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We obtain the full set of tidal Love numbers of non-rotating black holes in an effective field theory extension of general relativity. We achieve our results using a recently introduced modified Teukolsky equation that describes the perturbations of black holes in this theory. We show how to identify the Love numbers and their beta functions in a systematic and gauge invariant way, applying analytic continuation on the angular number $\ell$ when necessary. We observe that there are three types of Love numbers: electric, magnetic, and a ``mixing'' type, associated to parity-breaking theories, that we identify here for the first time. The modified Teukolsky equation proves to be very useful as it allows us to obtain all the different Love numbers in a unified framework. We compare our results with previous literature that utilized the Regge-Wheeler-Zerilli equations to compute Love numbers, finding perfect agreement. The method introduced here paves the way towards the computation of Love numbers of rotating black holes beyond general relativity., Comment: 28 pages, 1 table, no figures

Large language models (LLMs) have demonstrated vast capabilities on generative tasks in recent years, yet they struggle with guaranteeing the factual correctness of the generated content. This makes these models unreliable in realistic situations where factually accurate responses are expected. In this paper, we propose FactReasoner, a new factuality assessor that relies on probabilistic reasoning to assess the factuality of a long-form generated response. Specifically, FactReasoner decomposes the response into atomic units, retrieves relevant contexts for them from an external knowledge source, and constructs a joint probability distribution over the atoms and contexts using probabilistic encodings of the logical relationships (entailment, contradiction) between the textual utterances corresponding to the atoms and contexts. FactReasoner then computes the posterior probability of whether atomic units in the response are supported by the retrieved contexts. Our experiments on labeled and unlabeled benchmark datasets demonstrate clearly that FactReasoner improves considerably over state-of-the-art prompt-based approaches in terms of both factual precision and recall.

Satellite communication systems are shifting to higher frequency bands (Ka, Q/V, W) to support more data-intensive services and alleviate spectral congestion. However, the use of Extremely High Frequencies, typically above 20 GHz, causes significant tropospheric impairments, such as rain attenuation, which can causes system outages. To mitigate these effects, Smart Gateway Diversity (SGD) has emerged as a promising method for maximizing feeder link availability through an adaptive site diversity scheme. However, implementing such technique requires a decision-making policy to dynamically select the optimal set of gateways and prevent outages. This paper introduces AIRIS2, a deep learning algorithm that anticipates short-term rain events from rain attenuation measurement to enable efficient gateway switching. The approach is validated from five years of measured time series collected at Ka and Q/V bands at various sites and climatic conditions.

Solar energetic particles such as electrons can be accelerated to mildly-relativistic velocities in the solar corona. These electrons travel through the turbulent corona generating radio waves, which are then severely affected by scattering. The physical interpretation of the discrepancies between the actual and observed radio sources is still subject to debate. Here, we use radio emission observed by an unprecedented total of five spacecraft, to track the path of radio sources from the low corona to the inner heliosphere (15-75 R$_{\odot}$) generated during a solar event on 4 December 2021. In this study we use the Bayesian multilateration technique known as BELLA to track the apparent path of radio sources observed by Parker Solar Probe, STEREO A, Wind, Solar Orbiter and Mars Express. To validate the accuracy of the tracked path, we used Nan\c{c}ay Radioheliograph interferometric imaging at 150 MHz, which was found to agree with the estimated footpoints predicted by BELLA. We also further validated our results using ACE in-situ measurements. We found that the apparent radio sources followed the path of a Parker Spiral, with an associated solar wind velocity of approximately 493 km s-1 (consistent with the corresponding speed observed at 1 au at the relevant longitude) and connected to 75$^\circ$ longitude East at the solar surface. Finally, we made quantitative estimates of the scattering of radio waves that were found to be in good agreement with contemporary models of scattering. This work shows conclusive evidence that the disputed cause of the widely observed `higher than expected' electron densities at interplanetary distances is due to radio wave scattering, and provides a more detailed understanding of the propagation of radio waves emitted near the local plasma frequency in turbulent plasmas., Comment: 13 Pages, 9 Figures, 2 Appendix figures

Context. (469219) Kamo`oalewa is a small near-Earth asteroid, which is currently a quasi-satellite of the Earth. Lightcurve measurements also reveal a rotation period of only about 30 minutes. This asteroid has been selected as the target of the Tianwen-2 sample-return mission of the China National Space Administration. Aims. The first goal of this paper is to observe and improve the orbit determination of (469219) Kamo`oalewa, and better determine the Yarkovsky effect acting on it. The second goal is to estimate the thermal inertia of the asteroid, taking advantage of an improved Yarkovsky effect determination. Methods. Our observational campaign imaged the asteroid from the Loiano Astronomical Station and from the Calar Alto Observatory, in March 2024. We also accurately re-measured a precovery detection from the Sloan Digital Sky Survey from 2004. New astrometry was later used in a 7-dimensional orbit determination, aimed at estimating both the orbital elements and the Yarkovsky effect. Thermal inertia is later studied by using the ASTERIA, a new method that is suitable to estimate thermal inertia of small asteroids. Results. We detected a semi-major axis drift of $(-67.35 \pm 4.70) \times 10^{-4}$ au My$^{-1}$ due to the Yarkovsky effect, with a high signal-to-noise ratio of 14. The new orbit solution also significantly reduced the position uncertainty for the arrival of the Tianwen-2 spacecraft. By using different models for the physical parameters of Kamo`oalewa, the ASTERIA model estimated the thermal inertia at $\Gamma = 150^{+90}_{-45}$ J m$^{-2}$ K$^{-1}$ s$^{-1/2}$ or $\Gamma = 181^{+95}_{-60}$ J m$^{-2}$ K$^{-1}$ s$^{-1/2}$., Comment: Accepted for publication in Astronomy & Astrophysics

