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The Iberian Gravitational Waves Meeting is an international conference organised annually since 2011 by different members of the Spanish Gravitational Waves Physics Network (REDONGRA). This year, the meeting will be held from 23 to 25 June 2025 at CIEMAT (Madrid, Spain), starting at 9:00 AM on June 23 and concluding at 5:00 PM on June 25. It will be jointly organised by CIEMAT and IPARCOS (UCM).
The idea is to bring together researchers with an interest in the development of gravitational wave astronomy, including researchers from related fields of astrophysics, multi-messenger astronomy, cosmology, fundamental physics, instrumentation and data analysis, and, importantly, to foster collaboration between them.
In addition to contributed talks, we will host the following Invited Speakers:
A practical course on Explainable Artificial Intelligence (XAI) techniques, focusing on their application in gravitational wave data analysis and related scientific fields, will be held at CIEMAT on 26 June. For detailed information and registration, please visit this webpage.
We look forward to welcoming you to Madrid.
CIEMAT is a public research institute located in the west of Madrid, close to the Complutense University campus. The Gravitational Waves Group is part of the Fundamental Research Department.
Upon arrival at CIEMAT, enter the gatehouse and present your passport or ID card to the guards. They will verify that you are on the list of participants and provide you with a temporary access card and a map. The meeting will take place in the auditorium of Building 1. On the first day, a member of our team will be available to assist you if needed.
At CIEMAT, you can connect to the WiFi network eduroam (check connection details with your home institute before travelling).
To register for the conference, please follow this link or click on "Registration" in the menu on the left. Registration closes on 16 June at 23:59 CEST.
The registration fee is €100 for postdoctoral researchers and senior scientists, and €60 for PhD students (predoctoral researchers). This fee includes coffee and tea breaks, meals, and the workshop dinner. To pay the fee, please click on this link.
The lab is approximately 5 km (3 mi) from the city centre and 17 km (10 mi) from Madrid-Barajas Adolfo Suárez International Airport. A taxi ride from the airport to the city centre (meaning inside the M-30 ring) costs €33 (per trip, not per person!).
Information about the metro (Underground) to/from the airport can be found on this website.
The best way to get around Madrid is by public transport. First, get a Multi-Card (€2.50) from the machines in metro stations (including the airport) and load it with up to 20 metro bus tickets (10 tickets cost €6.10). A single card can be used by more than one person on the same journey (tick the appropriate number of passengers at the entrance). Click here for more details.
It is easy to reach CIEMAT by public transportation. Line 82 (Moncloa-CIEMAT) has a bus stop 50 m (165') away from the main entrance of the Institute (south gate). Details on how to reach CIEMAT are on this web page.
The workshop dinner will take place at the Zerain Basque Grill Restaurant. Please refer to the map and available menus: a standard menu (which includes meat and animal products) and a vegetarian menu (with some vegan options).
Madrid is located at about 650 m AMSL. The air is generally dry, and the wind chill is less pronounced than in humid places.
In this link, you will find the weather forecast for Madrid. We will add more details as we get closer to the workshop dates. Expect warm and dry weather with temperatures between 25°C and 35°C.
The official Madrid tourism website contains plenty of interesting suggestions.
Those visiting Madrid for the first time cannot miss the National Art Museums, El Prado, Reina Sofia and Thyssen-Bornemisza.
To get a taste of what life in Madrid is like, we suggest you take some time to stroll around El Retiro Park.
We have prepared for you a pleasant tour (see map) that will take you to some emblematic places in the centre of Madrid. Starting from Argüelles (pronounced [aɾɣ̞weʝes]), where some of the recommended hotels are located, you can go to the Temple of Debod to see the sunset. Afterwards, we suggest you go to the Plaza de la Paja (Straw Square) or the Cava Baja, where you will find typical restaurants where you can enjoy wine and tapas. The proposed route will take you past the Royal Palace and the Royal Theatre (Opera House), the Almudena Cathedral and the Segovia Viaduct. After dinner, you can walk through Plaza Mayor, Puerta del Sol (the centre of Madrid) and Plaza de Callao, where you can take the metro line 3, which will take you back to Argüelles in a few minutes. Free variations of this tour are encouraged, as they will allow you to discover hidden gems of Madrid.
