اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدA Numerical Relativity Waveform Surrogate Model for Generically Precessing Binary Black Hole Mergers
128
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
A generic, non-eccentric binary black hole (BBH) system emits gravitational waves (GWs) that are completely described by 7 intrinsic parameters: the black hole spin vectors and the ratio of their masses. Simulating a BBH coalescence by solving Einsteins equations numerically is computationally expensive, requiring days to months of computing resources for a single set of parameter values. Since theoretical predictions of the GWs are often needed for many different source parameters, a fast and accurate model is essential. We present the first surrogate model for GWs from the coalescence of BBHs including all $7$ dimensions of the intrinsic non-eccentric parameter space. The surrogate model, which we call NRSur7dq2, is built from the results of $744$ numerical relativity simulations. NRSur7dq2 covers spin magnitudes up to $0.8$ and mass ratios up to $2$, includes all $ell leq 4$ modes, begins about $20$ orbits before merger, and can be evaluated in $sim~50,mathrm{ms}$. We find the largest NRSur7dq2 errors to be comparable to the largest errors in the numerical relativity simulations, and more than an order of magnitude smaller than the errors of other waveform models. Our model, and more broadly the methods developed here, will enable studies that would otherwise require millions of numerical relativity waveforms, such as parameter inference and tests of general relativity with GW observations.
قيم البحث
اقرأ أيضاً
Gravitational wave astrophysics relies heavily on the use of matched filtering both to detect signals in noisy data from detectors, and to perform parameter estimation on those signals. Matched filtering relies upon prior knowledge of the signals exp
ected to be produced by a range of astrophysical systems, such as binary black holes. These waveform signals can be computed using numerical relativity techniques, where the Einstein field equations are solved numerically, and the signal is extracted from the simulation. Numerical relativity simulations are, however, computationally expensive, leading to the need for a surrogate model which can predict waveform signals in regions of the physical parameter space which have not been probed directly by simulation. We present a method for producing such a surrogate using Gaussian process regression which is trained directly on waveforms generated by numerical relativity. This model returns not just a single interpolated value for the waveform at a new point, but a full posterior probability distribution on the predicted value. This model is therefore an ideal component in a Bayesian analysis framework, through which the uncertainty in the interpolation can be taken into account when performing parameter estimation of signals.
The recent observation of GW190412, the first high-mass ratio binary black-hole (BBH) merger, by the LIGO-Virgo Collaboration (LVC) provides a unique opportunity to probe the impact of subdominant harmonics and precession effects encoded in a gravita
tional wave signal. We present refined estimates of source parameters for GW190412 using texttt{NRSur7dq4}, a recently developed numerical relativity waveform surrogate model that includes all $ell leq 4$ spin-weighted spherical harmonic modes as well as the full physical effects of precession. We compare our results with two different variants of phenomenological precessing BBH waveform models, texttt{IMRPhenomPv3HM} and texttt{IMRPhenomXPHM}, as well as to the LVC results. Our results are broadly in agreement with texttt{IMRPhenomXPHM} results and the reported LVC analysis compiled with the texttt{SEOBNRv4PHM} waveform model, but in tension with texttt{IMRPhenomPv3HM}. Using the texttt{NRSur7dq4} model, we provide a tighter constraint on the mass-ratio ($0.26^{+0.08}_{-0.06}$) as compared to the LVC estimate of $0.28^{+0.13}_{-0.07}$ (both reported as median values withs 90% credible intervals). We also constrain the binary to be more face-on, and find a broader posterior for the spin precession parameter. We further find that even though $ell=4$ harmonic modes have negligible signal-to-noise ratio, omission of these modes will influence the estimated posterior distribution of several source parameters including chirp mass, effective inspiral spin, luminosity distance, and inclination. We also find that commonly used model approximations, such as neglecting the asymmetric modes (which are generically excited during precession), have negligible impact on parameter recovery for moderate SNR-events similar to GW190412.