The integration of large language models (LLMs) on low-power edge devices such as Raspberry Pi, known as edge language models (ELMs), has introduced opportunities for more personalized, secure, and low-latency language intelligence that is accessible to all. However, the resource constraints inherent in edge devices and the lack of robust ethical safeguards in language models raise significant concerns about fairness, accountability, and transparency in model output generation. This paper conducts a comparative analysis of text-based bias across language model deployments on edge, cloud, and desktop environments, aiming to evaluate how deployment settings influence model fairness. Specifically, we examined an optimized Llama-2 model running on a Raspberry Pi 4; GPT 4o-mini, Gemini-1.5-flash, and Grok-beta models running on cloud servers; and Gemma2 and Mistral models running on a MacOS desktop machine. Our results demonstrate that Llama-2 running on Raspberry Pi 4 is 43.23% and 21.89% more prone to showing bias over time compared to models running on the desktop and cloud-based environments. We also propose the implementation of a feedback loop, a mechanism that iteratively adjusts model behavior based on previous outputs, where predefined constraint weights are applied layer-by-layer during inference, allowing the model to correct bias patterns, resulting in 79.28% reduction in model bias., Comment: Accepted as a full paper by the 2025 EDGE AI FOUNDATION Austin

This article presents a review about the main CERN n\_TOF contributions to the field of neutron-capture experiments of interest for $s$-process nucleosynthesis studies over the last 25 years, with special focus on the measurement of radioactive isotopes. A few recent capture experiments on stable isotopes of astrophysical interest are also discussed. Results on $s$-process branching nuclei are appropriate to illustrate how advances in detection systems and upgrades in the facility have enabled increasingly challenging experiments and, as a consequence, have led to a better understanding and modeling of the $s$-process mechanism of nucleosynthesis. New endeavors combining radioactive-ion beams from ISOLDE for the production of radioisotopically pure samples for activation experiments at the new NEAR facility at n\_TOF are briefly discussed. On the basis of these new exciting results, also current limitations of state-of-the-art TOF and activation techniques will be depicted, thereby showing the pressing need for further upgrades and enhancements on both facilities and detection systems. A brief account of the potential technique based on inverse kinematics for direct neutron-capture measurements is also presented., Comment: submitted to Eur. Phys. Jour. Topical Collection

Josephson-junction interferometry has played a pivotal role in uncovering unconventional superconductivity in the cuprates. Using a Ginzburg-Landau-like approach, we generalize previous results to the genuine multi-gap case. Thus, we show that fractional flux oscillations of the Josephson critical current can arise as a direct consequence of multi-gap superconductivity. These oscillations reveal key information about the underlying superconducting states, including the unconventional $s_\pm$-wave state. Thus, our findings suggest new phase-sensitive experiments to characterize the Cooper pairing of new emerging superconductors such as the nickelates., Comment: 4 pages, 3 figures

Asteroid 2024 XA$_1$ was discovered on 3 December 2024 at 05:54 UTC by the Bok telescope in Kitt Peak, Arizona, and impacted Earth about 10 hours later over a remote area of the Sakha Republic (Russia). The estimated size of the object was about one meter, and the atmospheric entry produced a bright fireball that was captured by a webcam and several eyewitnesses. The first impact alert was issued at 07:50 UTC by the Meerkat Asteroid Guard of the European Space Agency, which triggered subsequent follow-up observations that confirmed both the object to be real and the occurrence of the impact with Earth. Here we present the operations and results from the NEO Coordination Centre (NEOCC) upon the impact event. Because the entry likely dropped meteorites on the ground, we also estimate the possible strewn fields for future meteorite search campaigns., Comment: Accepted for publication on Icarus

On 13 March 2023, when the Parker Solar Probe was situated on the far side of the Sun as seen from Earth, a large solar eruption took place creating a strong solar energetic particle (SEP) event observed by multiple spacecraft (S/C). The energetic event was observed at six well-separated locations: Parker Solar Probe, Solar Orbiter, BepiColombo, STEREO~A, near-Earth S/C, and MAVEN. An in-situ shock crossing and a related energetic storm particle (ESP) event were observed at all inner-heliospheric S/C, suggesting that the interplanetary coronal mass ejection (CME)-driven shock extended all around the Sun. However, the solar event was accompanied by a series of pre-event CMEs. We aim to characterize this extreme widespread SEP event and to provide an explanation for the unusual observation of a circumsolar interplanetary shock and corresponding circumsolar ESP event. We analyse data from seven space missions to characterize the solar eruption at the Sun, the energetic particle event, and the interplanetary context at each observer location as well as the magnetic connectivity of each observer to the Sun. We employ magnetohydrodynamic simulations of the solar wind in which we inject various CMEs that were launched before as well as contemporaneously with the solar eruption under study. In particular, we test two different scenarios that could have produced the observed global ESP event: 1) a single circumsolar blast-wave-like shock launched by the associated solar eruption, and 2) the combination of multiple CMEs driving shocks into different directions. By comparing the simulations of the two scenarios with observations we find that both settings are able to explain the observations. However, the blast-wave scenario performs slightly better in terms of the predicted shock arrival times at the various observers.

