerman, “ripple: Differentiable and Hardware-Accelerated Waveforms for Gravitational Wave Data Analysis,”   (2023), arXiv:2302.05329 [astro-ph.IM] .
  32. Kaze W. K. Wong, Maximiliano Isi,  and Thomas D. P. Edwards, “Fast Gravitational-wave Parameter Estimation without Compromises,” Astrophys. J. 958, 129 (2023), arXiv:2302.05333 [astro-ph.IM] .
  33. Neil J. Cornish, “Fast Fisher Matrices and Lazy Likelihoods,”   (2010), arXiv:1007.4820 [gr-qc] .
  34. Barak Zackay, Liang Dai,  and Tejaswi Venumadhav, “Relative Binning and Fast Likelihood Evaluation for Gravitational Wave Parameter Estimation,”   (2018), arXiv:1806.08792 [astro-ph.IM] .
  35. Neil J. Cornish, “Heterodyned likelihood for rapid gravitational wave parameter inference,” Physical Review D 104, 104054 (2021).
  36. Gregory Ashton et al., “BILBY: A user-friendly Bayesian inference library for gravitational-wave astronomy,” Astrophys. J. Suppl. 241, 27 (2019), arXiv:1811.02042 [astro-ph.IM] .
  37. I. M. Romero-Shaw et al., “Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO–Virgo gravitational-wave transient catalogue,” Mon. Not. Roy. Astron. Soc. 499, 3295–3319 (2020), arXiv:2006.00714 [astro-ph.IM] .
  38. Daniel Finstad and Duncan A. Brown, “Fast Parameter Estimation of Binary Mergers for Multimessenger Follow-up,” Astrophys. J. Lett. 905, L9 (2020), arXiv:2009.13759 [astro-ph.IM] .
  39. Javier Roulet, Seth Olsen, Jonathan Mushkin, Tousif Islam, Tejaswi Venumadhav, Barak Zackay,  and Matias Zaldarriaga, “Removing degeneracy and multimodality in gravitational wave source parameters,” Phys. Rev. D 106, 123015 (2022), arXiv:2207.03508 [gr-qc] .
  40. Harsh Narola, Justin Janquart, Quirijn Meijer, K. Haris,  and Chris Van Den Broeck, “Relative binning for complete gravitational-wave parameter estimation with higher-order modes and precession, and applications to lensing and third-generation detectors,”   (2023), arXiv:2308.12140 [gr-qc] .
  41. Nathaniel Leslie, Liang Dai,  and Geraint Pratten, “Mode-by-mode relative binning: Fast likelihood estimation for gravitational waveforms with spin-orbit precession and multiple harmonics,” Phys. Rev. D 104, 123030 (2021), arXiv:2109.09872 [astro-ph.IM] .
  42. Tousif Islam, Javier Roulet,  and Tejaswi Venumadhav, “Factorized Parameter Estimation for Real-Time Gravitational Wave Inference,”   (2022), arXiv:2210.16278 [gr-qc] .
  43. Bikram Keshari Pradhan, Aditya Vijaykumar,  and Debarati Chatterjee, “Impact of updated multipole Love numbers and f-Love universal relations in the context of binary neutron stars,” Phys. Rev. D 107, 023010 (2023), arXiv:2210.09425 [astro-ph.HE] .
  44. Aditya Vijaykumar, Avinash Tiwari, Shasvath J. Kapadia, K. G. Arun,  and Parameswaran Ajith, “Waltzing Binaries: Probing the Line-of-sight Acceleration of Merging Compact Objects with Gravitational Waves,” Astrophys. J. 954, 105 (2023), arXiv:2302.09651 [astro-ph.HE] .
  45. Nikhil Sarin et al., “Redback: A Bayesian inference software package for electromagnetic transients,”   (2023), arXiv:2308.12806 [astro-ph.HE] .