If you're a fan of live music, there's no limit to what's on offer in Madrid. To name just one of our favourites, we recommend La Coquette Blues Bar, right in the centre of Madrid.
If you have extra time in the area, consider visiting Toledo (75 km/47 mi from Madrid) and/or Segovia (87 km/54 mi), cities rich in history, art and local cuisine.
Madrid is a very popular tourist destination. Although it is a very safe city, pickpockets are common, especially in the city centre. Keep an eye on your belongings, especially on public transport. Carry your rucksack/purse/computer bag in front of you.
In case of emergency, dial 112.
If you need any help, please contact Pablo.
The Einstein Telescope (ET), a third-generation gravitational-wave (GW) observatory, will extend the sensitivity and bandwidth of current detectors, enabling observations from ~1 Hz and vastly increasing the detection rate of compact binary coalescences (CBCs). This leap in capability introduces new data analysis challenges, including increased rates of overlapping signals that can generate confusion noise and limit the effectiveness of standard matched-filter techniques. ET's triangular configuration allows the construction of a null stream—a linear combination of detector outputs in which GW signals cancel—offering a powerful tool for background estimation and glitch mitigation. In this work, we present a proof-of-concept study using simulated ET Mock Data Challenge (MDC) data to explore the role of the null stream in enhancing search sensitivity. We implement a simplified PyCBC-based search using a non-spinning BBH template bank and test the utility of the null stream for improving background estimation in the presence of overlapping signals in Gaussian noise. These initial results highlight the potential of null stream methods in addressing key analysis challenges anticipated in ET-era searches.
The sensitivity of Gravitational Waves (GW) interferometers is limited by noise. Non-Gaussian transient noise artifacts, also known as glitches, are particularly challenging due to their similarity with astrophysical signals in the time and frequency domains; for this reason noise reduction and subtraction is one of the most important and challenging activities in GW research. Within the interTwin EU project we have developed GlitchFlow: a tool for modeling and generating glitches for GW interferometers using deep generative algorithms. GlitchFlow leverages the power of Convolutional Neural Networks (CNNs) to reconstruct the 2D spectrograms of glitches in the observational (strain) channel at Virgo, taking as input the spectrograms of the glitches in the data recorded by a small number of control sensors. Once a glitch has been generated, it is subtracted by the strain channel. The model has a noise-subtraction accuracy higher than 90% for Scattered Light glitches with Signal-To-Noise ratio of 6 or above. We aim to have the tool fully integrated into the Virgo data analysis pipelines by the next observing run.
Gravitational wave data are often contaminated by transient noise artifacts, called "glitches", which can mimic astrophysical signals and interfere with their detection. When represented in the time-frequency domain, glitches show peculiar morphologies, which allow their categorization into distinct families. As it is expected that glitches which share a similar morphology also share the same origin, this classification is very useful for detector characterization activities. Although this classification can be done manually by eye, Machine Learning methods have proved to be very powerful for these tasks. With this goal in mind, we present an automated classification pipeline for glitches from the Virgo gravitational wave detector, which classifies new glitches into the respective families and provides this information to the collaboration members. For each glitch, the pipeline takes as input the respective Omicron trigger. After the creation of the glitch spectrogram, it is fed to a Convolutional Neural Network, which was previously trained to achieve good classification accuracy. This neural network outputs the predicted glitch family. Then, these predictions are aggregated over a time period and plots which allow to study the population of glitches over that period and compare it with other periods. This automated pipeline provides timely feedback for detector characterization, supporting efforts to improve the detector and enhance gravitational wave detection.