The transparency principle of the General Data Protection Regulation (GDPR) requires data processing information to be clear, precise, and accessible. While language models show promise in this context, their probabilistic nature complicates truthfulness and comprehensibility. This paper examines state-of-the-art Retrieval Augmented Generation (RAG) systems enhanced with alignment techniques to fulfill GDPR obligations. We evaluate RAG systems incorporating an alignment module like Rewindable Auto-regressive Inference (RAIN) and our proposed multidimensional extension, MultiRAIN, using a Privacy Q&A dataset. Responses are optimized for preciseness and comprehensibility and are assessed through 21 metrics, including deterministic and large language model-based evaluations. Our results show that RAG systems with an alignment module outperform baseline RAG systems on most metrics, though none fully match human answers. Principal component analysis of the results reveals complex interactions between metrics, highlighting the need to refine metrics. This study provides a foundation for integrating advanced natural language processing systems into legal compliance frameworks., Comment: Submitted to ARR

Altermagnets form a subclass of collinear antiferromagnets with spin-split electronic states. Here, we introduce the Ruddlesden-Popper chromates Sr$_{n+1}$Cr$_n$O$_{3n+1}$ (including the perovskite SrCrO$_3$) as candidates for antiferromagnetic materials in which altermagnetism emerges from spontaneous orbital ordering, rather than crystal symmetry. Using first-principles calculations, we identify a layer-dependent spin splitting of the electronic states, driven by the interplay between spin and orbital order. We show that if the spin and orbital orders align in adjacent layers, the system exhibits a net spin splitting, and thus altermagnetism. In contrast, if either the spin or the orbital order is reversed in adjacent layers, we observe an anti-altermagnetic state where layerwise compensation leads to net zero spin splitting. We find that for odd $n$, altermagnetic and anti-altermagnetic phases can coexist, whereas for even $n$ and in the perovskite limit, the system remains strictly anti-altermagnetic. In both cases, increasing $n$ favors metallicity. Finally, we indicate that in odd $n$ compounds, epitaxial strain can promote the altermagnetic phase., Comment: 5 pages, 4 figures + supplement

The $\beta$-delayed neutron emission in the $^{85, 86}$As $\beta$-decays has been measured at the Ion Guide Isotope Separator On Line facility of the Accelerator Laboratory of the University of Jyv\"askyl\"a. The complete $\beta$-decays have been studied with a complex setup that consists of a plastic scintillator for $\beta$-particles, MONSTER -- the MOdular Neutron time-of-flight SpectromeTER -- for neutrons, and a high-purity germanium and four LaBr$_3$ crystals for $\gamma$-rays. The $\beta$-delayed neutron energy distributions have been determined by unfolding the time-of-flight spectra with an innovative methodology based on the iterative Bayesian unfolding method and accurate Monte Carlo simulations. The results obtained for $^{85}$As are in excellent agreement with the existing evaluated data, validating the proposed methodology. In the case of $^{86}$As, a stronger neutron intensity at higher energies than previously predicted is discovered., Comment: 10 pages, 11 figures, to be submitted to Physical Review C

This article provides a systematic up-to-date survey of automatic summarization techniques, datasets, models, and evaluation methods in the legal domain. Through specific source selection criteria, we thoroughly review over 120 papers spanning the modern `transformer' era of natural language processing (NLP), thus filling a gap in existing systematic surveys on the matter. We present existing research along several axes and discuss trends, challenges, and opportunities for future research.

Chemical reactions resulting from the ingress of carbonates into the cement matrix modify the properties of its pore solution, as well as its pore distribution and size. These changes lead to corrosion of the steel in reinforced concrete. The nature of conventional testing for the estimation of carbonation in cement-based materials is time-consuming and destructive. This paper presents a set of non-destructive ultrasound-based indexes, obtained solely from non-linear and linear analyses of ultrasonic signals, for measuring the carbonation of Portland cement pastes. Class 30RS cement pastes with three water/cement ratios by weight (0.4, 0.5, and 0.6) were considered. Carbonation was carried out for 120 days with a constant CO2 level of 4% by volume under controlled temperature and humidity, considering a unidirectional carbonation, parallel to the longitudinal axis of the samples. The level of carbonation was validated by FTIR measurements. From these analyses, different indexes with high correlation were obtained, estimated only from the ultrasonic signals and as a function of the days of exposure to carbonation, as well as of the percentage of carbonation. Further study is required for the evaluation of the reliability of these promising indexes for the determination of carbonation in cement-based materials.

