arXiv subjects

Michele Zanolin

Publications and source records attributed to Michele Zanolin.

At least 19 recordsLinked to original sources

arXiv2026

Parameter Estimation Horizon of Core-Collapse Supernovae with a Network of Gravitational-Wave Detectors

Core-collapse supernovae are among the most promising yet still undetected sources of gravitational waves. A future detection would provide a direct view of the physical processes occurring deep inside a collapsing star. In this work, we investigate how networks of current and future gravitational-wave detectors can constrain the properties of rapidly rotating core-collapse supernovae using their characteristic core-bounce and early post-bounce signals. Using deep-learning techniques, we estimate the peak frequency, rotation rate, and signal amplitude from noisy detector data and compare the performance of different detector-network configurations. We find that detector networks improve both parameter recovery and sky coverage. For current-generation networks, estimation of the peak frequency is possible out to about 30 kpc, while the rotation rate and signal amplitude remain recoverable out to distances exceeding 100 kpc. Third-generation observatories extend these distances by nearly an order of magnitude.

astro-ph.HE↗

arXiv2026

Classifying the nuclear equation of state in LVK interferometric noise through core-collapse supernova gravitational-wave signatures using convolutional neural networks

This paper presents a convolutional neural network (CNN) approach to classifying the nuclear equation of state (EOS). As illustrative examples, we use five two-dimensional core-collapse supernova (CCSN) simulations that differ only in their EOS. We analyze estimates of the initial slope of the high-frequency feature (HFF) reconstructed in real interferometric data from the O3b LIGO-Virgo-KAGRA (LVK) observing run at Galactic source distances of 1, 5, and 10 kpc. The CNN classifier achieves an overall accuracy of 98.58% at 1 kpc and 52.43% at 5 kpc. At 10 kpc, its ability to distinguish among the EOS classes is effectively lost. The successful EOS classification at 1 kpc suggests that this approach may be scalable to next-generation observatories. The expected order-of-magnitude sensitivity improvements of Cosmic Explorer and the Einstein Telescope could enable comparable classification performance at approximately ten times the current distance. More detailed performance metrics, including the macro-averaged one-vs-rest (OvR) area under the curve (AUC), yield values of 0.97 and 0.98 at 1 kpc. These results indicate strong classification performance both across the complete set of EOS classes and for the individual classes.

gr-qc↗

arXiv2026

From the Early Slope to Curvature: Future Prospects and challenges for Astrophysical Parameter Estimation Using the Core-Collapse Supernova High-Frequency Feature

Gravitational-wave (GW) signals from core-collapse supernovae (CCSNe) contain both stochastic and deterministic components. Among these, the High-Frequency Feature (HFF), associated with PNS oscillations, has emerged as a robust observable for probing dense-matter physics. Previous studies of the HFF have primarily focused on the early-time slope as a diagnostic of PNS contraction and its dependence on the equation of state (EOS). In this work, we extend the analysis beyond the early-time linear regime. In particular, we discuss how higher-order features of the HFF evolution, such as its curvature, may encode additional information about the time-dependent structure of the PNS and the transition between oscillation modes. Using real interferometric noise and reconstruction techniques on detected candidates by the coherent WaveBurst (cWB) algorithm in its cWB-XP implementation, we illustrate how such features can be accessed. By comparing reconstructed signals at different source distances, we assess the relative impact of detector noise.

gr-qc↗

arXiv2026

The impact of physically motivated calibration errors on search pipeline detection parameters for broadband burst Signals

Imperfections in the calibration of gravitational wave observatories introduce frequency dependent amplitude and phase errors on the measured GW signal. Previous unmodelled burst searches have approximated these effects using prescriptions such as a uniform amplitude rescaling or a constant time shift, which do not capture the frequency-dependent structure of calibration errors. This limitation is problematic for core-collapse supernovae, whose predicted GW signals occupy a wide frequency band and exhibit complex time-frequency morphology. In this work, we investigate how realistic calibration errors affect burst search pipelines by combining analytical modelling with large-scale injection campaigns. First-order estimates are derived to quantify how frequency-dependent amplitude and phase errors influence detection statistics such as the coherent network SNR and the correlation coefficient. These calculations predict that the relative impact on the coherent network SNR scales with the signal strength until it reaches an asymptotic value. The effect on the correlation coefficient is most pronounced near the detection threshold and is entirely suppressed at high SNR ratio. Injection studies confirm that calibration errors do modify the detection statistics, but show that the dominant contribution arises indirectly through changes in the number of time-frequency pixels selected in an event. Despite these measurable variations, detection efficiencies as a function of distance differ by less than one percent across all tested waveforms, and explosion-energy limits remain dominated by astrophysical uncertainties rather than calibration uncertainty. These results demonstrate that, at current detector sensitivity, realistic calibration errors have minimal impact on the detectability of broadband GW burst signals. The impact of calibration errors on parameter estimation is left for future work.