This work explores feature selection for glitch classification in gravitational wave detectors, where transient noise events are grouped by their time-frequency morphology. Gravity Spy is a citizen-science project that provides a standard dataset built from four Q-transform views of glitches. Follow-up studies introduced attention-based multi-view models, transfer learning, and examined the effect of the Q-transform quality factor. These results point to spectrogram parameters as a key factor in model generalisation and bias. We run a random search over Q-transform and time window settings, train several computer vision models, and evaluate their behaviour using Virgo data.
The speed-up of parameter estimation is an active field of research in gravitational-wave data analysis. In this paper we present GP12, a deep-learning method that merges residual networks and normalising 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 colour channels in an RGB image amenable to be processed with residual networks. GP12 is trained on simulated data for BBH mergers obtained with the IMRPhenomPXHM 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, with the worst performances found in the estimation of the luminosity distance and of the chirp mass. Our simple and fast-trainable model can produce large amounts of posterior samples in a few seconds, complementing existing approaches with normalising 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 augmenting the number of trainable parameters to enhance expressivity).
Source inference for deterministic gravitational waves is a computationally demanding task in LISA. In a novel approach, we investigate the capability of an active-learning Gaussian Processes-based framework to learn the posterior for source parameters, using a very small number of likelihood evaluations, and without the need for pretraining. We benchmark our method against a cutting-edge nested sampler by separately injecting on LISA noisy data a white dwarf binary, a stellar-mass black hole binary, and a super-massive black hole binary. We show that we need $\mathcal{O}(10^{−2})$ fewer likelihood evaluations to achieve comparable inference accuracy (except for the solar-mass binary). For the case of a super-massive black-hole binary, we obtain a speed-up of $\mathcal{O}(10^2)$, i.e. from a few weeks to a few hours, showing great potential for rapid LISA parameter inference, especially for costly likelihoods, without the trade-off of approximations in the calculations.
We develop a framework for accelerated parameter estimation for lensed gravitational waves in the wave-optics regime. To model these effects, we evaluate the amplification factor using GLoW, an accurate code that computes the frequency-dependent amplification factor for generic lens models and arbitrary impact parameters depending on the lens configuration. To extract physical parameters from the lensed gravitational wave signals, we employ the DINGO code, a machine learning framework based on neural posterior estimation to evaluate the posterior probability. We validate the method using point lens. By applying this method we can efficiently perform parameter estimation on diffracted gravitational wave signals, recovering the mass of the lens and the impact parameter independently.
Wave-optics phenomena in gravitational lensing occur when the signal's wavelength is commensurate to the gravitational radius of the lens. Although potentially detectable in lensed gravitational waves, fast radio bursts and pulsars, accurate numerical predictions are challenging to compute. In this talk I will present recent advances on numerical methods to tackle this problem and their implementation in GLoW (Gravitational Lensing of Waves): an accurate, flexible and fast code able to to compute the amplification factor for generic lenses and impact parameters in O(1 ms) to O(10 ms).
In the Standard Model (SM), the electroweak phase transition – which marked the breaking of the $SU(2) \otimes U(1)$ symmetry through the Higgs mechanism – is predicted to have been a crossover. Several extensions of the SM, however, can realize it as a first-order phase transition (FOPT), which might lead to successful electroweak baryogenesis in the early universe.
A FOPT proceeds through the nucleation of bubbles of the broken Higgs phase, which collide and interact with the surrounding plasma. These interactions are known to be a substantial source of stochastic gravitational waves (GW), and they may be detectable by future space-borne GW interferometers such as LISA. Therefore, they would serve as a probe of fundamental physics complementary to future colliders.
In this talk, I will give a pedagogical introduction to the computation of phase transitions from a quantum field theory perspective. Then, I shall focus on how a strong FOPT can source a detectable GW background and what it can tell us about the underlying fundamental physics.
