arXiv subjects

Tito Dal Canton

Publications and source records attributed to Tito Dal Canton.

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

Probing millisecond magnetar formation in binary neutron star mergers through X-ray follow-up of gravitational wave alerts

The nature of the remnant of a binary neutron star (BNS) merger is uncertain. Though certainly a black hole (BH) in the cases of the most massive BNSs, X-ray lightcurves from gamma-ray burst (GRB) afterglows suggest a neutron star (NS) as a viable candidate for both the merger remnant as well as the central engine of these transients. When jointly observed with gravitational waves (GWs), X-ray lightcurves from BNS merger events could provide critical constraints on the remnant's nature. We aim to assess the current and future capabilities to detect a NS remnant through X-ray observations following GW detections. To this end, we simulate GW signals from BNS mergers and the subsequent X-ray emission from newborn millisecond magnetars. The GW detectability is modeled for both current and next-generation interferometers, while the X-ray emission is reproduced using a dedicated numerical code that models magnetar spin-down and ejecta dynamics informed by numerical-relativity simulations. In our simulations, 2% - 16% of BNS mergers form millisecond magnetars. Among these, up to 70% could be detectable, amounting to up to 1 millisecond magnetar detection per year with SVOM/MXT-like instruments during the LIGO Virgo KAGRA LIGO India (LVKI) O5 run, with optimal detectability occurring about 2 hours post-merger. For next-generation GW interferometers, this rate could increase by up to three orders of magnitude, with peak detectability 3 to 4 hours post-merger. We also explore how the magnetar's magnetic field strength and observer viewing angle affect detectability and discuss optimized observational strategies. Although more likely with upcoming GW interferometers, detecting the spin-down emission of a millisecond magnetar may already be within reach, warranting sustained theoretical and observational efforts given the profound implications for mergers, GRBs, and NS physics of a single detection.

astro-ph.HE↗

arXiv2026

The geometry of lunar gravitational wave detection

The Lunar Gravitational Wave Antenna (LGWA) is a planned gravitational wave detector on the Moon, targeting the deci-Hertz band and expected to deliver breakthrough discoveries across several science cases, including the Moon's interior structure and astrophysics. In this work, we show that adopting a frame comoving with the Solar System barycenter (SSB), but with its origin at a location that minimizes timing uncertainty, reduces the sampling time by an order of magnitude. We present a systematic post-processing procedure to identify the optimal origin within the Solar System for any given signal. We explore alternative timing parametrizations beyond the merger time, and find that they have only a minor impact on parameter uncertainties. Using the stellar-mass black hole binary GW250114 as a case study, we illustrate how these geometrical considerations translate into improved parameter constraints. Two minutes before its merger, the LGWA would have measured its chirp mass to a precision of 0.0002 solar masses (90% symmetric) and constrained its sky position to within 65 square degrees (90% HPD area); these constraints are tighter than those obtained by the LIGO-Virgo-KAGRA (LVK) detectors, despite a lower signal-to-noise ratio. We connect our results to an analytical approximation proposed by Wen and Chen, which relates the area spanned by the orbital motion of a detector to its efficacy in constraining the sky position of a source. We verify its qualitative validity for compact binary sources with a series of injections, identifying the regimes in which its underlying assumptions break down. Our results demonstrate that inference for long-duration GW signals with the LGWA must be treated as a geometrical problem, in which detector motion, reference-frame choice, and signal evolution jointly determine both parameter constraints and computational efficiency.

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arXiv2026

Deep Learning Search for Gravitational Waves from Compact Binary Coalescence

Gravitational wave searches rely on a combination of methods, including matched filtering, coherent analyses, and more recent machine learning based pipelines. For compact binary coalescences, where signals originate from the relativistic dynamics of compact objects, matched filtering remains a central element, but its computational cost will increase substantially with the data volumes and parameter-space coverage required by next-generation interferometers such as the Einstein Telescope. Developing complementary strategies that reduce computational load while preserving detection performance is therefore essential. We investigate a hybrid approach that combines matched-filtering concepts with Convolutional Neural Networks, enabling efficient signal searches without relying on the usual $χ^2$ rejection test. Using simulated data sets that include injected signals in Gaussian noise, transient noise, and physical effects not represented in template bank, such as eccentricity, precession and higher-order modes, we show that the method achieves a detection efficiency comparable to a standard matched-filtering search while offering a more resource efficient pipeline. These results indicate that deep learning assisted searches can support sustainable gravitational-wave data analysis in future detector eras.