We propose a new architecture for 3D information systems that takes advantage of the inherent parallelism of the GPUs. This new solution structures information as thematic layers, allowing a level of detail independent of the resolution of the meshes. Previous proposals of layer based systems present issues, both in terms of performance and storage, due to the use of octrees to index information. In contrast, our approach employs two-dimensional textures, highly efficient in GPU, to store and index information. In this article we describe this architecture and detail the GPU algorithms required to edit these layers. Finally, we present a performance comparison of our approach against an octree based system., Comment: This is a preprint version of the article. For the full version, please follow this link: https://www.sciencedirect.com/science/article/abs/pii/S1296207418307167?via%3Dihub

The advent of Generative Artificial Intelligence (GenAI) has brought a significant change to our society. GenAI can be applied across numerous fields, with particular relevance in cybersecurity. Among the various areas of application, its use in penetration testing (pentesting) or ethical hacking processes is of special interest. In this paper, we have analyzed the potential of leading generic-purpose GenAI tools-Claude Opus, GPT-4 from ChatGPT, and Copilot-in augmenting the penetration testing process as defined by the Penetration Testing Execution Standard (PTES). Our analysis involved evaluating each tool across all PTES phases within a controlled virtualized environment. The findings reveal that, while these tools cannot fully automate the pentesting process, they provide substantial support by enhancing efficiency and effectiveness in specific tasks. Notably, all tools demonstrated utility; however, Claude Opus consistently outperformed the others in our experimental scenarios.

Purpose: This work addresses the detection of Helicobacter pylori (H. pylori) in histological images with immunohistochemical staining. This analysis is a time demanding task, currently done by an expert pathologist that visually inspects the samples. Given the effort required to localise the pathogen in images, a limited number of annotations might be available in an initial setting. Our goal is to design an approach that, using a limited set of annotations, is capable of obtaining results good enough to be used as a support tool. Methods: We propose to use autoencoders to learn the latent patterns of healthy patches and formulate a specific measure of the reconstruction error of the image in HSV space. ROC analysis is used to set the optimal threshold of this measure and the percentage of positive patches in a sample that determines the presence of H. pylori. Results: Our method has been tested on an own database of 245 Whole Slide Images (WSI) having 117 cases without H. pylori and different density of the bacteria in the remaining ones. The database has 1211 annotated patches, with only 163 positive patches. This dataset of positive annotations was used to train a baseline thresholding and an SVM using the features of a pre-trained RedNet18 and ViT models. A 10-fold cross-validation shows that our method has better performance with 91% accuracy, 86% sensitivity, 96% specificity and 0.97 AUC in the diagnosis of H. pylori. Conclusion: Unlike classification approaches, our shallow autoencoder with threshold adaptation for the detection of anomalous staining is able to achieve competitive results with a limited set of annotated data. This initial approach is good enough to be used as a guide for fast annotation of infected patches.

As AI-based decision-makers increasingly influence human lives, it is a growing concern that their decisions are often unfair or biased with respect to people's sensitive attributes, such as gender and race. Most existing bias prevention measures provide probabilistic fairness guarantees in the long run, and it is possible that the decisions are biased on specific instances of short decision sequences. We introduce fairness shielding, where a symbolic decision-maker -- the fairness shield -- continuously monitors the sequence of decisions of another deployed black-box decision-maker, and makes interventions so that a given fairness criterion is met while the total intervention costs are minimized. We present four different algorithms for computing fairness shields, among which one guarantees fairness over fixed horizons, and three guarantee fairness periodically after fixed intervals. Given a distribution over future decisions and their intervention costs, our algorithms solve different instances of bounded-horizon optimal control problems with different levels of computational costs and optimality guarantees. Our empirical evaluation demonstrates the effectiveness of these shields in ensuring fairness while maintaining cost efficiency across various scenarios., Comment: To appear in AAAI 2025

Quantization of Deep Neural Network (DNN) activations is a commonly used technique to reduce compute and memory demands during DNN inference, which can be particularly beneficial on resource-constrained devices. To achieve high accuracy, existing methods for quantizing activations rely on complex mathematical computations or perform extensive searches for the best hyper-parameters. However, these expensive operations are impractical on devices with limited computation capabilities, memory capacities, and energy budgets. Furthermore, many existing methods do not focus on sub-6-bit (or deep) quantization. To fill these gaps, in this paper we propose DQA (Deep Quantization of DNN Activations), a new method that focuses on sub-6-bit quantization of activations and leverages simple shifting-based operations and Huffman coding to be efficient and achieve high accuracy. We evaluate DQA with 3, 4, and 5-bit quantization levels and three different DNN models for two different tasks, image classification and image segmentation, on two different datasets. DQA shows significantly better accuracy (up to 29.28%) compared to the direct quantization method and the state-of-the-art NoisyQuant for sub-6-bit quantization., Comment: Accepted to Second Workshop on Machine Learning with New Compute Paradigms at NeurIPS 2024 (MLNCP 2024)

We establish that regular black holes can form from gravitational collapse. Our model builds on a recent construction that realized regular black holes as exact solutions to purely gravitational theories that incorporate an infinite tower of higher curvature corrections in any dimension $D \ge 5$ [arXiv:2403.04827]. We identify a two-dimensional Horndeski theory that captures the spherically symmetric dynamics of the theories in question and use this to prove a Birkhoff theorem and obtain the generalized Israel junction conditions. Armed with these tools, we consider the collapse of thin shells of pressureless matter, showing that this leads generically to the formation of regular black holes. The interior dynamics we uncover is intricate, consisting of shell bounces and white hole explosions into a new universe. The result is that regular black holes are the unique spherically symmetric solutions of the corresponding theories and also the endpoint of gravitational collapse of matter. Along the way, we establish evidence for a solution-independent upper bound on the curvature, suggestive of Markov's limiting curvature hypothesis., Comment: 26 pages, 5 figures