gr-qc↗

arXiv2026

Quantification of the parameter estimation error from Rotating Core Collapse supernovae

In this paper, we perform parameter estimation with an analytical model to simulate the gravitational wave emission during the core bounce phase of a rapidly rotating core collapse supernova progenitor. This approach enables us to estimate the parameter $β$, defined as the ratio of rotational kinetic energy to gravitational potential energy in core collapse supernovae. To verify the reliability of both the analytical model and the inferred value of $β$, we use a numerical template bank constructed from Abylkairovś gravitational waveform catalog and simulate O4 noise, characterized by the interferometers power spectral density. An average fitting factor of 94\% over the interval 0.02 $< β<$ 0.14 shows that our analytical model reproduces the key characteristics of the core-bounce waveform with high accuracy, leading to only a 6\% reduction in the optimal signal to noise ratio. This provides a quantitative measure of how well the analytical model performs. Subsequently, we analyze the error in estimating $β$ using a Matched Filter method and compare it to the corresponding Cramér Rao Lower Bound. The results obtained by considering noise and waveforms at distances of 5, 10, and 50 kpc enable an assessment of how accurately the selected statistical model fits the observed data. From the asymptotic expansion of the variance, we derive a theoretical lower bound for the error that falls below $10^{-1}$ when the parameter $β$ decreases with distance.

gr-qc↗

arXiv2026

Detecting Gravitational Wave Memory in the Next Galactic Core-Collapse Supernova

We present an approach to detecting (linear) gravitational wave memory in a Galactic core-collapse supernova using current interferometers. Gravitational wave memory is an important prediction of general relativity that has yet to be confirmed. Our approach uses a combination of Linear Prediction Filtering and Matched-Filtering. We present the results of our approach on data from core-collapse supernova simulations that span a range of progenitor mass and metallicity. We are able to detect gravitational wave memory out to 10 kpc. We also present the False Alarm Probabilities assuming an On-Source Window compatible with the presence of a neutrino detection. Errata: The neutrino-induced gravitational waveforms, a component of the total waveforms used to demonstrate the efficacy of the proposed detection method for gravitational wave memory, were computed incorrectly. They were underestimated by a factor of $4π$. As a result, the detection results improve and, most important, our primary conclusions are reinforced. In particular, with the corrected waveforms, see Fig. 1 and Fig. 3, the signal for D9.6-3D is in fact detectable at 1 kiloparsec, see Fig. 6 and Fig. 4. The corrected fit parameters are presented in Table 1. The false alarm probability for all three signals is impacted, as shown in Fig. 5. Fig. 5 demonstrates that our proposed method can reliably detect the D9.6-3D signal at 1 kpc for all cutoff values, but our conclusions regarding the inability to detect this signal at 10 and 100 kpc remain the same. We see a boost in the detectability of the D15-3D and D25-3D signals. We now obtain a lower false alarm probability at 10 and 100 kpc. The authors would like to acknowledge Lella et al. [87] for pointing out the discrepancy between our computed neutrino-induced waveforms and theirs, which prompted us to investigate the discrepancy and which led to the discovery of our error.

astro-ph.HE↗

arXiv2026

Low-Frequency Gravitational Waves in Three-Dimensional Core-Collapse Supernova Models

We discuss the low-frequency gravitational wave signals from three state-of-the-art three-dimensional core-collapse supernova models produced with the \textsc{Chimera} supernova code. We provide a detailed derivation of the gravitational wave signal sourced from the anisotropic emission of neutrinos and provide the total (fluid sourced and neutrino sourced) gravitational waves signal generated in our models. We discuss the templatablity of this low-frequency signal, which is useful for future work involving matched filtering for signal detection and parameter estimation. Errata: The neutrino-induced gravitational waveforms presented were computed incorrectly. They were underestimated by a factor of $4π$. While the results are impacted, the original conclusions are not. In fact, they are only reinforced. The corrected versions of Figs. 5--7, 11--16, and 19 are given here. The captions of Figs. 5--7, 11, 12, 16, and 19 are not modified. The captions of Figs. 13, 14, and 15 are corrected to the fit parameters for the corrected waveforms. The corrected versions of Tables I--III are given here. There is no correction to the caption. Finally the authors would like to acknowledge Lella et al. [90] for pointing out the discrepancy between our computed neutrino-induced waveforms and theirs, which prompted us to investigate the discrepancy and which led to the discovery of our error.