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arXiv2025

The Science of the Einstein Telescope

Einstein Telescope (ET) is the European project for a gravitational-wave (GW) observatory of third-generation. In this paper we present a comprehensive discussion of its science objectives, providing state-of-the-art predictions for the capabilities of ET in both geometries currently under consideration, a single-site triangular configuration or two L-shaped detectors. We discuss the impact that ET will have on domains as broad and diverse as fundamental physics, cosmology, early Universe, astrophysics of compact objects, physics of matter in extreme conditions, and dynamics of stellar collapse. We discuss how the study of extreme astrophysical events will be enhanced by multi-messenger observations. We highlight the ET synergies with ground-based and space-borne GW observatories, including multi-band investigations of the same sources, improved parameter estimation, and complementary information on astrophysical or cosmological mechanisms obtained combining observations from different frequency bands. We present advancements in waveform modeling dedicated to third-generation observatories, along with open tools developed within the ET Collaboration for assessing the scientific potentials of different detector configurations. We finally discuss the data analysis challenges posed by third-generation observatories, which will enable access to large populations of sources and provide unprecedented precision.

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arXiv2025

Weakly modeled search for compact binary coalescences in the Einstein Telescope

We search for gravitational-wave (GW) signals from compact binary coalescences (CBC) in the $2024$ mock data challenge of the Einstein Telescope (ET) with a detection algorithm that does not rely on the waveform of the signal searched. With the increased sensitivity of ET compared to current GW detectors, a very high rate of detectable sources is expected in the data, and the computational cost of the searches may become a limiting factor. This is why we explore the behavior of a weakly modeled search algorithm, which is intrinsically less sensitive than optimal search methods based on matched filtering techniques, but computationally much cheaper. This search recovers a significant fraction of CBC signals present in the data: 38% of the total number of binary black hole mergers, including 89% of the systems with a total mass above 100 solar masses, as well as the majority of binary neutron star (BNS) mergers closer than 850 Mpc (z=0.17). It is also able to estimate the chirp mass of the recovered BNS with an average precision of 1.3%. We also find that the usual method for estimating the background in transient GW searches, that consists in time-shifting the data from one detector with respect to the others, is impacted by the presence of loud CBC signals in the data, so we use the null stream instead as a signal-free channel to estimate the background of this search.

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arXiv2025

Prompt GRB recognition through waterfalls and deep learning

Gamma-ray Bursts (GRBs) are one of the most energetic phenomena in the cosmos, whose study probes physics extremes beyond the reach of laboratories on Earth. Our quest to unravel the origin of these events and understand their underlying physics is far from complete. Central to this pursuit is the rapid classification of GRBs to guide follow-up observations and analysis across the electromagnetic spectrum and beyond. Here, we introduce a compelling approach that can set milestone towards a new and robust GRB prompt classification method. Leveraging self-supervised deep learning, we pioneer a previously unexplored data product to approach this task: the GRB waterfalls.

astro-ph.HE↗

arXiv2024

A weakly-modeled search for compact binary coalescences in Einstein Telescope

Einstein Telescope (ET) is a project of third generation gravitational wave (GW) detector with a planned sensitivity 10 times better than current detectors such as Advanced LIGO and Advanced Virgo. The high rate of GW signals expected in the data will pose several data analysis challenges, like the ability to disentangle overlapping signals or the need to dimension the computational resources required to treat all the candidate events. We explore the behaviour and the performances of a data analysis pipeline designed to search for unmodelled GW signals with duration 1 to 1000 s on a mock dataset that consists of 1 month of data following ET design sensitivity on top of which is added a realistic distribution of compact binary coalescence (CBC) signals. Unmodelled searches are intrinsically less sensitive to CBC signals than template-based searches, but are computationally cheaper and more robust to uncertainties in the waveforms. This search recovers 38% of the total number of injected binary black hole (BBH) signals, including 89% of the systems with a total mass above 100 solar masses, as well as the majority of binary neutron star (BNS) signals closer than 850 Mpc (z = 0.17). It is also able to estimate the chirp mass of the recovered BNS with an average precision of 1.3%. Therefore, we show that this unmodelled search is able to detect a substantial amount of CBC events at a relatively low computational cost, which makes it interesting for low latency analyses and independent validation of detections made by matched filtering pipelines. We also find that the presence of many CBC signals only marginally impacts the sensitivity of the search to other kinds of unmodelled long duration transient signals, by 3% in average.

