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MALTA2 is a depleted monolithic active pixel sensor (DMAPS) designed for tracking at high rates and typically low detection threshold of $\sim150\,\mathrm{e^-}$. A precise knowledge of the threshold is crucial to understanding the charge collection in the pixel and specifying the environment for sensor application. A simple procedure is developed to calibrate the threshold to unit electrons making use of a dedicated charge injection circuit and an Fe-55 source with dominant charge deposition of $1600\, \mathrm{e^-}$. The injection voltage is determined which corresponds to the injection under Fe-55 exposure and is the basis for charge calibration. The charge injection circuit incorporates a capacitance with design value of $\mathrm{C_{inj}}=$ 230 aF. Experimentally, the average capacitance value for non-irradiated samples is found to be $\mathrm{C_{inj,exp}}=$ 257 aF. The 12 % divergence motivates the need for the presented precise calibration procedure, which is proposed to be performed for each MALTA2 sensor.

Information and communications technology and technology-enhanced learning have unquestionably transformed traditional teaching-learning processes and are positioned as key factors to promote quality education, one of the basic sustainable development goals of the 2030 agenda. Document annotation, which was traditionally carried out with pencil and paper and currently benefits from digital document annotation tools, is a representative example of this transformation. Using document annotation tools, students can enrich the documents with annotations that highlight the most relevant aspects of these documents. As the conceptual complexity of the learning domain increases, the annotation of the documents may require comprehensive domain knowledge and an expert analysis capability that students usually lack. Consequently, a proliferation of irrelevant, incorrect, and/or poorly decontextualized annotations may appear, while other relevant aspects are completely ignored by the students. The main hypothesis proposed by this paper is that the use of a guiding annotation ontology in the annotation activities is a keystone aspect to alleviate these shortcomings. Consequently, comprehension is improved, exhaustive content analysis is promoted, and meta-reflective thinking is developed. To test this hypothesis, we describe our own annotation tool, \@note, which fully implements this ontology-enhanced annotation paradigm, and we provide experimental evidence about how \@note can improve academic performance via a pilot study concerning critical literary annotation.

Artificial Intelligence (AI) faces growing challenges from evolving data protection laws and enforcement practices worldwide. Regulations like GDPR and CCPA impose strict compliance requirements on Machine Learning (ML) models, especially concerning personal data use. These laws grant individuals rights such as data correction and deletion, complicating the training and deployment of Large Language Models (LLMs) that rely on extensive datasets. Public data availability does not guarantee its lawful use for ML, amplifying these challenges. This paper introduces an adaptive system for mitigating risk of Personally Identifiable Information (PII) and Sensitive Personal Information (SPI) in LLMs. It dynamically aligns with diverse regulatory frameworks and integrates seamlessly into Governance, Risk, and Compliance (GRC) systems. The system uses advanced NLP techniques, context-aware analysis, and policy-driven masking to ensure regulatory compliance. Benchmarks highlight the system's effectiveness, with an F1 score of 0.95 for Passport Numbers, outperforming tools like Microsoft Presidio (0.33) and Amazon Comprehend (0.54). In human evaluations, the system achieved an average user trust score of 4.6/5, with participants acknowledging its accuracy and transparency. Observations demonstrate stricter anonymization under GDPR compared to CCPA, which permits pseudonymization and user opt-outs. These results validate the system as a scalable and robust solution for enterprise privacy compliance., Comment: This paper has been accepted at PPAI-25, the 6th AAAI Workshop on Privacy-Preserving Artificial Intelligence

The physical and orbital parameters of Trans-Neptunian Objects (TNOs) provide valuable information about the Solar System's formation and evolution. In particular, the characterization of binaries provides insights into the formation mechanisms that may be playing a role at such large distances from the Sun. Studies show two distinct populations, and (38628) Huya occupies an intermediate position between the unequal-size binaries and those with components of roughly equal sizes. In this work, we predicted and observed three stellar occultation events by Huya. Huya and its satellite - S/2012 (38628) 1 - were detected during occultations in March 2021 and again in June 2023. Additionally, an attempt to detect Huya in February 2023 resulted in an additional single-chord detection of the secondary. A spherical body with a minimum diameter of D = 165 km can explain the three single-chord observations and provide a lower limit for the satellite size. The astrometry of Huya's system, as derived from the occultations and supplemented by observations from the Hubble Space Telescope and Keck Observatory, provided constraints on the satellite orbit and the mass of the system. Therefore, assuming the secondary is in an equatorial orbit around the primary, the limb fitting was constrained by the satellite orbit position angle. The system density, calculated by summing the most precise measurement of Huya's volume to the spherical satellite average volume, is $\rho_{1}$ = 1073 $\pm$ 66 kg m$^{-3}$. The density that the object would have assuming a Maclaurin equilibrium shape with a rotational period of 6.725 $\pm$ 0.01 hours is $\rho_{2}$ = 768 $\pm$ 42 kg m$^{-3}$. This difference rules out the Maclaurin equilibrium assumption for the main body shape., Comment: Manuscript accepted by Planetary Science Journal (PSJ)

We report on a novel layout providing variable zoom in digital in-line holographic microscopy (VZ-DIHM). The implementation is in virtue of an electrically tunable lens (ETL) which enables to slightly shift the illumination source axial position without mechanical movement of any system component. Magnifications ranging from 15X to 35X are easily achievable using the same layout and resulting in a substantial variation of the total field of view (FOV). The performance of the proposed setup is, first, validated using a resolution test target where the main parameters are analyzed (theoretically and experimentally) and, second, corroborated analyzing biological sample (prostate cancer cells) showing its application to biomedical imaging.

