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Optimized Search for a Binary Black Hole Merger Population in LIGO-Virgo O3 Data (2403.10439v3)

Published 15 Mar 2024 in gr-qc and astro-ph.HE

Abstract: Maximizing the number of detections in matched filter searches for compact binary coalescence (CBC) gravitational wave (GW) signals requires a model of the source population distribution. In previous searches using the PyCBC framework, sensitivity to the population of binary black hole (BBH) mergers was improved by restricting the range of filter template mass ratios and use of a simple one-dimensional population model. However, this approach does not make use of our full knowledge of the population and cannot be extended to a full parameter space search. Here, we introduce a new ranking method, based on kernel density estimation (KDE) with adaptive bandwidth, to accurately model the probability distributions of binary source parameters over a template bank, both for signals and for noise events. We demonstrate this ranking method by conducting a search over LIGO-Virgo O3 data for BBH with unrestricted mass ratio, using a signal model derived from previous significant detected events. We achieve over 10% increase in sensitive volume for a simple power-law simulated signal population, compared to the previous BBH search. Correspondingly, with the new ranking, 8 additional candidate events above an inverse false alarm rate (IFAR) threshold 0.5 yr are identified.

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References (51)
  1. J. Aasi et al., “Advanced LIGO,” Class. Quant. Grav., vol. 32, p. 074001, 2015.
  2. F. Acernese et al., “Advanced Virgo: a second-generation interferometric gravitational wave detector,” Class. Quant. Grav., vol. 32, no. 2, p. 024001, 2015.
  3. Y. Aso, Y. Michimura, K. Somiya, M. Ando, O. Miyakawa, T. Sekiguchi, D. Tatsumi, and H. Yamamoto, “Interferometer design of the KAGRA gravitational wave detector,” Phys. Rev. D, vol. 88, no. 4, p. 043007, 2013.
  4. R. Abbott et al., “GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run,” Phys. Rev. X, vol. 13, no. 4, p. 041039, 2023.
  5. D. Davis et al., “LIGO detector characterization in the second and third observing runs,” Class. Quant. Grav., vol. 38, no. 13, p. 135014, 2021.
  6. D. Davis, M. Trevor, S. Mozzon, and L. K. Nuttall, “Incorporating information from LIGO data quality streams into the PyCBC search for gravitational waves,” Phys. Rev. D, vol. 106, no. 10, p. 102006, 2022.
  7. R. Biswas et al., “Likelihood-ratio ranking of gravitational-wave candidates in a non-Gaussian background,” Phys. Rev. D, vol. 85, p. 122008, 2012.
  8. K. Cannon, C. Hanna, and J. Peoples, “Likelihood-Ratio Ranking Statistic for Compact Binary Coalescence Candidates with Rate Estimation,” 4 2015.
  9. G. S. Davies, T. Dent, M. Tápai, I. Harry, C. McIsaac, and A. H. Nitz, “Extending the pycbc search for gravitational waves from compact binary mergers to a global network,” Physical Review D, vol. 102, no. 2, p. 022004, 2020.
  10. T. Dent and J. Veitch, “Optimizing gravitational-wave searches for a population of coalescing binaries: Intrinsic parameters,” Phys. Rev. D, vol. 89, no. 6, p. 062002, 2014.
  11. T. Dal Canton and I. W. Harry, “Designing a template bank to observe compact binary coalescences in Advanced LIGO’s second observing run,” 5 2017.
  12. S. Roy, A. S. Sengupta, and N. Thakor, “Hybrid geometric-random template-placement algorithm for gravitational wave searches from compact binary coalescences,” Phys. Rev. D, vol. 95, no. 10, p. 104045, 2017.
  13. C. Hanna et al., “Binary tree approach to template placement for searches for gravitational waves from compact binary mergers,” Phys. Rev. D, vol. 108, no. 4, p. 042003, 2023.
  14. B. P. Abbott et al., “Observation of Gravitational Waves from a Binary Black Hole Merger,” Phys. Rev. Lett., vol. 116, no. 6, p. 061102, 2016.
  15. J. Abadie et al., “Predictions for the Rates of Compact Binary Coalescences Observable by Ground-based Gravitational-wave Detectors,” Class. Quant. Grav., vol. 27, p. 173001, 2010.
