SEOBNRv6EHM is a multipolar EOB model for eccentric planar-orbit BBHs calibrated to NR simulations, showing low waveform mismatches up to eccentricity 0.9.
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The Fast and the Frame-Dragging: Efficient waveforms for asymmetric-mass eccentric equatorial inspirals into rapidly-spinning black holes
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abstract
Observations of gravitational-wave signals emitted by compact binary inspirals provide unique insights into their properties, but their analysis requires accurate and efficient waveform models. Intermediate- and extreme-mass-ratio inspirals (I/EMRIs), with mass ratios $q \gtrsim 10^2$, are promising sources for future detectors such as the Laser Interferometer Space Antenna (LISA). Modelling waveforms for these asymmetric-mass binaries is challenging, entailing the tracking of many harmonic modes over thousands to millions of cycles. The FastEMRIWaveforms (FEW) modelling framework addresses this need, leveraging precomputation of mode data and interpolation to rapidly compute adiabatic waveforms for eccentric inspirals into zero-spin black holes. In this work, we extend FEW to model eccentric equatorial inspirals into black holes with spin magnitudes $|a| \leq 0.999$. Our model supports eccentricities $e < 0.9$ and semi-latus recta $p < 200$, enabling the generation of long-duration IMRI waveforms, and produces waveforms in $\sim 100$ ms with hardware acceleration. Characterising systematic errors, we estimate that our model attains mismatches of $\sim 10^{-5}$ (for LISA sensitivity) with respect to error-free adiabatic waveforms over most of parameter space. We find that kludge models introduce errors in signal-to-noise ratios (SNRs) as great as $^{+60\%}_{-40\%}$ and induce marginal biases of up to $\sim 1\sigma$ in parameter estimation. We show LISA's horizon redshift for I/EMRI signals varies significantly with $a$, reaching a redshift of $3$ ($15$) for EMRIs (IMRIs) with only minor $(\sim10\%)$ dependence on $e$ for an SNR threshold of 20. For signals with SNR $\sim 50$, spin and eccentricity-at-plunge are measured with uncertainties of $\delta a \sim 10^{-7}$ and $\delta e_f \sim 10^{-5}$. This work advances the state-of-the-art in waveform generation for asymmetric-mass binaries.
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representative citing papers
Moderately mitigated glitch streams induce negligible to minor biases (0.04–0.6σ) in EMRI parameters while weakly mitigated streams with higher-SNR events can reach ~1σ biases, making EMRI inference more robust than for MBHBs.
Self-force theory is extended to compute merger and ringdown waveforms in beyond-GR black hole binaries under the extreme mass-ratio approximation, with first calculations of self-force corrections to the merger waveform.
Recoil kicks and binary interactions in AGN disks suppress EMRI formation except in young systems, predicting LISA rates of 1-30 per year dominated by low-mass AGNs.
Relativistic metric backreaction from scalar dark matter clouds in EMRIs produces dominant polar gravitational wave corrections for Mμ ≲ 0.12, exceeding axial and scalar radiation channels at small separations.
Extended 1PA self-force waveforms for slowly spinning primary and precessing secondary, with re-summed 1PAT1R variant showing improved accuracy against NR for q ≳ 5 and |χ1| ≲ 0.1.
LISA EMRIs can constrain deviations from Kerr equatorial symmetry to 10^{-2} and axial symmetry to 10^{-3} using Analytic Kludge waveforms and Fisher analysis.
Self-force calculations of radiated gravitational wave energy from hyperbolic orbits around Schwarzschild black holes agree with post-Minkowskian results for large impact parameters and velocities up to 0.7c, with further comparisons to post-Newtonian and numerical relativity.
For high-spin Kerr circular orbits, l_max >=30 and Chebyshev interpolation with global relative flux error matching the mass ratio yield mismatches below 10^{-3} and negligible parameter biases in 4-year EMRI signals with SNR ~100.
A neural-network-accelerated hierarchical Bayesian pipeline is developed and validated on a phenomenological model to constrain EMRI population parameters from LISA data.
A multi-parameter formalism is developed to describe asymmetric binaries in general matter distributions by perturbing around Schwarzschild and reducing metric and fluid perturbations to wave equations similar to the vacuum case.
The paper reports on the aims, activities, and conclusions of an early-career workshop focused on scientific overviews, transferable skills, and networking in gravitational physics.
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First-time assessment of glitch-induced bias and uncertainty in inference of extreme mass ratio inspirals
Moderately mitigated glitch streams induce negligible to minor biases (0.04–0.6σ) in EMRI parameters while weakly mitigated streams with higher-SNR events can reach ~1σ biases, making EMRI inference more robust than for MBHBs.
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Black hole mergers beyond general relativity: a self-force approach
Self-force theory is extended to compute merger and ringdown waveforms in beyond-GR black hole binaries under the extreme mass-ratio approximation, with first calculations of self-force corrections to the merger waveform.
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Post-adiabatic self-force waveforms: slowly spinning primary and precessing secondary
Extended 1PA self-force waveforms for slowly spinning primary and precessing secondary, with re-summed 1PAT1R variant showing improved accuracy against NR for q ≳ 5 and |χ1| ≲ 0.1.
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Gravitational radiation from hyperbolic orbits: comparison between self-force, post-Minkowskian, post-Newtonian, and numerical relativity results
Self-force calculations of radiated gravitational wave energy from hyperbolic orbits around Schwarzschild black holes agree with post-Minkowskian results for large impact parameters and velocities up to 0.7c, with further comparisons to post-Newtonian and numerical relativity.
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Systematic errors in fast relativistic waveforms for Extreme Mass Ratio Inspirals
For high-spin Kerr circular orbits, l_max >=30 and Chebyshev interpolation with global relative flux error matching the mass ratio yield mismatches below 10^{-3} and negligible parameter biases in 4-year EMRI signals with SNR ~100.
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Constraints on the extreme mass-ratio inspiral population from LISA data
A neural-network-accelerated hierarchical Bayesian pipeline is developed and validated on a phenomenological model to constrain EMRI population parameters from LISA data.
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A multi-parameter expansion for the evolution of asymmetric binaries in astrophysical environments
A multi-parameter formalism is developed to describe asymmetric binaries in general matter distributions by perturbing around Schwarzschild and reducing metric and fluid perturbations to wave equations similar to the vacuum case.
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The Early Career Workshop of GR-Amaldi 2025
The paper reports on the aims, activities, and conclusions of an early-career workshop focused on scientific overviews, transferable skills, and networking in gravitational physics.