arXiv subjects

Ian Harry

Publications and source records attributed to Ian Harry.

At least 19 recordsLinked to original sources

arXiv2026

PyCBC Live Search for Compact Binary Mergers in Advanced LIGO and Virgo's Fourth Observing Run

PyCBC Live is a low-latency search pipeline that identifies gravitational waves from compact binary coalescences and provides alerts for electromagnetic follow-up. This paper presents improvements to PyCBC Live that were implemented for the fourth observing run (O4) of the LIGO-Virgo-KAGRA network, which operated from May 2023 to November 2025. The ranking statistic was enhanced to incorporate time-dependent background modeling using data quality streams and daily updates of the noise model. Follow-up capabilities were improved through refined probability of astrophysical origin calculations, optimized SNR recovery with reduced computational cost, and a method to incorporate Virgo as a sky-map-only detector. An Early Warning search was implemented to detect binary neutron star and neutron star-black hole systems before merger, providing pre-merger alerts with a pipeline latency of 2.5-3.5 seconds and warning times up to 60 seconds before coalescence. The autogating procedure was extended to apply to the full strain buffer rather than individual analysis segments, improving rejection of loud and rapidly successive glitches. Performance validation using the Mock Data Challenge showed sensitivity improvements of factors of 1.7 to 2.3 for the coincident search depending on source mass at an inverse false alarm rate of 10 years, and factors of 1.3 to 1.7 for the single-detector search. For injections in two-detector time, the O4 configuration identified 1979 of 2495 injections with a decisive SNR greater than 6 at a false alarm rate below one per year (79.3%), compared to 1262 (50.6%) with the O3 configuration. For injections in single-detector time, the O4 configuration identified 218 of 1174 injections (18.6%), compared to 170 (14.5%) with the O3 configuration. The search maintained a median latency of 15.94 seconds from merger to candidate upload.

astro-ph.IM↗

arXiv2026

Inpainting over the cracks: challenges of applying pre-merger searches for massive black hole binaries to realistic LISA datasets

A key science target of the Large Interferometer Space Antenna (LISA) is to carry out multi-messenger observations of massive black hole binaries, observing the merger simultaneously in gravitational waves and with electromagnetic observatories. Identifying that a merger is happening and providing an updating estimate of the sky location in the hours, days and weeks before the merger is critical to enable electromagnetic observations of the merger event. In this work we demonstrate and compare two methods for premerger identification of massive black hole binaries; a zero-latency filter approach and, for the first time, an approach using an ``inpainting'' technique. We apply these methods to the LISA Data Challenge dataset 2a--Sangria-HM--and demonstrate the successful recovery of the 14 signals in the dataset that we expected to be identifiable at least half a day before merger. We show that the inpainting method can identify premerger signals even when gaps are present in the data, demonstrating the recovery of a signal even when 3 day-long data gaps are added to the 14 days preceding merger. Finally, we explore the challenge of overlapping signals, using a region of overlapping signals in the Sangria-HM dataset, all of which merge within a 10-day window, and show how removing signals that have been confidently identified from the data allows us to identify quieter signals in the same period.

astro-ph.IM↗

arXiv2026

Normalizing flows for density estimation in multi-detector gravitational-wave searches

Identifying compact binary coalescences buried within the non-Gaussian and non-stationary data taken by gravitational-wave interferometers requires sophisticated search pipelines, such as the PyCBC analysis. A critical task for these pipelines is determining the statistical significance of candidate events by comparing a "ranking statistic" against a large background set. Currently, PyCBC's ranking statistic incorporates the joint probability of the relative arrival times, phase delays and amplitude ratios of the signals seen in different detectors. These parameters are tightly constrained for physical signals but are more broadly distributed for noise. PyCBC currently relies on precomputed binned histogram-based density estimators using Monte-Carlo simulations to obtain these probabilities. However, the storage requirements for these histograms scale prohibitively with the size of the detector network, preventing PyCBC from effectively analyzing four or more detectors. In this paper, we demonstrate that these histograms can be replaced with normalizing flows, a machine learning approach to density estimation. Applying this method to data from the third observing run of Advanced LIGO and Virgo, we demonstrate that normalizing flows reduce storage requirements by over three orders of magnitude. Furthermore, our approach maintains high sensitivity, with less than a 0.05% drop in the recovery of simulated signals at a fixed false-alarm rate. By relaxing several simplifying assumptions previously required by Monte-Carlo methods, we also achieved up to a 6.55% increase in recovered signals for specific detector combinations. These results suggest that normalizing flows provide a scalable, flexible framework for the PyCBC pipeline as it expands to include four or more detectors, or to extend to searches for precessing or higher-mode signals, in future observing runs.

