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Although physics has become increasingly computational, with computing even being considered the third pillar of physics [1], it is still not well integrated into physics education [2]. Research suggests that integrating Computational Thinking (CT) into physics enhances conceptual understanding and strengthens students ability to model and analyze phenomena [3]. Building on this, we designed a didactic sequence for K9 students to foster specific CT practices while reinforcing fundamental kinematics concepts. Assessments highlight student's ability to apply CT skills to analyze accelerated motion. This activity can be seamlessly integrated into introductory kinematics courses.

Self-supervised learning models for speech processing, such as wav2vec2, HuBERT, WavLM, and Whisper, generate embeddings that capture both linguistic and paralinguistic information, making it challenging to analyze tone independently of spoken content. In this work, we introduce a method for disentangling paralinguistic features from linguistic content by regressing speech embeddings onto their corresponding text embeddings and using the residuals as a representation of vocal tone. We evaluate this approach across multiple self-supervised speech embeddings, demonstrating that residual embeddings significantly improve tone classification performance compared to raw speech embeddings. Our results show that this method enhances linear separability, enabling improved classification even with simple models such as logistic regression. Visualization of the residual embeddings further confirms the successful removal of linguistic information while preserving tone-related features. These findings highlight the potential of residual embeddings for applications in sentiment analysis, speaker characterization, and paralinguistic speech processing.

We study the effects of helical magnetic fields on chiral symmetry breaking within the AdS/QCD framework using the D3/D7-brane model. By analyzing the brane embeddings, we obtain three types of massless solutions, corresponding to three phases with different behavior in the dual field theory. From the study of quark condensates, free energy, and electric currents, we find that helical magnetic fields can counteract uniform-field-induced symmetry breaking, driving the system towards symmetry restoration. We also find an effect analog to the chiral magnetic effect whereby the current is parallel to the magnetic field. We further study the massive case, and find that the helical configuration is less effective in erasing the first order phase transition that is present in the case of a constant magnetic field., Comment: 15 pages + appendices

Frequency Phase Transfer (FPT) is a technique designed to increase coherence and sensitivity in radio interferometry by making use of the non-dispersive nature of the troposphere to calibrate high-frequency data using solutions derived at a lower frequency. While the Korean VLBI Network has pioneered the use of simultaneous multi-band systems for routine FPT up to an observing frequency of 130 GHz, this technique remains largely untested in the (sub)millimeter regime. A recent effort has been made to outfit dual-band systems at (sub)millimeter observatories participating in the Event Horizon Telescope (EHT) and to test the feasibility and performance of FPT up to the observing frequencies of the EHT. We present the results of simultaneous dual-frequency observations conducted in January 2024 on an Earth-sized baseline between the IRAM 30-m in Spain and the JCMT and SMA in Hawai`i. We performed simultaneous observations at 86 and 215 GHz on the bright sources J0958+6533 and OJ287, with strong detections obtained at both frequencies. We observe a strong correlation between the interferometric phases at the two frequencies, matching the trend expected for atmospheric fluctuations and demonstrating for the first time the viability of FPT for VLBI at a wavelength of $\sim$1 millimeter. We show that the application of FPT systematically increases the 215 GHz coherence on all averaging timescales. In addition, the use of the co-located JCMT and SMA as a single dual-frequency station demonstrates the feasibility of paired-antenna FPT for VLBI for the first time, with implications for future array capabilities (e.g., ALMA sub-arraying and ngVLA calibration strategies)., Comment: 11 pages, 5 figures, accepted to AJ

In recent neutrino detectors, neutrons produced in neutrino reactions play an important role. Muon capture on oxygen nuclei is one of the processes that produce neutrons in water Cherenkov detectors. We measured neutron multiplicity in the process using cosmic ray muons that stop in the gadolinium-loaded Super-Kamiokande detector. For this measurement, neutron detection efficiency is obtained with the muon capture events followed by gamma rays to be $50.2^{+2.0}_{-2.1}\%$. By fitting the observed multiplicity considering the detection efficiency, we measure neutron multiplicity in muon capture as $P(0)=24\pm3\%$, $P(1)=70^{+3}_{-2}\%$, $P(2)=6.1\pm0.5\%$, $P(3)=0.38\pm0.09\%$. This is the first measurement of the multiplicity of neutrons associated with muon capture without neutron energy threshold.

This work examines the often-overlooked role of the displacement current in systems beyond capacitors, particularly in coaxial cables and resistors with alternating currents. While its influence is negligible at low frequencies compared to conduction currents, displacement current becomes crucial at higher frequencies for precise field calculations. Introductory physics textbooks commonly restrict the concept to capacitor charging, potentially leading to misconceptions about its broader applications and the interdependence of Maxwell's equations in dynamic scenarios. By analyzing two specific cases, we clarify when displacement current can be disregarded, when simplified laws like Biot-Savart are valid, and where coupled electromagnetic equations are essential. This approach highlights the boundaries of common models and promotes a deeper understanding of dynamic field interactions., Comment: 5 pages

Current axion detection limits neglect the relevance of the relative velocity between the axion field and the detectors. However, this aspect can lead to a daily modulation of the detected axion signal. In this work, we calculate the cross-correlation of various signals potentially originated in multiple-cavity setups, and we analyze how the signal-to-noise ratio and directional sensitivity depend on the signal cross-correlation among multiple cavities. The signal-to-noise ratio after cross-correlation exhibits a greater rate of increase over time compared to the power-summation technique, making it clear that this method could be potentially employed in a real setup for the reduction of the exposure time. For the study of the daily modulation, three interferometric experiments have been proposed in this manuscript: (i) three rectangular cavities in different Earth locations; (ii) three rectangular cavities located in the same Earth spot but oriented towards different perpendicular directions; (iii) six rectangular cavities in the same Earth location but oriented towards different directions. In each set-up, we have simulated three different cavity lengths. Similar results have been found for the cases (i) and (ii): when the highest length upon the three proposed is considered, a phase difference between the recorded voltages of more than $2^{\circ}$ has been obtained with our numerical calculations. We observe a daily modulation in the imaginary part of the signals cross-correlation for experiment (iii), that could be potentially used for the characterization of the axion velocity distribution. To the knowledge of the authors, this is the first time that the cross-correlation technique has been applied to the directional sensitivity analysis of an array of haloscopes., Comment: 29 pages, 19 figures

