arXiv subjects

Tousif Islam

Publications and source records attributed to Tousif Islam.

At least 19 recordsLinked to original sources

arXiv2026

Unified remnant models for aligned-spin, precessing, and eccentric binary black hole mergers

Using approximately $5000$ numerical-relativity (NR) simulations spanning mass ratios up to $q=128$ and $1200$ black-hole-perturbation-theory (BHPT) simulations extending to $q=1000$, we present fully analytic models for the remnant properties of quasi-circular binary black hole mergers. The models gwModelRemS (for final mass, final spin, peak luminosity, and recoil kick) and gwModelRemP (for final mass, final spin, and peak luminosity) describe nonprecessing and precessing binaries, respectively. Our approach combines analytic insights from post-Newtonian theory and point-particle limits with a data-driven fitting framework which also includes validation-guided AI-agent-assisted optimization. The resulting fits outperform existing analytic models and achieve accuracies comparable to data-driven models within their domains of validity. We also construct gwModelRemP\_flow, a normalizing-flow model for recoil kicks from precessing binaries, marginalized over the in-plane spin orientations. This model additionally utilizes an enlarged low-fidelity training set, beyond the available NR and BHPT simulations, constructed through a waveform-based data-augmentation procedure. We also include simple eccentric extensions through leading-order dependence on eccentricity and orbital anomaly. The models span the equal-mass to extreme-mass-ratio regimes and are publicly available through the gwModels package for applications in gravitational-wave astronomy, astrophysical population studies, and cosmology.

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arXiv2026

gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy

Modern gravitational wave astronomy relies on modeling tasks that often require months of graduate-level effort, including building fast waveform surrogates from expensive numerical relativity simulations, modeling orbital dynamics of black holes, fitting merger remnant properties and constructing template banks. These problems demand extreme precision to support detection and parameter inference, with state-of-the-art models achieving $\lesssim 10^{-4}$ relative error. We study whether state-of-the-art LLM coding agents can perform such end-to-end scientific modeling, where success requires constructing models with stringent accuracy criteria and reasoning about physical systems. We introduce gwBenchmarks, a suite of eight tasks grounded in gravitational wave analytic calculations and numerical simulations collectively representing over $10^8$ core-hours of compute. The tasks span interpolation, regression, and high-dimensional time-series modeling, requiring a combination of numerical methods, machine learning, and physics-informed approaches. In preliminary experiments, agents frequently relied on proxy metrics, partial evaluation, or fabricated results to spuriously complete tasks. We therefore implement an external pre-defined framework to gauge agent progress. Evaluating twelve coding agents, we find no consistent winner. On the easiest task, multiple agents converge to the same cubic spline solution, with one rediscovering a coordinate transformation widely used in the literature. On harder tasks like analytic waveform modeling, all agents fall 1-2 orders of magnitude short of domain requirements and exhibit systematic failures, including metric misuse, constraint violations, and result fabrication. Our code, data, and website are publicly available.

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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.

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arXiv2026

Merger remnant and eccentricity dynamics surrogates for eccentric nonspinning black hole binaries

Accurate models of merger remnants are increasingly important for gravitational-wave science, including precision tests of gravity with ringdown, inference of black-hole populations, and modeling hierarchical mergers. For eccentric binaries, remnant mass, spin, and recoil carry nontrivial imprints of eccentricity that are both physically informative and more challenging to model, yet remain less developed than in the quasi-circular case. We present two new models trained on numerical-relativity (NR) simulations of unequal-mass, non-spinning eccentric binary black holes: NRSurE_q4NoSpin_Remnant, which predicts remnant properties, and NRSurE_q4NoSpin_Dynamics, a time-domain surrogate for the evolution of eccentricity and mean anomaly. Both models are trained on NR simulations over a three-dimensional parameter space with mass ratios $q \leq 4$, eccentricity $e < 0.23$, and mean anomaly $\ell \in [0,2\pi)$ radians, where both $e$ and $\ell$ defined at $t=-1000M$ relative to peak amplitude and $M$ is the total mass. We highlight some applications, including the phenomenological impact of eccentricity on remnant properties and the enhancement or suppression of recoil. We also provide error estimates for all modeled quantities, supporting reliable use in current and future gravitational-wave parameter-estimation analyses. Both models will be made available through open-source codes.

