arXiv subjects

José A. Font

Publications and source records attributed to José A. Font.

At least 19 recordsLinked to original sources

arXiv2026

Descalarization bursts from Galactic supramassive neutron stars: a kHz continuous-wave target

In massive scalar-tensor gravity, a scalarized neutron star must shed its scalar hair as it collapses into a black hole. Using 3D simulations of a realistic rotating progenitor we show that dispersion stretches the emitted burst into a quasi-monochromatic signal in the kHz frequency range lasting $>10^4$ yr and amenable to continuous-wave methods. We find that detecting these signals in directed searches of supernova remnants without a central pulsar requires sensitivity depths of 233--762 $\rm{Hz^{-1/2}}$ with the A+-ET-CE detector network. We estimate up to $\sim3$ of these signals in transit at any observational epoch.

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arXiv2026

Rotating Neutron Star Migrations as a Standardized Test for 3+1 Numerical Relativity

When simulating dynamically unstable neutron stars, truncation errors can introduce perturbations that drive the stellar configuration either toward gravitational collapse into a black hole or toward migration to a dynamically stable, lower-density configuration. This mechanism has become a standard benchmark for validating general-relativistic hydrodynamics codes in the case of spherically symmetric neutron-star models. In this work, we extend the analysis to the more general case of uniformly rotating neutron stars evolved in three spatial dimensions. We investigate these transitions using two equations of state: a cold polytrope and a hybrid prescription, which allow us to distinguish the barotropic response from the effects of shock-generated thermal pressure. We find that the migrated remnant remains close to uniform rotation after the transition, and we trace its quasi-radial pulsations through complementary diagnostics involving the central density, the rotation profile, and the axisymmetric gravitational-wave channel. We investigate the properties of these transitions and propose a standardized test for validating numerical-relativity codes by requiring the migration behavior to be consistent with the dynamics reported here.

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arXiv2026

DANSur_HM: Modularly incorporating higher modes in a deep learning based gravitational-wave surrogate

Numerical relativity (NR) simulations provide the most faithful representation of the gravitational waves (GWs) emitted by binary black hole (BBH) systems during merger. In the context of GW astronomy, tasks such as parameter estimation can require vast numbers of waveform evaluations per second across the entire parameter space. Since performing full NR simulations for each evaluation is not computationally feasible, interpolating methods for existing NR waveforms, known as surrogate models, have been developed with marked success. In this paper, we build on our previous work to introduce methods to train a fast surrogate model based on neural networks in order to generate BBH merger waveforms, including the fundamental (2,2) mode, as well as the (3,3), (2,1), (4,4), (3,2), (4,3) and (5,5) higher-order modes. Applying a pretraining step on approximant data before fine-tuning on NR data allows us to smooth out the parameter space, and making use of the parallelization ability of GPUs to project the NR waveforms in the inclination-phase $(ι, ϕ)$ sphere during training allows the fitting of all the explored modes simultaneously. The developed surrogate model, \texttt{DANSur\_HM}, achieves average mismatches of the order of $10^{-4}$, with the worst mismatch at $2.5\times10^{-3}$, and achieves throughput above $6\times10^5$ waveforms/second on an NVIDIA V100 GPU. Parameter estimation tests confirm the usefulness of the inclusion of higher modes.

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arXiv2026

Kerr Quasinormal Modes without Variable Separation: A Two-Dimensional Hyperboloidal Teukolsky Solver with Physics-Informed Neural Networks

We use physics-informed neural networks (PINNs) to solve the gravitational quasinormal-mode (QNM) eigenvalue problem for Kerr spacetime directly in the two-dimensional hyperboloidal formulation of the Teukolsky equation. This formulation does not require separation of variables and thus retains the coupled radial--angular structure. Such a scheme provides a prototype for calculating the QNMs of beyond-Kerr black holes for which the perturbation equations are non-separable. Sequences with increasing angular momentum are constructed, reaching close to the extremal limit. We focus on the fundamental modes $(\ell,m,n)=(2,0,0)$, $(2,1,0)$, $(2,2,0)$, $(3,3,0)$ and $(4,4,0)$, together with the first overtone $(2,2,1)$. Independent benchmark evaluation shows that every reported real and imaginary frequency component remains below $0.5\%$ error, with a median deviation of $0.1\%$. This accuracy is maintained in the near-extremal regime, where the damping rate becomes small and the modes are longest-lived. The results establish a non-spectral numerical route to multidimensional black-hole perturbation eigenproblems which does not match the substantially higher precision of dedicated Kerr solvers but offers greater flexibility and requires less analytical pre-processing. Non-separable rotating backgrounds and coupled systems, such as gravitational--electromagnetic Kerr--Newman perturbations, are natural extensions of the same construction.