astro-ph.HE↗

arXiv2026

Linear Gravitational Wave Memory Through the Window of Core-Collapse Supernovae

Low-frequency gravitational waves ($\lessapprox$ 50 Hz) from core-collapse supernovae are becoming more important for current and future gravitational wave studies. This frequency region is dominated by the global morphology of the explosion and the anisotropic emission of neutrinos from the event. This paper serves as a brief review of both theory and detection (prospects) for gravitational waves in the low-frequency region. We discuss the generation of the linear gravitational wave memory sourced from neutrino emission and show results from an example 15 $M_{\odot}$ Solar metallicity progenitor. We also discuss the detection of the linear gravitational wave memory in current detectors, utilizing a combination of a linear predictive filter and matched templating. Finally we will discuss detection prospects in future detectors such as Cosmic Explorer, Einstein Telescope, the Laser Interferometer Space Antenna, and the Lunar Gravitational-wave Antenna.

astro-ph.HE↗

arXiv2026

Bayesian parameter estimation for the Core-bounce phase of Rapidly Rotating Core-Collapse Supernovae in real interferometric data

We present a novel methodology to estimate the ratio of kinetic to gravitational potential energy in core-collapse supernova progenitors and to assess the equation of state (EOS) using gravitational-wave signals from the core-bounce phase of rapidly rotating stars in real interferometric data. We extend a previous phenomenological model by introducing an additional parameter that captures the signal timescale. The agreement between our template and numerical waveform databases is evaluated through fitting factors and Bayesian model comparison, also assessing consistency across datasets. The improved model increases the median fitting factor from 88.88% to 90.83%. Parameter estimation is performed via Markov Chain Monte Carlo using real O3aL1 noise. For 452 simulated signals, the rotational parameter $β$ is recovered with a median relative error of 11.93% (95th percentile: 38.41%) and an uncertainty of $σ_β= 1.083 \times 10^{-3}$ at 10 kpc, improving over previous matched-filtering results. We further analyze the impact of prior choices and noise properties, finding that real interferometric noise introduces biases up to 11.9%, while optimized priors can reduce them to 0.6%.

astro-ph.HE↗

arXiv2024

Dependence of the Reconstructed Core-Collapse Supernova Gravitational Wave High-Frequency Feature on the Nuclear Equation of State, in Real Interferometric Data

We present an analysis of gravitational wave (GW) predictions from five two-dimensional Core Collapse Supernova (CCSN) simulations that varied only in the Equation of State (EOS) implemented. The GW signals from these simulations are used to produce spectrograms in the absence of noise, and the emergent high-frequency feature (HFF) is found to differ quantitatively between simulations. Below 1 kHz, the HFF is well approximated by a first-order polynomial in time. The resulting slope was found to vary between 10-50% across all models. Further, using real interferometric noise we investigated the current capabilities of GW detectors to resolve these differences in HFF slope for a Galactic CCSN. We find that for distances up to 1 kpc, current detectors can resolve HFF slopes that vary by at least 30%. For further Galactic distances, current detectors are capable of distinguishing the upper and lower bounds of the HFF slope for groupings of our models that varied in EOS. With the higher sensitivity of future GW detectors, and with improved analysis of the HFF, our ability to resolve properties of the HFF will improve for all Galactic distances. This study shows the potential of using the HFF of CCSN produced GWs to provide insight into the physical processes occurring deep within CCSN during collapse, and in particular its potential to further constrain the EOS through GW detection.

astro-ph.HE↗

arXiv2024

Parameter estimation from the core-bounce phase of rotating core collapse supernovae in real interferometer noise

