arXiv subjects

Jacopo Tissino

Publications and source records attributed to Jacopo Tissino.

14 recordsLinked to original sources

arXiv2026

Inference with finite time series II: the window strikes back

Smooth window functions are often applied to strain data when inferring the parameters describing the astrophysical sources of gravitational-wave transients. Within the LIGO-Virgo-KAGRA collaboration, it is conventional to include a term to account for power loss due to this window in the likelihood function. We show that the inclusion of this factor leads to biased inference. The simplest solution to this, omitting the factor, leads to unbiased posteriors and Bayes factor estimates provided the window does not suppress the signal for signal-to-noise ratios $\lesssim O(100)$, but unreliable estimates of the absolute likelihood. Instead, we propose a multi-stage method that yields consistent estimates for the absolute likelihood in addition to unbiased posterior distributions and Bayes factors for signal-to-noise ratios $\lesssim O(1000)$. Additionally, we demonstrate that the commonly held wisdom that using rectangular windows necessarily leads to biased inference is incorrect.

gr-qc↗

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.

gr-qc↗

arXiv2026

Gravitational-wave parameter estimation to the Moon and back: massive binaries and the case of GW231123

We study the prospects of the Lunar Gravitational-Wave Antenna (LGWA), a proposed deci-Hz GW detector, to observe binary black holes (BBHs) and enable multiband science with ground-based detectors. We assess the detectability of the events observed by current instruments up to the GWTC-4.0 data release, and of simulated populations consistent with the latest reconstruction by the LIGO-Virgo-KAGRA Collaboration. We find that LGWA alone would have been able to observe more than one third of the events detected so far, and that it could detect $\sim\!90$ events merging in the ground-based band per year out to redshifts $z\sim3-5$. Current detectors at design sensitivity and 100% duty cycle could detect thousands of BBHs per year, with one to a few hundred multiband counterparts in LGWA. Third-generation (3G) detectors can observe most of the BBHs detected by LGWA merging in their frequency band in the simulated mass range $7\,{\rm M}_\odot\lesssim M_{\rm tot}\lesssim 600\,{\rm M}_\odot$, enabling systematic joint analyses of hundreds of events. The short time to merger from the deci-Hz band to the Hz-kHz band (typically months to a year) allows for early warning, targeted follow-up, and archival searches. Multiband observations of intermediate-mass BBHs in the deci-Hz band are particularly promising. We perform an injection study for a GW231123-like system (the most massive BBH detection to date, which accumulates $\sim 10^5$ inspiral cycles in LGWA) and show that deci-Hz observations can measure the chirp mass even better than 3G instruments and yield good sky localization and inclination measurement, even with a single observatory. Opening the deci-Hz band would substantially improve the prospects of GW astronomy for intermediate-mass BBHs.

gr-qc↗

arXiv2026

Comparing next-generation detector configurations for high-redshift gravitational wave sources with neural posterior estimation

The coming decade will be crucial for determining the final design and configuration of a global network of next-generation (XG) gravitational-wave detectors, including the Einstein Telescope (ET) and Cosmic Explorer (CE). In this study, and for the first time, we assessed the performance of various network configurations using neural posterior estimation (NPE) implemented in Dingo-IS-a method based on normalizing flows and importance sampling that enables fast and accurate inference. We focused on a specific science case involving short-duration, massive and high-redshift binary black hole mergers with detector-frame chirp masses $> 100~\mathrm{M}_\odot$. These systems encompass early-Universe stellar and primordial black holes, as well as intermediate-mass black hole binaries, for which XG observatories are expected to deliver major discoveries. Validation against standard Bayesian inference demonstrates that NPE robustly reproduces complex and disconnected posterior structures across all network configurations. For a network of two misaligned L-shaped ET detectors (2L MisA), the posterior distributions on luminosity distance can become multimodal and degenerate with the sky position, leading to less precise distance estimates compared to the triangular ET configuration. However, the number of sky-location multimodalities is substantially lower than the eight expected with the triangular ET, resulting in improved sky and volume localization. Adding CE to the network further reduces sky-position degeneracies, and the better performance of the 2L MisA configuration over the triangle remains evident.

gr-qc↗

arXiv2026

Validating Prior-informed Fisher-matrix Analyses against GWTC Data

Fisher-matrix methods are widely used to predict how accurately parameters can be estimated. Being computationally efficient, this approach is prompted by the large number of signals simulated in forecast studies for future gravitational-wave (GW) detectors, for which adequate analysis tools and computational resources are still unavailable to the scientific community. However, approximating the full likelihood function with a Gaussian may lead to inaccuracies, which we investigate in this work. To assess the accuracy of the Fisher approximation, we compare the results of the Fisher code GWFish against real data from the Gravitational Wave Transient Catalogs (GWTCs) provided by the Virgo/LIGO Bayesian analyses. Additionally, we present a sampling algorithm to include priors in GWFish, not only to ensure a fair comparison between GWFish results and the Virgo/LIGO posteriors but also to investigate the role of prior information and to assess the need to include it in standard Fisher analyses. We find that the impact of priors depends mostly on the level of signal-dependent degeneracy of the waveform parameterization, and priors are generally more important when the level of degeneracy is high. Our findings imply that Fisher-matrix methods are a valid tool for ET science-case studies.