Following the discovery of dimethyl sulfide (CH$_3$SCH$_3$, DMS) signatures in comet 67P/Churyumov-Gerasimenko, we report the first detection of this organosulfur species in the interstellar medium, during the exploration of an ultradeep molecular line survey performed toward the Galactic Center molecular cloud G+0.693-0.027 with the Yebes 40$\,$m and IRAM 30$\,$m telescopes. We derive a molecular column density of $N$ = (2.6 $\pm$ 0.3)$\times$10$^{13}$ cm$^{-2}$, yielding a fractional abundance relative to H$_2$ of $\sim$1.9$\times$10$^{-10}$. This implies that DMS is a factor of $\sim$1.6 times less abundant than its structural isomer CH$_3$CH$_2$SH and $\sim$30 times less abundant than its O-analogue dimethyl ether (CH$_3$OCH$_3$) toward this cloud, in excellent agreement with previous results on various O/S pairs. Furthermore, we find a remarkable resemblance between the relative abundance of DMS/CH$_3$OH in G+0.693-0.027 ($\sim$1.7$\times$10$^{-3}$) and in the comet ($\sim$1.3$\times$10$^{-3}$), further strengthening the connection between the chemical inventory of the interstellar medium and that of the minor bodies of the Solar System. Although the chemistry of DMS beyond Earth is yet to be fully disclosed, this discovery provides conclusive observational evidence on its efficient abiotic production in the interstellar medium, casting doubts about using DMS as a reliable biomarker in exoplanet science., Comment: 15 pages, 4 Figures and 5 Tables, re-submitted to ApJL after addressing the reviewers' comments. The initial submission was on November 26, 2024

The avoidance of water freezing is the holy grail in the cryopreservation of biological samples, food, and organs. Fast cooling rates are used to beat ice nucleation and avoid cell damage. This strategy can be enhanced by applying high pressures to decrease the nucleation rate, but the physics behind this procedure has not been fully understood yet. We perform computer experiments to investigate ice nucleation at high pressures consisting in embedding ice seeds in supercooled water. We find that the slowing down of the nucleation rate is mainly due to an increase of the ice I-water interfacial free energy with pressure. Our work also clarifies the molecular mechanism of ice nucleation for a wide pressure range. This study is not only relevant to cryopreservation, but also to water amorphization and climate change modeling., Comment: 6 pages and 3 figures

Organic diradicals are envisioned as elementary building blocks for designing a new generation of spintronic devices and have been used in constructing prototypical field effect transistors and non-linear optical devices. Open-shell systems, however, are also reactive, thus requiring design strategies to protect their radical character from the environment, especially when they are embedded into solid-state devices. Here, we report the persistence on a metallic surface of the diradical character of a diindeno[b,i]anthracene (DIAn) core protected by bulky end-groups. Our scanning tunneling spectroscopy measurements on single-molecules detected singlet-triplet excitations that were absent for DIAn species packed in assembled structures. Density functional theory simulations unravel that molecular geometry on the metal substrate can crucially modify the value of the single-triplet gap via the delocalization of the radical sites. The persistence of the diradical character over metallic substrates is a promising finding for integrating radical-based materials in functional devices.

This paper addresses the challenge of parking space detection in urban areas, focusing on the city of Granada. Utilizing aerial imagery, we develop and apply semantic segmentation techniques to accurately identify parked cars, moving cars and roads. A significant aspect of our research is the creation of a proprietary dataset specific to Granada, which is instrumental in training our neural network model. We employ Fully Convolutional Networks, Pyramid Networks and Dilated Convolutions, demonstrating their effectiveness in urban semantic segmentation. Our approach involves comparative analysis and optimization of various models, including Dynamic U-Net, PSPNet and DeepLabV3+, tailored for the segmentation of aerial images. The study includes a thorough experimentation phase, using datasets such as UDD5 and UAVid, alongside our custom Granada dataset. We evaluate our models using metrics like Foreground Accuracy, Dice Coefficient and Jaccard Index. Our results indicate that DeepLabV3+ offers the most promising performance. We conclude with future directions, emphasizing the need for a dedicated neural network for parked car detection and the potential for application in other urban environments. This work contributes to the fields of urban planning and traffic management, providing insights into efficient utilization of parking spaces through advanced image processing techniques., Comment: 9 pages, 5 figures

Context. The detection of the He I 10830 A triplet in exoplanet atmospheres has opened a new window for probing planetary properties, including atmospheric escape. Unlike Lyman alpha, the triplet is less affected by ISM absorption. Sufficient XUV stellar irradiation may trigger the formation of the He I triplet via photoionization and posterior recombination processes in the planet atmospheres. Only a weak trend between stellar XUV and the planetary He I strength has been observed so far. Aims. We aim to confirm this mechanism for producing the He I absorption in exoplanetary atmospheres by examining a sample of planetary systems. Methods. We obtained homogeneous measurements of the planetary He I line EW and consistently computed the stellar XUV ionizing irradiation. We first derived new coronal models for the planet-host stars. We used updated data from the X-exoplanets database, archival X-ray spectra of M-type stars (including AU Mic and Proxima Cen), and new XMM-Newton X-ray data obtained for the CARMENES project. These data were complemented at longer wavelengths with publicly available HST, FUSE, and EUVE spectra. A total of 75 stars are carefully analyzed to obtain a new calibration between X-ray and EUV emission. Results. Two distinct relationships between stellar X-ray emission (5-100 A) and EUV_H (100-920 A) or EUV_He (100-504 A) radiation are obtained to scale the emission from late-type stellar coronae. A total of 48 systems with reported planetary He I 10830 A studies, exhibit a robust relationship between the planetary He I feature and the ionizing XUV_He received by the planet, corrected by stellar and planetary radii, and the planet's gravitational potential. Some outliers could be explained by a different atmospheric composition or the lack of planetary gaseous atmospheres. This relation may be used to predict the He I 10830 A absorption in exoplanet atmospheres., Comment: Accepted by A&A. 12 pages, 5 figures in the main body (42 pages, 22 figures, 21 tables including appendices)