  46. Aviral Prakash, Ish Gupta, Matteo Breschi, Rahul Kashyap, David Radice, Sebastiano Bernuzzi, Domenico Logoteta,  and B. S. Sathyaprakash, “Detectability of QCD phase transitions in binary neutron star mergers: Bayesian inference with the next generation gravitational wave detectors,”   (2023), arXiv:2310.06025 [gr-qc] .
  47. Eric Thrane and Colm Talbot, “An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models,” Publications of the Astronomical Society of Australia 36 (2019), 10.1017/pasa.2019.2.
  48. Luc Blanchet, “Gravitational Radiation from Post-Newtonian Sources and Inspiralling Compact Binaries,” Living Rev. Rel. 17, 2 (2014), arXiv:1310.1528 [gr-qc] .
  49. Liang Dai, Tejaswi Venumadhav,  and Barak Zackay, “Parameter Estimation for GW170817 using Relative Binning,”  (2018), arXiv:1806.08793 [gr-qc] .
  50. Alessandra Buonanno, Bala Iyer, Evan Ochsner, Yi Pan,  and B. S. Sathyaprakash, “Comparison of post-Newtonian templates for compact binary inspiral signals in gravitational-wave detectors,” Phys. Rev. D 80, 084043 (2009), arXiv:0907.0700 [gr-qc] .
  51. Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, C. J. Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R. Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt,  and SciPy 1. 0 Contributors, “SciPy 1.0: fundamental algorithms for scientific computing in Python,” Nature Methods 17, 261–272 (2020), arXiv:1907.10121 [cs.MS] .
  52. Geert Raaijmakers et al., “The Challenges Ahead for Multimessenger Analyses of Gravitational Waves and Kilonova: A Case Study on GW190425,” Astrophys. J. 922, 269 (2021), arXiv:2102.11569 [astro-ph.HE] .
  53. Joshua S. Speagle, “dynesty: a dynamic nested sampling package for estimating Bayesian posteriors and evidences,” Mon. Not. Roy. Astron. Soc. 493, 3132–3158 (2020), arXiv:1904.02180 [astro-ph.IM] .
  54. B. P. Abbott et al. (LIGO Scientific, Virgo), ‘‘GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral,” Phys. Rev. Lett. 119, 161101 (2017c), arXiv:1710.05832 [gr-qc] .
  55. Tim Dietrich et al., “Matter imprints in waveform models for neutron star binaries: Tidal and self-spin effects,” Physical Review D 99, 1–21 (2019).
  56. B. P. Abbott et al. (LIGO Scientific, Virgo), “GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs,” Phys. Rev. X 9, 031040 (2019b), arXiv:1811.12907 [astro-ph.HE] .
  57. B. P. Abbott et al., “GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs,” Physical Review X 9 (2018c), 10.1103/PhysRevX.9.031040.
  58. J. Lin, “Divergence measures based on the Shannon entropy,” IEEE Trans. Info. Theor. 37, 145–151 (1991).
  59. Sebastian Khan, Katerina Chatziioannou, Mark Hannam,  and Frank Ohme, “Phenomenological model for the gravitational-wave signal from precessing binary black holes with two-spin effects,” Phys. Rev. D 100, 024059 (2019), arXiv:1809.10113 [gr-qc] .
  60. Andrew Gelman Samantha R Cook and Donald B Rubin, “Validation of software for bayesian models using posterior quantiles,” Journal of Computational and Graphical Statistics 15, 675–692 (2006).
  61. B. S. Sathyaprakash and Bernard F. Schutz, “Physics, astrophysics and cosmology with gravitational waves,” Living Reviews in Relativity 12, 1–140 (2009).
  62. Vijay Varma, Parameswaran Ajith, Sascha Husa, Juan Calderon Bustillo, Mark Hannam,  and Michael Pürrer, “Gravitational-wave observations of binary black holes: Effect of nonquadrupole modes,” Phys. Rev. D 90, 124004 (2014), arXiv:1409.2349 [gr-qc] .
