arXiv subjects

Matias Zaldarriaga

Publications and source records attributed to Matias Zaldarriaga.

At least 19 recordsLinked to original sources

arXiv2026

Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves

Fast surrogate models for expensive simulations are now essential across the sciences, yet they typically operate as black boxes. We present \texttt{GWAgent}, a large language model (LLM)-based workflow that constructs interpretable analytic surrogates directly from simulation data. Surrogate modeling is well suited to agentic workflows because candidate models can be quantitatively validated against ground-truth simulations at each iteration. As a demonstration, we build a surrogate for gravitational waveforms from eccentric binary black hole mergers. We show that providing the agent with a physics-informed domain ansatz substantially improves output model accuracy. The resulting analytic surrogate attains a median Advanced LIGO mismatch of $6.9\times10^{-4}$ together with an $\sim 8.4\times$ speedup in waveform evaluation, surpassing both symbolic regression and conventional machine learning baselines. Beyond producing an accurate model, the workflow identifies compact physical structure from the learned representation. As an astrophysical application, we use \texttt{GWAgent} to analyze the eccentricity of GW200129 and infer $e_{20\mathrm{Hz}}=0.099^{+0.063}_{-0.044}$. These results show that validation-constrained agentic workflows can produce accurate, fast, and interpretable surrogates for scientific simulations and inference.

gr-qc↗

arXiv2026

Anisotropies in the PTA gravitational wave background: what can they teach us about supermassive black hole binaries?

The gravitational wave background detected by pulsar timing arrays is sourced by a finite population of supermassive black hole binaries, and is therefore anisotropic. We ask what measuring that anisotropy can teach us about the population, using models that span a wide range of effective source counts, all normalized to the measured background amplitude. We find four things. First, the expected anisotropy is produced by the single brightest binary: a dipole at the level of the published NANOGrav 95% upper limit would require one source to supply about 60% of the power in the band. Second, no model that also reproduces the measured strain spectrum contains a source that bright. In every case the loudest binary stays below the NANOGrav continuous-wave upper limit at every frequency it covers, consistent with the joint search of the 15-year data, which finds no resolved source. Third, because the anisotropy is produced by one source, compressing the sky to an angular power spectrum discards the phase information that locates it. Such a search is never more sensitive than looking for the source directly, and is strictly worse once more than a dipole is kept. Fourth, the published upper limits on the angular power spectrum therefore reflect the analysis prior rather than the data: they coincide with the 95th percentile of the prior induced by the square-root spherical harmonic basis adopted in the analysis. What does constrain the population today is the shape of the strain spectrum. Rare, bright sources depress the median spectrum below its mean, and fitting the measured spectrum already disfavors mass functions dominated by binaries above about 10^10 solar masses.

astro-ph.CO↗

arXiv2026

Summary statistic for pulsar timing arrays

The timing residuals produced by gravitational-wave signals can be described as an incoherent (pulsar term) contribution and a coherent (Earth term) map on the sky, which PTAs measure at the locations of the timed pulsars. The observed Earth term map and the variance induced by the pulsar term contain all of the information about any GW signal available to a PTA (assuming pulsar distances are unknown). Furthermore, any type of signal produces on average the same angular correlation function, the Hellings and Downs curve, which decays steeply with multipole as $C_\ell \propto 1/[(\ell+2)(\ell+1)\ell(\ell-1)]$. This suggests that the signal is inherently low-dimensional and therefore only a small number of parameters are needed to fully characterize it. We present an expression for the PTA likelihood that makes the dependence on the Earth term map and pulsar term variance explicit, and show that only a few spherical harmonic coefficients are needed to capture most of the information about the signal. To quantify this in a realistic setting, we compute the Fisher matrix of the amplitude of a stochastic background or a deterministic point source assuming the noise properties and sky locations of the pulsars in the NANOGrav 15yr dataset. We find that $\ell_{\rm max}=2$ of the Earth term map and the monopole of the pulsar term variance retain $\sim 95\%$ of the information about the signal. For a point source, including the dipole of the pulsar term variance is important to achieve a similar fraction.