gr-qc↗

arXiv2025

Fast and accurate parameter estimation of high-redshift sources with the Einstein Telescope

The Einstein Telescope (ET), along with other third-generation gravitational wave (GW) detectors, will be a key instrument for detecting GWs in the coming decades. However, analyzing the data and estimating source parameters will be challenging, especially given the large number of expected detections-on the order of $10^5$ per year-which makes current methods based on stochastic sampling impractical. In this work, we use Dingo-IS to perform neural posterior estimation (NPE) of high-redshift events detectable with ET in its triangular configuration. NPE is a likelihood-free inference technique that leverages normalizing flows to approximate posterior distributions. After training, inference is fast, requiring only a few minutes per source, and accurate, as corrected through importance sampling and validated against standard Bayesian inference methods. To confirm previous findings on the ability to estimate parameters for high-redshift sources with ET, we compare NPE results with predictions from the Fisher information matrix (FIM) approximation. We find that NPE correctly recovers the eight degenerate sky modes induced by the triangular detector geometry, missed by the FIM analysis, resulting in an underestimation of sky localization uncertainties for most sources. FIM also overestimates the uncertainty in luminosity distance by a factor of $\sim 3$ on average when the injected luminosity distance is $d^{\mathrm{inj}}_{\mathrm{L}} > 10^5~$Mpc, further confirming that ET will be particularly well suited for studying the early Universe.

astro-ph.HE↗

arXiv2025

Revisiting GW150914 with a non-planar, eccentric waveform model

The first direct detection of gravitational waves by the LIGO collaboration, GW150914, marked the start of a new exciting era in astronomy, enabling the study of the Universe through a new messenger. Since then, the field has grown rapidly, with the development of increasingly more sophisticated techniques to detect, analyze and interpret the signals. In this paper we revisit GW150914, presenting updated estimates of its source parameters using a waveform model developed within the EOB formalism, able to describe gravitational-wave emission from generic non-circular, non-planar binaries. We provide a comprehensive analysis of the signal and its properties, considering and contrasting various scenarios for the source: from the simplest, aligned-spin quasi-circular binary black hole merger, to more complex scenarios, including precession, eccentricity or both. Unsurprisingly, we find that the signal is consistent with a quasi-circular ($e < 0.08$ at $15$ Hz), slowly spinning $(χ_{\rm eff} = -0.03^{+0.12}_{-0.13})$ binary black hole merger, a-posteriori validating a considerable body of works. This is the first analysis performed with an inspiral-merger-ringdown model containing both eccentricity and precession.

gr-qc↗

arXiv2024

The Lunar Gravitational-wave Antenna: Mission Studies and Science Case

The Lunar Gravitational-wave Antenna (LGWA) is a proposed array of next-generation inertial sensors to monitor the response of the Moon to gravitational waves (GWs). Given the size of the Moon and the expected noise produced by the lunar seismic background, the LGWA would be able to observe GWs from about 1 mHz to 1 Hz. This would make the LGWA the missing link between space-borne detectors like LISA with peak sensitivities around a few millihertz and proposed future terrestrial detectors like Einstein Telescope or Cosmic Explorer. In this article, we provide a first comprehensive analysis of the LGWA science case including its multi-messenger aspects and lunar science with LGWA data. We also describe the scientific analyses of the Moon required to plan the LGWA mission.

gr-qc↗

arXiv2024

Classifying binary black holes from Population III stars with the Einstein Telescope: A machine-learning approach

Third-generation (3G) gravitational-wave detectors such as the Einstein Telescope (ET) will observe binary black hole (BBH) mergers at redshifts up to $z\sim 100$. However, an unequivocal determination of the origin of high-redshift sources will remain uncertain because of the low signal-to-noise ratio (S/N) and poor estimate of their luminosity distance. This study proposes a machine-learning approach to infer the origins of high-redshift BBHs. We specifically differentiate those arising from Population III (Pop. III) stars, which probably are the first progenitors of star-born BBH mergers in the Universe, and those originated from Population I-II (Pop. I-II) stars. We considered a wide range of models that encompass the current uncertainties on Pop. III BBH mergers. We then estimated the parameter errors of the detected sources with ET using the Fisher information-matrix formalism, followed by a classification using XGBoost, which is a machine-learning algorithm based on decision trees. For a set of mock observed BBHs, we provide the probability that they belong to the Pop. III class while considering the parameter errors of each source. In our fiducial model, we accurately identify $\gtrsim 10\%$ of the detected BBHs that originate from Pop. III stars with a precision $>90\%$. Our study demonstrates that machine-learning enables us to achieve some pivotal aspects of the ET science case by exploring the origin of individual high-redshift GW observations. We set the basis for further studies, which will integrate additional simulated populations and account for further uncertainties in the population modeling.