In Co$_x$NbSe$_2$, crystal symmetry, and cobalt site occupation drive the formation of two distinct magnetic phases. At $x = 1/4$, the centrosymmetric structure ($P$6$_3$/$mmc$) promotes Co-Co interactions leading to the formation of an $A$-type antiferromagnetic structure phase with a transition temperature of $T_N^A$ = 169 K. At $x = 1/3$, the non-centrosymmetric structure ($P$6$_3$22) induces a lower-temperature magnetic phase with $T_N^S$ = 28 K. We report the coexistence of both substructures within a superlattice, with a nuclear propagation vector of (1/3, 1/3, 0) relative to the host lattice. Single crystals of Co$_{0.28}$NbSe$_2$ exhibit both magnetic transitions, with $T_N^A$ corresponding to the $x \sim 1/4$ phase and $T_N^S$ corresponding to the $x \sim 1/3$ phase. Magnetic susceptibility and specific heat measurements confirm these transitions, although only the high-temperature $T_N^A$ phase significantly affects resistivity. We successfully isolate each phase in powder samples, while single crystals with an intercalation ratio of $x = 0.28$ display the coexistence of both phases in a single sample. Using single-crystal neutron diffraction, we solved the magnetic structure of the high-temperature centrosymmetric phase ($T_N^A$), and neutron powder diffraction revealed the double-$q$ magnetic structure of the low-temperature noncentrosymmetric phase ($T_N^S$)

Fundamental research on two-dimensional (2D) magnetic systems based on van der Waals materials has been gaining traction rapidly since their recent discovery. With the increase of recent knowledge, it has become clear that such materials have also a strong potential for applications in devices that combine magnetism with electronics, optics, and nanomechanics. Nonetheless, many challenges still lay ahead. Several fundamental aspects of 2D magnetic materials are still unknown or poorly understood, such as their often-complicated electronic structure, optical properties, and magnetization dynamics, and their magnon spectrum. To elucidate their properties and facilitate integration in devices, advanced characterization techniques and theoretical frameworks need to be developed or adapted. Moreover, developing synthesis methods which increase critical temperatures and achieve large-scale, high-quality homogeneous thin films is crucial before these materials can be used for real-world applications. Therefore, the field of 2D magnetic materials provides many challenges and opportunities for the discovery and exploration of new phenomena, as well as the development of new applications. This Roadmap presents the background, challenges, and potential research directions for various relevant topics in the field on the fundamentals, synthesis, characterization, and applications. We hope that this work can provide a strong starting point for young researchers in the field and provide a general overview of the key challenges for more experienced researchers., Comment: 87 pages, 24 figures. Roadmap based on the discussions during the workshop on Quantum Magnetic Materials hosted by the Lorentz Centre in Leiden, the Netherlands (Oct. 2023)

Filtering is concerned with online estimation of the state of a dynamical system from partial and noisy observations. In applications where the state is high dimensional, ensemble Kalman filters are often the method of choice. This paper establishes long-time accuracy of ensemble Kalman filters. We introduce conditions on the dynamics and the observations under which the estimation error remains small in the long-time horizon. Our theory covers a wide class of partially-observed chaotic dynamical systems, which includes the Navier-Stokes equations and Lorenz models. In addition, we prove long-time accuracy of ensemble Kalman filters with surrogate dynamics, thus validating the use of machine-learned forecast models in ensemble data assimilation., Comment: 40 pages, 4 figures

Magnetic skyrmions are chiral spin textures with rich physics and great potential for unconventional computing. Typically, skyrmions form in bulk crystals with reduced symmetry or ultrathin film multilayers involving heavy metals. Here, we demonstrate the formation of fractional Bloch skyrmion tubes at room temperature by 3D printing ferromagnetic double-helix nanowires with two regions of opposite chirality. Using X-ray microscopy and micromagnetic simulations, we show that the coexistence of vortex and anti-parallel spin states induces the formation of fractional skyrmion tubes at zero magnetic fields, minimising the energy cost of breaking the coupling between geometric and magnetic chirality. We also demonstrate control over zero-field states, including pure vortex, or mixed skyrmion-vortex states, highlighting the magnetic reconfigurability of these 3D nanowires. This work shows how interfacing chiral geometries at the nanoscale can enable advanced forms of topological spintronics.

Let $C$ be a cusp in $(\mathbb C^2,\mathbf 0)$ with Puiseux pair $(n,m)$. This paper is devoted to show how the semimodule of differential values of $C$ determines a subset of the roots of the Bernstein-Sato polynomial of $C$. We add more precise results when the multiplicity of the cusp is $n\leq 4$.

Multiplicity studies greatly benefit from focusing on M dwarfs because they are often paired in a variety of configurations with both stellar and substellar objects, including exoplanets. We aim to address the observed multiplicity of M dwarfs by conducting a systematic analysis using the latest available astrophotometric data. For every star in a sample of 2214 M dwarfs from the CARMENES catalogue, we investigated the existence of resolved and unresolved physical companions in the literature and in all-sky surveys, especially in Gaia DR3 data products. We covered a very wide range of separations, from known spectroscopic binaries in tight arrangements $\sim$0.01 au to remarkably separated ultra-wide pairs ($\sim$10$^5$ au). We identified 835 M dwarfs in 720 multiple systems, predominantly binaries. Thus, we propose 327 new binary candidates based on Gaia data. If these candidates are finally confirmed, we expect the multiplicity fraction of M dwarfs to be 40.3$^{+2.1}_{-2.0}$ %. When only considering the systems already identified, the multiplicity fraction is reduced to 27.8$^{+1.9}_{-1.8}$ %. This result is in line with most of the values published in the literature. We also identified M-dwarf multiple systems with FGK, white dwarf, ultra-cool dwarf, and exoplanet companions, as well as those in young stellar kinematic groups. We studied their physical separations, orbital periods, binding energies, and mass ratios. We argue that based on reliable astrometric data and spectroscopic investigations from the literature (even when considering detection biases), the multiplicity fraction of M dwarfs could still be significantly underestimated. This calls for further high-resolution follow-up studies to validate these findings.