In this work we propose an analytical model that reproduces the core-bounds phase of gravitational waves (GW) of Rapidly Rotating (RR) from Core Collapse Supernovae (CCSNe), as a function of three parameters, the arrival time $τ$, the ratio of the kinetic and potential energy $β$ and a phenomenological parameter $α$ related to rotation and equation of state (EOS). To validate the model we use 126 waveforms from the Richers catalog \cite{Richers_2017} selected with the criteria of exploring a range of rotation profiles, and involving EOS. To quantify the degree of accuracy of the proposed model, with a particular focus on the rotation parameter $β$, we show that the average Fitting Factor (FF) between the simulated waveforms with the templates is 94.4\%. In order to estimate the parameters we propose a frequentist matched filtering approach in real interferometric noise which does not require assigning any priors. We use the Matched Filter (MF) technique, where we inject a bank of templates considering simulated colored Gaussian noise and the real noise of O3L1. For example for A300w6.00\_BHBLP at 10Kpc we obtain a standar deviation of $σ= 3.34\times 10^{-3}$ for simulated colored Gaussian noise and $σ= 1.46\times 10^{-2}$ for real noise. On the other hand, from the asymptotic expansion of the variance we obtain the theoretical minimum error for $\hatβ$ at 10 kpc and optimal orientation. The estimation error in this case is from $10^{-2}$ to $10^{-3}$ as $β$ increases. We show that the results of the estimation error of $β$ for the 3-parameter space (3D) is consistent with the single-parameter space (1D), which allows us to conclude that $β$ is decoupled from the others two parameters.

gr-qc↗

arXiv2024

An Optically Targeted Search for Gravitational Waves emitted by Core-Collapse Supernovae during the Third Observing Run of Advanced LIGO and Advanced Virgo

We present the results from a search for gravitational-wave transients associated with core-collapse supernovae observed optically within 30 Mpc during the third observing run of Advanced LIGO and Advanced Virgo. No gravitational wave associated with a core-collapse supernova has been identified. We then report the detection efficiency for a variety of possible gravitational-wave emissions. For neutrino-driven explosions, the distance at which we reach 50% detection efficiency is up to 8.9 kpc, while more energetic magnetorotationally-driven explosions are detectable at larger distances. The distance reaches for selected models of the black hole formation, and quantum chromodynamics phase transition are also provided. We then constrain the core-collapse supernova engine across a wide frequency range from 50 Hz to 2 kHz. The upper limits on gravitational-wave energy and luminosity emission are at low frequencies down to $10^{-4}\,M_\odot c^2$ and $6 \times 10^{-4}\,M_\odot c^2$/s, respectively. The upper limits on the proto-neutron star ellipticity are down to 3 at high frequencies. Finally, by combining the results obtained with the data from the first and second observing runs of LIGO and Virgo, we improve the constraints of the parameter spaces of the extreme emission models. Specifically, the proto-neutron star ellipticities for the long-lasting bar mode model are down to 1 for long emission (1 s) at high frequency.

astro-ph.HE↗

arXiv2024

Gravitational Waves from Neutrino-Driven Core Collapse Supernovae: Predictions, Detection, and Parameter Estimation

Three-dimensional modeling has reached a level of maturity to provide detailed predictions of the gravitational wave emission in neutrino-driven core collapse supernovae. We review the status of these modeling efforts, current predictions for core collapse supernova gravitational wave emission, and the status of algorithms for the detection of core collapse supernova gravitational waves and the estimation of physical parameters associated with these events, which we hope to use to cull information about the central engine.

astro-ph.HE↗

arXiv2023

Gravito-optics and intensity correlations for binary inspiral signal detections

We examine the correlation functions associated with intensity interferometry and gravito-optics of gravitational wave signals from compact binary coalescences. Previous theoretical studies of the gravito-optics of gravitational waves has concentrated on the characterization of both the classical and the non-classical properties of signals from cosmological sources in the early Universe. These previous works assume a periodic signal similar to the signals studied widely in optics and quantum optics and do not apply to transient signals. We develop the gravito-optics of intensity correlations for descriptions of the detection of transient signals from compact binary coalescences and apply these methods to calculate the two-point intensity correlations for the gravitational wave discovery. We also discuss the necessary theoretical work required for the description of the quantum gravito-optics of intensity correlations in the detection of signals from binary inspirals.

gr-qc↗

arXiv2023

Characterizing the gravitational wave temporal evolution of the gmode fundamental resonant frequency for a core collapse supernova: A neural network approach