This paper proposes a hierarchical Bayesian multitask learning model that is applicable to the general multi-task binary classification learning problem where the model assumes a shared sparsity structure across different tasks. We derive a computationally efficient inference algorithm based on variational inference to approximate the posterior distribution. We demonstrate the potential of the new approach on various synthetic datasets and for predicting human health status based on microbiome profile. Our analysis incorporates data pooled from multiple microbiome studies, along with a comprehensive comparison with other benchmark methods. Results in synthetic datasets show that the proposed approach has superior support recovery property when the underlying regression coefficients share a common sparsity structure across different tasks. Our experiments on microbiome classification demonstrate the utility of the method in extracting informative taxa while providing well-calibrated predictions with uncertainty quantification and achieving competitive performance in terms of prediction metrics. Notably, despite the heterogeneity of the pooled datasets (e.g., different experimental objectives, laboratory setups, sequencing equipment, patient demographics), our method delivers robust results.

Noncoherent communication systems have regained interest due to the growing demand for high-mobility and low-latency applications. Most existing studies using large antenna arrays rely on the far-field approximation, which assumes locally plane wavefronts. This assumption becomes inaccurate at higher frequencies and shorter ranges, where wavefront curvature plays a significant role and antenna arrays may operate in the radiative near field. In this letter, we adopt a model for the channel spatial correlation matrix that remains valid in both near and far field scenarios. Using this model, we demonstrate that noncoherent systems can leverage the benefits of wavefront spherical curvature, even beyond the Fraunhofer distance, revealing that the classical far-field approximation may significantly underestimate system performance. Moreover, we show that large antenna arrays enable the multiplexing of various users and facilitate near-optimal noncoherent detection with low computational complexity., Comment: This work has been submitted to the IEEE for possible publication

Breast cancer is one of the most common causes of death among women worldwide. Early detection helps in reducing the number of deaths. Automated 3D Breast Ultrasound (ABUS) is a newer approach for breast screening, which has many advantages over handheld mammography such as safety, speed, and higher detection rate of breast cancer. Tumor detection, segmentation, and classification are key components in the analysis of medical images, especially challenging in the context of 3D ABUS due to the significant variability in tumor size and shape, unclear tumor boundaries, and a low signal-to-noise ratio. The lack of publicly accessible, well-labeled ABUS datasets further hinders the advancement of systems for breast tumor analysis. Addressing this gap, we have organized the inaugural Tumor Detection, Segmentation, and Classification Challenge on Automated 3D Breast Ultrasound 2023 (TDSC-ABUS2023). This initiative aims to spearhead research in this field and create a definitive benchmark for tasks associated with 3D ABUS image analysis. In this paper, we summarize the top-performing algorithms from the challenge and provide critical analysis for ABUS image examination. We offer the TDSC-ABUS challenge as an open-access platform at https://tdsc-abus2023.grand-challenge.org/ to benchmark and inspire future developments in algorithmic research.

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 2,700 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai., Comment: 27 pages, 6 figures

The $\frac12$-BPS indices of $\mathcal{N}=4$ Super Yang-Mills theory with unitary, orthogonal, and symplectic groups all admit $q$-expansions suggesting an interpretation in terms of D-branes in the dual bulk AdS$_5$ string theories. We present a derivation of these expansions in the corresponding bulk duals by quantizing the moduli space of $\frac12$-BPS giant gravitons using supersymmetric localization, extending and clarifying our study in arxiv:2312.14921. We perform a detailed analysis of the one-loop fluctuations around the maximal giants (the fixed points), and show how the Hamiltonian analysis is recovered from the functional integral for the equivariant index. We show that the analytic continuation for these giant graviton expansions observed in the literature maps precisely to a wall-crossing phenomenon for the index. In the case of orthogonal and symplectic gauge groups, the $\mathbb{Z}_2$ quotient in the bulk leads to a corresponding projection in the $q$-expansion. Additional terms in the expansion related to the Pfaffian operator arise from topologically stable branes in the bulk dual on AdS$_5 \times \mathbb{RP}^5$.

The colliding-wind binary system $\eta$ Carinae has been identified as a source of high-energy (HE, below $\sim$100\,GeV) and very-high-energy (VHE, above $\sim$100\,GeV) gamma rays in the last decade, making it unique among these systems. With its eccentric 5.5-year-long orbit, the periastron passage, during which the stars are separated by only $1-2$\,au, is an intriguing time interval to probe particle acceleration processes within the system. In this work, we report on an extensive VHE observation campaign that for the first time covers the full periastron passage carried out with the High Energy Stereoscopic System (H.E.S.S.) in its 5-telescope configuration with upgraded cameras. VHE gamma-ray emission from $\eta$ Carinae was detected during the periastron passage with a steep spectrum with spectral index $\Gamma= 3.3 \pm 0.2_{\mathrm{stat}} \, \pm 0.1_{\mathrm{syst}}$. Together with previous and follow-up observations, we derive a long-term light curve sampling one full orbit, showing hints of an increase of the VHE flux towards periastron, but no hint of variability during the passage itself. An analysis of contemporaneous Fermi-LAT data shows that the VHE spectrum represents a smooth continuation of the HE spectrum. From modelling the combined spectrum we conclude that the gamma-ray emission region is located at distances of ${\sim}10 - 20$\,au from the centre of mass of the system and that protons are accelerated up to energies of at least several TeV inside the system in this phase., Comment: Accepted at A&A; 11 pages, 9 figures

