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The Laser Interferometer Space Antenna (LISA) is a planned space-based observatory to measure gravitational waves in the millihertz frequency band.
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2009
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S. Babak, J. G. Baker, M. J. Benacquista, N. J. Cornish, S. L. Larson, I. Mandel, S. T. McWilliams, A. Petiteau, E. K. Porter, E. L. Robinson, et al. , The mock lisa data challenges: from challenge 3 to challenge 4, Classical and Quantum Gravity 27
2010
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A. Petiteau, Y. Shang, S. Babak, and F. Feroz, Search for spinning black hole binaries in mock lisa data using a genetic algorithm, Physical Review D 81
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2021
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S. Marsat, J. G. Baker, and T. D. Canton, Exploring the bayesian parameter estimation of binary black holes with lisa, Physical Review D 103
2021
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K. Dey, N. Karnesis, A. Toubiana, E. Barausse, N. Korsakova, Q. Baghi, and S. Basak, Effect of data gaps on the detectability and parameter estimation of massive black hole binaries with lisa, Physical Review D 104
2021
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N. Karnesis, S. Babak, M. Pieroni, N. Cornish, and T. Littenberg, Characterization of the stochastic signal originating from compact binary populations as measured by lisa, Physical Review D 104
2021
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A. Petiteau, S. Babak, and A. Sesana, Constraining the dark energy equation of state using lisa observations of spinning massive black hole binaries, The Astrophysical Journal 732
2011
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T. B. Littenberg, Detection pipeline for galactic binaries in lisa data, Physical Review D 84
2011
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2012
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2013
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2014
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M. Tinto and S. V. Dhurandhar, Time-delay interferometry, Living Reviews in Relativity 17
2014
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E. K. Porter and N. J. Cornish, Fisher versus bayes: A comparison of parameter estimation techniques for massive black hole binaries to high redshifts with elisa, Physical Review D 91
2015
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2016
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2021
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M. C. Digman and N. J. Cornish, Lisa gravitational wave sources in a time-varying galactic stochastic background, The Astrophysical Journal 940
2022
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M. L. Katz, Fully automated end-to-end pipeline for massive black hole binary signal extraction from lisa data, Physical Review D 105
2022
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S. H. Strub, L. Ferraioli, C. Schmelzbach, S. C. Stähler, and D. Giardini, Bayesian parameter estimation of galactic binaries in lisa data with gaussian process regression, Phys. Rev. D 106
2022
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N. J. Cornish, Low latency detection of massive black hole binaries, Physical Review D 105
2022
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M. L. Katz, J.-B. Bayle, A. J. K. Chua, and M. Vallisneri, Assessing the data-analysis impact of lisa orbit approximations using a gpu-accelerated response model, Physical Review D 106
2022
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M. Katz and J.-B. Bayle, mikekatz04/lisa-on-gpu: First official public release!, 10.5281/zenodo.5867731 (2022)
2022
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P. Gao, X.-L. Fan, Z.-J. Cao, and X.-H. Zhang, Fast resolution of galactic binaries in lisa data, Physical Review D 107
2023
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2023
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N. Karnesis, M. L. Katz, N. Korsakova, J. R. Gair, and N. Stergioulas, Eryn: a multipurpose sampler for bayesian inference, Monthly Notices of the Royal Astronomical Society 526
2023
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S. H. Strub, L. Ferraioli, C. Schmelzbach, S. C. Stähler, and D. Giardini, Accelerating global parameter estimation of gravitational waves from galactic binaries using a genetic algorithm and gpus, Physical Review D 108
2023
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2023
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K. Lackeos, T. B. Littenberg, N. J. Cornish, and J. I. Thorpe, The lisa data challenge radler analysis and time-dependent ultra-compact binary catalogues, Astronomy & Astrophysics 678
2023
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2024
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