astro-ph.CO↗

arXiv2026

The diffraction-lensing interpretation of GW231123 with astrophysical priors

GW231123, if unlensed, is a rare binary black hole merger with high masses and high spins for both progenitors. We show that the signal is better fitted by a lower-mass, lower-spin merger that is diffraction-lensed by an isolated object of redshifted mass $\sim 1000\,\rm M_\odot$, modeled either as a point mass or as a spherically symmetric compact halo. Because diffraction-lensed events are also rare, hypothesis testing should quote the posterior odds ratio rather than the Bayes factor, which requires quantifying our prior belief in the two hypotheses. We adopt the GWTC-5 population distribution as our source parameter prior, and quantify the prior on the lens hypothesis through the lensing optical depth. For a point-mass lens, observational constraints on the abundance of black holes in the Universe yield an upper bound on the optical depth, and hence on the posterior odds, which do not rule out lensing. However, using a predicted mass function of intermediate-mass black holes formed in star clusters gives a low optical depth that strongly disfavors lensing. For a dark matter halo lens, standard collisionless cold dark matter does not form halos compact enough to give the required optical depth, but self-interacting dark matter with a large cross section at low velocities can trigger gravothermal collapse and form them, in which case the posterior odds are inconclusive. In either case, from a frequentist perspective, we show that detecting a lensed event with properties like GW231123 is unlikely. These conclusions apply to isolated lenses, while a lens embedded in an external gravitational potential could change the picture.

astro-ph.CO↗

arXiv2026

Universal distance modes from DESI BAO and Type Ia supernovae: what do cosmological rulers actually measure?

We use an SVD decomposition of the low-redshift distance measurements from DESI BAO and three Type Ia supernova compilations to identify the leading linear directions probed by the data and to localize the tension with the LCDM CMB-anchored predictions. The leading direction V_0 -- whose data amplitude we denote c_0 -- is, to high accuracy, a measurement of Omega_m h^2: the projection of the data on V_0 probes essentially this one CMB-derived parameter combination. BAO constrains this parameter more tightly than the CMB itself; the three SN compilations do not. In every extension of LCDM we consider, the leading measurable direction remains V_0, and it is where most of the tension with the CMB resides. In the w0-wa extension a second direction V_1 becomes measurable and provides an independent test of dynamical dark energy; the data show no significant tension in this direction. The only other beyond-LCDM extension that opens a genuinely new measurable direction is spatial curvature, and only marginally and only for BAO; both measurable directions then independently prefer positive spatial curvature, though the second direction is poorly constrained.

astro-ph.CO↗

arXiv2026

A Joint Optimal Search for Gravitational Waves from Resolved and Unresolved Supermassive Binary Black Holes with Pulsar Timing Arrays

We introduce, from first principles, a joint model of the gravitational wave background (GWB) and brightest supermassive black hole binary (SMBHB) sources that may be individually resolvable in Pulsar Timing Array (PTA) searches for gravitational waves. We propose the characteristic number of SMBHB sources, $N_{\rm c}$, as a detection statistic for the astrophysical origin of the GWB. We then demonstrate how the brightest SMBHBs assist in resolving $N_{\rm c}$. Applying our method to the simulated NANOGrav 15-year data, which replicates all aspects of real data's known noise, observations, and the inferred GWB power spectrum, we demonstrate direct astrophysical limits on the strain amplitude of individually resolvable SMBHBs. We find that 21 of 114 SMBHB candidates from active galactic nuclei observations are in tension with the NANOGrav's observations. In contrast, only one candidate is in tension with the NANOGrav data based on the upper limits reported in the original analysis. Constraining the Poisson-specific characteristic number of SMBHBs, $N_{\rm c}$, at ${\rm yr}^{-1}$, we outline implications for the population properties of SMBHBs. Based on our new model applied to the simulated NANOGrav data, we calculate the probability of detecting GWs from isolated SMBHB in the 15-year data to be 2\% at the ${\rm SNR}=5$ level. Our projection towards the expected NANOGrav 20-year data suggests an increase to 5\%. With this, we estimate the probability of finding an outlier with an SNR of 2 in the NANOGrav 20-year data to be $40\%$.

astro-ph.HE↗

arXiv2026

Data-driven extraction, phenomenology and modeling of eccentric harmonics in binary black hole merger waveforms