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arXiv2026

Automatic classification pipeline for glitches in the Virgo detector

Glitches frequently contaminate data in gravitational-wave detectors, complicating the observation and analysis of astrophysical signals. This work introduces VIGILant, an automatic pipeline for classification and visualization of glitches in the Virgo detector. Using a curated dataset of Virgo O3b glitches, two machine learning approaches are evaluated: tree-based models (Decision Tree, Random Forest and XGBoost) using structured Omicron parameters, and Convolutional Neural Networks (ResNet) trained on spectrogram images. While tree-based models offer higher interpretability and fast training, the ResNet34 model achieved superior performance, reaching a F1 score of 0.9772 and accuracy of 0.9833 in the testing set, with inference times of tens of milliseconds per glitch. The pipeline has been deployed for daily operation at the Virgo site since observing run O4c, providing the Virgo collaboration with an interactive dashboard to monitor glitch populations and detector behavior. This allows to identify low-confidence predictions, highlighting glitches requiring further attention.

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arXiv2026

Viscosity effects on the shadow of a non-rotating black hole

We study the effect of shear viscosity in stationary magnetized accretion tori on synthetic images of non-rotating black hole shadows. Shear viscosity and spacetime-curvature contributions are introduced perturbatively in the tori through first and second-order transport coefficients within a second-order causal theory of non-ideal relativistic hydrodynamics. Synthetic black hole shadow images at 230\,GHz are obtained via general relativistic radiative transfer computations assuming thermal synchrotron emission and for a wide range of plasma magnetization parameters, viewing inclination angles, electron-temperature prescriptions, and viscosity parameters. A comparative pixel-by-pixel analysis using two normalized metrics shows that the largest image differences occur for strongly magnetized tori. While shear viscosity induces only minor changes in the overall shadow morphology, its combined effects with spacetime curvature are more evident in localized modifications of the synchrotron emission and pixel-wise flux distribution. These effects become increasingly pronounced at higher inclination angles, with the largest brightness differences between viscous and non-viscous configurations occurring for larger values of the electron-temperature parameter. Overall, our results indicate that shear viscosity and spacetime curvature leave only modest imprints on black hole shadow images produced by stationary thick disks, with differences remaining at the level of a few $μ$Jy. Since our analysis is limited to stationary tori, the effects of shear viscosity might however be more significant in fully dynamical accretion systems.

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arXiv2026

Rapidly Rotating Neutron Star Collapse in Massive Scalar-Tensor Theories

We present a full 3D numerical evolution code to study neutron stars in massive-scalar-tensor theories. The code is embedded in the Einstein Toolkit framework and its implementation constitutes a modified version of the Baumgarte-Shapiro-Shibata-Nakamura formalism with an additional nonminimally coupled scalar field. The approach we follow preserves the standard hydrodynamic evolution for matter fields, allowing eventually for a straightforward inclusion of more microphysical effects and better flexibility. Using this code, we examine the gravitational collapse of rapidly rotating, scalarized neutron stars to a black hole by exploring the influence of the scalar field on the dynamical features of the process and on the gravitational-wave emission. We find that for the configurations studied in this work, there is an observational degeneracy in the tensorial gravitational-wave emission between collapsing scalarized stars and their counterparts in general relativity. However, this degeneracy can be broken through the emission of scalar radiation, which carries an energy of ~10^-3 M_sun c^2. This is orders of magnitude higher than the quadrupolar emission (~10^-7 M_sun c^2) and might be used as an observational probe of modified gravity. We also find that rapid rotation can enhance this signal, since fast rotating stars can sustain larger scalar field amplitudes.