We study dynamical gravitational collapse in a theory with an infinite tower of higher-derivative corrections to the Einstein-Hilbert action and we show that, under very general conditions, it leads to the formation of regular black holes. Our results are facilitated by the use of a class of theories that possess second-order equations on spherically symmetric metrics, but which are general enough to provide a basis for the gravitational effective action. We analytically solve the collapse of a thin shell of dust and show that it inevitably experiences a bounce at small radius and that its motion can be extended to arbitrary proper time. The collapse of the shell always gives rise to a singularity-free, geodesically complete spacetime that contains horizons if the total mass is above a critical value. In that case, the shell bounces into a new universe through a white hole explosion. Our construction provides, to the best of our knowlege, the first fully dynamical description of formation of regular black holes, and it suggests that higher-derivative corrections may be the most natural way to resolve the singularities of Einstein's theory., Comment: 5 pages + appendices; 2 figures

The design of fast reactors burning MOX fuels requires accurate capture and fission cross sections. For the particular case of neutron capture on 242Pu, the NEA recommends that an accuracy of 8-12% should be achieved in the fast energy region (2 keV-500 keV) compared to their estimation of 35% for the current uncertainty. Integral irradiation experiments suggest that the evaluated cross section of the JEFF-3.1 library overestimates the 242Pu(n,{\gamma}) cross section by 14% in the range between 1 keV and 1 MeV. In addition, the last measurement at LANSCE reported a systematic reduction of 20-30% in the 1-40 keV range relative to the evaluated libraries and previous data sets. In the present work this cross section has been determined up to 600 keV in order to solve the mentioned discrepancies. A 242Pu target of 95(4) mg enriched to 99.959% was irradiated at the n TOF-EAR1 facility at CERN. The capture cross section of 242Pu has been obtained between 1 and 600 keV with a systematic uncertainty (dominated by background subtraction) between 8 and 12%, reducing the current uncertainties of 35% and achieving the accuracy requested by the NEA in a large energy range. The shape of the cross section has been analyzed in terms of average resonance parameters using the FITACS code as implemented in SAMMY, yielding results compatible with our recent analysis of the resolved resonance region.The results are in good agreement with the data of Wisshak and K\"appeler and on average 10-14% below JEFF-3.2 from 1 to 250 keV, which helps to achieve consistency between integral experiments and cross section data. At higher energies our results show a reasonable agreement within uncertainties with both ENDF/B-VII.1 and JEFF-3.2. Our results indicate that the last experiment from DANCE underestimates the capture cross section of 242Pu by as much as 40% above a few keV., Comment: 20 pages, 19 figures, submitted to Phys. Rev. C

Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called $\gamma$-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps toward such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setup at CERN n\_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C$_{6}$D$_{6}$ detectors, and one LaCl$_{3}$(Ce) detector. The performance of these detection systems is compared using $^{93}$Nb($n$,$\gamma$) data. We also developed a detailed \textsc{Geant4} Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a $\gamma$ detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigaged experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability.

Quasinormal modes of rapidly rotating black holes were recently computed in a generic effective-field-theory extension of general relativity with higher-derivative corrections. We exploit this breakthrough to perform the most complete search for signatures of new physics in black hole spectra to date. We construct a template that describes the post-merger gravitational-wave emission in comparable-mass binary black hole mergers at current detector sensitivity, notably including isospectrality breaking. The analysis of all events with detectable quasinormal-driven ringdown signatures yields no evidence of higher-derivative corrections in the spectra, and we set an upper bound $\ell \lesssim$ 35 km on the length scale of new physics. Looking ahead, our scheme enables new studies on the capabilities of future detectors to robustly search for signatures of new gravitational physics., Comment: 9 pages, 6 figures

Current asymmetric cryptography is based on the principle that while classical computers can efficiently multiply large integers, the inverse operation, factorization, is significantly more complex. For sufficiently large integers, this factorization process can take in classical computers hundreds or even thousands of years to complete. However, there exist some quantum algorithms that might be able to factor integers theoretically -- the theory works properly, but the hardware requirements are far away from what we can build nowadays -- and, for instance, Yan, B. et al. ([14]) claim to have constructed a hybrid algorithm which could be able even to challenge RSA-2048 in the near future. This work analyses this article and replicates the experiments they carried out, but with a different quantum method (VQE), being able to factor the number 1961., Comment: 12 pages, 1 algortihm, 1 figure, 2 tables

