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Ajit Kumar Mehta

Publications and source records attributed to Ajit Kumar Mehta.

At least 19 recordsLinked to original sources

Probing Neutron Star Equation of State Universality with Gravitational Waves

Current neutron star equation-of-state inferences assume that a common equation of state describes all neutron stars. However, {poorly understood dense-matter physics may give rise to distinct long-lived stellar subpopulations following different mass--tidal-deformability relations, invalidating this assumption. In this Letter, we demonstrate that next-generation gravitational-wave observatories enable neutron star equation-of-state universality to be transformed from an assumption into a testable hypothesis. By combining hierarchical Bayesian inference with a piecewise-polytropic parametrization of the neutron star equation of state, we establish a framework for testing equation-of-state universality with next-generation gravitational-wave observatories. We find that about 30 (50) loud binary neutron star mergers with network SNRs above 100 are sufficient to provide compelling evidence for departures from equation-of-state universality, even if only 20% (10%) of the population exhibits one of the representative non-universality parametrizations considered here.

gr-qc

Testing the spin-induced multipole moments of compact binary coalescences using the flexible theory-independent framework

According to the no-hair theorem, the multipole moments of an electrically neutral black hole in general relativity are entirely determined by its mass and spin. However, this is not in general true for compact objects: The multipole moments of neutron stars or exotic compact objects can depend on their formation history and internal processes, which are encoded in an equation of state. Furthermore, their spin-induced multipole moments differ from those of black holes of the same mass and spin, leaving an imprint on the dynamics and emitted gravitational waves of the binary. Gravitational waves can thus be used to test the nature of compact binary coalescences. Here, we present a test of the spin-induced quadrupole and octupole moments of compact objects based on the flexible theory-independent (FTI) framework. FTI is a parameterized inspiral test of general relativity which enables the addition of post-Newtonian coefficient deviations to the gravitational-wave phase of a generic aligned-spin frequency-domain waveform model. We use this test on synthetic signals to study the measurability of spin-induced quadrupole and octupole moments. Next, we apply the test to a subset of signals observed by the LIGO-Virgo-KAGRA Collaboration. Lastly, we present forecasts for next-generation ground-based detectors, such as Einstein Telescope and Cosmic Explorer. Our estimates suggest that these detectors will be capable of placing stringent constraints on the spin-induced quadrupole and octupole moments of $\mathcal{O}(10^{-2})$ and $\mathcal{O}(10^{-1})$ respectively, which is two orders of magnitude tighter than current constraints, and thus on the nature of black holes in a compact binary coalescence.

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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

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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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

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.

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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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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.

gr-qc

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

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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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

gwharmone: first data-driven surrogate for eccentric harmonics in binary black hole merger waveforms

We present gwharmone, the first data-driven surrogate model for eccentric harmonics (as well as the full radiation content) of the dominant quadrupolar mode in eccentric, non-spinning binary black hole mergers. Our model is trained on 173 waveforms, each $100,000M$ long (where $M$ is the total mass), generated for mass ratios $q \in [1,3.5]$ and eccentricities $e_{\rm ref} \in [0,0.2]$ (at the start of the waveform). The eccentric harmonics are extracted from the effective-one-body waveforms using the \texttt{gwMiner} package. We apply a singular value decomposition (SVD) to obtain a set of reduced basis vectors, necessary to construct a lower-dimensional representation of data, and use Gaussian Process Regression (GPR) to interpolate SVD coefficients across parameter space, allowing for prediction at new parameter points. The model includes the effect of mean anomaly, its evaluation cost is only $\sim 0.1$ second and it achieves an average time-domain (validation) error of ~0.001 and frequency-domain (validation) mismatches below 0.01 for advanced LIGO sensitivity. Our model can therefore be useful in efficient searches and parameter estimation of eccentric mergers. gwharmone will be publicly available through the gwModels package.

astro-ph.HE

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 $j\phi_{\lambda}+\phi_{\rm ecc}$ ($jf_{\lambda}+f_{\rm ecc}$) where $\phi_{\lambda}$ ($f_{\lambda}$) is related to the secular orbital phase (frequency) and $\phi_{\rm ecc}$ ($f_{\rm ecc}$) 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

Significant increase in sensitive volume of a gravitational wave search upon including higher harmonics

Most gravitational wave searches to date have included only the quadrupole mode in their search templates. Here, we demonstrate that incorporating higher harmonics improves the search sensitive volume for detecting binary black hole mergers, challenging the conclusion of previous studies. Using the $\tt{IAS-HM}$ detection pipeline, and the simulated (injection) signals from the LIGO-Virgo-Kagra (LVK) collaboration, we quantify the improvement in sensitivity due to the inclusion of higher harmonics. This improvement is significant for systems with higher mass ratios and larger total masses, with gains in sensitivity even exceeding $100\%$ at certain high masses. We also show that, due to using a marginalized detection statistic, the $\tt{IAS-HM}$ pipeline performs roughly as well as its quadrupole-mode-only counterpart even for equal mass-ratio mergers, and its sensitive volume is either better than or comparable to that of the individual LVK pipelines.