This paper presents the SareQuant project, which aims to evolve the Basque NREN (National Research and Education Networks) into a quantum-based communication infrastructure. SareQuant focuses on the network design and on the integration of quantum technologies into real-world scenarios and applications. Therefore, this paper provides insights into the opportunities and challenges regarding the integration of quantum technologies, thus paving the way for a secure and advanced Quantum Internet.

This paper studies the estimation of large precision matrices and Cholesky factors obtained by observing a Gaussian process at many locations. Under general assumptions on the precision and the observations, we show that the sample complexity scales poly-logarithmically with the size of the precision matrix and its Cholesky factor. The key challenge in these estimation tasks is the polynomial growth of the condition number of the target matrices with their size. For precision estimation, our theory hinges on an intuitive local regression technique on the lattice graph which exploits the approximate sparsity implied by the screening effect. For Cholesky factor estimation, we leverage a block-Cholesky decomposition recently used to establish complexity bounds for sparse Cholesky factorization., Comment: 28 pages

Surface plasmon polaritons have received much attention over the last decades in fields such as photonics or nanotechnology due to their inherent high sensitivity to metal surface variations (e.g., presence of adsorbates or changes in the roughness). Because of this important property, it is expected that they will find promising major applications in widely cross-disciplinary areas ranging from material science to medicine. Motivated by this ever-growing interest, here we introduce a novel theoretical framework suitable to design new types of structured paraxial surface plasmon beams and to control their propagation along the interface between a dielectric and a lossy metal. This is possible by virtue of a convenient Hermite-Gaussian mode expansion, which constitutes a complete basis set upon which new types of structured paraxial plasmon beams can be generated. The beams obtained from this method present a rather peculiar feature, as they exhibit local intensity maxima at different propagation distances. This way of creating tightly confined structured light allows us control where to place the beam energy. This, thus, opens up worth exploring pathways to manipulate light propagation along metal surfaces at the nanoscale. As a proof-of-concept, we provide numerical evidence of the feasibility of the method by considering the analysis of the propagation of Airy-based surface plasmon polaritons along an air-silver interface., Comment: 20 pages, 3 figures (plus 6 pages with supplemental information)

We give a new construction of binary quantum codes that enables the generation of a CSS-T code from any given CSS code. Using this construction, we prove the existence of asymptotically good binary CSS-T codes, resolving a previously open problem in the literature. Furthermore, we demonstrate that the same result holds for binary quantum low-density parity check CSS-T codes, and establish the existence of asymptotically good CSS codes that support any given $Z$ rotation transversally. Finally, we analyze the structure of the logical operators corresponding to certain non-Clifford gates supported by the quantum codes obtained from our construction.

We present a new study on the Gravity-Mediated Dark Matter (GMDM) scenario, where interactions between dark matter (DM) and the Standard Model are mediated by spin-two particles. Expanding on this established framework, we explore a novel regime characterized by a low reheating temperature that offers an alternative to the conventional thermal relic paradigm. This approach opens new possibilities for understanding the dynamics of the dark sector, encompassing both the dark matter particles (fermion, scalar and vector) and the spin-two mediators. Our analysis examines the constraints imposed by the relic abundance of DM, collider experiments, and direct detection searches, spanning a wide mass range for the dark sector, from very light to extremely heavy states. This work opens new possibilities for the phenomenology of GMDM., Comment: 26 pages, 4 figures

We study the potential of symbolic regression (SR) to derive compact and precise analytic expressions that can improve the accuracy and simplicity of phenomenological analyses at the Large Hadron Collider (LHC). As a benchmark, we apply SR to equation recovery in quantum electrodynamics (QED), where established analytical results from quantum field theory provide a reliable framework for evaluation. This benchmark serves to validate the performance and reliability of SR before extending its application to structure functions in the Drell-Yan process mediated by virtual photons, which lack analytic representations from first principles. By combining the simplicity of analytic expressions with the predictive power of machine learning techniques, SR offers a useful tool for facilitating phenomenological analyses in high energy physics., Comment: 7 pages, 7 figures, 3 tables. Accepted for the Machine Learning and the Physical Sciences Workshop NeurIPS 2024

The production of silicon monoxide (SiO) can be considered as a fingerprint of shock interaction. In this work, we use high-sensitivity observations of the SiO (2-1) and H$^{13}$CO$^{+}$ (1-0) emission to investigate the broad and narrow SiO emission toward 146 massive star-forming regions in the ATOMS survey. We detected SiO emission in 136 regions and distinguished broad and narrow components across the extension of 118 sources (including 58 UC $H_{II}$ regions) with an average angular resolution of 2.5$^{\prime}$$^{\prime}$. The derived SiO luminosity ($L_{SiO}$) across the whole sample shows that the majority of $L_{SiO}$ (above 66$\%$) can be attributed to broad SiO, indicating its association with strong outflows. The comparison of the ALMA SiO images with the filamentary skeletons identified from H$^{13}$CO$^{+}$ and in the infrared data (at 4.5, 8, and 24 $mu$m), further confirms that most SiO emission originates from outflows. However, note that for nine sources in our sample, the observed SiO emission may be generated by expanding UC $H_{II}$ regions. There is a moderate positive correlation between the bolometric luminosity ($L_{bol}$) and $L_{SiO}$ for both components (narrow and broad). The UC $H_{II}$ sources show a weaker positive correlation between $L_{bol}$ and $L_{SiO}$ and higher $L_{SiO}$ compared to the sources without UC $H_{II}$ regions. These results imply that the SiO emission from UC $H_{II}$ sources might be affected by UV-photochemistry induced by UC $H_{II}$ regions., Comment: 23 pages, 14 figures