Self-interacting dark matter (SIDM) model with a density spike can potentially solve the final-parsec problem. Hence, we probe this model using the gravitational wave background data from pulsar timing array. We found that our results for the SIDM model parameters are consistent with the existing literature.
Two of the world's most advanced cosmological surveys, DESI (Dark Energy Spectroscopic Instrument) and DES (Dark Energy Survey), are challenging the LCDM model of cosmology. Their new results, recently released, in combination with CMB and other measurements, suggest a time-varying dark energy. In this talk, we will review the most recent DES and DESI results and their implications for the properties of the mysterious dark energy.
We present a study of scattered light noise in ground-based gravitational-wave detectors, based on advanced simulations for the Einstein Telescope (ET) and Virgo. Stray light mitigation remains a critical challenge for current interferometers, as the residual light can couple into the main beam and limit the sensitivity. For ET, we present updated noise estimations for both the high- and low-frequency interferometers, incorporating also the effect of beam misalignments, offsets and the presence of point absorbers. We additionally present the results for a 15 km arms L-shaped configuration. For the current generation of detectors, there is an active campaign to monitor and mitigate scattered light and, to this end, the installation of instrumented baffles is part of the Advanced Virgo Plus upgrade in time for the O5 observing run. They were originally envisaged to be suspended, mounted on new payloads and surrounding new larger end mirrors. We demonstrate using simulations that placing the instrumented baffles just beyond the cryotrap gate valve and in front of the end mirrors would be equally effective for monitoring scattered light inside the cavities, while minimizing contamination risks and potential interferences with the mirrors. Additionally, we provide a noise estimation that proves that these instrumented baffles will not compromise Virgo’s sensitivity. The installation of these instrumented baffles will serve as a technology demonstrator for an active monitoring strategy of scattered light for ET.
Accurate interferometric simulations are essential to understand and optimize the performance of current gravitational wave (GW) detectors, as well as to design next-generation observatories. Sim- ulations play a crucial role in improving detector sensitivity, testing new control strategies and devel- oping advanced noise mitigation techniques. Particularly as the global GW network sensitivity band moves toward lower frequencies and fainter astrophysical signals.
Finesse has been a key simulation tool for modeling interferometers in the gravitational wave community for over two decades, supporting detectors like LIGO, Virgo and KAGRA. Finesse3 builds on this foundation as a modern, open-source framework with a Python-based interface, symbolic pa- rameters and intuitive component connections. These features make it easier to create and share realistic models, supporting collaboration and reproducibility across the global GW community.
In this contribution, I will present the current status and applications of Finesse3, focusing in par- ticular on the modeling of Advanced Virgo. As part of this effort, we are developing updated inter- ferometer models that closely match experimental measurements and offer a deeper understanding of optical responses and control dynamics. These models are used to investigate unexplained noise sources by comparing simulated and measured transfer functions or other relevant figures of merit. This approach supports the systematic testing of hypotheses related to optical and mechanical cou- plings, helping to confirm or rule out possible origins.
Beyond current detectors, Finesse3 plays a central role in design studies for future gravitational wave facilities such as the Einstein Telescope (ET) and Cosmic Explorer. A growing number of studies now rely on Finesse3 to simulate complex spatial mode behavior, optical asymmetries, and realistic sensing and actuation chains. In particular, it is being used to investigate potential noise sources in ET, such as birefringence-induced phase shifts in the silicon test masses, which could impact sensitivity through polarization effects.
Finesse 3 is a collaborative project within the gravitational wave community, with core devel- opment, testing, training materials, tutorials, examples and documentation primarily carried out at Nikhef, in the Netherlands. As the ability to model and test complex detector behavior prior to im- plementation becomes increasingly important, tools like Finesse3 enable faster design cycles, sys- tematic model validation and shared understanding between modeling and commissioning teams. In the broader context of detector evolution, this strengthens our capacity to face the technological challenges of the coming decades in GW astronomy.