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

Optimizing the low-latency localization of gravitational waves

Gravitational-wave data from interferometric detectors like LIGO, Virgo and KAGRA is routinely analyzed by rapid matched-filtering algorithms to detect compact binary merger events and rapidly infer their spatial position, which enables the discovery of associated non-GW transients like GRB 170817A and AT2017gfo. One of the critical requirements for finding such counterparts is that the rapidly inferred sky location, usually performed by the Bayestar algorithm, is correct. The reliability of this data product relies on various assumptions and a tuning parameter in Bayestar, which we investigate in this paper in the context of PyCBC Live, one of the rapid search algorithms used by LIGO, Virgo and KAGRA. We perform simulations of compact binary coalescence signals recovered by PyCBC Live and localized by Bayestar, under various configurations with different balances between simplicity and realism, and we test the resulting sky localizations for consistency based on the widely-used PP plot. We identify some aspects of the search configuration which drive the optimal setting of Bayestar's tuning parameter, in particular the properties of the template bank used for matched filtering. On the other hand, we find that this parameter does not depend strongly on the nonstationary and non-Gaussian properties of the detector noise.

gr-qc↗

arXiv2024

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↗

arXiv2022

Observing GW190521-like binary black holes and their environment with LISA

Binaries of relatively massive black holes like GW190521 have been proposed to form in dense gas environments, such as the disks of Active Galactic Nuclei (AGNs), and they might be associated with transient electromagnetic counterparts. The interactions of this putative environment with the binary could leave a significant imprint at the low gravitational wave frequencies observable with the Laser Interferometer Space Antenna (LISA). We show that LISA will be able to detect up to ten GW190521-like black hole binaries, with sky position errors $\lesssim1$ deg$^2$. Moreover, it will measure directly various effects due to the orbital motion around the supermassive black hole at the center of the AGN, especially the Doppler modulation and the Shapiro time delay. Thanks to a careful treatment of their frequency domain signal, we were able to perform the full parameter estimation of Doppler and Shapiro-modulated binaries as seen by LISA. We find that the Doppler and Shapiro effects will allow for measuring the AGN parameters (radius and inclination of the orbit around the AGN, central black hole mass) with up to percent-level precision. Properly modeling these low-frequency environmental effects is crucial to determine the binary formation history, as well as to avoid biases in the reconstruction of the source parameters and in tests of general relativity with gravitational waves.

gr-qc↗

arXiv2022

Searches for Modulated γ-Ray Precursors to Compact Binary Mergers in Fermi-GBM Data

GW170817 is the only gravitational-wave (GW) event, for which a confirmed γ-ray counterpart, GRB 170817A, has been detected. Here we present a method to search for another type of γ-ray signal, a γ-ray burst precursor, associated with a compact binary merger. If emitted shortly before the coalescence, a high-energy electromagnetic (EM) flash travels through a highly dynamical and relativistic environment, created by the two compact objects orbiting each other. Thus, the EM signal arriving at an Earth observer could present a somewhat predictable time-dependent modulation. We describe a targeted search method for lightcurves exhibiting such a modulation, parameterized by the observer-frame component masses and binary merger time, using Fermi-GBM data. The sensitivity of the method is assessed based on simulated signals added to GBM data. The method is then applied to a selection of potentially interesting compact binary mergers detected during the second (O2) and third (O3) observing runs of Advanced LIGO and Advanced Virgo. We find no significant modulated γ-ray precursor signal associated with any of the considered events.

astro-ph.HE↗

arXiv2022

An Infrared Search for Kilonovae with the WINTER Telescope. I. Binary Neutron Star Mergers

The Wide-Field Infrared Transient Explorer (WINTER) is a new 1 $\text{deg}^2$ seeing-limited time-domain survey instrument designed for dedicated near-infrared follow-up of kilonovae from binary neutron star (BNS) and neutron star-black hole mergers. WINTER will observe in the near-infrared Y, J, and short-H bands (0.9-1.7 microns, to $\text{J}_{AB}=21$ magnitudes) on a dedicated 1-meter telescope at Palomar Observatory. To date, most prompt kilonova follow-up has been in optical wavelengths; however, near-infrared emission fades more slowly and depends less on geometry and viewing angle than optical emission. We present an end-to-end simulation of a follow-up campaign during the fourth observing run (O4) of the LIGO, Virgo, and KAGRA interferometers, including simulating 625 BNS mergers, their detection in gravitational waves, low-latency and full parameter estimation skymaps, and a suite of kilonova lightcurves from two different model grids. We predict up to five new kilonovae independently discovered by WINTER during O4, given a realistic BNS merger rate. Using a larger grid of kilonova parameters, we find that kilonova emission is $\approx$2 times longer-lived and red kilonovae are detected $\approx$1.5 times further in the infrared than in the optical. For 90% localization areas smaller than 150 (450) $\rm{deg}^{2}$, WINTER will be sensitive to more than 10% of the kilonova model grid out to 350 (200) Mpc. We develop a generalized toolkit to create an optimal BNS follow-up strategy with any electromagnetic telescope and present WINTER's observing strategy with this framework. This toolkit, all simulated gravitational-wave events, and skymaps are made available for use by the community.

astro-ph.HE↗

arXiv2022

Realtime search for compact binary mergers in Advanced LIGO and Virgo's third observing run using PyCBC Live