Newtonian and post-Newtonian (PN) calculations suggest that each spherical harmonic mode of the gravitational waveforms (radiation) emitted by eccentric binaries can be further decomposed into several eccentricity-induced modes (indexed by $j=1$ to $j=\infty$), referred to as eccentric harmonics. These harmonics exhibit monotonically time-varying amplitudes and instantaneous frequencies, unlike the full eccentric spherical harmonic modes. However, computing or extracting these harmonics are not straightforward in current numerical relativity (NR) simulations and eccentric waveform models. To address this, Patterson \textit{et al} have developed a framework to extract the eccentric harmonics directly from effective-one-body formalism waveforms. In this paper, we build on the ideas presented in Patterson \textit{et al} and propose a data-driven framework, utilizing singular-value decomposition (SVD), that incorporates additional features based on PN intuition to ensure monotonicity in the extracted harmonics. We further demonstrate that the phase (frequency) of these harmonics is simply $jϕ_λ+ϕ_{\rm ecc}$ ($jf_λ+f_{\rm ecc}$) where $ϕ_λ$ ($f_λ$) is related to the secular orbital phase (frequency) and $ϕ_{\rm ecc}$ ($f_{\rm ecc}$) is an additional phase (frequency) that only depends on the eccentricity. We also provide simple analytical fits to obtain the harmonics as a function of the mean anomaly. These relations may prove useful in constructing faithful models that can be employed in cheap and efficient searches and parameter estimation of eccentric mergers. Our framework is modular and can be extended for any other eccentric waveform models or simulation frameworks. The framework is available through the \texttt{gwMiner} package.

gr-qc↗

arXiv2026

GW190711_030756 and GW200114_020818: astrophysical interpretation of two asymmetric binary black hole mergers in the IAS catalog

We provide a comprehensive analysis of GW190711_030756 and GW200114_020818, two of the most significant binary black hole merger candidates in the IAS catalog, with probabilities of astrophysical origin $p_{\rm astro}=0.99$ and $0.71$, respectively, and signal-to-noise ratios of approximately $10.0$ and $13.4$. We employ numerical relativity surrogate models to infer both the source properties and the remnant properties of these two candidates. We find that both GW190711_030756 and GW200114_020818 are asymmetric-mass binaries, with inferred mass ratios of $0.35^{+0.32}_{-0.15}$ and $\leq 0.20$. In addition, GW200114_020818 is inferred to have a source-frame total mass of approximately $220M_{\odot}$ and highly spinning black holes, with primary (secondary) dimensionless spin magnitudes of $0.96^{+0.03}_{-0.07}$ ($0.84^{+0.13}_{-0.34}$), closely resembling GW231123_135430. We further find that GW200114\_020818 has a confidently negative effective inspiral spin of $χ_{\rm eff}=-0.60^{+0.22}_{-0.13}$ and exhibits strong spin precession, characterized by an effective precession parameter of $χ_{\rm p}=0.60^{+0.21}_{-0.19}$. GW200114_020818 (when considered alongside GW231123_135430) points towards an emerging population of massive, rapidly spinning BBH mergers. While GW231123_135430 is consistent with mergers in globular clusters, producing systems like GW200114_020818 in such environments remains difficult even under hierarchical merger scenarios. The probability that the remnant black hole of GW190711_030756 (GW200114_020818) is retained in its host environment is $0.079$ ($0.0002$), $0.62$ ($0.965$), and $0.997$ ($1$) if the merger occurred in a globular cluster, a nuclear star cluster, or an elliptical galaxy, respectively.

astro-ph.HE↗

arXiv2026

Searching for precessing binary systems with mode-by-mode filtering and marginalization

Nearly all previous binary black hole searches in LIGO--Virgo--KAGRA (LVK) gravitational wave data have assumed that the component spins are aligned with the orbital angular momentum, thereby neglecting spin-precession effects in the waveform, which can lead to potentially missing interesting signals. Precessing searches are challenging, because the extra degrees of freedom due to misaligned spins lead to: $(i)$ a much larger number of templates compared to the aligned-spin configurations, $(ii)$ an increased rate of background triggers. To address this, we develop novel precessing signal template banks using mode-by-mode filtering and marginalization methods. We use the precession harmonic decomposition from Fairhurst et al. (2019) and filter each precessing harmonic separately with the data. We then marginalize over the SNRs from different harmonics in our detection statistic. We also use machine learning methods to improve our search efficiency: $(i)$ we use singular value decomposition together with random forest regressor to reduce redundancy in the dominant precessing-harmonic templates; $(ii)$ we use normalizing flows to generate optimal prior samples for harmonic SNRs for the marginalized statistic. We show that marginalizing (instead of maximizing) over the harmonic mode SNRs increases the search sensitive volume by $\sim 10\%$. Results from searching in LVK data using this framework will be reported in a companion paper.