Spin qubits in quantum dots are a promising technology for quantum computing due to their fast response time and long coherence times. An electromagnetic pulse is applied to the system for a specific duration to perform a desired rotation. To avoid decoherence, the amplitude and gate time must be highly accurate. In this work, we aim to study the impact of leakage during the gate time evolution of a spin qubit encoded in a double quantum dot device. We prove that, in the weak interaction regime, leakage introduces a shift in the phase of the time evolution operator, causing over- or under-rotations. Indeed, controlling the leakage terms is useful for adjusting the time needed to perform a quantum computation. This is crucial for running fault-tolerant algorithms and is beneficial for Quantum Error Mitigation techniques., Comment: 13 pages, 6 figures

Modeling observations as random distributions embedded within Wasserstein spaces is becoming increasingly popular across scientific fields, as it captures the variability and geometric structure of the data more effectively. However, the distinct geometry and unique properties of Wasserstein space pose challenges to the application of conventional statistical tools, which are primarily designed for Euclidean spaces. Consequently, adapting and developing new methodologies for analysis within Wasserstein spaces has become essential. The space of distributions on $\mathbb{R}^d$ with $d>1$ is not linear, and ''mimic'' the geometry of a Riemannian manifold. In this paper, we extend the concept of statistical depth to distribution-valued data, introducing the notion of {\it Wasserstein spatial depth}. This new measure provides a way to rank and order distributions, enabling the development of order-based clustering techniques and inferential tools. We show that Wasserstein spatial depth (WSD) preserves critical properties of conventional statistical depths, notably, ranging within $[0,1]$, transformation invariance, vanishing at infinity, reaching a maximum at the geometric median, and continuity. Additionally, the population WSD has a straightforward plug-in estimator based on sampled empirical distributions. We establish the estimator's consistency and asymptotic normality. Extensive simulation and real-data application showcase the practical efficacy of WSD.

In-operando techniques enable real-time measurement of intricate physical properties at the micro- and nano-scale under external stimuli, allowing the study of a wide range of materials and functionalities. In nanomagnetism, in-operando techniques greatly benefit from precise three-dimensional (3D) magnetic field control, enabling access to complex magnetic states forming in systems where multiple energies are set to compete with each other. However, achieving such precision is challenging and uncommon, as specific applications impose constraints on the type and geometry of magnetic field sources, limiting their capabilities. Here, we introduce an approach that leverages machine learning algorithms to achieve precise 3D magnetic field control using a hexapole electromagnet that is composed of three independent, non-collinear dipole electromagnets. In our experimental setup, magnetic field sensors are placed at a distance from the sample position due to inherent constraints, leading to indirect field measurements that differ from the magnetic field experienced by the sample. We find that the existing relationship between the remote and sample frames of reference is non-linear, thus requiring a more complex calibration method. To address this, we employ a multi-layer perceptron neural network that processes multiple inputs from a dynamic magnetic field sequence, effectively capturing the time-dependent non-linear field response. The network achieves high calibration accuracy and demonstrates exceptional generalization to unseen magnetic field sequences. This study highlights the significant potential of machine learning in achieving high-precision control and calibration, crucial for in-operando experiments where direct measurement at the point of interest is not possible.

Heatwaves (HWs) are extreme atmospheric events that produce significant societal and environmental impacts. Predicting these extreme events remains challenging, as their complex interactions with large-scale atmospheric and climatic variables are difficult to capture with traditional statistical and dynamical models. This work presents a general method for driver identification in extreme climate events. A novel framework (STCO-FS) is proposed to identify key immediate (short-term) HW drivers by combining clustering algorithms with an ensemble evolutionary algorithm. The framework analyzes spatio-temporal data, reduces dimensionality by grouping similar geographical nodes for each variable, and develops driver selection in spatial and temporal domains, identifying the best time lags between predictive variables and HW occurrences. The proposed method has been applied to analyze HWs in the Adda river basin in Italy. The approach effectively identifies significant variables influencing HWs in this region. This research can potentially enhance our understanding of HW drivers and predictability., Comment: 28 pages, 10 figures, 4 tables

The theory of interfacial properties in liquid-liquid or liquid-vapour systems is nearly 200 years old. The advent of computational tools has greatly advanced the field, mainly through the use of Molecular Dynamics simulations. Despite the successes and advances in the theory of interfacial phenomena for liquid-liquid systems, the study of solid-liquid interfaces remains a challenge both theoretically and experimentally. The main reason why the treatment of solid-liquid systems has fallen behind that of liquid-liquid systems is that there are complications that arise whenever an interface involving solid systems is considered involving both theory of the solid-liquid interface and the calculations using MD simulations. An example of the former is that, contrary to the liquid-liquid case, the interfacial properties of solids depend on the lattice orientation. The main complications in these calculations arise from the fact that for solids the ``mechanical route'' cannot be used. To overcome this problem, several numerical approaches were proposed. The main purpose of this review is to provide an overview of these different methodologies and to discuss their strengths and weaknesses. We classify these methodologies into two main groups: direct and indirect methods. Direct methods are those that can calculate directly the properties of interfaces, while in indirect approaches the properties of the interface are not the primary result of the simulations. We also included a discussion on the origin of the difficulties in considering solid interfaces from a thermodynamic point of view. In the second part of the review, we discuss two key related topics: nucleation theory and curved interfaces. They both represent an important problem in the study of interfaces and in the context of solid-liquid ones for which the research is still extremely active., Comment: 111 pages, 14 figures