The objective of this study is to analyze the CO2 emissions and economic impacts of the implementation of the National Efficient Cooking Program (NECP) in Ecuador, which aims to migrate the population from Liquefied Petroleum Gas (LPG)-based stoves to electric induction stoves. This program is rooted in the current effort to change Ecuador's energy balance, with hydroelectric power expected to generate 83.61% of national electricity by 2022, ending the need for subsidized LPG. For this analysis, the 2014 baseline situation has been compared with two future scenarios for 2022: a business-as-usual scenario and an NECP-success scenario. This study demonstrates the viability of migration from imported fossil fuels to locally-produced renewable energy as the basis for an efficient cooking facility. The new policies scenario would save US$ 1.162 billion in annual government expenditure on cooking subsidies, and reducing CO2 emissions associated to energy for cooking in 1.8 tCO2/y., Comment: 6 pages, 1 figure, 4 table, research article

Many active galaxies harbor powerful relativistic jets, however, the detailed mechanisms of their formation and acceleration remain poorly understood. To investigate the area of jet acceleration and collimation with the highest available angular resolution, we study the innermost region of the bipolar jet in the nearby low-ionization nuclear emission-line region (LINER) galaxy NGC 1052. We combined observations of NGC 1052 taken with VLBA, GMVA, and EHT over one week in the spring of 2017. For the first time, NGC 1052 was detected with the EHT, providing a size of the central region in-between both jet bases of 250 RS (Schwarzschild radii) perpendicular to the jet axes. This size estimate supports previous studies of the jets expansion profile which suggest two breaks of the profile at around 300 RS and 10000 RS distances to the core. Furthermore, we estimated the magnetic field to be 1.25 Gauss at a distance of 22 {\mu}as from the central engine by fitting a synchrotron-self absorption spectrum to the innermost emission feature, which shows a spectral turn-over at about 130 GHz. Assuming a purely poloidal magnetic field, this implies an upper limit on the magnetic field strength at the event horizon of 26000 Gauss, which is consistent with previous measurements. The complex, low-brightness, double-sided jet structure in NGC 1052 makes it a challenge to detect the source at millimeter (mm) wavelengths. However, our first EHT observations have demonstrated that detection is possible up to at least 230 GHz. This study offers a glimpse through the dense surrounding torus and into the innermost central region, where the jets are formed. This has enabled us to finally resolve this region and provide improved constraints on its expansion and magnetic field strength., Comment: 22 pages, 10 figures, published in A&A

A 2.1-year periodic oscillation of the gamma-ray flux from the blazar PG 1553+113 has previously been tentatively identified in almost 7 year of data from the Fermi Large Area Telescope. After 15 years of Fermi sky-survey observations, doubling the total time range, we report >7 cycle gamma-ray modulation with an estimated significance of 4 sigma against stochastic red noise. Independent determinations of oscillation period and phase in the earlier and the new data are in close agreement (chance probability <0.01). Pulse timing over the full light curve is also consistent with a coherent periodicity. Multiwavelength new data from Swift X-Ray Telescope, Burst Alert Telescope, and UVOT, and from KAIT, Catalina Sky Survey, All-Sky Automated Survey for Supernovae, and Owens Valley Radio Observatory ground-based observatories as well as archival Rossi X-Ray Timing Explorer satellite-All Sky Monitor data, published optical data of Tuorla, and optical historical Harvard plates data are included in our work. Optical and radio light curves show clear correlations with the gamma-ray modulation, possibly with a nonconstant time lag for the radio flux. We interpret the gamma-ray periodicity as possibly arising from a pulsational accretion flow in a sub-parsec binary supermassive black hole system of elevated mass ratio, with orbital modulation of the supplied material and energy in the jet. Other astrophysical scenarios introduced include instabilities, disk and jet precession, rotation or nutation, and perturbations by massive stars or intermediate-mass black holes in polar orbit., Comment: 23 pages, 14 figures, 20 plots, 1 table, accepted and published by The Astrophysical Journal. Article produced by the Fermi Large Area Telescope (LAT) Collaboration

Highly collimated outflows (jets) are observed across a wide range of astrophysical systems involving the accretion of material onto central objects, from supermassive black holes in active galaxies to proto-brown dwarfs and stellar-mass black holes. Despite the diversity of their driving sources, it is believed that all jets are different manifestations of a single universal phenomenon. However, a unified explanation for their ejection and collimation remains elusive. In this study we present the first rotation measure analysis of the polarized synchrotron emission ever performed in a protostellar radio jet, which allows us to reveal its true 3D magnetic structure. Unlike extragalactic radio jets, which often exhibit faint counterjets, protostellar radio jets allow both the jet and the counterjet to be analyzed. This exceptional circumstance allows us to unveil the magnetic field structure of both components. Our findings provide the first solid evidence for a helical magnetic field within a protostellar jet, supporting the universality of the jet collimation mechanism., Comment: 8 pages, 3 figures. Published in the Astrophysical Journal Letters, Volume 978, Number 2

The Ampere-Maxwell's law and the displacement current constitute one of the most difficult aspects of electromagnetic theory for students in introductory electromagnetics courses. Here we present a set of examples that go beyond the classical ones usually discussed in introductory textbooks. In-depth analysis of these examples allows students to develop a deeper understanding of electromagnetic theory even in students who have not acquired the full mathematical toolkit of the more advanced courses.

We prove a Lipschitz-volume rigidity result for $1$-Lipschitz maps of non-zero degree between metric manifolds (metric spaces homeomorphic to a closed oriented manifold) and Riemannian manifolds. The proof is based on degree theory and recent developments of Lipschitz-volume rigidity for integral currents.

The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-K\"onigl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.

We present a new paradigm for generating complex structured materials based on the three-gap theorem that unifies and generalises several key concepts in the study of localised edge states. Our model has both the discretised coupling strengths of the SSH model and a modulation parameter that can be used to characterise the spectral flow of edge modes and produce images reminiscent of the Hofstadter butterfly. By defining a localisation factor associated to each eigenmode, we are able to establish conditions for the existence of localised edge states in finite systems. This allows us to compare their eigenfrequencies with the spectra of the corresponding infinitely periodic problem and characterise the rich pattern of localised edge modes appearing and disappearing (in the sense of becoming delocalised) as the parameters of our three-gap algorithm are varied.