Accurate modeling of gravitational waves from precessing binary systems is essential for improving signal detection and parameter estimation in current and future detectors. Hybrid waveforms, which stitch together gravitational wave signals from different modeling approaches, provide a way to generate complete inspiral-merger-ringdown signals. While hybridization is well-established for aligned-spin systems, precession introduces additional complexities due to gauge ambiguities, frame-dependence, and spin dynamics.
In this work we present a general and robust methodology for constructing hybrid waveforms of precessing, quasi-circular binaries. Our approach relies on minimal assumptions about the merger waveform, employs the quadrupole-aligned (QA) frame to mitigate mode-mixing, and introduces a systematic alignment of waveform modes and coprecessing frames. We demonstrate the advantages of this strategy through detailed validation across a range of configurations. Our framework expands the applicability of hybridization techniques, facilitating more flexible waveform construction for parameter estimation, model calibration, and gravitational-wave data analysis.
The modeling of spin-precession and orbital eccentricity in gravitational-wave (GW) signals is crucial for understanding the astrophysical formation of compact binaries and ensuring that GW detector data is explored fully and without biases. However, describing these effects accurately and efficiently remains a challenge. In this talk, I will present pyEFPE, a frequency-domain post-Newtonian (PN) waveform model for precessing-eccentric inspirals. pyEFPE improves upon previous models by introducing analytical expressions for the eccentric amplitudes, enhancing the numerical stability of the spin-precession description, and adding recently derived post-Newtonian corrections, critical for accurately describing signals in GW detectors. Additionally, we introduce an amplitude interpolation scheme that improves computational efficiency and makes the model practical for data analysis. I will demonstrate these improvements by comparing pyEFPE against existing models and showcasing its application in parameter estimation studies.
The first three observing runs of the LIGO-Virgo-KAGRA (LVK) Collaboration have led to the detection of over 90 gravitational wave (GW) events from compact object binaries, but understanding their formation channels still remains an open question in GW astrophysics. While most inspiraling binaries detected by ground-based detectors likely form through isolated binary evolution and are expected to circularize before entering the detector band, other formation channels may preserve significant orbital eccentricity. Detecting eccentricity in GW signals will provide crucial insights into binary formation and evolution, which requires accurate waveform models for robust parameter estimation.
We present IMRPhenomTEHM, the first time-domain eccentric multipolar phenomenological waveform model for aligned-spin binaries with two eccentric parameters. Built upon the quasi-circular IMRPhenomTHM model, IMRPhenomTEHM includes post-Newtonian eccentric and spin corrections up to third order, providing an accurate and computationally efficient full inspiral-merger-ringdown description. Using this model, we perform a systematic reanalysis of binary black hole and neutron star–black hole mergers from the first three LVK observing runs, focusing on events identified as potentially eccentric, precessing, or significantly asymmetric in mass. Our results demonstrate the efficiency and accuracy of IMRPhenomTEHM, enabling the first eccentric study using standard parameter estimation techniques for quasi-circular binaries—without relying on resampling or machine learning methods. We identify events with a strong preference for the eccentric hypothesis, highlighting the importance of eccentric waveform modeling in GW astrophysics to avoid biases in parameter estimation.
A non-negligible population of binary black holes (BBHs) forming dynamically in active astrophysical environments is predicted to radiate graviational waves (GWs)
in the frequency band of ground-based LIGO, Virgo and KAGRA (LVK) GW detectors. Thus, strong evidence for orbital eccentricity in GW detections will play a pivotal role in unveiling the astrophysical origins of BBH mergers. Despite recent progress on modelling GWs from eccentric binaries, GW data analysis of BBH mergers is still limited to systems on quasi-circular orbits, due to the lack of waveform models that accurately predict the signals of eccentric BBH mergers in a computationally efficient manner. In this work, we present an inspiral-merger-ringdown phenomenological waveform model in frequency domain for binary black holes with non-precessing spins in ellitpical orbits. Eccentric corrections are incorporated in the waveform multipoles, and validated against eccentric numerical relativity waveforms finding unfaithfulness below 2%. Additionally, we perform parameter estimation runs on GW events detected by the LVK and demonstrate that the computational efficiency of the model enables routine GW data analysis and systematic studies of large populations of generic BBHs.