gr-qc↗

arXiv2025

Binary black hole population inference combining confident and marginal events from the $\tt{IAS\text{-}HM}$ search pipeline

We present the population properties of binary black hole mergers identified by the $\tt{IAS\text{-}HM}$ pipeline (which incorporates higher-order modes in the search templates) during the third observing run (O3) of the LIGO, Virgo, and KAGRA (LVK) detectors. In our population inference analysis, instead of only using events above a sharp cut based on a particular detection threshold (e.g., false alarm rate), we use a Bayesian framework to consistently include both marginal and confident events. We find that our inference based solely on highly significant events ($p_{\mathrm{astro}} \sim 1$) is broadly consistent with the GWTC-3 population analysis performed by the LVK collaboration. However, incorporating marginal events into the analysis leads to a preference for stronger redshift evolution in the merger rate and an increased density of asymmetric mass-ratio mergers relative to the GWTC-3 analysis, while remaining within its allowed parameter ranges. Using simple parametric models to describe the binary black hole population, we estimate a merger rate density of $32.4^{+18.5}_{-12.2}\ \mathrm{Gpc}^{-3}\,\mathrm{yr}^{-1}$ at redshift $z = 0.2$, and a redshift evolution parameter of $κ= 4.4^{+1.9}_{-2.0}$. Assuming a power-law form for the mass ratio distribution ($\propto q^β$), we infer $β= 0.1^{+1.9}_{-1.4}$, indicating a relatively flat distribution. These results highlight the potential impact of marginal events on population inferences and motivate future analyses with data from upcoming observing runs.

gr-qc↗

arXiv2025

Generating optimal Gravitational-Wave template banks with metric-preserving autoencoders

Matched filtering for signal detection in noisy data requires template banks that capture variation in signal waveforms while minimizing computational cost. Dimensionality reduction of signal waveforms can be important for building efficient template banks. In various domains of physics, dimensionality reduction is very commonly performed using linear methods such as singular value decomposition (SVD). This can, however, introduce redundancies if the signals span curved, nonlinear manifolds in parameter space. Alternatively, autoencoders are a type of neural networks that can be used for non-linear dimensionality reduction. We use a variation of the autoencoder which preserves the metric in its latent space ($g_{ij}^{\text{latent}} \approx g_{ij}^{\text{physical}}$); this enables template banks to be constructed by simply placing a uniform grid in the autoencoder's low-dimensional latent space. We apply our method for creating geometric template banks for gravitational wave searches and show that our banks require fewer dimensions compared to using the SVD basis. Our method can also be useful for other applications requiring dimensionality reduction, such as gravitational waveform modeling, fast parameter estimation and model-independent tests of general relativity. Finally, we discuss extensions to other domains including cosmological parameter estimation, and we show tests of our method in extreme cases of periodic signal manifolds.

gr-qc↗

arXiv2025

Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses

We extend field-level inference to jointly constrain the cosmological parameters $\{A,ω_{\rm cdm},H_0\}$, in both real and redshift space. Our analyses are based on mock data generated using a perturbative forward model, with noise drawn from a Gaussian distribution with a constant power spectrum. This idealized setting, where the field-level likelihood is exactly Gaussian, allows us to precisely quantify the information content in the nonlinear field on large scales. We find that field-level inference accurately recovers all cosmological parameters in both real and redshift space, with uncertainties consistent with perturbation theory expectations. We show that these error bars are comparable to those obtained from a joint power spectrum and bispectrum analysis using the same perturbative model. Finally, we perform several tests using the Gaussian field-level likelihood to fit the mock data where the true noise model is non-Gaussian, and find significant biases in the inferred cosmological parameters. These results highlight that the success of field-level inference critically depends on using the correct likelihood, which may be the primary challenge for applying this method to smaller scales even in the perturbative regime.

astro-ph.CO↗

arXiv2025

Data-driven extraction and phenomenology of eccentric harmonics in eccentric spinning binary black hole mergers