We present a detailed study of the large-scale shock front in Stephan's Quintet, a byproduct of past and ongoing interactions. Using integral-field spectroscopy from the new William Herschel Telescope Enhanced Area Velocity Explorer (WEAVE), recent 144 MHz observations from the LOFAR Two-metre Sky Survey (LoTSS), and archival data from the Very Large Array and James Webb Space Telescope (JWST), we obtain new measurements of key shock properties and determine its impact on the system. Harnessing the WEAVE large integral field unit's (LIFU) field of view (90 $\times$ 78 arcsec$^{2}$), spectral resolution ($R\sim2500$) and continuous wavelength coverage across the optical band, we perform robust emission line modeling and dynamically locate the shock within the multi-phase intergalactic medium (IGM) with higher precision than previously possible. The shocking of the cold gas phase is hypersonic, and comparisons with shock models show that it can readily account for the observed emission line ratios. In contrast, we demonstrate that the shock is relatively weak in the hot plasma visible in X-rays (with Mach number of $\mathcal{M} \sim 2 - 4$), making it inefficient at producing the relativistic particles needed to explain the observed synchrotron emission. Instead, we propose that it has led to an adiabatic compression of the medium, which has increased the radio luminosity ten-fold. Comparison of the Balmer line-derived extinction map with the molecular gas and hot dust observed with JWST suggests that pre-existing dust may have survived the collision, allowing the condensation of H$_{2}$ - a key channel for dissipating the shock energy., Comment: 23 pages, 15 figures, accepted for publication in MNRAS

In this paper an asymptotic expansion of the global error on the stepsize for partitioned linear multistep methods is proved. This provides a tool to analyse the behaviour of these integrators with respect to error growth with time and conservation of invariants. In particular, symmetric partitioned linear multistep methods with no common roots in their first characteristic polynomials, except unity, appear as efficient methods to approximate non-separable Hamiltonian systems since they can be explicit and show good long term behaviour at the same time. As a case study, a thorough analysis is given for small oscillations of the double pendulum problem, which is illustrated by numerical experiments.

Shock-generated transients, such as hot flow anomalies (HFAs), upstream of planetary bow shocks, play a critical role in electron acceleration. Using multi-mission data from NASA's Magnetospheric Multiscale (MMS) and ESA's Cluster missions, we demonstrate the transmission of HFAs through Earth's quasi-parallel bow shock, associated with acceleration of electrons up to relativistic energies. Energetic electrons, initially accelerated upstream, are shown to remain broadly confined within the transmitted transient structures downstream, where betatron acceleration further boosts their energy due to elevated compression levels. Additionally, high-speed jets form at the compressive edges of HFAs, exhibiting a significant increase in dynamic pressure and potentially contributing to driving further localized compression. Our findings emphasize the efficiency of quasi-parallel shocks in driving particle acceleration far beyond the immediate shock transition region, expanding the acceleration region to a larger spatial domain. Finally, this study underscores the importance of multi-scale observational approach in understanding the convoluted processes behind collisionless shock physics and their broader implications.

Understanding and predicting the structure and evolution of coronal mass ejections (CMEs) in the heliosphere remains one of the most sought-after goals in heliophysics and space weather research. A powerful tool for improving current knowledge and capabilities consists of multi-spacecraft observations of the same event, which take place when two or more spacecraft fortuitously find themselves in the path of a single CME. Multi-probe events can not only supply useful data to evaluate the large-scale of CMEs from 1D in-situ trajectories, but also provide additional constraints and validation opportunities for CME propagation models. In this work, we analyse and simulate the coronal and heliospheric evolution of a slow, streamer-blowout CME that erupted on 23 September 2021 and was encountered in situ by four spacecraft approximately equally distributed in heliocentric distance between 0.4 and 1 au. We employ the Open Solar Physics Rapid Ensemble Information (OSPREI) modelling suite in ensemble mode to predict the CME arrival and structure in a hindcast fashion and to compute the "best-fit" solutions at the different spacecraft individually and together. We find that the spread in the predicted quantities increases with heliocentric distance, suggesting that there may be a maximum (angular and radial) separation between an inner and an outer probe beyond which estimates of the in-situ magnetic field orientation (parameterised by flux rope model geometry) increasingly diverge. We discuss the importance of these exceptional observations and the results of our investigation in the context of advancing our understanding of CME structure and evolution as well as improving space weather forecasts., Comment: 20 pages, 12 figures, 3 tables; accepted for publication in MNRAS

Efforts are needed to identify and measure both communities' exposure to climate hazards and the social vulnerabilities that interact with these hazards, but the science of validating hazard vulnerability indicators is still in its infancy. Progress is needed to improve: 1) the selection of variables that are used as proxies to represent hazard vulnerability; 2) the applicability and scale for which these indicators are intended, including their transnational applicability. We administered an international urban survey in Buenos Aires, Argentina; Johannesburg, South Africa; London, United Kingdom; New York City, United States; and Seoul, South Korea in order to collect data on exposure to various types of extreme weather events, socioeconomic characteristics commonly used as proxies for vulnerability (i.e., income, education level, gender, and age), and additional characteristics not often included in existing composite indices (i.e., queer identity, disability identity, non-dominant primary language, and self-perceptions of both discrimination and vulnerability to flood risk). We then use feature importance analysis with gradient-boosted decision trees to measure the importance that these variables have in predicting exposure to various types of extreme weather events. Our results show that non-traditional variables were more relevant to self-reported exposure to extreme weather events than traditionally employed variables such as income or age. Furthermore, differences in variable relevance across different types of hazards and across urban contexts suggest that vulnerability indicators need to be fit to context and should not be used in a one-size-fits-all fashion., Comment: 15 pages, 2 figures

