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Quantifying the Scientific Potential of Intermediate and Extreme Mass Ratio Inspirals with the Laser Interferometer Space Antenna
Authors:
Lorenzo Speri,
Francisco Duque,
Susanna Barsanti,
Alessandro Santini,
Shubham Kejriwal,
Ollie Burke,
Christian E. A. Chapman-Bird
Abstract:
The Laser Interferometer Space Antenna (LISA) will enable precision studies of Extreme and Intermediate Mass Ratio Inspirals (EMRIs/IMRIs), providing unique probes of astrophysical environments of galactic nuclei and strong-field gravity. Using a fully relativistic pipeline across primary masses $m_1 \in [5\times10^4, 10^7]\,M_\odot$ and secondary masses $m_2 \in [1, 10^4]\,M_\odot$, we map instru…
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The Laser Interferometer Space Antenna (LISA) will enable precision studies of Extreme and Intermediate Mass Ratio Inspirals (EMRIs/IMRIs), providing unique probes of astrophysical environments of galactic nuclei and strong-field gravity. Using a fully relativistic pipeline across primary masses $m_1 \in [5\times10^4, 10^7]\,M_\odot$ and secondary masses $m_2 \in [1, 10^4]\,M_\odot$, we map instrumental performance directly to detection horizons and parameter measurement precision. EMRIs with $m_1 = 10^7\,M_\odot$ and $m_2 \sim 1\,M_\odot$ are the most sensitive to instrument degradation, with redshift horizons at $z \sim 0.01$, while IMRIs are the least sensitive to degradation and reach redshifts $z \sim 1-3$. All prograde systems considered achieve sub-percent spin precision within three months of observation. The full 4.5-year mission increases the horizon of systems with $m_1 = 10^7\,M_\odot$ and $m_2 \sim 1\,M_\odot$ by a factor of $\sim 4$ and improves sky localization by one to two orders of magnitude reaching $ < 10\,\mathrm{deg}^2$. IMRI detection is robust against degradation, but their parameter estimation is more vulnerable due to fewer cycles in band. With the full baseline, EMRI observations constrain scalar dipole emission and Kerr quadrupole deviations below ground-based bounds by one to two orders of magnitude. We release the accompanying software and an interactive website to enable the community to rapidly quantify the scientific potential of EMRIs and IMRIs.
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Submitted 17 March, 2026;
originally announced March 2026.
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Inferring the population properties of galactic binaries from LISA's stochastic foreground
Authors:
Federico De Santi,
Alessandro Santini,
Alexandre Toubiana,
Nikolaos Karnesis,
Davide Gerosa
Abstract:
Galactic binaries are expected to be the most numerous LISA sources and to produce a stochastic gravitational-wave foreground whose spectral shape encodes information about the underlying population. Extracting this information with standard hierarchical methods is challenging due to the high dimensionality of the problem and the computational cost of global-fit analyses. We present a simulation-b…
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Galactic binaries are expected to be the most numerous LISA sources and to produce a stochastic gravitational-wave foreground whose spectral shape encodes information about the underlying population. Extracting this information with standard hierarchical methods is challenging due to the high dimensionality of the problem and the computational cost of global-fit analyses. We present a simulation-based inference framework to measure the population properties of galactic binaries directly from the reconstructed foreground. Adopting an astrophysically agnostic parametrization in the observable space -- defined by signal amplitude, frequency, and frequency derivative -- we generate synthetic catalogs and foreground spectra using a global-fit-inspired subtraction algorithm. We then train a neural posterior estimator to map spectra to population parameters. We validate our method on simulated data and recover population parameters with good accuracy, including the total number of binaries. As a by-product, we present a GPU-accelerated version of the subtraction algorithm, which delivers a ~100X speed-up compared to previous implementations in the literature. Our results demonstrate that LISA's stochastic foreground alone carries significant information about the Galactic binary population and provide a practical step toward joint inference from resolved and unresolved sources.
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Submitted 20 February, 2026;
originally announced February 2026.