astro-ph.HE↗

arXiv2026

Search for Precessing Binary Black Holes in Advanced LIGO's Third Observing Run using Harmonic Decomposition

Binary black holes (BBHs) exhibiting spin-induced orbital precession offer unique insight into compact-binary formation channels, cosmology, and tests of general relativity. We conduct a dedicated search for precessing BBHs with unequal masses in Advanced LIGO's third observing run (O3) using the harmonic decomposition method of precessing waveforms. We introduce a novel scheme to reduce the number of filters in a harmonic search. With our new approach, our template bank requires $5\times$ fewer filters compared to another proposed precessing search in the same region. We do not find any new significant events. Our new search method achieves up to $\sim 28\%$ improvement in sensitivity and up to $5\times$ lower computational costs compared to existing precessing search pipelines. Our method enables scalable, sensitive searches for precessing BBHs in future gravitational-wave observing runs.

astro-ph.IM↗

arXiv2025

The Missing Multipole Problem: Investigating biases from model starting frequency in gravitational-wave analyses

Our ability to infer the true source properties of colliding black holes from gravitational wave observations requires not only accurate waveform models but also their correct use. A key property when evaluating time-domain models is when to start the waveform: choosing a time that is too late can omit low-frequency power from higher order multipoles. By focusing on binary systems with total mass $\ge 200 \, M_{\odot}$, we show that current detectors are sensitive to this missing power and biased source properties can be obtained. We show that for systems with total mass $\lesssim 300 \, M_{\odot}$, mass ratio $\gtrsim 0.33$, and signal-to-noise ratio $\rho \gtrsim 20$, templates starting at $20 \, \mathrm{Hz}$ recover biased source properties. As the total mass increases, and the component masses become more asymmetric, templates starting from $13 \, \mathrm{Hz}$ recover biased properties. If the gravitational-wave signal is observed at signal-to-noise ratio $\rho < 20$, time-domain models can start from $20\, \mathrm{Hz}$ as statistical uncertainties dominate.

gr-qc↗

arXiv2025

Archival Inference for Eccentric Stellar-Mass Binary Black Holes in Space-Based Gravitational Wave Observations

Space-based gravitational-wave observatories will detect the early inspiral of stellar-mass binary black holes and can track their eccentricity evolution. However, untargeted searches in the space band are computationally demanding and require relatively high detection thresholds (signal-to-noise ratio $\sim 15$). Information from ground-based detections can significantly shrink the parameter space for space-band analyses and thereby substantially reduce the detection threshold. We present a Bayesian inference pipeline for ground-triggered archival space-band analyses that includes eccentricity. Using ground-informed priors, we demonstrate that with one year of LISA or TianQin data a GW190521-like source with signal-to-noise ratio $\sim 7$ can be distinguished and tightly constrained. In this setup, space observations sharpened the redshifted chirp mass from $\mathcal{O}(10^{-3})M_\odot$ to $\mathcal{O}(10^{-5})M_\odot$, and constrain the eccentricity to $\mathcal{O}(10^{-5})$ around the injected value $e_{0.01\mathrm{Hz}}=0.1$. These results demonstrate that inference of eccentric stellar-mass binary black holes in noisy space-band data is practically feasible, supports an expanded yield of multiband detections, and strengthens prospects for future astrophysical and gravitational tests.

astro-ph.HE↗

arXiv2025

Multiband parameter estimation with phase coherence and extrinsic marginalization: Extracting more information from low-SNR CBC signals in LISA data

This paper presents a novel coherent multiband analysis framework for characterizing stellar- and intermediate-mass binary black holes using LISA and next-generation ground-based detectors (ET and CE), leveraging the latest developments in the \texttt{PyCBC} pipeline. Given the population parameters inferred from LVK results and LISA's sensitivity limits at high frequencies, most stellar-mass binary black holes would likely have SNRs below 5 in LISA, but the most state-of-the-art multiband parameter estimation methods, such as those using ET and CE posteriors as priors for LISA, typically struggle to analyze sources with a LISA SNR less than 5. We present a novel coherent multiband parameter estimation method that directly calculates a joint likelihood, which is highly efficient; this efficiency is enabled by multiband marginalization of the extrinsic parameter space, implemented using importance sampling, which can work robustly even when the LISA SNR is as low as 3. Having an SNR of $\sim 3$ allows LISA to contribute nearly double the number of multiband sources. Even if LISA only observes for one year, most of the multiband detector-frame chirp mass's 90\% credible interval (less than $10^{-4} \mathrm{M}_\odot$) is still better than that of the most accurately measured events for ET+2CE network in 7.5 years of observation, by at least one order of magnitude. For the first time, we show efficient multiband Bayesian parameter estimation results on the population scale, which paves the way for large-scale astrophysical tests using multibanding.