The recent discovery of an axial amplitude (Higgs) mode in the long-studied charge density wave (CDW) systems GdTe$_3$ and LaTe$_3$ suggests a heretofore unidentified hidden order. A theoretical study proposed that the axial Higgs results from a hidden ferroaxial component of the CDW, which could arise from non-trivial orbital texture. Here, we report extensive experimental studies on ErTe$_3$ and HoTe$_3$ that possess a high-temperature CDW similar to other RTe$_3$ (R = rare earth), along with an additional low-temperature CDW with an orthogonal ordering vector. Combining Raman spectroscopy with large-angle convergent beam electron diffraction (LACBED), rotational anisotropy second-harmonic generation (RA-SHG), and muon-spin relaxation ($\mu$SR), we provide unambiguous evidence that the high-temperature CDW breaks translation, rotation, and all vertical and diagonal mirror symmetries, but not time-reversal or inversion. In contrast, the low-temperature CDW only additionally breaks translation symmetry. Simultaneously, Raman scattering shows the high-temperature CDW produces an axial Higgs mode while the low-temperature mode is scalar. The weak monoclinic structural distortion and clear axial response in Raman and SHG are consistent with a ferroaxial phase in RTe$_3$ driven by coupled orbital and charge orders. Thus, our study provides a new standard for uncovering unconventional orders and confirms the power of Higgs modes to reveal them., Comment: 28 pages, 5 figures

In recent years, it has become increasingly clear that space weather disturbances can be triggered by transient upstream mesoscale structures (TUMS), independently of the occurrence of large-scale solar wind (SW) structures, such as interplanetary coronal mass ejections and stream interaction regions. Different types of magnetospheric pulsations, transient perturbations of the geomagnetic field and auroral structures are often observed during times when SW monitors indicate quiet conditions, and have been found to be associated to TUMS. In this mini-review we describe the space weather phenomena that have been associated with four of the largest-scale and the most energetic TUMS, namely hot flow anomalies, foreshock bubbles, travelling foreshocks and foreshock compressional boundaries. The space weather phenomena associated with TUMS tend to be more localized and less intense compared to geomagnetic storms. However, the quiet time space weather may occur more often since, especially during solar minima, quiet SW periods prevail over the perturbed times., Comment: 1 figure, 1 table

The NEO Coordination Centre (NEOCC) of the European Space Agency is an operational centre that, among other activities, computes the orbits of near-Earth objects and their probabilities of impact with the Earth. The NEOCC started providing information about near-Earth objects in 2012 on a dedicated web portal, accessible at https://neo.ssa.esa.int/. Since the beginning of the operational phase, many developments and improvements have been implemented regarding the software, the data provided, and the portal. One of the most important upgrades is that the NEOCC is now independently providing data through a newly developed Orbit Determination and Impact Monitoring system, named Aegis. All the data computed by Aegis is publicly available on the NEOCC web portal, and Aegis is also used to maintain all the major services offered. The most important services comprise an orbital catalogue of all known asteroids, a list of possible future impacts with the Earth (also called Risk List), a list of forthcoming close approaches, a set of graphical toolkits, and an on-demand ephemerides service. Many of the services are also available through dedicated APIs, which can be used to automatically retrieve data. Here we give an overview of the algorithms implemented in the Aegis software, and provide a summary of the services offered by the NEOCC that are supported by Aegis., Comment: Accepted for publication on CMDA

Interplanetary shocks are fundamental constituents of the heliosphere, where they form as a result of solar activity. We use previously unavailable measurements of interplanetary shocks in the inner heliosphere provided by Solar Orbiter, and present a survey of the first 100 shocks observed in situ at different heliocentric distances during the rising phase of solar cycle 25. The fundamental shock parameters (shock normals, shock normal angles, shock speeds, compression ratios, Mach numbers) have been estimated and studied as a function of heliocentric distance, revealing a rich scenario of configurations. Comparison with large surveys of shocks at 1~au show that shocks in the quasi-parallel regime and with high speed are more commonly observed in the inner heliosphere. The wave environment of the shocks has also been addressed, with about 50\% of the events exhibiting clear shock-induced upstream fluctuations. We characterize energetic particle responses to the passage of IP shocks at different energies, often revealing complex features arising from the interaction between IP shocks and pre-existing fluctuations, including solar wind structures being processed upon shock crossing. Finally, we give details and guidance on the access use of the present survey, available on the EU-project ``solar energetic particle analysis platform for the inner heliosphere'' (SERPENTINE) website. The algorithm used to identify shocks in large datasets, now publicly available, is also described.

We analyze data from multiple flybys by the Solar Orbiter, BepiColombo, and Parker Solar Probe (PSP) missions to study the interaction between Venus' plasma environment and the solar wind forming the induced magnetosphere. Through examination of magnetic field and plasma density signatures we characterize the spatial extent and dynamics of Venus' magnetotail, focusing mainly on boundary crossings. Notably, we observe significant differences in boundary crossing location and appearance between flybys, highlighting the dynamic nature of Venus' magnetotail. In particular, during Solar Orbiter's third flyby, extreme solar wind conditions led to significant variations in the magnetosheath plasma density and magnetic field properties, but the increased dynamic pressure did not compress the magnetotail. Instead, it is possible that the increased EUV flux at this time rather caused it to expand in size. Key findings also include the identification of several far downstream bow shock (BS), or bow wave, crossings to at least 60 Rv (1 Rv = 6,052 km is the radius of Venus), and the induced magnetospheric boundary to at least 20 Rv. These crossings provide insight into the extent of the induced magnetosphere. Pre-existing models from Venus Express were only constrained to within ~5 Rv of the planet, and we provide modifications to better fit the far-downstream crossings. The new model BS is now significantly closer to the central tail than previously suggested, by about 10 Rv at 60 Rv downstream.