PSR J2030+4415 is a gamma-ray pulsar with an X-ray pulsar wind nebula elongated along the north-south direction. The system shows a prominent X-ray filament oriented at an angle of 130{\deg} to the nebula axis. To improve our understanding of the non-thermal processes occurring in the pulsar wind nebula, we attempted to determine the possible existence of a radio counterpart, study its morphology, and obtain restrictive upper limits of the pulsar and filament emission at radio wavelengths. We performed observations of the pulsar PSR J2030+4415 and its surroundings with the upgraded Giant Metrewave Radio Telescope (uGMRT) at two frequency bands, and put the results in context with findings at other wavelengths. We obtained radio images at 736 and 1274 MHz that reveal a structure trailing the pulsar, with a morphology overlapping the X-ray nebula. This radio structure is the radio counterpart of the X-ray pulsar wind nebula. The derived spectral index along this structure shows spatial variation. There are no hints of the pulsar and the filament at any of the explored radio frequencies, but we obtained restrictive upper limits. A physical scenario that combines the radio and the X-ray observations, and consistent with IR data, of the nebula and the filament is presented. We propose that particle acceleration occurs in the nebula tail due to the presence of a re-collimation shock, and the highest energy particles gradually escape from it through energy-dependent diffusion. We also find a lower limit in the energy of the particles escaping along the X-ray filament of ~GeV., Comment: 8 pages, 6 figures. Accepted for publication in A&A

Geodetic and astrometric VLBI has entered a new era with the implementation of the VLBI Global Observing System (VGOS). These broadband and dual linear polarization observations aim at an accuracy of station coordinates of 1 mm and a reference frame stability of 0.1 mm/year. Although the extended brightness distribution of many of the radio-loud active galactic nuclei observed during geodetic VLBI sessions is resolved by the interferometer, the established processing chain still treats these objects as point sources. We investigate the impact of source structure on the visibility level and develop tools to remove the structure from the visibility data, right after correlation. Here we present our approach and show results obtained from observational VGOS data., Comment: 4 pages, 6 figures, published in Proceedings of the 16th EVN Symposium, Ed. E. Ros, P. Benke, S.A. Dzib, I. Rottmann, & J.A. Zensus, Bonn: Max-Planck-Institut f\"ur Radioastronomie, 2024, pages 145-148

We study the dynamics of chaos across the phase transition in a 2-coupled Sachdev-Ye-Kitaev (SYK) model, with a focus on the unstable "hot wormhole" phase. Using the Schwinger-Keldysh formalism, we employ two non-equilibrium protocols that allow access to this phase, which is inaccessible through equilibrium simulations: one involves cooling the system via a coupling to a thermal bath, while in the other we periodically drive the coupling parameter between the two sides. We numerically compute the Lyapunov exponents of the hot wormhole for the two cases. Our results uncover a rich structure within this phase, including both thermal and non-thermal solutions. These behaviors are analyzed in detail, with partial insights provided by the Schwarzian approximation, which captures certain but not all aspects of the observed dynamics., Comment: 26 pages. Extra analysis added in v3

The square inverse law with distance plays an important role in many fields of physics covering electromagnetism, optics or acoustics. However, as every law in physics has its range of validity. We propose an open-inquiry laboratory where we challenge these concepts by proposing experiments where the intensity of light decays linearly or even remains constant over a range of distances. Using the light sensors built into smartphones, it is possible to measure light curves for different sources: point, linear, planar and even LED ring lights. The analysis of these curves allows us to discuss the limits of the physical theories. This low-cost laboratory, initially proposed in the context of the COVID19 pandemic, has the virtue of challenging intuition and encouraging the critical spirit of the students., Comment: 8 pages, 8 figs

We consider three conditions on metric manifolds with finite volume: (1) the existence of a metric fundamental class, (2) local index bounds for Lipschitz maps, and (3) Gromov--Hausdorff approximation with volume control by bi-Lipschitz manifolds. Condition (1) is known for metric manifolds satisfying the LLC condition by work of Basso--Marti--Wenger, while (3) is known for metric surfaces by work of Ntalampekos--Romney. We prove that for metric manifolds with finite Nagata dimension, all three conditions are equivalent and that without assuming finite Nagata dimension, (1) implies (2) and (3) implies (1). As a corollary we obtain a generalization of the approximation result of Ntalampekos--Romney to metric manifolds of dimension $n\ge 2$, which have the LLC property and finite Nagata dimension., Comment: 25 pages, comments welcome!

The solubility of helium in liquid metals is a knowledge of fundamental importance in the design of the future nuclear fusion reactors, since the formation of helium bubbles inside the breeding blankets of the reactors can be a threat to the durability of the devices and, more importantly, to the efficiency of tritium recovery. In the present work we report a detailed set of calculations of the solubility of helium in lead and lead-lithium alloys. A series of molecular dynamics simulations have been combined with a classical perturbative procedure able to compute the free energy of insertion of a helium atom inside a liquid metal bath, directly related to the solubility of helium. As the most important case, the concentration of the eutectic solution has been explored in full detail. We have found that solubility of helium in pure lithium is lower than in pure lead, predicting a value at the eutectic state (16% Li-84% Pb at 508 K) of about $5 \times 10^{-16}$ Pa$^{-1}$. The observed trend indicates that solubilties rise with increasing temperatures., Comment: 31 pages, 12 figures