We address the challenge to evaluate the response of the Laser Interferometer Space Antenna (LISA) in an accurate and computationally efficient way.
Without approximations, the full LISA response is computationally expensive and traditional approaches, such as the long-wavelength approximation, accelerate the response calculation at the cost of reducing accuracy at high frequencies. Here we introduce a novel hybrid time-domain response for LISA, that balances computational efficiency and accuracy across the binary’s evolution. Our method implements a fast low-frequency approximation using central finite differences during the early inspiral—where most binaries spend most of the time in the sensitive frequency band of LISA —while reserving the computationally intensive full-response calculations for the late inspiral, merger, and ringdown phases. This hybrid approach supports CPU and GPU implementations, TDI generations 1.5 and 2.0, and flexible time-delay complexity, and has potential to accelerate parts of the global fit, and reduce power consumption.
As an application we present parameter estimation results using state-of-the-art phenomenological waveform models for LISA, which include orbital eccentricity, and the oscillatory and memory parts of the (2,0) spherical harmonic. Additionally, we evaluate the low-frequency response efficacy in early-warning pipelines by performing inspiral-only Bayesian inference.
Gravitational waves from binary black hole mergers encode astrophysical information in multiple spherical harmonic modes. While dominant and subdominant modes have been extensively studied, the (l=2, m=0) mode has only recently been incorporated into waveform models.
We present a phenomenological waveform model for the (2,0) mode, capturing its two components: the non-oscillatory displacement memory and the quasi-normal ringdown. Incorporating this mode refines waveform accuracy, especially in the merger and post-merger regimes. Additionally, the displacement memory effect, which is mainly contained in this mode, remains undetected and this waveform model can be used to study its detectability. The model is first developed for aligned-spin binaries and then extended to precession, expanding its applicability across a wider parameter space.
Our implementation builds upon the computationally efficient IMRPhenomTHM and IMRPhenomTPHM models, which are optimal for Bayesian parameter estimation. Through extensive studies, we quantify the biases introduced when this mode is omitted, demonstrating its crucial role in accurately recovering individual mass and spin components and constraining the distance-inclination degeneracy. We present results for the Advanced LIGO A# sensitivity and Einstein Telescope.
Targeting the modeling of generic waveforms, we also present preliminary results regarding the (2,0) mode in eccentric systems.
By incorporating this missing piece of the gravitational wave signal, our work not only enhances the precision of parameter estimation, but also takes a step forward the possible detection of the displacement memory.
We present IMRPhenomXHM_NSBH, a new phenomenological model for graviational-wave (GW) emission from neutron star–black hole (NSBH) coalescences. This model features a newly developed numerical relativity (NR)-calibrated amplitude prescription incorporating tidal contributions up to 7.5PN order, a phasing model tuned to NR simulations incorporating dynamical tidal effects (NRTidalv3), and the inclusion of higher GW strain harmonics also including tidal corrections calibrated to numerical relativity.
This model represents a significant improvement over previous phenomenological GW models for NSBHs, providing smooth and well-behaved waveforms across the parameter space with enhanced physical fidelity while introducing minimal computational overhead compared to its baseline binary black hole model, IMRPhenomXHM. As a result, it is the fastest NSBH model including higher-order harmonics, with its (2,2) mode being roughly an order of magnitude faster than previous NSBH models for this mode.
Finally, we discuss the prospects of extending the model to incorporate spin-precession and orbital eccentricity effects.