gr-qc

New search pipeline for gravitational waves with higher-order modes using mode-by-mode filtering

Nearly all template-based gravitational wave (GW) searches only include the quasi-circular quadrupolar modes of the signals in their templates. Including additional degrees of freedom in the GW templates corresponding to higher-order harmonics, orbital precession, or eccentricity is challenging because: ($i$) the size of template banks and the matched-filtering cost increases significantly with the number of degrees of freedom, $(ii)$ if these additional degrees are not included properly, the search can lose sensitivity overall (due to an increase in the rate of background triggers). Here, we focus on including aligned-spin higher harmonics in GW search templates. We use a new mode-by-mode filtering approach, where we separately filter GW strain data with three harmonics [namely $(\ell, |m|)=(2,2)$, $(3,3)$ and $(4,4)$]. This results in an increase in the matched-filtering cost by only a factor of $3$ compared to that of a $(2,2)$-only search. We develop computationally cheap trigger-ranking statistics to optimally combine the different signal-to-noise ratios (SNR) timeseries from different harmonics, which ensure only physically-allowed combinations of the different harmonics are triggered on. We use an empirical template-dependent background model in our ranking statistic to account for non-Gaussian transients. In addition, we develop a tool called band eraser which specifically excises narrow time-varying noisy bands in time-frequency space (without having to excise entire time chunks in the data). New GW candidate events that we detect using our $\texttt{IAS-HM}$ search pipeline and the details of our template banks are discussed in accompanying papers: Wadekar et al. [1] and [2] respectively. Apart from higher harmonics, we expect our methodology to also be useful for cheap and optimal searches including orbital precession and eccentricity in GW waveforms.

gr-qc

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 $\chi_{\rm eff}$ 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

New binary black hole mergers in the LIGO-Virgo O3b data

We report the detection of 6 new candidate binary black hole (BBH) merger signals in the publicly released data from the second half of the third observing run (O3b) of advanced LIGO and advanced Virgo. The LIGO-Virgo-KAGRA (LVK) collaboration reported 35 compact binary coalescences (CBCs) in their analysis of the O3b data [1], with 30 BBH mergers having coincidence in the Hanford and Livingston detectors. We confirm 17 of these for a total of 23 detections in our analysis of the Hanford-Livingston coincident O3b data. We identify candidates using a search pipeline employing aligned-spin quadrupole-only waveforms. Our pipeline is similar to the one used in our O3a coincident analysis [2], except for a few improvements in the veto procedure and the ranking statistic, and we continue to use an astrophysical probability of one half as our detection threshold, following the approach of the LVK catalogs. Most of the new candidates reported in this work are placed in the upper and lower-mass gap of the black hole (BH) mass distribution. We also identify a possible neutron star-black hole (NSBH) merger. We expect these events to help inform the black hole mass and spin distributions inferred in a full population analysis.

gr-qc

New approach to template banks of gravitational waves with higher harmonics: Reducing matched-filtering cost by over an order of magnitude

Searches for gravitational wave events use models, or templates, for the signals of interest. The templates used in current searches in the LIGO-Virgo-Kagra (LVK) data model the dominant quadrupole mode $(\ell,|m|)=(2,2)$ of the signals, and omit sub-dominant higher-order modes (HM) such as $(\ell,|m|)=(3,3)$, $(4,4)$, which are predicted by general relativity. This omission reduces search sensitivity to black hole mergers in interesting parts of parameter space, such as systems with high masses and asymmetric mass-ratios. We develop a new strategy to include HM in template banks: instead of making templates containing a combination of different modes, we separately store normalized templates corresponding to $(2,2)$, $(3,3)$ and $(4,4)$ modes. To model aligned-spin $(3,3)$, $(4,4)$ waveforms corresponding to a given $(2,2)$ waveform, we use a combination of post-Newtonian formulae and machine learning tools. In the matched filtering stage, one can filter each mode separately with the data and collect the timeseries of signal-to-noise ratios (SNR). This leads to a HM template bank whose matched-filtering cost is just $\approx 3\times$ that of a quadrupole-only search (as opposed to $\approx\! 100 \times$ in previously proposed HM search methods). Our method is effectual and generally applicable for template banks constructed with either stochastic or geometric placement techniques. New GW candidate events that we detect using our HM banks and details for combining the different SNR mode timeseries are presented in accompanying papers: Wadekar et al. [1] and [2] respectively. Additionally, we discuss non-linear compression of $(2,2)$-only geometric-placement template banks using machine learning algorithms.

gr-qc