  63. Maite Mateu-Lucena, Sascha Husa, Marta Colleoni, Héctor Estellés, Cecilio García-Quirós, David Keitel, Maria de Lluc Planas,  and Antoni Ramos-Buades, “Parameter estimation with the current generation of phenomenological waveform models applied to the black hole mergers of GWTC-1,” Mon. Not. Roy. Astron. Soc. 517, 2403–2425 (2022), arXiv:2105.05960 [gr-qc] .
  64. Geraint Pratten et al., “Computationally efficient models for the dominant and subdominant harmonic modes of precessing binary black holes,” Phys. Rev. D 103, 104056 (2021), arXiv:2004.06503 [gr-qc] .
  65. R. Abbott et al. (LIGO Scientific, Virgo), “GW190412: Observation of a Binary-Black-Hole Coalescence with Asymmetric Masses,” Phys. Rev. D 102, 043015 (2020), arXiv:2004.08342 [astro-ph.HE] .
  66. R. Abbott et al. (LIGO Scientific, VIRGO), “GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run,”  (2021d), arXiv:2108.01045 [gr-qc] .
  67. LIGO Scientific Collaboration and Virgo Collaboration, “GWTC-2.1: Deep Extended Catalog of Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run - Parameter Estimation Data Release,”   (2022), 10.5281/zenodo.6513631.
  68. Ssohrab Borhanian and B. S. Sathyaprakash, “Listening to the Universe with Next Generation Ground-Based Gravitational-Wave Detectors,”   (2022), arXiv:2202.11048 [gr-qc] .
  69. Ish Gupta et al., “Characterizing Gravitational Wave Detector Networks: From A♯♯{}^{\sharp}start_FLOATSUPERSCRIPT ♯ end_FLOATSUPERSCRIPT to Cosmic Explorer,”   (2023), arXiv:2307.10421 [gr-qc] .
  70. Marica Branchesi et al., “Science with the Einstein Telescope: a comparison of different designs,” JCAP 07, 068 (2023), arXiv:2303.15923 [gr-qc] .
  71. Rich Abbott et al. (LIGO Scientific, Virgo), “Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo,” SoftwareX 13, 100658 (2021e), arXiv:1912.11716 [gr-qc] .
  72. Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, Robert Kern, Matti Picus, Stephan Hoyer, Marten H. van Kerkwijk, Matthew Brett, Allan Haldane, Jaime Fernández del Río, Mark Wiebe, Pearu Peterson, Pierre Gérard-Marchant, Kevin Sheppard, Tyler Reddy, Warren Weckesser, Hameer Abbasi, Christoph Gohlke,  and Travis E. Oliphant, “Array programming with NumPy,” Nature (London) 585, 357–362 (2020), arXiv:2006.10256 [cs.MS] .
  73. John D. Hunter, “Matplotlib: A 2D Graphics Environment,” Computing in Science and Engineering 9, 90–95 (2007).
  74. Thomas Kluyver, Benjain Ragan-Kelley, Fernando Pérez, Brian Granger, Matthias Bussonnier, Jonathan Frederic, Kyle Kelley, Jessica Hamrick, Jason Grout, Sylvain Corlay, Paul Ivanov, Damián Avila, Safia Abdalla, Carol Willing,  and Jupyter Development Team, “Jupyter Notebooks—a publishing format for reproducible computational workflows,” in IOS Press (IOS Press, 2016) pp. 87–90.
  75. Wes McKinney, “Data Structures for Statistical Computing in Python,” in Proceedings of the 9th Python in Science Conference, edited by Stéfan van der Walt and Jarrod Millman (2010) pp. 56 – 61.
  76. Daniel Foreman-Mackey, “corner.py: Scatterplot matrices in python,” The Journal of Open Source Software 1, 24 (2016).
  77. Charlie Hoy and Vivien Raymond, “PESummary: the code agnostic Parameter Estimation Summary page builder,” SoftwareX 15, 100765 (2021), arXiv:2006.06639 [astro-ph.IM] .
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