astro-ph.HE↗

arXiv2024

GWFish: A simulation software to evaluate parameter-estimation capabilities of gravitational-wave detector networks

An important step in the planning of future gravitational-wave (GW) detectors and of the networks they will form is the estimation of their detection and parameter-estimation capabilities, which is the basis of science-case studies. Several future GW detectors have been proposed or are under development, which might also operate and observe in parallel. These detectors include terrestrial, lunar, and space-borne detectors. In this paper, we present GWFish, a new software to simulate GW detector networks and to calculate measurement uncertainties based on the Fisher-matrix approximation. GWFish models the impact of detector motion on PE and makes it possible to analyze multiband scenarios, i.e., observation of a GW signal by different detectors in different frequency bands. We showcase a few examples for the Einstein Telescope (ET) including the sky-localization of binary neutron stars, and ET's capability to measure the polarization of GWs.

gr-qc↗

arXiv2024

Using gravitational wave early warning to pre-point neutron star mergers with Imaging Atmospheric Cherenkov telescopes

The LIGO-Virgo-KAGRA (LVK) collaboration has recently made it possible for early warning alerts to be sent out, potentially before the end of the gravitational wave (GW) emission from a neutron star binary. If we get such alerts in this (the fourth) or the next observing run they may arrive up to tens of seconds before the merger, which is comparable to the slewing times of the Large Size Telescopes (designed to observe very high energy gamma rays): it would be therefore possible to point to the source right before it starts emitting an electromagnetic signal. This new mode of observation would allow us to detect the TeV component of prompt emission, which is currently poorly constrained and understood. There are many technical challenges to overcome before this can be realized: improving the synergy between gravitational observatories and telescopes, reducing operational latencies and, from the gravitational wave side, providing more information, such as real-time updates on early warning candidates and the probability distribution of the inclination angle. Although we may need to wait a few years -- in the worst case scenario, until the next generation of GW detectors is built -- before the first detection of this kind is made, implementing these improvements is a necessity.

astro-ph.HE↗

arXiv2024

Camelidae on BOAT: observation of a second spectral component in GRB 221009A

Observing and understanding the origin of the very-high-energy (VHE) spectral component in gamma-ray bursts (GRBs) has been challenging because of the lack of sensitivity in MeV-GeV observations, so far. The majestic GRB 221009A, known as the brightest of all times (BOAT), offers a unique opportunity to identify spectral components during the prompt and early afterglow phases and probe their origin. Analyzing simultaneous observations spanning from keV to TeV energies, we identified two distinct spectral components during the initial 20 minutes of the burst. The second spectral component peaks between $10-300$ GeV, and the bolometric fluence (10 MeV-10 TeV) is estimated to be greater than 2$\times10^{-3}$ erg/ cm$^{2}$. Performing broad-band spectral modeling, we provide constraints on the magnetic field and the energies of electrons accelerated in the external relativistic shock. We interpret the VHE component as an afterglow emission that is affected by luminous prompt MeV radiation at early times.

astro-ph.HE↗

arXiv2023

Opportunities and limits of lunar gravitational-wave detection

A new era of lunar exploration has begun with participation of all major space agencies. This activity brings opportunities for revolutionary science experiments and observatories on the Moon. The idea of a lunar gravitational-wave detector was already proposed during the Apollo program. The key characteristic of the Moon is that it is seismically extremely quiet. It was also pointed out that the permanently shadowed regions at the lunar poles provide ideal conditions for gravitational-wave detection. In recent years, three different detector concepts were proposed with varying levels of technological complexity and science potential. In this paper, we confront the three concepts in terms of their observational capabilities based on a first more detailed modeling of instrumental noise. We identify important technological challenges and potential show-stoppers.

astro-ph.IM↗

arXiv2022

Combining effective-one-body accuracy and reduced-order-quadrature speed for binary neutron star merger parameter estimation with machine learning

We present mlgw-bns, a gravitational waveform surrogate that allows for a significant improvement in the generation speed of frequency-domain waveforms for binary neutron star mergers, at a negligible cost in accuracy. This improvement is achieved by training a machine-learning model on a dataset of waveforms generated with an accurate but comparatively costlier approximant: the state-of-the-art effective-one-body model TEOBResumSPA. When coupled to a reduced-order scheme, mlgw-bns can accelerate waveform generation up to a factor of ~35, outperforming all other approximants of similar accuracy. By analyzing GW170817 in realistic parameter estimation settings with our scheme, we showcase an overall speedup against TEOBResumSPA greater than an order of magnitude. Our methodology will bear a significant impact on the scientific program of next generation detectors by allowing routine usage of accurate effective-one-body models.

gr-qc↗