The third observing run of Advanced LIGO and Advanced Virgo took place between April 2019 and March 2020 and resulted in dozens of gravitational-wave candidates, many of which are now published as confident detections. A crucial requirement of the third observing run has been the rapid identification and public reporting of compact binary mergers, which enabled massive followup observation campaigns with electromagnetic and neutrino observatories. PyCBC Live is a low-latency search for compact binary mergers based on frequency-domain matched filtering, which has been used during the second and third observing runs, together with other low-latency analyses, to generate these rapid alerts from the data acquired by LIGO and Virgo. This paper describes and evaluates the improvements made to PyCBC Live after the second observing run, which defined its operation and performance during the third observing run.

astro-ph.HE↗

arXiv2021

Pre-merger localization of compact-binary mergers with third generation observatories

We present the prospects for the pre-merger detection and localization of binary neutron star mergers with third generation gravitational-wave observatories. We consider a wide variety of gravitational-wave networks which may be operating in the 2030's and beyond; these networks include up to two Cosmic Explorer sites, the Einstein Telescope, and continued observation with the existing second generation ground-based detectors. For a fiducial local merger rate of 300 Gpc$^{-3}$yr$^{-1}$, we find that the Einstein Telescope on its own is able to detect 6 and 2 sources per year at 5 and 30 minutes before merger, respectively, while providing a localization of $<10~\textrm{deg}^2$. A single Cosmic Explorer would detect but be unable to localize sources on its own. A two-detector Cosmic Explorer network, however, would detect 22 and 0.4 mergers per year using the same criteria. A full three-detector network with the operation of dual Cosmic Explorers and the Einstein Telescope would allow for $<1~\textrm{deg}^2$ source localization at 5 minutes before merger for $\sim7$ sources per year. Given the dramatic increase in localization and detection capabilities, third generation observatories will enable the regular observation of the prompt emission of mergers by a broad array of observatories including gamma-ray, x-ray, and optical telescopes. Moreover, sub-degree localizations minutes before merger, combined with narrow-field-of-view high-energy telescopes, could strongly constrain the high-energy pre-merger emission models proposed in the last decade.

astro-ph.HE↗

arXiv2021

First demonstration of early warning gravitational wave alerts

Gravitational-wave observations became commonplace in Advanced LIGO-Virgo's recently concluded third observing run. 56 non-retracted candidates were identified and publicly announced in near real time. Gravitational waves from binary neutron star mergers, however, remain of special interest since they can be precursors to high-energy astrophysical phenomena like $γ$-ray bursts and kilonovae. While late-time electromagnetic emissions provide important information about the astrophysical processes within, the prompt emission along with gravitational waves uniquely reveals the extreme matter and gravity during - and in the seconds following - merger. Rapid communication of source location and properties from the gravitational-wave data is crucial to facilitate multi-messenger follow-up of such sources. This is especially enabled if the partner facilities are forewarned via an early-warning (pre-merger) alert. Here we describe the commissioning and performance of such a low-latency infrastructure within LIGO-Virgo. We present results from an end-to-end mock data challenge that detects binary neutron star mergers and alerts partner facilities before merger. We set expectations for these alerts in future observing runs.

astro-ph.HE↗

arXiv2021

Parameter estimation of stellar-mass black hole binaries with LISA

Stellar-mass black hole binaries (SBHBs), like those currently being detected with the ground-based gravitational-wave (GW) observatories LIGO and Virgo, are also an anticipated GW source for LISA. LISA will observe them during the early inspiral stage of evolution; some of them will chirp through the LISA band and reappear some time later in the band of $3^{rd}$ generation ground-based detectors. SBHBs could serve as laboratories for testing the theory of General Relativity and inferring the astrophysical properties of the underlying population. In this study, we assess LISA's ability to infer the parameters of those systems, a crucial first step in understanding and interpreting the observation of those binaries and their use in fundamental physics and astrophysics. We simulate LISA observations for several fiducial sources and perform a full Bayesian analysis. We demonstrate and explain degeneracies in the parameters of some systems. We show that the redshifted chirp mass and the sky location are always very well determined, with typical errors below $10^{-4}$ (fractional) and $0.4 \ {\rm deg^2}$. The luminosity distance to the source is typically measured within $40-60\%$, resulting in a measurement of the chirp mass in the source frame of $\mathcal{O}(1 \%)$. The error on the time to coalescence improves from $\mathcal{O}(1 \ {\rm day})$ to $\mathcal{O}(30 \ {\rm s})$ as we observe the systems closer to their merger. We introduce an augmented Fisher-matrix analysis which gives reliable predictions for the intrinsic parameters compared to the full Bayesian analysis. Finally, we show that combining the use of the long-wavelength approximation for the LISA instrumental response together with the introduction of a degradation function at high frequencies yields reliable results for the posterior distribution when used self-consistently, but not in the analysis of real LISA data.

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