Since the first detection of a binary neutron star system, GW170817, the number of compact binary systems involving neutron stars observed by the LVK network has continued to grow. The tidal deformability of neutron stars influences the gravitational waves emitted during inspiral phase, making these effects observable. Consequently, waveform models used to analyze such signals must incorporate tidal interactions. In these models, the inspiral phase is typically described using post-Newtonian theory. Accurately modeling neutron star deformability is therefore essential. In this talk, I will present the post-Newtonian formalism, with a focus on its application to the effective description of tidal effects, and discuss recent developments in the field.
Zerain, basque restaurant
One of the longest-standing science targets of gravitational-wave detectors are spinning deformed neutron stars. While exceedingly weak and hence still eluding detection, "continuous waves" from such individual objects will bring a new regime of gravitational astrophysics where we can keep observing the same source over and over and perform rich multi-messenger studies. They promise an unprecedented probe into the structure, interior, and dynamics of the densest stellar objects in the Universe. This talk will summarise the first results from searches for known pulsars in the O4a observing run and provide an overview of other ongoing LIGO-Virgo-KAGRA searches.
Neutron stars are expected to produce continuous gravitational waves arising due to precession and, crucially, deformations in the crust, also called mountains. The microscopical resistance to breaking used in ellipticity calculations is obtained from Molecular Dynamics simulations. In this talk I will show our results from our simulations, that incorporate finite size and magnetic fields. I will explain how non-trivial plastic deformations produced by the interplay between finite size and magnetic fields affect our understanding of the elasticity and breaking properties of the crust, and what limits on ellipticity and amplitude does it put, with eyes set on future gravitational wave detection missions.
While standard analyses of black-hole mergers assume these happen in vacuum, it is expected that these will happen in dense environments. This is particularly true for mergers involving component black holes populating the so-called pair-instability supernova gap, which should form hierarchically as the result of a previous merger in an environment dense enough to retain the remnant black hole. In this talk we will present a fully Bayesian and self-consistent framework to identify the parameters of the potential ancestors of LIGO-Virgo-KAGRA black holes as well as the escape velocity of the corresponding environments. In turn, this allows us to assign posterior probabilities both to the "generation" to which these black-holes belong and to the nature of the corresponding environment. We will showcase the application of these method to existing O1-O3 events.
Black holes and neutron stars are the leading candidates for the sources of currently observed gravitational waves. However, exotic compact objects have been proposed as potential alternatives, capable of mimicking the gravitational-wave signatures of these standard sources. Among them, Proca stars—Bose-Einstein condensates of complex vector ultralight bosons—have attracted attention due to their ability to reproduce features of certain LIGO–Virgo–KAGRA events. We use a Bayesian mixture model to analyze the consistency of boson-mass estimates across multiple events. We find that even when no individual event provides conclusive evidence for a Proca-star merger, a consistent boson-mass estimates across events can yield strong cumulative evidence for their existence. This approach allows us to infer both the common boson mass and the fraction of Proca-star mergers hidden within a given dataset.
A mock data study suggests that 5–9 future observations of similar events to those observed to date could decisively confirm a population of Proca-star mergers—if the boson masses align. This method opens a new path to detect exotic compact objects in next-generation gravitational-wave catalogs.
Binary supermassive black holes are expected to form and merge at galactic centers. Their dynamics encode information on their formation and environments, and can be observed by low frequency gravitational-wave detectors, potentially offering a multi-messenger source. Despite this interest, no close-by (sub parsec) binaries have been confidently identified yet.
I will describe a new method to identify and characterize supermassive binaries in non-active galactic nuclei by the gravitational lensing of individual bright stars, located behind them in the host galaxy. The motion of `caustics' - regions where point-like sources become infinitely bright - due to SMBH orbit and inspiral leads to quasi-periodic lensing of starlight: The extreme lensing magnification of individual stars produces a significant variation in the host galaxies' luminosity; its lightcurve traces the orbit of the binary system and its evolution, analogous to the waveforms recorded by gravitational-wave detectors. I will discuss the phenomenology of quasi-periodic lensing by binary SMBHs, its potential for discovering binary systems and the prospects for multi-messenger observations.