The interactions between jets from active galactic nuclei (AGN) and their stellar environments significantly influence jet dynamics and emission characteristics. In low-power jets, such as those in Fanaroff-Riley I (FR I) galaxies, the jet-star interactions can notably affect jet deceleration and energy dissipation. Recent numerical studies suggest that mass loading from stellar winds is a key factor in decelerating jets, accounting for many observed characteristics in FR I jets. Additionally, a radio-optical positional offset has been observed, with optical emission detected further down the jet than radio emission. This observation may challenge traditional explanations based solely on recollimation shocks and instabilities. This work utilizes the radiative transfer code RIPTIDE to generate synthetic synchrotron maps, from a population of re-accelerated electrons, in both radio and optical bands from jet simulations incorporating various mass-loading profiles and distributions of gas and stars within the ambient medium. Our findings emphasize the importance of mass entrainment in replicating the extended and diffuse radio/optical emissions observed in FR I jets and explaining the radio-optical offsets. These offsets are influenced by the galaxy's physical properties, the surrounding stellar populations, and observational biases. We successfully reproduce typical radio-optical offsets by considering a mass-load equivalent to $10^{-9}~M_\odot \cdot \rm{yr}^{-1} \cdot \rm{pc}^{-3}$. Overall, our results demonstrate that positive offset measurements are a promising tool for revealing the fundamental properties of galaxies and potentially their stellar populations, particularly in the context of FR I jets., Comment: 13 pages, 8 figures

The conversion of thermal energy into work is usually more efficient in the slow-driving regime, where the power output is vanishingly small. Efficient work extraction for fast driving protocols remains an outstanding challenge at the nanoscale, where fluctuations play a significant role. In this Letter, we use a quantum-dot Szilard engine to extract work from thermal fluctuations with maximum efficiency over two decades of driving speed. We design and implement a family of optimised protocols ranging from the slow- to the fast-driving regime, and measure the engine's efficiency as well as the mean and variance of its power output in each case. These optimised protocols exhibit significant improvements in power and efficiency compared to the naive approach. Our results also show that, when optimising for efficiency, boosting the power output of a Szilard engine inevitably comes at the cost of increased power fluctuations., Comment: main text: 5 pages, 2 figures, appendix: 3 pages, 2 figures. arXiv admin note: text overlap with arXiv:2410.18903

The opaque nature of transformer-based models, particularly in applications susceptible to unethical practices such as dark-patterns in user interfaces, requires models that integrate uncertainty quantification to enhance trust in predictions. This study focuses on dark-pattern detection, deceptive design choices that manipulate user decisions, undermining autonomy and consent. We propose a differential fine-tuning approach implemented at the final classification head via uncertainty quantification with transformer-based pre-trained models. Employing a dense neural network (DNN) head architecture as a baseline, we examine two methods capable of quantifying uncertainty: Spectral-normalized Neural Gaussian Processes (SNGPs) and Bayesian Neural Networks (BNNs). These methods are evaluated on a set of open-source foundational models across multiple dimensions: model performance, variance in certainty of predictions and environmental impact during training and inference phases. Results demonstrate that integrating uncertainty quantification maintains performance while providing insights into challenging instances within the models. Moreover, the study reveals that the environmental impact does not uniformly increase with the incorporation of uncertainty quantification techniques. The study's findings demonstrate that uncertainty quantification enhances transparency and provides measurable confidence in predictions, improving the explainability and clarity of black-box models. This facilitates informed decision-making and mitigates the influence of dark-patterns on user interfaces. These results highlight the importance of incorporating uncertainty quantification techniques in developing machine learning models, particularly in domains where interpretability and trustworthiness are critical.

We show that for every g greater or equal than 5, the locus of Prym varieties in the moduli space of principally polarized abelian varieties of dimension g-1 that possess a pseudoreflection of geometric origin is the union of three different non-empty explicit irreducible families. This is in stark contrast to the loci of Jacobian varieties that possess a pseudoreflection of geometric origin, which is empty for any genus greater than 3. In g=6, a distinguished example of Prym varieties with a pseudoreflection is given by intermediate Jacobians of cubic threefolds that possess an Eckardt point., Comment: 17 pages, comments are welcome

As countries develop, the relative importance of agriculture declines and economic activity becomes spatially concentrated. We develop a model integrating structural change and regional disparities to jointly capture these phenomena. A key modeling innovation ensuring analytical tractability is the introduction of non-homothetic Cobb-Douglas preferences, which are characterized by constant unitary elasticity of substitution and non-constant income elasticity. As labor productivity increases over time, economic well-being rises, leading to a declining expenditure share on agricultural goods. Labor reallocates away from agriculture, and industry concentrates spatially, further increasing aggregate productivity: structural change and regional disparities are two mutually reinforcing outcomes and propagators of the growth process.

We consider the estimation of an unknown parameter $\theta$ via a many-body probe. The probe is initially prepared in a product state and many-body interactions enhance its $\theta$-sensitivity during the dynamics and/or in the steady state. We present bounds on the Quantum Fisher Information, and corresponding optimal interacting Hamiltonians, for two paradigmatic scenarios for encoding $\theta$: (i) via unitary Hamiltonian dynamics (dynamical metrology), and (ii) in the Gibbs and diagonal ensembles (time-averaged dephased state), two ubiquitous steady states of many-body open dynamics. We then move to the specific problem of estimating the strength of a magnetic field via interacting spins and derive two-body interacting Hamiltonians that can approach the fundamental precision bounds. In this case, we additionally analyze the transient regime leading to the steady states and characterize tradeoffs between equilibration times and measurement precision. Overall, our results provide a comprehensive picture of the potential of many-body control in quantum sensing., Comment: 16 + 19 pages, 10 figures, 2 tables

Flat elastic sheets tend to display wrinkles and folds. From pieces of clothing down to two-dimensional crystals, these corrugations appear in response to strain generated by sheet compression or stretching, thermal or mechanical mismatch with other elastic layers, or surface tension. Extensively studied in metals, polymers and, more recently, in van der Waals exfoliated layers, with the advent of thin single crystal freestanding films of complex oxides, researchers are now paying attention to novel microstructural effects induced by bending ferroelectric-ferroelastics, where polarization is strongly coupled to lattice deformation. Here we show that wrinkle undulations in BaTiO3 sheets bonded to a viscoelastic substrate transform into a buckle delamination geometry when transferred onto a rigid substrate. Using spatially resolved techniques at different scales (Raman, scanning probe and electron microscopy), we show how these delaminations in the free BaTiO3 sheets display a self-organization of ferroelastic domains along the buckle profile that strongly differs from the more studied sinusoidal wrinkle geometry. Moreover, we disclose the hierarchical distribution of a secondary set of domains induced by the misalignment of these folding structures from the preferred in-plane crystallographic orientations. Our results disclose the relevance of the morphology and orientation of buckling instabilities in ferroelectric free sheets, for the stabilization of different domain structures, pointing to new routes for domain engineering of ferroelectrics in flexible oxide sheets.

