REVIEW 5 cited by
Improved inspiral-merger-ringdown model for BBHs on elliptical orbits
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Improved inspiral-merger-ringdown model for BBHs on elliptical orbits
read the original abstract
Gravitational waveforms capturing binary evolution through the early-inspiral phase play a critical role in extracting orbital features that nearly disappear during the late-inspiral and subsequent merger phase due to radiation reaction forces; for instance, the effect of orbital eccentricity. Phenomenological approaches that model compact binary mergers rely heavily on combining inputs from both analytical and numerical approaches to reduce the computational cost of generating templates for data analysis purposes. In a recent work, Chattaraj et al., Phys. Rev. D 106, 124008 (2022) constructed a dominant ($\ell=2$, $|m|=2$) mode model for nonspinning binary black holes (BBHs) on elliptical orbits. The model was constructed in time domain and is fully analytical. The current work is an attempt to improve this model by making a few important changes in our approach. The most significant of those involves identifying initial values of orbital parameters with which the inspiral part of the model is evolved. While the ingredients remain the same as in the previous work, the resulting (new) model, when compared against a set of target waveforms constructed here, produces match values better than 96.5% for systems heavier than $80M_\odot$, while with the old model this limit on the total mass is $115M_\odot$. The updated model is validated against an independent eccentric waveform family (TEOBResumS-Dali) for an initial eccentricity ($e_0$), mass ratio ($q$) and mean anomaly ($l_0$) in the range $0\lesssim e_0\lesssim0.3$, $1\lesssim q\lesssim3$ and $-\pi\leq l_0\leq\pi$, respectively. Further, an alternate model including the effect of higher order modes is also provided. Finally, while our model assumes nonspinning components, we show that it could also be used for systems with component spin vectors (anti-) aligned w.r.t. the orbital angular momentum and small spin magnitudes.
Forward citations
Cited by 5 Pith papers
-
Accurate waveforms for generic planar-orbit binary black holes: The multipolar effective-one-body model SEOBNRv6EHM
SEOBNRv6EHM is a multipolar EOB model for eccentric planar-orbit BBHs calibrated to NR simulations, showing low waveform mismatches up to eccentricity 0.9.
-
Including higher-order modes in a quadrupolar eccentric numerical relativity surrogate using universal eccentric modulation functions
The gwNRHME framework constructs a multi-modal non-spinning eccentric gravitational waveform surrogate by modulating quasi-circular models with universal eccentric functions, achieving median mismatches of ~9e-5 again...
-
Efficient Eccentric Effective-One-Body Dynamics via Near-Identity Averaging Transformations
Near-identity averaging transformations applied to osculating orbital elements reduce the computational cost of eccentric EOB inspirals by up to two orders of magnitude while maintaining accuracy for moderate to large...
-
Chase Orbits, not Time: A Scalable Paradigm for Long-Duration Eccentric Gravitational-Wave Surrogates
Eccentric inspiral waveforms are modeled against mean anomaly rather than time, yielding an order-of-magnitude compression and a 2.77e6 M surrogate that is ~20x faster to evaluate.
-
Biased parameter inference of eccentric, spin-precessing binary black holes
Eccentric BBH signals recovered with quasi-circular precessing models show biases in chirp mass and χ_p; Bayes factors favor eccentric aligned-spin models when both eccentricity and precession are present.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.