gr-qc↗

arXiv2025

Constraining the neutron star-black hole merger rate

Current template-based gravitational-wave searches for compact binary mergers neglect the general relativistic phenomenon of spin-induced orbital precession. Owing to their asymmetric masses, gravitational-waves from neutron star-black hole (NSBH) binaries are prime candidates for displaying strong imprints of spin-precession. Current searches may therefore miss a significant fraction of the astrophysical population, and the detected NSBH population may be significantly suppressed or biased. Here we report the most sensitive search for NSBH binaries to date by including spin-precession for the first time. We analyze data from the entirety of the third LIGO--Virgo--KAGRA gravitational-wave observing run and show that when accounting for spin-precession, our search is up to 100% more sensitive than the search techniques currently adopted by the LIGO--Virgo--KAGRA collaboration (for systems with strong precessional effects). This allows us to more tightly constrain the rate of NSBH mergers in the local Universe. When focusing on a potentially precessing subpopulation of NSBH mergers, the lack of observed candidates allows us to place an upper limit on the merger rate of $R_{90} = 79\, \mathrm{Gpc}^{-3}\mathrm{yr}^{-1}$ with 90% confidence. We then show that if there is no preferred direction of component spin, the overall rate of NSBH mergers is on average 16% smaller than previously believed. Finally, we report four new subthreshold NSBH candidates, all with strong imprints of spin precession, but note that these are most likely to be of terrestrial origin.

hep-ex↗

arXiv2024

Premerger observation and characterization of massive black hole binaries

We demonstrate an end-to-end technique for observing and characterizing massive black hole binary signals before they merge with the LISA space-based gravitational-wave observatory. Our method uses a zero-latency whitening filter, originally designed for rapidly observing compact binary mergers in ground-based observatories, to be able to observe signals with no additional latency due to filter length. We show that with minimal computational cost, we are able to reliably observe signals as early as 14 days premerger as long as the signal has accrued a signal-to-noise ratio of at least 8 in the LISA data. We also demonstrate that this method can be used to characterize the source properties, providing early estimates of the source's merger time, chirp mass, and sky localization. Early observation and characterization of massive black holes is crucial to enable the possibility of rapid multimessenger observations, and to ensure that LISA can enter a protected operating period when the merger signal arrives.

hep-ex↗

arXiv2024

A rapid multi-modal parameter estimation technique for LISA

The Laser Interferometer Space Antenna (LISA) will observe gravitational-wave signals from a wide range of sources, including massive black hole binaries. Although numerous techniques have been developed to perform Bayesian inference for LISA, they are often computationally expensive; analyses often take at least $\sim 1$ month on a single CPU, even when using accelerated techniques. Not only does this make it difficult to concurrently analyse more than one gravitational-wave signal, it also makes it challenging to rapidly produce parameter estimates for possible electromagnetic follow-up campaigns. simple-pe was recently developed to produce rapid parameter estimates for gravitational-wave signals observed with ground-based gravitational-wave detectors. In this work, we extend simple-pe to produce rapid parameter estimates for LISA sources, including the effects of higher order multipole moments. We show that simple-pe infers the source properties of massive black hole binaries in zero-noise at least $\sim 100\times$ faster than existing techniques; $\sim 12$ hours on a single CPU. We further demonstrate that simple-pe can be applied before existing Bayesian techniques to mitigate biases in multi-modal parameter estimation analyses of MBHBs.

gr-qc↗

arXiv2024

Efficient Stochastic Template Bank using Inner Product Inequalities

Gravitational wave searches are crucial for studying compact sources like neutron stars and black holes. Many sensitive modeled searches use matched filtering to compare gravitational strain data to a set of waveform models known as template banks. We introduce a new stochastic placement method for constructing template banks, offering efficiency and flexibility to handle arbitrary parameter spaces, including orbital eccentricity, tidal deformability, and other extrinsic parameters. This method can be computationally limited by the ability to compare proposal templates with the accepted templates in the bank. To alleviate this computational load, we introduce the use of inner product inequalities to reduce the number of required comparisons. We also introduce a novel application of Gaussian Kernel Density Estimation to enhance waveform coverage in sparser regions. Our approach has been employed to search for eccentric binary neutron stars, low-mass neutron stars, primordial black holes, supermassive black hole binaries. We demonstrate that our method produces self-consistent banks that recover the required minimum fraction of signals. For common parameter spaces, our method shows comparable computational performance and similar template bank sizes to geometric placement methods and stochastic methods, while easily extending to higher-dimensional problems. The time to run a search exceeds the time to generate the bank by a factor of $\mathcal{O}(10^5)$ for dedicated template banks, such as geometric, mass-only stochastic, and aligned spin cases, $\mathcal{O}(10^4)$ for eccentric and $\mathcal{O}(10^3)$ for the tidal deformable bank. With the advent of efficient template bank generation, the primary area for improvement is developing more efficient search methodologies.