  16. B. P. Abbott et al., “GW150914: First results from the search for binary black hole coalescence with Advanced LIGO,” Phys. Rev. D, vol. 93, no. 12, p. 122003, 2016.
  17. B. P. Abbott et al., “Binary Black Hole Mergers in the first Advanced LIGO Observing Run,” Phys. Rev. X, vol. 6, no. 4, p. 041015, 2016. [Erratum: Phys.Rev.X 8, 039903 (2018)].
  18. A. H. Nitz, T. Dent, T. Dal Canton, S. Fairhurst, and D. A. Brown, “Detecting binary compact-object mergers with gravitational waves: Understanding and Improving the sensitivity of the PyCBC search,” Astrophys. J., vol. 849, no. 2, p. 118, 2017.
  19. R. Abbott et al., “Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog,” Astrophys. J. Lett., vol. 913, no. 1, p. L7, 2021.
  20. R. Abbott et al., “Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3,” Phys. Rev. X, vol. 13, no. 1, p. 011048, 2023.
  21. N. Andres et al., “Assessing the compact-binary merger candidates reported by the MBTA pipeline in the LIGO–Virgo O3 run: probability of astrophysical origin, classification, and associated uncertainties,” Class. Quant. Grav., vol. 39, no. 5, p. 055002, 2022.
  22. R. Abbott et al., “GWTC-2.1: Deep extended catalog of compact binary coalescences observed by LIGO and Virgo during the first half of the third observing run,” Phys. Rev. D, vol. 109, no. 2, p. 022001, 2024.
  23. S. A. Usman, A. H. Nitz, I. W. Harry, C. M. Biwer, D. A. Brown, M. Cabero, C. D. Capano, T. Dal Canton, T. Dent, S. Fairhurst, et al., “The pycbc search for gravitational waves from compact binary coalescence,” Classical and Quantum Gravity, vol. 33, no. 21, p. 215004, 2016.
  24. R. Abbott et al., “GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run,” Phys. Rev. X, vol. 11, p. 021053, 2021.
  25. A. H. Nitz, C. D. Capano, S. Kumar, Y.-F. Wang, S. Kastha, M. Schäfer, R. Dhurkunde, and M. Cabero, “3-OGC: Catalog of Gravitational Waves from Compact-binary Mergers,” Astrophys. J., vol. 922, no. 1, p. 76, 2021.
  26. A. H. Nitz, S. Kumar, Y.-F. Wang, S. Kastha, S. Wu, M. Schäfer, R. Dhurkunde, and C. D. Capano, “4-OGC: Catalog of gravitational waves from compact-binary mergers,” 12 2021.
  27. H. K. Y. Fong, From simulations to signals: Analyzing gravitational waves from compact binary coalescences. PhD thesis, Toronto U., 2018.
  28. K. S. Phukon, G. Baltus, S. Caudill, S. Clesse, A. Depasse, M. Fays, H. Fong, S. J. Kapadia, R. Magee, and A. J. Tanasijczuk, “The hunt for sub-solar primordial black holes in low mass ratio binaries is open,” 5 2021.
  29. B. Allen, W. G. Anderson, P. R. Brady, D. A. Brown, and J. D. E. Creighton, “FINDCHIRP: An Algorithm for detection of gravitational waves from inspiraling compact binaries,” Phys. Rev. D, vol. 85, p. 122006, 2012.
  30. T. Dal Canton et al., “Implementing a search for aligned-spin neutron star-black hole systems with advanced ground based gravitational wave detectors,” Phys. Rev. D, vol. 90, no. 8, p. 082004, 2014.
  31. B. Allen, “χ2superscript𝜒2{\chi}^{2}italic_χ start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT time-frequency discriminator for gravitational wave detection,” Phys. Rev. D, vol. 71, p. 062001, 2005.
  32. A. H. Nitz, T. Dent, G. S. Davies, S. Kumar, C. D. Capano, I. Harry, S. Mozzon, L. Nuttall, A. Lundgren, and M. Tápai, “2-OGC: Open Gravitational-wave Catalog of binary mergers from analysis of public Advanced LIGO and Virgo data,” Astrophys. J., vol. 891, p. 123, 3 2020.
  33. R. Magee et al., “Sub-threshold Binary Neutron Star Search in Advanced LIGO’s First Observing Run,” Astrophys. J. Lett., vol. 878, no. 1, p. L17, 2019.
