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Register a new userImpact of subdominant modes on the interpretation of gravitational-wave signals from heavy binary black hole systems
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Over the past year, a handful of new gravitational wave models have been developed to include multiple harmonic modes thereby enabling for the first time fully Bayesian inference studies including higher modes to be performed. Using one recently-developed numerical relativity surrogate model, NRHybSur3dq8, we investigate the importance of higher modes on parameter inference of coalescing massive binary black holes. We focus on examples relevant to the current three-detector network of observatories, with a detector-frame mass set to $120 M_odot$ and with signal amplitude values that are consistent with plausible candidates for the next few observing runs. We show that for such systems the higher mode content will be important for interpreting coalescing binary black holes, reducing systematic bias, and computing properties of the remnant object. Even for comparable-mass binaries and at low signal amplitude, the omission of higher modes can influence posterior probability distributions. We discuss the impact of our results on source population inference and self-consistency tests of general relativity. Our work can be used to better understand asymmetric binary black hole merger events, such as GW190412. Higher modes are critical for such systems, and their omission usually produces substantial parameter biases.
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We present a systematic comparison of the binary black hole (BBH) signal waveform reconstructed by two independent and complementary approaches used in LIGO and Virgo source inference: a template-based analysis, and a morphology-independent analysis. We apply the two approaches to real events and to two sets of simulated observations made by adding simulated BBH signals to LIGO and Virgo detector noise. The first set is representative of the 10 BBH events in the first Gravitational Wave Transient Catalog (GWTC-1). The second set is constructed from a population of BBH systems with total mass and signal strength in the ranges that ground based detectors are typically sensitive. We find that the reconstruction quality of the GWTC-1 events is consistent with the results of both sets of simulated signals. We also demonstrate a simulated case where the presence of a mismodelled effect in the observed signal, namely higher order modes, can be identified through the morphology-independent analysis. This study is relevant for currently progressing and future observational runs by LIGO and Virgo.
Accurate extractions of the detected gravitational wave (GW) signal waveforms are essential to validate a detection and to probe the astrophysics behind the sources producing the GWs. This however could be difficult in realistic scenarios where the signals detected by existing GW detectors could be contaminated with non-stationary and non-Gaussian noise. While the performance of existing waveform extraction methods are optimal, they are not fast enough for online application, which is important for multi-messenger astronomy. In this paper, we demonstrate that a deep learning architecture consisting of Convolutional Neural Network and bidirectional Long Short-Term Memory components can be used to extract binary black hole (BBH) GW waveforms from realistic noise in a few milli-seconds. We have tested our network systematically on injected GW signals, with component masses uniformly distributed in the range of 10 to 80 solar masses, on Gaussian noise and LIGO detector noise. We find that our model can extract GW waveforms with overlaps of more than 0.95 with pure Numerical Relativity templates for signals with signal-to-noise ratio (SNR) greater than six, and is also robust against interfering glitches. We then apply our model to all ten detected BBH events from the first (O1) and second (O2) observation runs, obtaining greater than 0.97 overlaps for all ten extracted BBH waveforms with the corresponding pure templates. We discuss the implication of our result and its future applications to GW localization and mass estimation.
The inspiral and merger of black-hole binary systems are a promising source of gravitational waves. The most effective method to look for a signal with a well understood waveform, such as the binary black hole signal, is matched filtering against a library of model waveforms. Current model waveforms are comprised solely of the dominant radiation mode, the quadrupole mode, although it is known that there can be significant power in the higher-order modes. The binary black hole waveforms produced by numerical relativity are accurate through late inspiral, merger, and ringdown and include the higher-order modes. The available numerical-relativity waveforms span an increasing portion of the physical parameter space of unequal mass, spin and precession. In this paper, we investigate the degree to which gravitational-wave searches could be improved by the inclusion of higher modes in the model waveforms, for signals with a variety of initial mass ratios and generic spins. Our investigation studies how well the quadrupole-only waveform model matches the signal as a function of the inclination and orientation of the source and how the modes contribute to the distance reach into the Universe of Advanced LIGO for a fixed set of internal source parameters. The mismatch between signals and quadrupole-only waveform can be large, dropping below 0.97 for up to 65% of the source-sky for the non-precessing cases we studied, and over a larger area in one precessing case. There is a corresponding 30% increase in detection volume that could be achieved by adding higher modes to the search; however, this is mitigated by the fact that the mismatch is largest for signals which radiate the least energy and to which the search is therefore least sensitive. Likewise, the mismatch is largest in directions from the source along which the least energy is radiated.
Current template-based gravitational wave searches for compact binary coalescences (CBC) use waveform models that neglect the higher order modes content of the gravitational radiation emitted, considering only the quadrupolar $(ell,|m|)=(2,2)$ modes. We study the effect of such a neglection for the case of aligned-spin CBC searches for equal-spin (and non-spinning) binary black holes in the context of t
We introduce a gravitational waveform inversion strategy that discovers mechanical models of binary black hole (BBH) systems. We show that only a single time series of (possibly noisy) waveform data is necessary to construct the equations of motion for a BBH system. Starting with a class of universal differential equations parameterized by feed-forward neural networks, our strategy involves the construction of a space of plausible mechanical models and a physics-informed constrained optimization within that space to minimize the waveform error. We apply our method to various BBH systems including extreme and comparable mass ratio systems in eccentric and non-eccentric orbits. We show the resulting differential equations apply to time durations longer than the training interval, and relativistic effects, such as perihelion precession, radiation reaction, and orbital plunge, are automatically accounted for. The methods outlined here provide a new, data-driven approach to studying the dynamics of binary black hole systems.
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