Mathematical reasoning capabilities are increasing with tool-augmented language agents, but methods often rely either on closed-source or large models, external data, or extensive prompt engineering. This work introduces MATATA, a novel cost-effective method to train LLM agents for tabular data problems through reasoning, planning, and tool use. With a progressive self-improvement paradigm and an iterative weak supervision, it empowers 3.8B/8B Small Language Models (SLMs), particularly suited for local hosting and sensitive business contexts where data privacy is crucial. By employing a flexible and reusable tools across different datasets, it achieves robust performance with effective scalability across shared tasks. Experiments show that MATATA reaches state-of-the-art performances on FinQA and TAT-QA among reasoning frameworks based on open-source models. Moreover, MATATA models compete with GPT-4 based frameworks on TabMWP, while being SLMs.

Integrating 2D mammography with 3D magnetic resonance imaging (MRI) is crucial for improving breast cancer diagnosis and treatment planning. However, this integration is challenging due to differences in imaging modalities and the need for precise tissue segmentation and alignment. This paper addresses these challenges by enhancing biomechanical breast models in two main aspects: improving tissue identification using nnU-Net segmentation models and evaluating finite element (FE) biomechanical solvers, specifically comparing NiftySim and FEBio. We performed a detailed six-class segmentation of breast MRI data using the nnU-Net architecture, achieving Dice Coefficients of 0.94 for fat, 0.88 for glandular tissue, and 0.87 for pectoral muscle. The overall foreground segmentation reached a mean Dice Coefficient of 0.83 through an ensemble of 2D and 3D U-Net configurations, providing a solid foundation for 3D reconstruction and biomechanical modeling. The segmented data was then used to generate detailed 3D meshes and develop biomechanical models using NiftySim and FEBio, which simulate breast tissue's physical behaviors under compression. Our results include a comparison between NiftySim and FEBio, providing insights into the accuracy and reliability of these simulations in studying breast tissue responses under compression. The findings of this study have the potential to improve the integration of 2D and 3D imaging modalities, thereby enhancing diagnostic accuracy and treatment planning for breast cancer., Comment: Deep Breath @ MICCAI 2024

Thermodynamic computing has emerged as a promising paradigm for accelerating computation by harnessing the thermalization properties of physical systems. This work introduces a novel approach to solving quadratic programming problems using thermodynamic hardware. By incorporating a thermodynamic subroutine for solving linear systems into the interior-point method, we present a hybrid digital-analog algorithm that outperforms traditional digital algorithms in terms of speed. Notably, we achieve a polynomial asymptotic speedup compared to conventional digital approaches. Additionally, we simulate the algorithm for a support vector machine and predict substantial practical speedups with only minimal degradation in solution quality. Finally, we detail how our method can be applied to portfolio optimization and the simulation of nonlinear resistive networks., Comment: 13 pages, 4 figures

Owing to their rapid cooling rate and hence loss-limited propagation distance, cosmic-ray electrons and positrons (CRe) at very high energies probe local cosmic-ray accelerators and provide constraints on exotic production mechanisms such as annihilation of dark matter particles. We present a high-statistics measurement of the spectrum of CRe candidate events from 0.3 to 40 TeV with the High Energy Stereoscopic System (H.E.S.S.), covering two orders of magnitude in energy and reaching a proton rejection power of better than $10^{4}$. The measured spectrum is well described by a broken power law, with a break around 1 TeV, where the spectral index increases from $\Gamma_1 = 3.25$ $\pm$ 0.02 (stat) $\pm$ 0.2 (sys) to $\Gamma_2 = 4.49$ $\pm$ 0.04 (stat) $\pm$ 0.2 (sys). Apart from the break, the spectrum is featureless. The absence of distinct signatures at multi-TeV energies imposes constraints on the presence of nearby CRe accelerators and the local CRe propagation mechanisms., Comment: main paper: 8 pages, 4 figures, supplemental material: 12 pages, 14 figures, accepted for publication in Physical Review Letters https://journals.aps.org/prl/

The recent detection of extended $\gamma$-ray emission around middle-aged pulsars is interpreted as inverse-Compton scattering of ambient photons by electron-positron pairs escaping the pulsar wind nebula, which are confined near the system by unclear mechanisms. This emerging population of $\gamma$-ray sources was first discovered at TeV energies and remains underexplored in the GeV range. To address this, we conducted a systematic search for extended sources along the Galactic plane using 14 years of Fermi-LAT data above 10 GeV, aiming to identify a number of pulsar halo candidates and extend our view to lower energies. The search covered the inner Galactic plane ($\lvert l\rvert\leq$ 100$^{\circ}$, $\lvert b\rvert\leq$ 1$^{\circ}$) and the positions of known TeV sources and bright pulsars, yielding broader astrophysical interest. We found 40 such sources, forming the Second Fermi Galactic Extended Sources Catalog (2FGES), most with 68% containment radii smaller than 1.0$^{\circ}$ and relatively hard spectra with photon indices below 2.5. We assessed detection robustness using field-specific alternative interstellar emission models and by inspecting significance maps. Noting 13 sources previously known as extended in the 4FGL-DR3 catalog and five dubious sources from complex regions, we report 22 newly detected extended sources above 10 GeV. Of these, 13 coincide with H.E.S.S., HAWC, or LHAASO sources; six coincide with bright pulsars (including four also coincident with TeV sources); six are associated with 4FGL point sources only; and one has no association in the scanned catalogs. Notably, six to eight sources may be related to pulsars as classical pulsar wind nebulae or pulsar halos., Comment: 43 pages, 17 figures, 11 tables