The magnetic orientation of coronal mass ejections (CMEs) is of great importance to understand their space weather effects. Although many evidences suggest that CMEs can undergo significant rotation during the early phases of evolution in the solar corona, there are few reports that CMEs rotate in the interplanetary space. In this work, we use multi-spacecraft observations and a numerical simulation starting from the lower corona close to the solar surface to understand the CME event on 2021 December 4, with an emphatic investigation of its rotation. This event is observed as a partial halo CME from the back side of the Sun by coronagraphs, and reaches the BepiColombo spacecraft and the MAVEN/Tianwen-1 as a magnetic flux rope-like structure. The simulation discloses that in the solar corona the CME is approximately a translational motion, while the interplanetary propagation process evidences a gradual change of axis orientation of the CME's flux rope-like structure. It is also found that the downside and the right flank of the CME moves with the fast solar wind, and the upside does in the slow-speed stream. The different parts of the CME with different speeds generate the nonidentical displacements of its magnetic structure, resulting in the rotation of the CME in the interplanetary space. Furthermore, at the right flank of the CME exists a corotating interaction region (CIR), which makes the orientation of the CME alter, and also deviates from its route due to the CME. These results provide new insight on interpreting CMEs' dynamics and structures during their travelling through the heliosphere., Comment: Accepted By ApJ, 22 pages, 6 figures

Modern computer systems store vast amounts of personal data, enabling advances in AI and ML but risking user privacy and trust. For privacy reasons, it is desired sometimes for an ML model to forget part of the data it was trained on. This paper presents a new approach to machine unlearning using forgetting neural networks (FNN). FNNs are neural networks with specific forgetting layers, that take inspiration from the processes involved when a human brain forgets. While FNNs had been proposed as a theoretical construct, they have not been previously used as a machine unlearning method. We describe four different types of forgetting layers and study their properties. In our experimental evaluation, we report our results on the MNIST handwritten digit recognition and fashion datasets. The effectiveness of the unlearned models was tested using Membership Inference Attacks (MIA). Successful experimental results demonstrate the great potential of our proposed method for dealing with the machine unlearning problem.

Demixing properties of planetary major constituents influence the interior structure and evolution of planets. Comparing experimental and computational data on the miscibility of hydrogen and water to adiabatic profiles suggests phase separation between these components occurs in the ice giants Uranus and Neptune. We aim to predict the atmospheric water abundance and transition pressure between the water-poor outer envelope and the water-rich deep interior in Uranus and Neptune. We construct seven H2-H2O phase diagrams from the available experimental and computational data. We compute interior adiabatic structure models and compare these to the phase diagrams to infer whether demixing is occurring. We obtain a strong water depletion in the top layer due to rain-out of water and find upper limits on the atmospheric water mass fraction Z_atm of 0.21 for Uranus and 0.16 for Neptune. The transition from the water-poor to the water-rich layer is sharp and occurs at pressures P_Z between 4 and 11 GPa. Using these constraints on Z_atm and P_Z, we find that the observed gravitational harmonics J2 and J4 can be reproduced if P_Z > 10 GPa in Uranus and > 5 GPa in Neptune, and if the deep interior has a high primordial water mass fraction of 0.8, unless rocks are also present. The agreement with J4 is improved if rocks are confined deeper than P_Z, for instance below a rock cloud level at 2000 K (20-30 GPa). These findings confirm classical few-layer models and suggest that a layered structure may result from a combination of primordial mass accretion and subsequent phase separation. Reduced observational uncertainty in J4 and its dynamic contribution, atmospheric water abundance measurements from an Orbiter with a Probe mission to Uranus (UOP) or Neptune, and better understanding of the mixing behaviour of constituents are needed to constrain the interiors of ice giants., Comment: Accepted for publication in Astronomy and Astrophysics

Data stream learning is a very relevant paradigm because of the increasing real-world scenarios generating data at high velocities and in unbounded sequences. Stream learning aims at developing models that can process instances as they arrive, so models constantly adapt to new concepts and the temporal evolution in the stream. In multi-label data stream environments where instances have the peculiarity of belonging simultaneously to more than one class, the problem becomes even more complex and poses unique challenges such as different concept drifts impacting different labels at simultaneous or distinct times, higher class imbalance, or new labels emerging in the stream. This paper proposes a novel approach to multi-label data stream classification called Multi-Label Hoeffding Adaptive Tree (MLHAT). MLHAT leverages the Hoeffding adaptive tree to address these challenges by considering possible relations and label co-occurrences in the partitioning process of the decision tree, dynamically adapting the learner in each leaf node of the tree, and implementing a concept drift detector that can quickly detect and replace tree branches that are no longer performing well. The proposed approach is compared with other 18 online multi-label classifiers on 41 datasets. The results, validated with statistical analysis, show that MLHAT outperforms other state-of-the-art approaches in 12 well-known multi-label metrics.