In this paper, a parallel computing method is proposed to perform the background denoising and wheezing detection from a multi-channel recording captured during the auscultation process. The proposed system is based on a non-negative matrix factorization (NMF) approach and a detection strategy. Moreover, the initialization of the proposed model is based on singular value decomposition to avoid dependence on the initial values of the NMF parameters. Additionally, novel update rules to simultaneously address the multichannel denoising while preserving an orthogonal constraint to maximize source separation have been designed. The proposed system has been evaluated for the task of wheezing detection showing a significant improvement over state-of-the-art algorithms when noisy sound sources are present. Moreover, parallel and high-performance techniques have been used to speedup the execution of the proposed system, showing that it is possible to achieve fast execution times, which enables its implementation in real-world scenarios.

Content moderation typically combines the efforts of human moderators and machine learning models. However, these systems often rely on data where significant disagreement occurs during moderation, reflecting the subjective nature of toxicity perception. Rather than dismissing this disagreement as noise, we interpret it as a valuable signal that highlights the inherent ambiguity of the content,an insight missed when only the majority label is considered. In this work, we introduce a novel content moderation framework that emphasizes the importance of capturing annotation disagreement. Our approach uses multitask learning, where toxicity classification serves as the primary task and annotation disagreement is addressed as an auxiliary task. Additionally, we leverage uncertainty estimation techniques, specifically Conformal Prediction, to account for both the ambiguity in comment annotations and the model's inherent uncertainty in predicting toxicity and disagreement.The framework also allows moderators to adjust thresholds for annotation disagreement, offering flexibility in determining when ambiguity should trigger a review. We demonstrate that our joint approach enhances model performance, calibration, and uncertainty estimation, while offering greater parameter efficiency and improving the review process in comparison to single-task methods., Comment: 35 pages, 1 figure

JWST, despite not being designed to observe astrophysical phenomena that vary on rapid time scales, can be an unparalleled tool for such studies. If timing systematics can be controlled, JWST will be able to open up the sub-second infrared timescale regime. Rapid time-domain studies, such as lag measurements in accreting compact objects and Solar System stellar occultations, require both precise inter-frame timing and knowing when a time series begins to an absolute accuracy significantly below 1s. In this work we present two long-duration observations of the deeply eclipsing double white dwarf system ZTF J153932.16+502738.8, which we use as a natural timing calibrator to measure the absolute timing accuracy of JWST's clock. From our two epochs, we measure an average clock accuracy of $0.12\pm0.06$s, implying that JWST can be used for sub-second time-resolution studies down to the $\sim100$ms level, a factor $\sim5$ improvement upon the pre-launch clock accuracy requirement. We also find an asymmetric eclipse profile in the F322W2 band, which we suggest has a physical origin., Comment: 16 pages, 13 figures, accepted for publication in AJ

We consider an SPDE driven by a parabolic second order partial differential operator with a nonlinear random external forcing defined by a Gaussian noise that is white in time and has a spatially homogeneous covariance. We prove existence and uniqueness of a random field solution to this SPDE. Our main result concerns the space-time sample path regularity of its solution., Comment: 28 pages

The goal of optimal transport (OT) is to find optimal assignments or matchings between data sets which minimize the total cost for a given cost function. However, sometimes the cost function is unknown but we have access to (parts of) the solution to the OT problem, e.g. the OT plan or the value of the objective function. Recovering the cost from such information is called inverse OT and has become recently of certain interest triggered by novel applications, e.g. in social science and economics. This raises the issue under which circumstances such cost is identifiable, i.e., it can be uniquely recovered from other OT quantities. In this work we provide sufficient and necessary conditions for the identifiability of the cost function on finite ground spaces. We find that such conditions correspond to the combinatorial structure of the corresponding linear program., Comment: 24 pages, 2 figures

Computational fluid dynamics (CFD) is a specialised branch of fluid mechanics that utilises numerical methods and algorithms to solve and analyze fluid-flow problems. One promising avenue to enhance CFD is the use of quantum computing, which has the potential to resolve nonlinear differential equations more efficiently than classical computers. Here, we try to answer the question of which regimes of nonlinear partial differential equations (PDEs) for fluid dynamics can have an efficient quantum algorithm. We propose a connection between the numerical parameter, $R$, that guarantees efficiency in the truncation of the Carleman linearisation, and the physical parameters that describe the fluid flow. This link can be made thanks to the Kolmogorov scale, which determines the minimum size of the grid needed to properly resolve the energy cascade induced by the nonlinear term. Additionally, we introduce the formalism for vector field simulation in different spatial dimensions, providing the discretisation of the operators and the boundary conditions.

We report on the discovery of a very prominent mid-infrared (18-25 {\mu}m) excess associated with the trans-Neptunian dwarf planet (136472) Makemake. The excess, detected by the MIRI instrument of the James Webb Space Telescope, along with previous measurements from the Spitzer and Herschel space telescopes, indicates the occurrence of temperatures of about 150 K, much higher than what solid surfaces at Makemake's heliocentric distance could reach by solar irradiation. We identify two potential explanations: a continuously visible, currently active region, powered by subsurface upwelling and possibly cryovolcanic activity, covering <1% of Makemake's surface, or an as yet undetected ring containing very small carbonaceous dust grains, which have not been seen before in trans-Neptunian or Centaur rings. Both scenarios point to unprecedented phenomena among trans-Neptunian objects and could greatly impact our understanding of these distant worlds., Comment: Accepted for publication in The Astrophysical Journal Letters