We present a methodology based on the implementation of a fully connected neural network to estimate the gravitational wave (GW) temporal evolution of the gmode fundamental resonant frequency for a Core Collapse Supernova (CCSN). To perform the estimation, we construct a training data set, using synthetic waveforms, that serves to train the ML algorithm, and then use several CCSN waveforms to test the model. According to the results obtained from the implementation of our model, we provide numerical evidence to support the classification of progenitors according to their degree of rotation. The relative error associated with the estimate of the slope of the resonant frequency versus time for the GW from CCSN signals is within $13\%$ for the tested candidates included in this study. This method of classification does not require priors or templates, it is based on physical modelling, and can be combined with studies that classify the progenitor with other physical features.

gr-qc↗

arXiv2023

Characterizing a supernova's Standing Accretion Shock Instability with neutrinos and gravitational waves

We perform a novel multi-messenger analysis for the identification and parameter estimation of the Standing Accretion Shock Instability (SASI) in a core collapse supernova with neutrino and gravitational wave (GW) signals. In the neutrino channel, this method performs a likelihood ratio test for the presence of SASI in the frequency domain. For gravitational wave signals we process an event with a modified constrained likelihood method. Using simulated supernova signals, the properties of the Hyper-Kamiokande neutrino detector, and O3 LIGO Interferometric data, we produce the two-dimensional probability density function (PDF) of the SASI activity indicator and calculate the probability of detection $P_\mathrm{D}$ as well as the false identification probability $P_\mathrm{FI}$. We discuss the probability to establish the presence of the SASI as a function of the source distance in each observational channel, as well as jointly. Compared to a single-messenger approach, the joint analysis results in $P_\mathrm{D}$ (at $P_\mathrm{FI}=0.1$) of SASI activities that is larger by up to $\approx~40\%$ for a distance to the supernova of 5 kpc. We also discuss how accurately the frequency and duration of the SASI activity can be estimated in each channel separately. Our methodology is suitable for implementation in a realistic data analysis and a multi-messenger setting.

astro-ph.HE↗

arXiv2022

Gravitational Waves from the Propagation of Long Gamma-Ray Burst jets

Gamma-ray bursts (GRBs) are produced during the propagation of ultra-relativistic jets. It is challenging to study the jet close to the central source, due to the high opacity of the medium. In this paper, we present numerical simulations of relativistic jets propagating through a massive, stripped envelope star associated to long GRBs, breaking out of the star and accelerating into the circumstellar medium. We compute the gravitational wave (GW) signal resulting from the propagation of the jet through the star and the circumstellar medium. We show that key parameters of the jet propagation can be directly determined by the GW signal. The signal presents a first peak corresponding to the jet duration and a second peak which corresponds to the break-out time for an observer located close to the jet axis (which in turn depends on the stellar size), or to much larger times (corresponding to the end of the acceleration phase) for off-axis observers. We also show that the slope of the GW signal before and around the first peak tracks the jet luminosity history and the structure of the progenitor star. The amplitude of the GW signal is $h_+D \sim$ hundreds to several thousands cm. Although this signal, for extragalactic sources, is outside the range of detectability of current GW detectors, it can be detected by future instruments as BBO, DECIGO and ALIA. Our results illustrate that future detections of GW associated to GRB jets may represent a revolution in our understanding of this phenomenon.

astro-ph.HE↗

arXiv2022

Modeling Core-Collapse Supernovae Gravitational-Wave Memory in Laser Interferometric Data

We study the properties of the gravitational wave (GW) emission between $10^{-5}$ Hz and $50$ Hz (which we refer to as low-frequency emission) from core-collapse supernovae, in the context of studying such signals in laser interferometric data as well as performing multi-messenger astronomy. We pay particular attention to the GW linear memory, which is when the signal amplitude does not return to zero after the GW burst. Based on the long term simulation of a core-collapse supernova of a solar-metallicity star with a zero-age main sequence mass of 15 solar masses, we discuss the spectral properties, the memory's dependence on observer position and the polarization of low-frequency GWs from slowly non (or slowly) rotating core-collapse supernovae. We make recommendations on the angular spacing of the orientations needed to properly produce results that are averaged over multiple observer locations by investigating the angular dependence of the GW emission. We propose semi-analytical models that quantify the relationship between the bulk motion of the supernova shock-wave and the GW memory amplitude. We discuss how to extend neutrino generated GW signals from numerical simulations that were terminated before the neutrino emission has subsided. We discuss how the premature halt of simulations and the non-zero amplitude of the GW memory can induce artefacts during the data analysis process. Lastly, we also investigate potential solutions and issues in the use of taperings for both ground and space-based interferometers.

astro-ph.HE↗