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arXiv2026

Assessment of normalizing flows for parameter estimation on time-frequency representations of gravitational-wave data

The speed-up of parameter estimation is an active field of research in gravitational-wave data analysis. In this paper we present GP15, a deep-learning method that merges residual networks and normalizing flows into a general-purpose, image-based estimator of binary black hole (BBH) parameters. Building on our early work, we map BBH spectrograms from the Advanced LIGO and Advanced Virgo detectors to color channels in an RGB image amenable to be processed with residual networks. GP15 is trained on simulated data for BBH mergers obtained with the \texttt{IMRPhenomXPHM} waveform approximant and tested for all three-detector events from the GWTC-3 and GWTC-2.1 catalogs reported by the LIGO-Virgo-KAGRA (LVK) collaboration. Overall, our model yields good agreement with the LVK results over most parameters. Our simple model can produce large amounts of posterior samples in the order of a second, complementing existing approaches with normalizing flows based on time or frequency representation of gravitational-wave data. We also discuss current shortcomings of our model and possible improvements for future extensions (e.g. including noise conditioning from the detectors' PSD or splitting the parameter space into intrinsic and extrinsic subspaces).

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arXiv2026

Rotating Fermion-Boson Stars in $R$-squared Gravity

Fermion-boson stars are compact equilibrium configurations composed of ordinary fermionic matter and a bosonic dark component interacting only through gravity. Such systems provide a natural framework for exploring deviations from standard neutron-star models, including the possible accumulation of dark matter inside neutron stars, and may be relevant for compact objects near the low-mass black-hole gap. We construct static and uniformly rotating fermion-boson stars within the framework of $R$-squared $f(R)$ gravity, characterized by the functional form $f(R)=R+aR^{2}$, where $a$ is a positive parameter governing the effective mass scale from the scalar degree of freedom. The fermionic sector is modeled as a perfect fluid described by a tabulated equation of state at zero temperature, while the bosonic component is represented by a self-interacting complex bosonic field. Our results show that the scalar degree of freedom modifies the spatial distribution of both the bosonic field and the fermionic pressure, enlarges the domain of admissible equilibrium solutions, and increases the maximum supported masses relative to general relativity. Our models remain compatible with current astrophysical and gravitational-wave constraints, suggesting that fermion-boson stars in $R$-squared gravity offer a promising framework to investigate the combined effects of dark bosonic matter, rotation, and strong-field modifications of gravity in compact objects.

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arXiv2026

Testing bosonic dark matter through white dwarf mass measurements

Mass estimates of white dwarfs via electromagnetic methods, often differ from those obtained through gravitational redshift measurements, in some cases with discrepancies ranging in $5-15\%$ across independent datasets. Although many of the discrepancies reported in large spectroscopic surveys and confirmed by high-precision techniques such as astrometric microlensing and wide-binary analyses may be attributable to thermal effects, model uncertainties or measurement errors prevent a complete description of some of the observations. Here, we explore an alternative explanation based on the presence of a gravitationally coupled bosonic scalar field that contributes to the stellar mass while remaining electromagnetically invisible. We construct stationary, static mixed configurations consisting of a white dwarf that presents a bosonic scalar field (dark matter) component, forming a composite white dwarf-boson star system. We explore families of solutions showing that a scalar field fraction $f_{\rm DM} \sim 5-15\%$ to the mass contribution can account for the observed redshift excess. Our models provide a physically motivated explanation for the mass bias, might offer new observational signatures, and allow us to place preliminary constraints on the mass and compactness of the scalar field configuration. Finally, using our theoretical framework in combination with Bayesian model selection we provide plausible bounds for the mass of the constituent (ultralight) bosonic particle.

astro-ph.HE↗

arXiv2026

Constraint-satisfying binary boson star initial data via XCFC

Numerical-relativity simulations with non-trivial matter configurations require initial data that satisfy the Hamiltonian and momentum constraints of the Einstein equations. We construct constraint-satisfying scalar-field initial data using the eXtended Conformally Flat Condition (XCFC) formalism, in which the matter variables are conformally rescaled and an auxiliary vector field is introduced. In doing so, we overcome the issues of local uniqueness and convergence of the solutions that arise in the second-order elliptic equations associated with the constraints. Using an iterative solver method, we demonstrate the convergence of the XCFC approach to a solution for several scalar-field matter systems. Those include Gaussian-like profiles, topological torus configurations, and equal-mass boson star binaries. In particular, for the latter case, it is common to employ the superposition of two isolated boson star solutions in order to build the initial data. We show that our formalism significantly improves upon a superposition approach by generating genuinely constraint-satisfying initial data for boson star binaries.