We investigate the production of dark radiation (DR) from axions and axion-like particles (ALPs) as potential origins of dark matter. Focusing on the dark matter misalignment mechanism, we examine non-thermal, pre-inflationary scenarios that could lead to the generation of DR. A key part of our analysis involves a Bayesian approach to confront ALP parameter space with current cosmological data. Additionally, we explore whether DR production could offer solutions to persistent cosmological anomalies, particularly those related to the Hubble constant $H_0$ tension and the $S_8$ parameter discrepancy. Our findings aim to shed new light on the role of ALPs in addressing these open issues in cosmology., Comment: 37 pages, 6 figures, 3 tables. v2: updated references and figures

In these proceedings we present the main results of [arXiv:2311.04280 [hep-ph]], where we explore the phenomenological implications of multi-Higgs boson production through longitudinal vector boson scattering within the framework of Effective Field Theories (EFTs). We derive compact expressions for effective tree-level amplitudes involving up to four final-state Higgs bosons. Subsequently, we compute total cross sections for scenarios relevant to the LHC, where we observe that the general Higgs Effective Theory (HEFT) prediction avoids the strong suppression found in the Standard Model Effective Field Theory (SMEFT), typically expected to be several orders of magnitude smaller., Comment: Proceedings of the 42nd International Conference on High Energy Physics (ICHEP2024), 18-24 July 2024, Prague, Czech Republic

We study the connections between ordinary differential equations and optimization algorithms in a non-Euclidean setting. We propose a novel accelerated algorithm for minimising convex functions over a convex constrained set. This algorithm is a natural generalization of Nesterov's accelerated gradient descent method to the non-Euclidean setting and can be interpreted as an additive Runge-Kutta algorithm. The algorithm can also be derived as a numerical discretization of the ODE appearing in Krichene et al. (2015a). We use Lyapunov functions to establish convergence rates for the ODE and show that the discretizations considered achieve acceleration beyond the setting studied in Krichene et al. (2015a). Finally, we discuss how the proposed algorithm connects to various equations and algorithms in the literature., Comment: 25 pages, 5 figures

Recent work has used optimal transport ideas to generalize the notion of (center-outward) quantiles to dimension $d\geq 2$. We study the robustness properties of these transport-based quantiles by deriving their breakdown point, roughly, the smallest amount of contamination required to make these quantiles take arbitrarily aberrant values. We prove that the transport median defined in Chernozhukov et al.~(2017) and Hallin et al.~(2021) has breakdown point of $1/2$. Moreover, a point in the transport depth contour of order $\tau\in [0,1/2]$ has breakdown point of $\tau$. This shows that the multivariate transport depth shares the same breakdown properties as its univariate counterpart. Our proof relies on a general argument connecting the breakdown point of transport maps evaluated at a point to the Tukey depth of that point in the reference measure.

Experiments have confirmed the presence of a mass gap between the Standard Model and potential New Physics. Consequently, the exploration of effective field theories to detect signals indicative of Physics Beyond the Standard Model is of great interest. In this study, we examine a non-linear realization of the electroweak symmetry breaking, wherein the Higgs is a singlet with independent couplings, and Standard Model fields are additionally coupled to heavy bosonic resonances. We present a next-to-leading-order determination of the oblique $S$ and $T$ parameters. Comparing our predictions with experimental values allows us to impose constraints on resonance masses, requiring them to exceed the TeV scale ($M_R > 2\,$TeV). This finding aligns with our earlier analysis, employing a less generalized approach and the experimental bounds of that time, where we computed these observables., Comment: 6 pages, 2 figures. Talk given at the 42nd International Conference on High Energy Physics - ICHEP2024 (18-24 July 2024, Prague, Czech Republic)

The aim of these notes is to demonstrate the potential for ideas in machine learning to impact on the fields of inverse problems and data assimilation. The perspective is one that is primarily aimed at researchers from inverse problems and/or data assimilation who wish to see a mathematical presentation of machine learning as it pertains to their fields. As a by-product, we include a succinct mathematical treatment of various topics in machine learning., Comment: 254 pages

Qubit-based variational quantum algorithms have undergone rapid development in recent years but still face several challenges. In this context, we propose a symmetry-enhanced digitized counterdiabatic quantum algorithm utilizing qudits instead of qubits. This approach offers three types of compression as compared to with respect to conventional variational circuits. First, compression in the circuit depth is achieved by counterdiabatic protocols. Second, information about the problem is compressed by replacing qubits with qudits, allowing for a more efficient representation of the problem. Lastly, the number of parameters is reduced by employing the symmetries of the system. We illustrate this approach by tackling a graph-based optimization problem Max-3-Cut and a highly-entangled state preparation, the qutrit W state. As our numerical results show, we achieve a better convergence with a lower circuit depth and less measurement overhead in all the cases considered. This work leads to a better design of shallow variational quantum circuits, improving the feasibility of their implementation on near-term qudit devices

The quadratically regularized optimal transport problem is empirically known to have sparse solutions: its optimal coupling $\pi_{\varepsilon}$ has sparse support for small regularization parameter $\varepsilon$, in contrast to entropic regularization whose solutions have full support for any $\varepsilon>0$. Focusing on continuous and scalar marginals, we provide the first precise description of this sparsity. Namely, we show that the support of $\pi_{\varepsilon}$ shrinks to the Monge graph at the sharp rate $\varepsilon^{1/3}$. This result is based on a detailed analysis of the dual potential $f_{\varepsilon}$ for small $\varepsilon$. In particular, we prove that $f_{\varepsilon}$ is twice differentiable a.s. and bound the second derivative uniformly in $\varepsilon$, showing that $f_{\varepsilon}$ is uniformly strongly convex. Convergence rates for $f_{\varepsilon}$ and its derivative are also obtained.