Newtonian and post-Newtonian (PN) calculations indicate that the phenomenology of eccentric binary black hole (BBH) merger waveforms is significantly more complex than that of their quasi-circular counterparts. Each spherical harmonic mode of the radiation can be further decomposed into several eccentricity-induced components, referred to as eccentric harmonics. Unlike the (cumulative) spherical harmonic modes, these constituent eccentric harmonics exhibit monotonically time-varying amplitudes and frequencies. However, these eccentric harmonics are not directly accessible in numerical relativity (NR) simulations or current eccentric waveform models. Using the recently developed data-driven framework gwMiner, which combines singular value decomposition, input from post-Newtonian theory, and signal processing techniques, we extract eccentric harmonics from eccentric, aligned-spin waveforms for six different spherical harmonic modes: (2,1), (2,2), (3,2), (3,3), (4,3), (4,4). We demonstrate that the phase (frequency) of each eccentric harmonic takes the form $j\,ϕ_{\ell,m,λ} + ϕ_{\ell,m,\rm ecc}$ ($j\,f_{\ell,m,λ} + f_{\ell,m,\rm ecc}$), where $ϕ_{\ell,m,λ}$ ($f_{\ell,m,λ}$) corresponds to the secular orbital phase (frequency), and $ϕ_{\ell,m,\rm ecc}$ ($f_{\ell,m,\rm ecc}$) is an additional contribution that depends solely on the eccentricity. We further find that $ϕ_{\ell,m,λ}$ is the same across different spherical harmonic modes $(\ell, m)$, whereas the eccentric correction term $ϕ_{\ell,m,\rm ecc}$ scales with $\ell$. Using effective-one-body dynamics, we further show that $ϕ_{\ell,m,λ}$ is nothing but the relativistic anomaly and $ϕ_{\ell,m,\rm ecc}$ is related to the precession advances.

gr-qc↗

arXiv2025

Uncertainties in the supermassive black hole abundance and implications for the GW background

The present-day mass function of supermassive black holes is the most important observable quantity for the prediction and theoretical interpretation of the gravitational wave background (GWB) measured by pulsar timing arrays (PTAs). Due to the limited sample size of galaxies with dynamically inferred SMBH masses, more readily measurable galaxy properties $X$ that correlate with the black hole mass are used as labels (via scaling relations $M_{\bullet}-X$), which can then be counted in a larger galaxy catalog to produce a measurement of the mass function. Estimating the amplitude of the GWB from the local mass function is therefore simpler than general measurements of scaling relations and galaxy mass/luminosity functions for two reasons: the contribution to the characteristic strain is dominated by a narrow range of masses, and the mass proxy $X$ is always marginalized over. While consistent errors in $X$ in both catalogs are irrelevant, relatively small biases between them can produce significant shifts in the predicted SMBH abundance. In this work, we explore measurements of the SMBH mass function using different mass proxies through a set of catalogs with a number of redundant measurements between them. This enables us to investigate internal inconsistencies that lead to discrepancies in the final black hole abundance, while minimizing observational systematic biases induced by combining disparate sets of measurements. We focus on 3 proxies: the velocity dispersion $σ$, K-band luminosity $L$, and a combination of $L$ and radius $R$ defined by the fundamental plane. We show that all three can be reconciled to some degree, but highlight the remaining dependence on poorly-quantified systematic corrections between the scaling relation catalogs and the mass function catalogs, as well as the potential impact of selection effects.

astro-ph.GA↗

arXiv2025

Sampler-free gravitational wave inference using matrix multiplication

Parameter estimation (PE) for compact binary coalescence (CBC) events observed by gravitational wave (GW) laser interferometers is a core task in GW astrophysics. We present a method to compute the posterior distribution efficiently without relying on stochastic samplers. First, we show how to select sets of intrinsic and extrinsic parameters that efficiently cover the relevant phase space. We then show how to compute the likelihood for all combinations of these parameters using dot products. We describe how to assess and tune the integration accuracy, making the outcome predictable and adaptable to different applications. The low computational cost allows full PE in minutes on a single CPU, with the potential for further acceleration using multiple CPUs or GPUs. We implement this method in the $\texttt{dot-PE}$ package, enabling sensitive searches using the full evidence integral for precessing CBCs and supporting large waveform banks ($\sim10^5$--$10^6$ waveforms), regardless of waveform generation cost.