  34. J. Sadiq, T. Dent, and D. Wysocki, “Flexible and fast estimation of binary merger population distributions with an adaptive kernel density estimator,” Physical Review D, vol. 105, no. 12, p. 123014, 2022.
  35. John Wiley & Sons, 2015.
  36. I. W. Harry, B. Allen, and B. Sathyaprakash, “Stochastic template placement algorithm for gravitational wave data analysis,” Physical Review D, vol. 80, no. 10, p. 104014, 2009.
  37. K. Chandra, V. Villa-Ortega, T. Dent, C. McIsaac, A. Pai, I. Harry, G. C. Davies, and K. Soni, “Optimized pycbc search for gravitational waves from intermediate-mass black hole mergers,” Physical Review D, vol. 104, no. 4, p. 042004, 2021.
  38. LSC, Virgo, and KAGRA Collaborations, “GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run — O3 search sensitivity estimates,” May 2023.
  39. S. Roy, A. S. Sengupta, and P. Ajith, “Effectual template banks for upcoming compact binary searches in Advanced-LIGO and Virgo data,” Phys. Rev. D, vol. 99, no. 2, p. 024048, 2019.
  40. S. Olsen, T. Venumadhav, J. Mushkin, J. Roulet, B. Zackay, and M. Zaldarriaga, “New binary black hole mergers in the ligo-virgo o3a data,” Physical Review D, vol. 106, no. 4, p. 043009, 2022.
  41. A. K. Mehta, S. Olsen, D. Wadekar, J. Roulet, T. Venumadhav, J. Mushkin, B. Zackay, and M. Zaldarriaga, “New binary black hole mergers in the ligo-virgo o3b data,” arXiv preprint arXiv:2311.06061, 2023.
  42. R. Abbott, T. D. Abbott, F. Acernese, K. Ackley, C. Adams, N. Adhikari, R. X. Adhikari, V. B. Adya, C. Affeldt, D. Agarwal, et al., “Search for intermediate-mass black hole binaries in the third observing run of advanced ligo and advanced virgo,” Astronomy & Astrophysics, vol. 659, p. A84, 2022.
  43. W. M. Farr, J. R. Gair, I. Mandel, and C. Cutler, “Counting And Confusion: Bayesian Rate Estimation With Multiple Populations,” Phys. Rev. D, vol. 91, no. 2, p. 023005, 2015.
  44. B. P. Abbott et al., “Supplement: The Rate of Binary Black Hole Mergers Inferred from Advanced LIGO Observations Surrounding GW150914,” Astrophys. J. Suppl., vol. 227, no. 2, p. 14, 2016.
  45. J. Creighton, “Certain identities in FGMC,” Tech. Rep. T1700029-v2, LIGO DCC, 2017.
  46. M. Dominik, E. Berti, R. O’Shaughnessy, I. Mandel, K. Belczynski, C. Fryer, D. E. Holz, T. Bulik, and F. Pannarale, “Double Compact Objects III: Gravitational Wave Detection Rates,” Astrophys. J., vol. 806, no. 2, p. 263, 2015.
  47. A. K. Y. Li, J. C. L. Chan, H. Fong, A. H. Y. Chong, A. J. Weinstein, and J. M. Ezquiaga, “TESLA-X: An effective method to search for sub-threshold lensed gravitational waves with a targeted population model,” 11 2023.
  48. I. Harry, J. Calderón Bustillo, and A. Nitz, “Searching for the full symphony of black hole binary mergers,” Phys. Rev. D, vol. 97, no. 2, p. 023004, 2018.
  49. K. Chandra, J. Calderón Bustillo, A. Pai, and I. W. Harry, “First gravitational-wave search for intermediate-mass black hole mergers with higher-order harmonics,” Phys. Rev. D, vol. 106, no. 12, p. 123003, 2022.
  50. Y. Pan, A. Buonanno, Y.-b. Chen, and M. Vallisneri, “A Physical template family for gravitational waves from precessing binaries of spinning compact objects: Application to single spin binaries,” Phys. Rev. D, vol. 69, p. 104017, 2004. [Erratum: Phys.Rev.D 74, 029905 (2006)].
  51. C. McIsaac, C. Hoy, and I. Harry, “Search technique to observe precessing compact binary mergers in the advanced detector era,” Phys. Rev. D, vol. 108, no. 12, p. 123016, 2023.
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