astro-ph.HE↗

arXiv2024

Calibrating gravitational-wave search algorithms with conformal prediction

In astronomy, we frequently face the decision problem: does this data contain a signal? Typically, a statistical approach is used, which requires a threshold. The choice of threshold presents a common challenge in settings where signals and noise must be delineated, but their distributions overlap. Gravitational-wave astronomy, which has gone from the first discovery to catalogues of hundreds of events in less than a decade, presents a fascinating case study. For signals from colliding compact objects, the field has evolved from a frequentist to a Bayesian methodology. However, the issue of choosing a threshold and validating noise contamination in a catalogue persists. Confusion and debate often arise due to the misapplication of statistical concepts, the complicated nature of the detection statistics, and the inclusion of astrophysical background models. We introduce Conformal Prediction (CP), a framework developed in Machine Learning to provide distribution-free uncertainty quantification to point predictors. We show that CP can be viewed as an extension of the traditional statistical frameworks whereby thresholds are calibrated such that the uncertainty intervals are statistically rigorous and the error rate can be validated. Moreover, we discuss how CP offers a framework to optimally build a meta-pipeline combining the outputs from multiple independent searches. We introduce CP with a toy cosmic-ray detector, which captures the salient features of most astrophysical search problems and allows us to demonstrate the features of CP in a simple context. We then apply the approach to a recent gravitational-wave Mock Data Challenge using multiple search algorithms for compact binary coalescence signals in interferometric gravitational-wave data. Finally, we conclude with a discussion on the future potential of the method for gravitational-wave astronomy.

gr-qc↗

arXiv2024

LISA Definition Study Report

The Laser Interferometer Space Antenna (LISA) is the first scientific endeavour to detect and study gravitational waves from space. LISA will survey the sky for Gravitational Waves in the 0.1 mHz to 1 Hz frequency band which will enable the study of a vast number of objects ranging from Galactic binaries and stellar mass black holes in the Milky Way, to distant massive black-hole mergers and the expansion of the Universe. This definition study report, or Red Book, presents a summary of the very large body of work that has been undertaken on the LISA mission over the LISA definition phase.

astro-ph.CO↗

arXiv2023

Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run

Multi-messenger searches for BNS and NSBH mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to GWs has resumed with O4. To support this effort, public semi-automated data products are sent in near real-time and include localization and source properties to guide complementary observations. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a MDC in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-to-end performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. We present an overview of the low-latency infrastructure and the performance of the data products that are now being released during O4 based on the MDC. We report the expected median latency for the preliminary alert of full bandwidth searches (29.5s) and show consistency and accuracy of released data products using the MDC. For the first time, we report the expected median latency for triggers from early warning searches (-3.1s), which are new in O4 and target neutron star mergers during inspiral phase. This paper provides a performance overview for LVK low-latency alert infrastructure and data products using the MDC and serves as a useful reference for the interpretation of O4 detections.

astro-ph.HE↗

arXiv2023

Follow-up Analyses to the O3 LIGO-Virgo-KAGRA Lensing Searches

Along their path from source to observer, gravitational waves may be gravitationally lensed by massive objects. This results in distortions of the observed signal which can be used to extract new information about fundamental physics, astrophysics, and cosmology. Searches for these distortions amongst the observed signals from the current detector network have already been carried out, though there have as yet been no confident detections. However, predictions of the observation rate of lensing suggest detection in the future is a realistic possibility. Therefore, preparations need to be made to thoroughly investigate the candidate lensed signals. In this work, we present some of the follow-up analyses and strategies that could be applied to assess the significance of such events and ascertain what information may be extracted about the lens-source system from such candidate signals by applying them to a number of O3 candidate events, even if these signals did not yield a high significance for any of the lensing hypotheses. For strongly-lensed candidates, we verify their significance using a background of simulated unlensed events and statistics computed from lensing catalogs. We also look for potential electromagnetic counterparts. In addition, we analyse in detail a candidate for a strongly-lensed sub-threshold counterpart that is identified by a new method. For microlensing candidates, we perform model selection using a number of lens models to investigate our ability to determine the mass density profile of the lens and constrain the lens parameters. We also look for millilensing signatures in one of the lensed candidates. Applying these additional analyses does not lead to any additional evidence for lensing in the candidates that have been examined. However, it does provide important insight into potential avenues to deal with high-significance candidates in future observations.