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arXiv2026

Including higher-order modes in a quadrupolar eccentric numerical relativity surrogate using universal eccentric modulation functions

\texttt{gwNRHME} is a framework that converts multi-modal (i.e., containing several spherical harmonic modes) quasi-circular waveforms into their eccentric counterparts, provided the quadrupolar eccentric mode is known, by exploiting universal eccentric modulation functions. Leveraging this framework, we combine the quasi-circular NR surrogate model \texttt{NRHybSur3dq8} with the quadrupolar, non-spinning, eccentric surrogate \texttt{NRSurE\_q4NoSpin\_22} to construct a multi-modal, non-spinning, eccentric model, denoted as \model{}, which includes nine modes: $(2,\{1,2\})$, $(3,\{1,2,3\})$, $(4,\{2,3,4\})$, and $(5,5)$. When compared against 156 eccentric SXS NR waveforms, \model{} achieves median frequency-domain mismatches (computed using the Advanced LIGO design sensitivity) of $\sim 9\times 10^{-5}$, with a standard deviation of $\sim 2 \times 10^{-4}$. To demonstrate the modularity of the framework, we further combine \texttt{NRSurE\_q4NoSpin\_22} with effective-one-body (EOB) models \texttt{SEOBNRv5HM} and \texttt{TEOBResumS-Dali} in their non-spinning limits, yielding eccentric waveforms with median mismatches of $\sim 2\times10^{-4}$ and $\sim 10^{-3}$, respectively, with standard deviation of $\sim 2 \times 10^{-3}$ and $\sim 2 \times 10^{-2}$ respectively. Finally, we provide both a surrogate model, \texttt{gwEccEvolve\_q4NoSpin\_Sur}, and an analytical model, \texttt{gwEccEvNSv2}, for the eccentricity evolution up to $2M$ before merger, based on eccentricity definitions derived from the universal modulation functions. The \texttt{gwNRHME} framework is publicly available through the \texttt{gwModels} package, and the resulting waveform models will be released via the \texttt{gwsurrogate} package.

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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 $\chi_{\rm eff}=-0.60^{+0.22}_{-0.13}$ and exhibits strong spin precession, characterized by an effective precession parameter of $\chi_{\rm p}=0.60^{+0.21}_{-0.19}$. 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

Recoil kicks from binary black hole mergers in GWTC catalogs: implications for retention and hierarchical mergers

We infer recoil (kick) velocities for both individual binary black hole (BBH) mergers and candidate intermediate-mass black hole events, as well as for the BBH populations inferred from GWTC catalogs up to GWTC-5. We obtain informative recoil constraints for several events, including GW231028-153006 ($v_{\rm kick}=839^{+1018}_{-681}\,\mathrm{km\,s^{-1}}$) and GW231123-135430 ($v_{\rm kick}=974^{+944}_{-760}\,\mathrm{km\,s^{-1}}$), while finding that the majority of event-level recoil posteriors remain broad and only weakly informative. We further infer consistent population-level recoil distributions across GWTC-3, GWTC-4, and GWTC-5, with median kick velocities of approximately $300$--$330\,\mathrm{km\,s^{-1}}$. Using both event-level and population-level recoil estimates, we find typical retention probabilities of $\sim2$--$3\%$ for globular clusters, $\sim28$--$32\%$ for nuclear star clusters, $\sim25$--$29\%$ for dwarf galaxies, and $\sim92$--$94\%$ for elliptical galaxies. We also compute recoil-induced displacements and dynamical-friction return times, finding that retained remnants in globular clusters and nuclear star clusters can remain displaced from their host cores for extended periods. Our results show that retention alone is not sufficient to determine the prospects for hierarchical mergers: hierarchical-merger efficiency depends on both remnant retention and post-kick re-centering.

astro-ph.HE↗

arXiv2026

Kick matters: The impact of a new recoil model on the retention of hierarchical black-hole remnants in globular clusters

In globular clusters, hierarchical mergers are among the most promising pathways to forming massive black holes such as GW231123. A key factor determining whether a merger-remnant black hole will be retained in these environments and thus participate in subsequent hierarchical mergers is the recoil kick velocity. Analytic models for the recoil velocity are currently employed in nearly all population-synthesis frameworks. We instead use a state-of-the-art recoil-kick model gwModel_flow_prec developed from a combination of numerical-relativity and black-hole perturbation-theory data, together with data-driven techniques such as normalizing flows and the post-Newtonian structure of the kick. Employing both back-of-the-envelope estimates and detailed N-body as well as semi-analytical cluster simulations, we show that gwModel_flow_prec leads to a noticeable increase in the retention probability of hierarchical-merger remnants compared to the previously used analytic model and changes the mass and spin distribution of the black holes formed through hierarchical mergers. Additionally, we discuss the implications of our results in the context of massive binaries such as GW231123.