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A flexible, GPU-accelerated approach for the joint characterization of LISA instrumental noise and Stochastic Gravitational Wave Backgrounds
Authors:
Alessandro Santini,
Martina Muratore,
Jonathan Gair,
Olaf Hartwig
Abstract:
LISA data analysis represents one of the most challenging tasks ahead for the future of gravitational-wave (GW) astronomy. Characterizing the instrument's noise properties while fitting for all the other detectable sources is a key requirement of any robust inference pipeline. Noise estimation will also play a crucial role in searches and parameter estimation of cosmological and astrophysical stoc…
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LISA data analysis represents one of the most challenging tasks ahead for the future of gravitational-wave (GW) astronomy. Characterizing the instrument's noise properties while fitting for all the other detectable sources is a key requirement of any robust inference pipeline. Noise estimation will also play a crucial role in searches and parameter estimation of cosmological and astrophysical stochastic signals. Previous studies have tackled this topic by assuming perfect knowledge of the spectral shape of the instrumental noise and of different possible types of GW Stochastic Backgrounds (SGWBs), usually resorting to parametrized templates. Recently, various works that employ template-agnostic methods have been presented. In this work, we take an additional step further, introducing flexible spectral shapes in both the instrumental noise and the stochastic signals. We account for the lack of knowledge of the exact shape of the individual contributions to the overall power spectral density by using splines to represent arbitrary perturbations of the noise and signal spectral densities. We implement a data-driven Reversible Jump MCMC algorithm to fit different components simultaneously and to infer the level of flexibility required under different scenarios. We test this approach on simulated LISA data produced under different assumptions. We investigate the impact of this increased flexibility on the reconstruction of both the injected signal and the noise level, and we discuss the prospects for claiming a successful SGWB detection.
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Submitted 20 October, 2025; v1 submitted 8 July, 2025;
originally announced July 2025.
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The Fast and the Frame-Dragging: Efficient waveforms for asymmetric-mass eccentric equatorial inspirals into rapidly-spinning black holes
Authors:
Christian E. A. Chapman-Bird,
Lorenzo Speri,
Zachary Nasipak,
Ollie Burke,
Michael L. Katz,
Alessandro Santini,
Shubham Kejriwal,
Philip Lynch,
Josh Mathews,
Hassan Khalvati,
Jonathan E. Thompson,
Soichiro Isoyama,
Scott A. Hughes,
Niels Warburton,
Alvin J. K. Chua,
Maxime Pigou
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 wavef…
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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 $\sim 1σ$ 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 $δa \sim 10^{-7}$ and $δe_f \sim 10^{-5}$. This work advances the state-of-the-art in waveform generation for asymmetric-mass binaries.
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Submitted 17 November, 2025; v1 submitted 11 June, 2025;
originally announced June 2025.
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Reconstructing parametric gravitational-wave population fits from non-parametric results without refitting the data
Authors:
Cecilia Maria Fabbri,
Davide Gerosa,
Alessandro Santini,
Matthew Mould,
Alexandre Toubiana,
Jonathan Gair
Abstract:
Combining multiple events into population analyses is a cornerstone of gravitational-wave astronomy. A critical component of such studies is the assumed population model, which can range from astrophysically motivated functional forms to non-parametric treatments that are flexible but difficult to interpret. In practice, the current approach is to fit the data multiple times with different populat…
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Combining multiple events into population analyses is a cornerstone of gravitational-wave astronomy. A critical component of such studies is the assumed population model, which can range from astrophysically motivated functional forms to non-parametric treatments that are flexible but difficult to interpret. In practice, the current approach is to fit the data multiple times with different population models to identify robust features. We propose an alternative strategy: assuming the data have already been fit with a flexible model, we present a practical recipe to reconstruct the population distribution of a different model. As our procedure postprocesses existing results, it avoids the need to access the underlying gravitational-wave data again and handle selection effects. Additionally, our reconstruction metric provides a goodness-of-fit measure to compare multiple models. We apply this method to the mass distribution of black-hole binaries detected by LIGO/Virgo/KAGRA. Our work paves the way for streamlined gravitational-wave population analyses by fitting the data once and for all with advanced non-parametric methods and careful handling of selection effects, while the astrophysical interpretation is then made accessible using our reconstruction procedure on targeted models. The key principle is that of conceptually separating data description from data interpretation.