The yet-to-be-detected gravitational wave signal from core-collapse supernovae is expected to be dominated by oscillation modes of the newly born proto-neutron star (PNS). I am going to present a new general relativistic framework for computing the oscillation modes of a PNS, including, for the first time, an accretion flow and a surrounding stalled accretion shock. The oscillations can be described by a system of partial differential equations, which can be solved as an eigenvalue problem. In that frame, the eigenvalues are the characteristic frequencies of the oscillation modes. In this work, I have considered two different schemes, spectral methods and a machine learning method based on physics-informed-neural-networks, as the eigenvalue solver. By doing so, we can explore the PNS oscillation modes and especially those related to the standing-accretion-shock instability (SASI). In that way, we include some of the missing ingredients towards a more realistic PNS asteroseismology.
The accurate modelling of neutron star oscillations is essential as we prepare for the next generation of gravitational-wave detectors, which will be able to probe the rich astrophysical content of post-merger signals. In this talk, I will present recent updates to ROXAS, a spectral code to numerically simulate the dynamical evolution of perturbed rotating neutron stars. ROXAS uses a well-balanced formulation of the hydrodynamical equations within the conformal flatness approximation, and extracts the emitted gravitational waves. Current work focuses on extending the code to support differentially rotating stars, a key step towards a more realistic modelling of post-merger remnants.
A deep correspondence exists between the quasi-normal modes (QNMs) of ultra-compact objects and their observable gravitational lensing features, such as photon rings and shadows. In the era of multi-messenger astrophysics, a comprehensive understanding of this relation is crucial for extracting fundamental spacetime properties. We present how we can use this correspondence to test beyond General Relativity theories. We present a methodology using simulated images of exotic compact object, analyzing their gravitational lensing observables, such as the shadow and photon ring properties, that directly map to their predicted QNM spectra. This approach offers a powerful, complementary tool for doing fundamental physics in the gravitational waves and black hole imaging communities.
Blazars show variability across the entire electromagnetic spectrum and over a wide range of timescales. In some cases, characteristic emission patterns have been observed, such as the multi-year modulation detected in PG 1553+113. Quasi-periodic oscillations (QPOs) can arise from various astrophysical mechanisms, including jet precession, accretion disk instabilities, and supermassive binary black holes (SMBBHs). While the latter is a particularly compelling possibility, potentially linking galaxy mergers and gravitational wave progenitors to jet physics, the other scenarios also offer valuable information about the physical processes governing blazar variability, which remain poorly understood. In this work, we apply Singular Spectrum Analysis (SSA) to a large sample of Fermi-LAT blazars to systematically search for QPOs. SSA decomposes the signal into trend, oscillatory, and noise components, allowing robust detection of periodic features and construction of forecasting models. We identify 46 QPO candidates, including 25 previously unreported, representing the largest sample to date and enabling the first steps toward population-level statistical analyses of these phenomena. By identifying promising candidates and exploring their relevance within the broader context of multi-messenger astrophysics, this study establishes a foundation for future investigations into the physical origins of blazar variability and the potential connection to gravitational wave sources.
Pulsar Timing Array (PTA) observations provide strong evidence for a stochastic gravitational wave background (SGWB), potentially originating from astrophysical sources or early universe phenomena. If the SGWB is cosmological, our relative motion with respect to the SGWB rest frame induces a kinematic anisotropy, which could dominate over intrinsic anisotropies, similar to the cosmic microwave background dipole. We studied PTA sensitivity to this dipole and forecasted its detectability with future experiments like SKA. Additionally, astrometry is a complementary method to PTA observations, and by cross-correlating astrometric and PTA data, constraints on SGWB properties can be improved, aiding in determining its origin.