Breast compression simulation is essential for accurate image registration from 3D modalities to X-ray procedures like mammography. It accounts for tissue shape and position changes due to compression, ensuring precise alignment and improved analysis. Although Finite Element Analysis (FEA) is reliable for approximating soft tissue deformation, it struggles with balancing accuracy and computational efficiency. Recent studies have used data-driven models trained on FEA results to speed up tissue deformation predictions. We propose to explore Physics-based Graph Neural Networks (PhysGNN) for breast compression simulation. PhysGNN has been used for data-driven modelling in other domains, and this work presents the first investigation of their potential in predicting breast deformation during mammographic compression. Unlike conventional data-driven models, PhysGNN, which incorporates mesh structural information and enables inductive learning on unstructured grids, is well-suited for capturing complex breast tissue geometries. Trained on deformations from incremental FEA simulations, PhysGNN's performance is evaluated by comparing predicted nodal displacements with those from finite element (FE) simulations. This deep learning (DL) framework shows promise for accurate, rapid breast deformation approximations, offering enhanced computational efficiency for real-world scenarios., Comment: Deep Breath @ MICCAI 2024 | The code is available at this URL: https://github.com/hadiiiil/GNNs-BreastCompression

Context. Star-forming regions are gaining considerable interest in the high-energy astrophysics community as possible Galactic particle accelerators. In general, the role of electrons has not been fully considered in this kind of cosmic-ray source. However, the intense radiation fields inside these regions might make electrons significant gamma-ray contributors. Aims. We study the young and compact star-forming region NGC 3603, a well known gamma-ray emitter. Our intention is to test whether its gamma-ray emission can be produced by cosmic-ray electrons. Methods. We build a novel model by creating realistic 3D distributions of the gas and the radiation field in the region. We introduce these models into PICARD to perform cosmic-ray transport simulations and produce gamma-ray emission maps. The results are compared with a dedicated Fermi Large Area Telescope data analysis at high energies. We also explore the radio and neutrino emissions of the system. Results. We improve the existing upper limits of the NGC 3603 gamma-ray source extension. Although the gamma-ray spectrum is well reproduced with the injection of CR protons, it requires nearly 30\% acceleration efficiency. In addition, the resulting extension of the simulated hadronic source is in mild tension with the extension data upper limit. The radio data disfavours the lepton-only scenario. Finally, combining both populations, the results are consistent with all observables, although the exact contributions are ambiguous., Comment: 12 pages, 10 figures

This article introduces a groundbreaking analytical workflow designed for the holistic characterisation, modelling and physical simulation of device heterostructures. Our innovative workflow autonomously, comprehensively and locally characterises the crystallographic information and 3D orientation of the crystal phases, the elemental composition, and the strain maps of devices from (scanning) transmission electron microscopy data. It converts a manual characterisation process that traditionally takes days into an automatic routine completed in minutes. This is achieved through a physics-guided artificial intelligence model that combines unsupervised and supervised machine learning in a modular way to provide a representative 3D description of the devices, materials structures, or samples under analysis. To culminate the process, we integrate the extracted knowledge to automate the generation of both 3D finite element and atomic models of millions of atoms acting as digital twins, enabling simulations that yield essential physical and chemical insights crucial for understanding the device's behaviour in practical applications. We prove this end-to-end workflow with a state-of-the-art materials platform based on SiGe planar heterostructures for hosting coherent and scalable spin qubits. Our workflow connects representative digital twins of the experimental devices with their theoretical properties to reveal the true impact that every atom in the structure has on their electronic properties, and eventually, into their functional quantum performance. Notably, the versatility of our workflow is demonstrated through its successful application to a wide array of materials systems, device configurations and sample morphologies.

We explore the fundamental limits on thermodynamic irreversibility when cooling a quantum system in the presence of a finite-size reservoir. First, we prove that for any non-interacting $n$-particle reservoir, the entropy production $\Sigma$ decays at most linearly with $n$. Instead, we derive a cooling protocol in which $\Sigma \propto 1/n^2$, which is in fact the best possible scaling. This becomes possible due to the presence of interactions in the finite-size reservoir, which must be prepared at the verge of a phase transition. Our results open the possibility of cooling with a higher energetic efficiency via interacting reservoirs., Comment: 5+7 pages. Comments welcome!

Security and RAS are two non-functional requirements under focus for current systems developed for the computing continuum. Due to the increased number of interconnected computer systems across the continuum, security becomes especially pervasive at all levels, from the smallest edge device to the high-performance cloud at the other end. Similarly, RAS (Reliability, Availability, and Serviceability) ensures the robustness of a system towards hardware defects. Namely, making them reliable, with high availability and design for easy service. In this paper and as a result of the Vitamin-V EU project, the authors detail the comprehensive approach to malware and hardware attack detection; as well as, the RAS features envisioned for future systems across the computing continuum.