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arXiv2026

On the treatment of thermal effects in the equation of state on neutron star merger remnants

We present results from long-term, numerical-relativity simulations of binary neutron star mergers modeled using both, fully tabulated, finite-temperature, equations of state and their corresponding hybrid representations. The simulations extend up to 150 ms which allows us to assess the role of the treatment of finite-temperature effects on the dynamics of the hypermassive neutron star remnant. Our study focuses on the analysis of the spectra of the post-merger gravitational-wave signals and on how these are affected by the treatment of thermal effects in the two EOS representations. Our simulations highlight distinct differences in the GW frequency evolution related to the thermal modeling of the EOS, demonstrating that deviations from established quasi-universal relations become significant at late post-merger phases. Furthermore, we investigate the stability of the HMNS against convection. Employing both the Ledoux criterion, necessary condition for the development of convective instabilities, and the Solberg-Høiland criterion, a generalized criterion for axisymmetric perturbations based on a combined analysis of the Brunt-Väisälä frequency and of the epicyclic frequency, we show that differential rotation and thermal stratification in the HMNS give rise to local (yet sustained) convective patterns that persist beyond 100 ms after merger. Those convective patterns, while substantially different between tabulated and hybrid EOS treatments, trigger the the excitation of inertial modes with frequencies smaller than those attained by the fundamental quadrupolar mode, and are potentially within reach of third-generation GW detectors. The late-time excitation of inertial modes, previously reported in studies based on hybrid EOS, is fully supported by the tabulated, finite-temperature EOS simulations presented here, which account for thermal effects in a more consistent way.

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arXiv2026

Probing cosmic strings via gravitational-wave lensing

We present a framework for detecting gravitational-wave signals lensed by cosmic strings (CSs), addressing a key gap in current searches. CSs, whose detection would provide a unique probe of high-energy physics and the early Universe, possess distinct topological and geometric features that require a dedicated search strategy. Our approach employs a full-wave transmission factor, expressed analytically via Fresnel integrals, which captures the characteristic diffraction and interference effects of the conical spacetime around a straight CS. We contrast CS lensing with the well-studied point mass lens (PML) model, highlighting their fundamental differences: CS lensing depends on cosmological distances, string tension $Δ$, and wavelength $λ$, and produces two non-amplified images set by the global conical geometry. In contrast, PML lensing is governed by the distance-independent ratio $\sim M_{Lz}/λ$, where $M_{Lz}$ represents the redshifted mass of the lens, with image properties derived from the lens equation. For BBH mergers lensed by CSs, we show that the waveforms exhibit a characteristic beating pattern or time-separated exact replicas. We derive a detectability bound on the string tension and, using Bayesian model selection, demonstrate that CS lensing is distinguishable from both unlensed and PML-lensed signals across a wide region of parameter space.

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arXiv2025

Classification of the equation of state of neutron stars via sparse dictionary learning

The post-merger phase of binary neutron star (BNS) mergers encodes valuable information about the equation of state (EOS) of supranuclear matter. Extracting this information from the analysis of the post-merger waveforms remains challenging due to the high-frequency limitations of current detectors. Future third-generation observatories, such as the Einstein Telescope (ET) and NEMO, will have the sensitivity required to resolve post-merger signals with high fidelity. In this work, we apply CLAWDIA, our recently developed sparse dictionary learning (SDL) framework, to classify different EOS models using only the post-merger gravitational-wave emission of simulated BNS mergers available in the CoRe database. Our dataset comprises five EOS models representative of a broad range of neutron star properties. The SDL framework is optimised under realistic detection conditions by injecting signals into simulated noise matching the sensitivity curves of ET and NEMO. Our results show that classification is primarily driven by the dominant post-merger frequency, $f_2$, which encodes EOS-dependent information. At a modest signal-to-noise ratio of 5, our method achieves $F_1$ scores of $0.76$ for ET and $0.70$ for NEMO, with performance improving for higher signal-to-noise ratios. The reliability and generalisation capabilities of the model are assessed with additional tests, including the classification of an EOS not included in the training dataset and the analysis of detector-specific biases.