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Submitted 20 May, 2025; v1 submitted 28 January, 2025;
originally announced January 2025.
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Impact of relativistic waveforms in LISA's science objectives with extreme-mass-ratio inspirals
Authors:
Hassan Khalvati,
Alessandro Santini,
Francisco Duque,
Lorenzo Speri,
Jonathan Gair,
Huan Yang,
Richard Brito
Abstract:
Extreme-Mass-Ratio Inspirals (EMRIs) are one of the key targets for future space-based gravitational wave detectors, such as LISA. The scientific potential of these sources can only be fully realized with fast and accurate waveform models. In this work, we extend the \textsc{FastEMRIWaveform} (\texttt{FEW}) framework by providing fully relativistic waveforms at adiabatic order for circular, equato…
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Extreme-Mass-Ratio Inspirals (EMRIs) are one of the key targets for future space-based gravitational wave detectors, such as LISA. The scientific potential of these sources can only be fully realized with fast and accurate waveform models. In this work, we extend the \textsc{FastEMRIWaveform} (\texttt{FEW}) framework by providing fully relativistic waveforms at adiabatic order for circular, equatorial orbits in Kerr spacetime, for mass ratios up to $10^{-3}$. We investigate the significance of including relativistic corrections in the waveform for both vacuum and non-vacuum environments. Specifically, we develop relativistic non-vacuum EMRI waveforms including two different environmental effects in the EMRI waveforms: power-law migration torques, and superradiance scalar clouds. For EMRIs in vacuum, we find that non-relativistic waveforms incorrectly estimate the predicted source's horizon redshift by approximately $35\%$ error. Our analysis shows that incorporating relativistic corrections enhances constraints on accretion disks, modeled through power-law torques, and improves the constraints on disk parameter estimates (error $\simeq 8\%$), representing a significant improvement over previous estimates. Additionally, we assess the evidence for models in a scenario where ignoring the accretion disk biases the parameter estimation (PE), reporting a $\log_{10}$ Bayes factor of $1.1$ in favor of the accretion disk model. In a fully relativistic setup, we also estimate the parameters of superradiant scalar clouds with relative errors $\simeq 0.3\%$ for the scalar cloud's mass. These results demonstrate that incorporating relativistic effects is essential for LISA science objectives with EMRIs.
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Submitted 28 April, 2025; v1 submitted 22 October, 2024;
originally announced October 2024.
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Black-hole mergers in disklike environments could explain the observed $q$-$χ_\mathrm{eff}$ correlation
Authors:
Alessandro Santini,
Davide Gerosa,
Roberto Cotesta,
Emanuele Berti
Abstract:
Current gravitational-wave data from stellar-mass black-hole binary mergers suggest a correlation between the binary mass ratio $q$ and the effective spin $χ_\mathrm{eff}$: more unequal-mass binaries consistently show larger and positive values of the effective spin. Multiple generations of black-hole mergers in dense astrophysical environments may provide a way to form unequal-mass systems, but t…
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Current gravitational-wave data from stellar-mass black-hole binary mergers suggest a correlation between the binary mass ratio $q$ and the effective spin $χ_\mathrm{eff}$: more unequal-mass binaries consistently show larger and positive values of the effective spin. Multiple generations of black-hole mergers in dense astrophysical environments may provide a way to form unequal-mass systems, but they cannot explain the observed correlation on their own. We show that the symmetry of the astrophysical environment is a crucial feature to shed light on this otherwise puzzling piece of observational evidence. We present a toy model that reproduces, at least qualitatively, the observed correlation. The model relies on axisymmetric, disk-like environments where binaries participating in hierarchical mergers share a preferential direction. Migration traps in AGN disks are a prime candidate for this setup, hinting at the exciting possibility of constraining their occurrence with gravitational-wave data.
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Submitted 24 October, 2023; v1 submitted 24 August, 2023;
originally announced August 2023.