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Register a new userInvestigating Binary Black Hole Mergers with Principal Component Analysis
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Despite recent progress in numerical simulations of the coalescence of binary black hole systems, highly asymmetric spinning systems and the construction of accurate physical templates remain challenging and computationally expensive. We explore the feasibility of a prompt and robust test of whether the signals exhibit evidence for generic features that can educate new simulations. We form catalogs of numerical relativity waveforms with distinct physical effects and compute the relative probability that a gravitational wave signal belongs to each catalog. We introduce an algorithm designed to perform this task for coalescence signals using principal component analysis of waveform catalogs and Bayesian model selection and demonstrate its effectiveness.
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Scalar fields coupled to the Gauss-Bonnet invariant can undergo a tachyonic instability, leading to spontaneous scalarization of black holes. Studies of this effect have so far been restricted to single black hole spacetimes. We present the first results on dynamical scalarization in head-on collisions and quasicircular inspirals of black hole binaries with numerical relativity simulations. We show that black hole binaries can either form a scalarized remnant or dynamically descalarize by shedding off its initial scalar hair. The observational implications of these findings are discussed.
Matched filtering is a popular data analysis framework used to search for gravitational wave signals emitted by compact object binaries. The templates used in matched filtering searches are constructed predominantly from the quadrupolar mode because this mode is the energetically most dominant channel. However, for highly precessing binaries or binaries with moderately large mass ratios, significant power is also carried by higher-order modes. We investigate how the inclusion of higher modes in the templates increases the prospects for detecting gravitational waves. Specifically, we use numerical relativity waveforms from the late inspiral and coalescence of binary black holes to identify mode hierarchies that cover the sky of binary orientations. We show that the ordering in these hierarchies depends on the characteristics of the binary system and the mode strengths. Our study demonstrates that detecting moderately high precessing or unequal mass binaries requires the inclusion of higher modes in the templates banks.
Recently, it has been shown that with the inclusion of overtones, the post-merger gravitational waveform at infinity of a binary black hole system is well-modelled using pure linear theory. However, given that a binary black hole merger is expected to be highly non-linear, where do these non-linearities, which do not make it out to infinity, go? We visualize quantities measuring non-linearity in the strong-field region of a numerical relativity binary black hole merger in order to begin to answer this question.
In a binary black hole merger, it is known that the inspiral portion of the waveform corresponds to two distinct horizons orbiting each other, and the merger and ringdown signals correspond to the final horizon being formed and settling down to equilibrium. However, we still lack a detailed understanding of the relation between the horizon geometry in these three regimes and the observed waveform. Here we show that the well known inspiral chirp waveform has a clear counterpart on black hole horizons, namely, the shear of the outgoing null rays at the horizon. We demonstrate that the shear behaves very much like a compact binary coalescence waveform with increasing frequency and amplitude. Furthermore, the parameters of the system estimated from the horizon agree with those estimated from the waveform. This implies that even though black hole horizons are causally disconnected from us, assuming general relativity to be true, we can potentially infer some of their detailed properties from gravitational wave observations.
We apply machine learning methods to build a time-domain model for gravitational waveforms from binary black hole mergers, called mlgw. The dimensionality of the problem is handled by representing the waveforms amplitude and phase using a principal component analysis. We train mlgw on about $mathcal{O}(10^3)$ TEOBResumS and SEOBNRv4 effective-one-body waveforms with mass ratios $qin[1,20]$ and aligned dimensionless spins $sin[-0.80,0.95]$. The resulting models are faithful to the training sets at the ${sim}10^{-3}$ level (averaged on the parameter space). The speed up for a single waveform generation is a factor 10 to 50 (depending on the binary mass and initial frequency) for TEOBResumS and approximately an order of magnitude more for SEOBNRv4. Furthermore, mlgw provides a closed form expression for the waveform and its gradient with respect to the orbital parameters; such an information might be useful for future improvements in GW data analysis. As demonstration of the capabilities of mlgw to perform a full parameter estimation, we re-analyze the public data from the first GW transient catalog (GWTC-1). We find broadly consistent results with previous analyses at a fraction of the cost, although the analysis with spin aligned waveforms gives systematic larger values of the effective spins with respect to previous analyses with precessing waveforms. Since the generation time does not depend on the length of the signal, our model is particularly suitable for the analysis of the long signals that are expected to be detected by third-generation detectors. Future applications include the analysis of waveform systematics and model selection in parameter estimation.
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