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arXiv2025

AT2025ulz and S250818k: zooming in with the Hubble Space Telescope

AT2025ulz is an optical/near-infrared transient discovered during follow-up of the candidate gravitational wave (GW) event S250818k. Its young age ($\lesssim$1 d), rapid decline and strong color evolution over the first 48 hr classify it as a potential kilonova candidate. In this work, we present the results of our observing campaign, carried out with the Gran Telescopio Canarias (GTC) and the Hubble Space Telescope (HST). Although the early time evolution of AT2025ulz resembles some aspects of a kilonova, its rapid onset ($\sim$3 hr after the GW trigger) and luminosity (a factor of $\sim5$ brighter than AT2017gfo in $g$-band) are difficult to reproduce. Only a small subset of our kilonova models matches its multi-color light curve, and the inferred ejecta mass is uncomfortably large given the low chirp mass ($\lesssim\!0.87\!$ M$_{\odot}$) of the GW candidate. HST observations place the transient within a nearby ($z=0.08489$) spiral galaxy with on-going star-formation and measure a color ($F336W-F160W\!\approx\!1.4$ mag) that is too blue to match with a kilonova. Our data support the classification of AT2025ulz as a supernova, initially undergoing a shock-cooling phase and later entering its photospheric phase, and spectroscopically identified via its broad absorption features.

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arXiv2025

Gravitational synchronization in bosonic dark matter admixed neutron stars

While the search for dark matter remains a central focus of modern astrophysics and high-energy physics, neutron stars provide natural laboratories in which the interaction between dark matter and baryonic matter can be studied. In this work we model dark matter as an ultralight bosonic field, which can accrete onto the neutron star and form a composite object bound through gravity. Using long-term, numerical relativity simulations in spherical symmetry, we extract and analyze the frequency spectra of the radial oscillation modes of fermion-boson stars. Our simulations reveal that the fermionic and bosonic components synchronize through gravitational coupling, enriching their oscillation spectrum. This synchronization leads to new multi-state scalar configurations and reshapes the hierarchy of the neutron-star radial modes. We further propose a procedure to compute the values of the new dominant modes as a function of the bosonic mass, and discuss the implications for neutron-star physics and gravitational-wave astronomy.

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arXiv2025

Improving the inference of the stellar quantities using the extended $I$-Love-$Q$-$δM$ relations

In relativistic Astrophysics the $I$-Love-$Q$ relations refer to approximately EoS-independent relations involving the moment of inertia, Love number, and quadrupole moment through some quantities that are normalised by the mass $M_0$ of the background configuration of the perturbative scheme. Since $M_0$ is not an observable quantity, this normalisation hinders the direct applicability of the relations. A common remedy assumes that $M_0$ coincides with the actual mass of the star $M_S$; however, this approximation is only adequate for very slow rotation (when the dimensionless spin parameter is $χ_S<0.1$). The more accurate alternative approach, based on the $I$-Love-$Q$-$δM$ set of relations, circumvents this limitation by enabling the inference of $M_0$. Here we review both approaches and provide numerical comparisons.

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arXiv2025

Addressing the gravitational collapse of a massless scalar field with Physics-Informed Neural Networks

The gravitational collapse of a massless scalar field remains a demanding benchmark for numerical methods in numerical relativity, as it exhibits critical behavior at the boundary between dispersion and black hole formation. In this work we revisit this problem by relying on Physics-Informed Neural Networks (PINNs) as flexible solvers for partial differential equations, thereby providing a comparative assessment of several recent neural architectures. Building on the Einstein-massless-Klein-Gordon formulation in polar-areal coordinates, we consider four initial-value problems encompassing subcritical, critical, and supercritical regimes and use high-resolution finite-difference simulations as reference solutions. Our study is primarily comparative: we evaluate several state-of-the-art deep learning architectures, including vanilla and high-precision PINNs, sinusoidal-feature and quadratic-residual variants, and Kolmogorov-Arnold Networks, all trained under a common loss design that encodes the field equations, boundary conditions, and causal time-space enforcement, together with a novel adaptive spacetime sampling. Within this framework we also introduce ModPINN, a modest modification of standard PINNs that augments standard multilayer perceptrons with coordinate embeddings, quadratic layers, and other common ingredients in recent literature. This study shows that deep-learning-based methods can reproduce finite-difference solutions for the scalar field and the spacetime metric with competitive accuracy using significantly fewer collocation points than more traditional methodologies. While no single architecture dominates in all regimes, ModPINN achieves particularly stable and accurate solutions near criticality, indicating that suitably designed embeddings and adaptive sampling can enhance the robustness of PINNs for challenging gravitational-collapse scenarios.

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