Numerical relativity (NR) simulations provide the most accurate binary black hole gravitational waveforms, but are prohibitively expensive for applications such as parameter estimation. Surrogate models of NR waveforms have been shown to be both fast
and accurate. However, NR-based surrogate models are limited by the training waveforms length, which is typically about 20 orbits before merger. We remedy this by hybridizing the NR waveforms using both post-Newtonian and effective one body waveforms for the early inspiral. We present NRHybSur3dq8, a surrogate model for hybridized nonprecessing numerical relativity waveforms, that is valid for the entire LIGO band (starting at $20~text{Hz}$) for stellar mass binaries with total masses as low as $2.25,M_{odot}$. We include the $ell leq 4$ and $(5,5)$ spin-weighted spherical harmonic modes but not the $(4,1)$ or $(4,0)$ modes. This model has been trained against hybridized waveforms based on 104 NR waveforms with mass ratios $qleq8$, and $|chi_{1z}|,|chi_{2z}| leq 0.8$, where $chi_{1z}$ ($chi_{2z}$) is the spin of the heavier (lighter) BH in the direction of orbital angular momentum. The surrogate reproduces the hybrid waveforms accurately, with mismatches $lesssim 3times10^{-4}$ over the mass range $2.25M_{odot} leq M leq 300 M_{odot}$. At high masses ($Mgtrsim40M_{odot}$), where the merger and ringdown are more prominent, we show roughly two orders of magnitude improvement over existing waveform models. We also show that the surrogate works well even when extrapolated outside its training parameter space range, including at spins as large as 0.998. Finally, we show that this model accurately reproduces the spheroidal-spherical mode mixing present in the NR ringdown signal.
We present the first set of numerical relativity simulations of binary neutron mergers that include spin precession effects and are evolved with multiple resolutions. Our simulations employ consistent initial data in general relativity with different
spin configurations and dimensionless spin magnitudes $sim 0.1$. They start at a gravitational-wave frequency of $sim392$~Hz and cover more than $1$ precession period and about 15 orbits up to merger. We discuss the spin precession dynamics by analyzing coordinate trajectories, quasi-local spin measurements, and energetics, by comparing spin aligned, antialigned, and irrotational configurations. Gravitational waveforms from different spin configuration are compared by calculating the mismatch between pairs of waveforms in the late inspiral. We find that precession effects are not distinguishable from nonprecessing configurations with aligned spins for approximately face-on binaries, while the latter are distinguishable from a nonspinning configurations. Spin precession effects are instead clearly visible for approximately edge-on binaries. For the parameters considered here, precession does not significantly affect the characteristic postmerger gravitational-wave frequencies nor the mass ejection. Our results pave the way for the modeling of spin precession effects in the gravitational waveform from binary neutron star events.
Only numerical relativity simulations can capture the full complexities of binary black hole mergers. These simulations, however, are prohibitively expensive for direct data analysis applications such as parameter estimation. We present two new fast
and accurate surrogate models for the outputs of these simulations: the first model, NRSur7dq4, predicts the gravitational waveform and the second model, RemnantModel, predicts the properties of the remnant black hole. These models extend previous 7-dimensional, non-eccentric precessing models to higher mass ratios, and have been trained against 1528 simulations with mass ratios $qleq4$ and spin magnitudes $chi_1,chi_2 leq 0.8$, with generic spin directions. The waveform model, NRSur7dq4, which begins about 20 orbits before merger, includes all $ell leq 4$ spin-weighted spherical harmonic modes, as well as the precession frame dynamics and spin evolution of the black holes. The final black hole model, RemnantModel, models the mass, spin, and recoil kick velocity of the remnant black hole. In their training parameter range, both models are shown to be more accurate than existing models by at least an order of magnitude, with errors comparable to the estimated errors in the numerical relativity simulations. We also show that the surrogate models work well even when extrapolated outside their training parameter space range, up to mass ratios $q=6$.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
