Calypso is a parameter-conditioned stochastic surrogate model for circumbinary accretion flows using PCA and multivariate Gaussian modeling, released as open-source software with a closed-form likelihood for parameter inference from time series.
Eccentric Massive Black Hole Binaries in LISA I : The Detection Capabilities of Circular Templates
2 Pith papers cite this work, alongside 13 external citations. Polarity classification is still indexing.
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abstract
One of the major assumptions in the search for gravitational wave signatures from massive and supermassive black hole binaries with LISA, is that these systems will have circularized before entering the LISA bandwidth. Current astrophysical simulations now suggest that systems could have a non-negligible eccentricity in the LISA band, and an important level of eccentricity in the Pulsar Timing regime. In this work, we use a set of source catalogues from astrophysically motivated models of massive black hole binary formation and assume a one year LISA mission lifetime. Depending on the model in question, the initial eccentricities in the final year of the inspiral can be as high as 0.6 for high mass seeds and 0.8 for low mass seeds. We show that restricted post-Newtonian circular templates are extremely inefficient in recovering eccentric binaries, with median optimal signal to noise ratio recoveries of approximately 10% for all models considered. This coupled with extremely large errors in parameter recovery from individual Markov chain Monte Carlo's demonstrate quite clearly that even to search for binaries with initial eccentricities as low as $10^{-4}$, we will require eccentric templates for LISA data analysis.
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A framework using scale separation in the Isaacson description defines observable gravitational memory rise for compact binary coalescences, providing a basis for hypothesis testing in LISA data.
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\texttt{calypso}: a Parameter-Conditioned Stochastic Surrogate Model for Circumbinary Accretion Time-Series
Calypso is a parameter-conditioned stochastic surrogate model for circumbinary accretion flows using PCA and multivariate Gaussian modeling, released as open-source software with a closed-form likelihood for parameter inference from time series.
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Toward claiming a detection of gravitational memory
A framework using scale separation in the Isaacson description defines observable gravitational memory rise for compact binary coalescences, providing a basis for hypothesis testing in LISA data.