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↗

arXiv2026

Progenitor of the recoiling super-massive black hole RBH-1 identified using HST/JWST imaging

Using a combination of \textit{Hubble Space Telescope} and \textit{James Webb Space Telescope} imaging, a runaway supermassive black hole (RBH-1) was recently identified with an inferred velocity of $954^{+110}_{-126}\,\mathrm{km\,s^{-1}}$, likely ejected from a compact star-forming galaxy (denoted as GX) at $z \approx 0.96$. Assuming the runaway black hole was the outcome of the gravitational-wave-driven merger of two black holes, we use its measured runaway velocity together with gravitational-wave recoil predictions from numerical relativity and black hole perturbation theory to constrain the mass ratio and spin configuration of the progenitor SMBHs that overcame the final-parsec problem and merged $\sim 70$~Myr ago. We find that the progenitor binary must have been precessing, with a mass ratio $m_1/m_2\lesssim 6$, and that the more massive SMBH must have possessed a high spin (dimensionless spin magnitude $\sim 0.75$) in order to generate a recoil of this magnitude. This has important astrophysical implications as similar SMBH mergers can be an interesting source population for the upcoming LISA mission with signal-to-noise ratios $\gtrsim$ 1000. Furthermore, the progenitor SMBH properties imply that GX was likely formed through a major, gas-rich (``wet'') merger between two galaxies of comparable mass, with a mass ratio $\lesssim 4$.

astro-ph.HE↗

arXiv2025

Analysis of late-time tails in spin-aligned eccentric binary black hole mergers

We present a comprehensive analysis of late-time tails in gravitational radiation from merging spin-aligned eccentric binary black holes, using high-accuracy point-particle black hole perturbation theory simulations. We simulate the late-time evolution of 15 binary black hole mergers with mass ratio $q = 1000$, dimensionless spins $\chi = [-0.9, -0.6, 0.0, 0.6, 0.9]$ and eccentricity at the last stable orbit $e_{\rm LSO} = [0.8, 0.9, 0.95]$. We track the tail amplitudes and exponents up to a retarded time coordinate $t = 9000M$ after merger for the six spin-weighted spherical harmonic modes $(2,1)$, $(2,2)$, $(3,2)$, $(3,3)$, $(4,3)$, and $(4,4)$ employing both frequentist and Bayesian approaches. We note that the tails are increasingly pronounced for binaries with high eccentricity $e_{\rm LSO}$ and large negative spin $\chi$. We find that the overall late-time exponents closely approach their predicted asymptotic values ($p=-\ell-4$ for Weyl curvature scalar $\psi_{4,\ell m}$ where $\ell$ is the spin-weighted spherical harmonic index), while estimates restricted to the latest portion of the data exactly recover them. We further verify numerically that modes with the same spherical index $\ell$ share identical tail exponents, while variations in $m$ do not affect the tail behavior. Our analysis framework is publicly available through the gwtails Python package.

gr-qc↗

arXiv2025

Accurate models for recoil velocity distribution in black hole mergers with comparable to extreme mass-ratios and their astrophysical implications

Modeling the remnant recoil velocity (kick) distribution from binary black hole mergers is crucial for understanding hierarchical mergers in active galactic nuclei or globular clusters. Existing analytic models often show large discrepancies with numerical relativity (NR) data, while data-driven models are limited to mass ratios of q<=8 (aligned spins) and q<=4 (precessing spins) and break down when extrapolated outside their training ranges. Using ~5000 of NR simulations from the SXS and RIT catalogs up to q=128 and ~100 black hole perturbation theory simulations up to q=200, we present two classes of models: (i) gwModel_kick_q200 (gwModel_kick_q200_GPR), an analytic (Gaussian process regression) model for aligned-spin binaries. (ii) gwModel_kick_prec_flow, a normalizing-flow model for kick distribution from precessing binaries with isotropic spins. Our approach combines analytic insights from post-Newtonian theory with data-driven techniques to ensure correct limiting behavior and high accuracy across parameter space. Both gwModel_kick_q200 and gwModel_kick_prec_flow are valid from comparable to extreme mass ratios. Extensive validation shows all three models outperform existing ones within their respective domains. Finally, using both back-of-the-envelope estimates and 1404 detailed star cluster simulations incorporating our kick models, we find that the black hole retention probability in low mass globular clusters can vary noticeably when the gwModel_kick_prec_flow model is employed. The models are publicly available through the gwModels package.