Excess molar enthalpies, $H_{\text{m}}^{\text{E}}$, have been measured using a Tian-Calvet microcalorimeter for the systems CH$_3$(CH$_2$)$_{u-1}$OH ($u$ = 1,2,3,4,7,10) + cyclohexylamine at 298.15 K and 0.1 MPa. The $H_{\text{m}}^{\text{E}}$ values are large and negative, indicating the existence of strong interactions between unlike molecules, which is consistent with the also large and negative excess molar volumes, $V_{\text{m}}^{\text{E}}$, of these solutions, previously measured by us. The contribution from the equation of state term to $H_{\text{m}}^{\text{E}}$ has been evaluated for the 1-alkanol + cyclohexylamine, or + 1-hexylamine, or + aniline mixtures, and the corresponding excess molar internal energies at constant volume, $U_{\text{m,}V}^{\text{E}}$, have been determined. It is shown that such contribution is particularly important for the methanol + aniline system, in such a way that the excess functions $H_{\text{m}}^{\text{E}}$ and $U_{\text{m,}V}^{\text{E}}$ have different sign at $x_1$ = 0.5. The DISQUAC and ERAS models have been applied to the cyclohexylamine systems, and the interaction parameters have been reported. DISQUAC improves ERAS results on $H_{\text{m}}^{\text{E}}$. The latter model describes correctly the $V_{\text{m}}^{\text{E}}$ curves. The variation of of CH$_3$(CH$_2$)$_{u-1}$OH + cyclohexylamine, or + 1-hexylamine, or + aniline mixtures with $u$ along a homologous series with a given amine, or with the amine in mixtures with a given 1-alkanol is discussed in terms of the different interactional contributions to $H_{\text{m}}^{\text{E}}$.

Autoresonance is a phenomenon of physical interest that may take place when a nonlinear oscillator is forced at a frequency that varies slowly. The stroboscopic averaging method (SAM), which provides an efficient numerical technique for the integration of highly oscillatory systems, cannot be used directly to study autoresonance due to the slow changes of the forcing frequency. We study how to modify SAM to cater for such slow variations. Numerical experiments show the computational advantages of using SAM.

Trans-Neptunian objects (TNOs) are considered to be among the most primitive objects in our Solar System. Knowledge of their primary physical properties is essential for understanding their origin and the evolution of the outer Solar System. We predicted a stellar occultation by this TNO for 2020 October 23 UT and ran a specific campaign to investigate this event. We derived the projected profile shape and size from the occultation observations by means of an elliptical fit to the occultation chords. We also performed photometric observations of (143707) 2003 UY117 to obtain the absolute magnitude and the rotational period from the observed rotational light curve. Finally, we combined these results to derive the three-dimensional shape, volume-equivalent diameter, and geometric albedo for this TNO. From the stellar occultation, we obtained a projected ellipse with axes of $(282 \pm 18) \times (184 \pm 32)$ km. The area-equivalent diameter for this ellipse is $D_\textrm{eq,A} = 228 \pm 21$ km. From our photometric $R$ band observations, we derived an absolute magnitude of $H_V = 5.97 \pm 0.07$ mag using $V-R = 0.46 \pm 0.07$ mag, which was derived from a $V$ band subset of these data. The rotational light curve has a peak-to-valley amplitude of $\Delta m = 0.36 \pm 0.13$ mag. We find the most likely rotation period to be $P = 12.376 \pm 0.0033$ hours. By combining the occultation with the rotational light curve results and assuming a triaxial ellipsoid, we derived axes of $a \times b \times c = (332 \pm 24)$ km $\times$ $(216 \pm 24)$ km $\times$ $(180\substack{+28\\-24})$ km for this ellipsoid, and therefore a volume-equivalent diameter of $D_\textrm{eq,V} = 235 \pm 25$ km. Finally, the values for the absolute magnitude and for the area-equivalent diameter yield a geometric albedo of $p_V = 0.139 \pm 0.027$., Comment: 9 pages, 7 figures, accepted for publication in Astronomy and Astrophysics on Sept 13, 2024

Excess molar enthalpies, $H_{\text{m}}^{\text{E}}$, at 298.15 K and 0.1 MPa have been measured by means of a Tian-Calvet microcalorimeter for the systems benzylamine (phenylmethanamine) + heptane, or + methanol, or + 1-propanol, or + 1-pentanol, or + 1-heptanol, or + 1-decanol. In addition, excess molar volumes, $V_{\text{m}}^{\text{E}}$, at the same conditions have been also determined using a densimeter Anton Paar model DSA 5000 for the benzylamine + heptane mixture. The $H_{\text{m}}^{\text{E}}$ of this solution is large and positive since at 298.15 K the system temperature is close to its upper critical solution temperature. Thus, systems with n-alkanes show positive deviations from the Raoult's law. The measured $|V_{\text{m}}^{\text{E}}|$ values are low, indicating the existence of large structural effects. $H_{\text{m}}^{\text{E}}$ values of mixtures involving 1-alkanols are large and negative. That is, interactions between unlike molecules are dominant and the systems are characterized by negative deviations from Raoult's law. It is shown that the enthalpy of the hydrogen bonding between molecules of 1-alkanol and benzyalmine are more negative than those between 1-alkanol molecules. The $V_{\text{m}}^{\text{E}}$ values of the systems with 1-alkanols are also large and negative, and are determined mainly by interactional effects since they increase in line with $H_{\text{m}}^{\text{E}}$ and with the alcohol size. The different contributions to $H_{\text{m}}^{\text{E}}$ have been evaluated. The systems have been studied using the DISQUAC and ERAS models. ERAS describes correctly the $V_{\text{m}}^{\text{E}}$ function. DISQUAC largely improves ERAS results on $H_{\text{m}}^{\text{E}}$ or on excess molar heat capacities at constant pressure for the mixtures with 1-alkanols, which underlines that physical interactions are very relevant in such solutions.