gr-qc↗

arXiv2025

New black hole mergers in the LIGO-Virgo O3 data from a gravitational wave search including higher-order harmonics

Nearly all of the previous gravitational wave (GW) searches in the LIGO-Virgo data included GW waveforms with only the dominant quadrupole harmonic, i.e., omitting higher-order harmonics which are predicted by general relativity. We improved the IAS pipeline by efficiently introducing higher harmonics in the GW templates using the techniques in Wadekar et al. [1, 2]. Using the IAS-HM pipeline on the public LIGO-Virgo data from the O3 run, we find 11 new candidate BBH mergers with $0.52\leq p_\mathrm{astro}\leq 0.88$ (we use the detection threshold as the astrophysical probability, $p_\mathrm{astro}$, being over 0.5, following the approach of other pipelines). We broadly recover the high-significance events from earlier catalogs, except a few which were vetoed. We also find that including higher harmonics in our search raises the significance of a few previously reported marginal events (e.g., GW190711_030756). A few notable properties of our new candidate events are as follows. At $>95$% credibility, 4 candidates have primary masses in the intermediate-mass black hole (IMBH) range (i.e., above $\sim$100 $M_\odot$). 5 candidates have median mass ratio $q \leq 0.5$. 5 candidates have median redshift $z \geq 0.8$. 3 candidates have non-zero $χ_{\rm eff}$ at $>95\%$ credibility. While our new candidate events have modest false alarm rates ($\gtrsim 1.5 $/yr), a population inference study including these can better inform the parameter space of BHs corresponding to the pair instability mass gap, high redshifts and asymmetric mass ratios.

gr-qc↗

arXiv2025

Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation

We introduce a machine learning (ML) framework called $\texttt{TIER}$ for improving the sensitivity of gravitational wave search pipelines. Typically, search pipelines only use a small region of strain data in the vicinity of a candidate signal to construct the detection statistic. However, extended strain data ($\sim 10$ s) in the candidate's vicinity can also carry valuable complementary information. We show that this information can be efficiently captured by ML classifier models trained on sparse summary representation/features of the extended data. Our framework is easy to train and can be used with already existing candidates from any search pipeline, and without requiring expensive injection campaigns. Furthermore, the output of our model can be easily integrated into the detection statistic of a search pipeline. Using $\texttt{TIER}$ on triggers from the $\texttt{IAS-HM}$ pipeline, we find up to $\sim 20\%$ improvement in sensitive volume time in LIGO-Virgo-Kagra O3 data, with improvements concentrated in regions of high masses and unequal mass ratios. Applying our framework increases the significance of several near-threshold gravitational-wave candidates, especially in the pair-instability mass gap and intermediate-mass black hole (IMBH) ranges.

gr-qc↗

arXiv2025

Searching for intermediate mass ratio binary black hole mergers in the third observing run of LIGO-Virgo-KAGRA

Intermediate mass ratio inspirals (IMRIs) of binary black holes with mass ratios $10^{-4}\lesssim q \lesssim 0.1$ are astrophysically interesting sources of gravitational waves. Mergers of intermediate-mass black holes (IMBHs) with stellar-mass black holes would be IMRIs, so their detection can help us probe the formation mechanisms of IMBHs. They can also help us perform precise tests of general relativity due to the presence of strong higher-order mode emission. We perform a search for aligned-spin IMRIs within the data of the two LIGO detectors in the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) collaboration, including higher modes in the template banks for the first time. We use the IAS-HM pipeline for our search and construct template banks in the range $1/100 < q<1/18$ using the SEOBNRv5HM waveform model. Our banks retain a similar level of effectualness for IMRPhenomXHM and BHPTNRSur2dq1e3 waveforms, making our search results relatively robust against waveform systematics. We show that the sensitivity volume of the search increases by up to $\sim 500\%$ upon inclusion of higher modes. We do not find any significant candidates with inverse false alarm rate (IFAR) $> 1$ year in the O3 data. This gives us upper limits on the IMRI merger rate in the local Universe, ranging from $\sim 30$ to $10^3$ Gpc$^{-3}$ yr$^{-1}$ depending on the masses of the black holes in the binary. These constraints are consistent with rate predictions in the literature. Our projections indicate that we would be able to detect IMRIs or constrain some of their proposed formation channels in the fourth (O4) and fifth (O5) observing runs.

gr-qc↗