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arXiv2025

Consistency of spin effects between numerical relativity and perturbation theory for inspiraling comparable-mass black hole binaries

Numerical relativity (NR) provides the most accurate waveforms for comparable-mass binary black holes but becomes prohibitively expensive for increasingly asymmetric mass ratios. Point-particle black hole perturbation theory (ppBHPT), which expands the Einstein equations in the small-mass-ratio limit, offers a computationally efficient alternative but is expected to break down in the comparable-mass regime because it neglects nonlinear effects. Nonetheless, several recent studies have shown that ppBHPT can model non-spinning binaries with high accuracy when supplemented by simple calibrations or a first post-adiabatic (PA) correction. Here we assess the applicability of ppBHPT to quasi-circular binaries with a spinning primary by comparing waveform amplitudes, orbital frequencies, and orbital phases. We find that spin effects in ppBHPT waveforms (without additional spin information beyond adiabatic order) are in surprisingly close agreement with the corresponding NR calculation (outperforming some post-Newtonian models) over the last $\approx 20$ orbital cycles. This suggests that, after incorporating higher-order corrections into ppBHPT waveforms in the non-spinning limit -- via second-order self-force results or semi-analytical fits -- only modest spin-dependent adjustments may be required to achieve NR-faithful ppBHPT waveforms. We also show that combining non-spinning NR information with adiabatic ppBHPT can provide a reasonably accurate inspiral waveform for spins $\chi \lesssim 0.5$ mass ratios $q \gtrsim 5$.

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arXiv2025

Eccentric binary black holes: A new framework for numerical relativity waveform surrogates

Mounting evidence indicates that some of the gravitational wave signals observed by the LIGO/Virgo/KAGRA observatories might arise from eccentric compact object binaries, increasing the urgency for accurate waveform models for such systems. While for non-eccentric binaries, surrogate models are efficient and accurate, the additional features due to eccentricity have posed a challenge. In this letter, we present a novel method for decomposing eccentric numerical relativity waveforms which makes them amenable to surrogate modelling techniques. We parameterize the inspiral in the radial phase domain, factoring out eccentricity-induced dephasing and thus enhancing compressibility and accuracy. This is combined with a second surrogate for the merger-ringdown in the time-domain and a novel technique to take advantage of the approximate periodicity with radial oscillations during the inspiral. We apply this procedure to the $(2,2)$ mode for non-spinning black hole binaries, and demonstrate that the resulting surrogate, NRSurE_q4NoSpin_22, is able to faithfully reproduce the underlying numerical relativity waveforms, with maximum mismatches of $5\times10^{-4}$ and median mismatches of $2\times10^{-5}$. This technique paves the way for high-accuracy parameter estimation with eccentric models, a key ingredient for astrophysical inference and tests of general relativity.

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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 $j\,\phi_{\ell,m,\lambda} + \phi_{\ell,m,\rm ecc}$ ($j\,f_{\ell,m,\lambda} + f_{\ell,m,\rm ecc}$), where $\phi_{\ell,m,\lambda}$ ($f_{\ell,m,\lambda}$) corresponds to the secular orbital phase (frequency), and $\phi_{\ell,m,\rm ecc}$ ($f_{\ell,m,\rm ecc}$) is an additional contribution that depends solely on the eccentricity. We further find that $\phi_{\ell,m,\lambda}$ is the same across different spherical harmonic modes $(\ell, m)$, whereas the eccentric correction term $\phi_{\ell,m,\rm ecc}$ scales with $\ell$. Using effective-one-body dynamics, we further show that $\phi_{\ell,m,\lambda}$ is nothing but the relativistic anomaly and $\phi_{\ell,m,\rm ecc}$ is related to the precession advances.

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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 $\kappa = 4.4^{+1.9}_{-2.0}$. Assuming a power-law form for the mass ratio distribution ($\propto q^{\beta}$), we infer $\beta = 0.1^{+1.9}_{-1.4}$, 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.

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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.

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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.

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