We study superfluid helium droplets multiply charged with ions. When stable, the charges are found to reside in equilibrium close to the droplet surface, thus representing a physical realization of Thomson's model. We find the minimum radius of the helium droplet that can host a given number of ions using a model whose physical ingredients are the solvation energy of the cations, calculated within the He-DFT approach, and their mutual Coulomb repulsion energy. Our model goes beyond the often used liquid drop model, where charges are smeared out either within the droplet or on its surface, and which neglects the solid-like helium shell around the ions. We find that below a threshold droplet radius R_0, the total energy of the system becomes higher than that of the separated system of the pristine helium droplet and the charges embedded in their solvation microcluster ("snowball"). However, the ions are still kept within the droplet by the presence of energy barriers which hinder Coulomb explosion. A further reduction of the droplet radius below a value R_expl eventually results in the disappearance of such barrier, leading to Coulomb explosion. Surprisingly, our results are rather insensitive to the ion atomic species. This makes room to discuss them in the context of intrinsic multicharged helium droplets, where the charges are triatomic He3+ ions. Our calculated values for R_expl display the correct scaling with the number of cations compared to available experimental results, at variance with other estimates for the critical radii., Comment: 12 pages, 10 figures

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of experiments, in particular the Cherenkov Telescope Array Observatory (CTAO), sets ambitious goals for discoveries of new gamma-ray sources and precise measurements of the already discovered ones. To achieve these goals, both hardware and data analysis must employ cutting-edge techniques. This also applies to the LST-1, the first IACT built for the CTAO, which is currently taking data on the Canary island of La Palma. This paper introduces a new event reconstruction technique for IACT data, aiming to improve the image reconstruction quality and the discrimination between the signal and the background from misidentified hadrons and electrons. The technique models the development of the extensive air shower signal, recorded as a waveform per pixel, seen by CTAO telescopes' cameras. Model parameters are subsequently passed to random forest regressors and classifiers to extract information on the primary particle. The new reconstruction was applied to simulated data and to data from observations of the Crab Nebula performed by the LST-1. The event reconstruction method presented here shows promising performance improvements. The angular and energy resolution, and the sensitivity, are improved by 10 to 20% over most of the energy range. At low energy, improvements reach up to 22%, 47%, and 50%, respectively. A future extension of the method to stereoscopic analysis for telescope arrays will be the next important step., Comment: Accepted in A&A

High-quality audio data is a critical prerequisite for training robust text-to-speech models, which often limits the use of opportunistic or crowdsourced datasets. This paper presents an approach to overcome this limitation by implementing a denoising pipeline on the Catalan subset of Commonvoice, a crowd-sourced corpus known for its inherent noise and variability. The pipeline incorporates an audio enhancement phase followed by a selective filtering strategy. We developed an automatic filtering mechanism leveraging Non-Intrusive Speech Quality Assessment (NISQA) models to identify and retain the highest quality samples post-enhancement. To evaluate the efficacy of this approach, we trained a state of the art diffusion-based TTS model on the processed dataset. The results show a significant improvement, with an increase of 0.4 in the UTMOS Score compared to the baseline dataset without enhancement. This methodology shows promise for expanding the utility of crowdsourced data in TTS applications, particularly for mid to low resource languages like Catalan., Comment: Submitted to Iberspeech 2024

Microquasars are compact binary systems hosting collimated relativistic jets. They have long been proposed as cosmic-ray accelerators, probed via the gamma-ray emission produced by relativistic particles. However, the observational evidence is steadily increasing but limited: there are around twenty microquasars known to date, of which only three have so far been firmly detected in the GeV gamma-ray range, always in a flaring or special spectral state. Here we present Fermi-LAT observations of the region around the microquasar GRS 1915+105, which reveal the presence of previously unknown multi-GeV emission consistent with the position of the microquasar. No periodicity or variability is found, indicating a persistent source of gamma rays. The properties of the emission are consistent with a scenario in which protons accelerated in the jets interact with nearby gas and produce gamma rays. We find that if the jet has been operating at an average of 1% of the Eddington limit for 10% of the time that GRS 1915+105 spent in its current mass-transfer state, the transfer of 10% of the available power to protons is enough to reach the $\sim 3 \cdot 10^{49}$ erg required to explain the GeV signal. Therefore our results support a scenario in which microquasars with low-mass stellar companions act as hadronic accelerators, strengthening the idea that microquasars as a class contribute to at least some fraction of the observed cosmic-ray flux., Comment: Submitted to ApJL. 14 pages, 6 figures, 2 tables

We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission (SFC) through the lens of complex network analysis. This dataset, spanning 21 years with daily granularity, provides a unique view of the evolving social network between licensed professionals and their affiliated firms in Hong Kong's financial sector. Leveraging large language models, we classify firms (e.g., asset managers, banks) and infer the likely nationality and gender of employees based on their names. This application enhances the dataset by adding rich demographic and organizational context, enabling more precise network analysis. Our preliminary findings reveal key structural features, offering new insights into the dynamics of Hong Kong's financial landscape. We release the structured dataset to enable further research, establishing a foundation for future studies that may inform recruitment strategies, policy-making, and risk management in the financial industry., Comment: Complex Networks 2024

[SHORTENED VERSION] Observations of radio emission from young core-collapse supernovae (CCSNe) allow one to study the history of the pre-supernova stellar wind, trace the density structure of the ejected material, and probe the magnetohydrodynamics that describe the interaction between the two, as the forward shock expands into the circumstellar medium. The radio shell of supernova SN1993J has been observed with very long baseline interferometry (VLBI) for ~20 years, giving one of the most complete pictures of the evolution of a CCSN shock. However, different results about the expansion curve and properties of the radio-emitting structure have been reported by different authors, likely due to systematics in the data calibration and/or model assumptions made by each team. We aim to perform an analysis of the complete set of VLBI observations of SN1993J that accounts for different instrumental and source-intrinsic effects, by exploring the posterior probability distribution of a complete data model, using Markov chains. Our model accounts for antenna calibration effects, as well as different kinds of radio-emission structures for the supernova. The posterior parameter distributions strongly favor a spherical shell-like radio structure with a nonuniform radial intensity profile, with a broad brightness distribution that peaks close to or just above the region where the contact discontinuity is expected to be located. There is clear evidence of a relative widening of the shell width beyond day 2600-3300 after the explosion, due to an increased deceleration of the inner shell boundary. These results suggest a scenario in which the magnetic field is amplified mainly by the Rayleigh-Taylor instability, which emanates from the contact discontinuity. Furthermore, the reverse shock enters a region of the ejecta at around 3000 days, where the density distribution is substantially flatter., Comment: 17 pages, 11 figures. Accepted for publication in Astronomy & Astrophysics