gr-qc↗

arXiv2023

Space-based Gravitational Wave Observatories Will Be Able to Use Eccentricity to Unveil Stellar-mass Binary Black Hole Formation

The measurement of eccentricity would provide strong constraints on the formation channel of stellar-mass binary black holes. However, current ground-based gravitational wave detectors will, in most cases, not be able to measure eccentricity due to orbital circularization. Space-based observatories, in contrast, can determine binary eccentricity at 0.01Hz to $e_{0.01}\gtrsim\mathcal{O}(10^{-4}) $. Directly observing stellar-mass binary black holes with space-based observatories remains a challenging problem. However, observing such systems with ground-based detectors allows the possibility to identify the same signal in archival data from space-based observatories in the years previous. Since ground-based detectors provide little constraints on eccentricity, including eccentricity in the archival search will increase the required number of filter waveforms for the archival search by 5 orders of magnitudes [from $\sim \mathcal{O}(10^3)$ to $\sim \mathcal{O}(10^8)$], and will correspondingly need $ \sim8\times10^5 $ core hours (and $ \sim 10^5$ GB of memory), even for a mild upper limit on eccentricity of $0.1$. In this work, we have constructed the first template bank for an archival search of space-based gravitational wave detectors, including eccentricity. We have demonstrated that even though the inclusion of eccentricity brings extra computational burden, an archival search including eccentricity will be feasible in the time frame of planned space-based observatories, and will provide strong constraints on the eccentricities of stellar-mass binary black holes.

astro-ph.HE↗

arXiv2023

A search technique to observe precessing compact binary mergers in the advanced detector era

Gravitational-wave signals from compact binary coalescences are most efficiently identified through matched filter searches, which match the data against a pre-generated bank of gravitational-wave templates. Although different techniques for performing the matched filter, as well as generating the template bank, exist, currently all modelled gravitational-wave searches use templates that restrict the component spins to be aligned (or anti-aligned) with the orbital angular momentum. This means that current searches are less sensitive to gravitational-wave signals generated from binaries with generic spins (precessing), suggesting that, potentially, a significant fraction of signals may remain undetected. In this work we introduce a matched filter search that is sensitive to signals generated from precessing binaries and can realistically be used during a gravitational-wave observing run. We take advantage of the fact that a gravitational-wave signal from a precessing binary can be decomposed into a power series of five harmonics, to show that a generic-spin template bank, which is only $\sim 3\times$ larger than existing aligned-spin banks, is needed to increase our sensitive volume by $\sim 100\%$ for neutron star black hole binaries with total mass larger than $17.5\, M_{\odot}$ and in-plane spins $>0.67$. In fact, our generic spin search performs as well as existing aligned-spin searches for neutron star black hole signals with insignificant in-plane spins, but improves sensitivity by $\sim60\%$ on average across the full generic spin parameter space. We anticipate that this improved technique will identify significantly more gravitational-wave signals, and, ultimately, help shed light on the unknown spin distribution of binaries in the universe.

gr-qc↗

arXiv2022

Addressing the challenges of detecting time-overlapping compact binary coalescences

Standard detection and analysis techniques for transient gravitational waves make the assumption that detector data contains, at most, one signal at any time. As detectors improve in sensitivity, this assumption will no longer be valid. In this paper we examine how current search techniques for transient gravitational waves will behave under the presence of more than one signal. We perform searches on data sets containing time-overlapping compact binary coalescences. This includes a modelled, matched filter search (PyCBC), and an unmodelled coherent search, coherent WaveBurst (cWB). Both of these searches are used by the LIGO-Virgo-KAGRA collaboration. We find that both searches are capable of identifying both signals correctly when the signals are dissimilar in merger time, $|\Delta t_c| \geq 1$ second, with PyCBC losing only $1\%$ of signals for overlapping binary black hole mergers. Both pipelines can find signal pairings within the region $|\Delta t_c| < 1$ second. However, clustering routines in the pipelines will cause only one of the two signals to be recovered, as such the efficiency is reduced. Within this region, we find that cWB can identify both signals. We also find that matched filter searches can be modified to provide estimates of the correct parameters for each signal.

gr-qc↗