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The speed of response by search and rescue teams at sea is of vital importance, as survival may depend on it. Recent technological advancements have led to the development of more efficient systems for locating individuals involved in a maritime incident, such as the use of Unmanned Aerial Vehicles (UAVs) equipped with cameras and other integrated sensors. Over the past decade, several researchers have contributed to the development of automatic systems capable of detecting people using aerial images, particularly by leveraging the advantages of deep learning. In this article, we provide a comprehensive review of the existing literature on this topic. We analyze the methods proposed to date, including both traditional techniques and more advanced approaches based on machine learning and neural networks. Additionally, we take into account the use of synthetic data to cover a wider range of scenarios without the need to deploy a team to collect data, which is one of the major obstacles for these systems. Overall, this paper situates the reader in the field of detecting people at sea using aerial images by quickly identifying the most suitable methodology for each scenario, as well as providing an in-depth discussion and direction for future trends.

We analyze the dynamics of a gravitational bounded cloud of generic bosons or a boson star in the non-relativistic regime, assuming from the very beginning that the boson star is in a Bose-Einstein condensed state. Also, we have taken into account multi-particle interactions within the boson star, which are described through the so-called logarithmic potential. Assuming energy conservation conditions at any time, we are able to describe the boson star as a some kind of gravitational quantum liquid, or more specifically, as a macroscopic gravitational quantum droplet. The assumption of logarithmic interactions, lead us to establish several scenarios in which the system is able to oscillates around the equilibrium radius. The approach analyzed in the present report shows that the interpretation of a boson star as a macroscopic gravitational quantum droplet can be applied to the dynamics analysis of a large number of systems on different size scales., Comment: 15 pages, 10 figures

Stacking monolayers of transition metal dichalcogenides (TMDs) has led to the discovery of a plethora of new exotic phenomena, resulting from moir\'e pattern formation. Due to the atomic thickness and high surface-to-volume ratio of heterostructures, the interfaces play a crucial role. Fluctuations in the interlayer distance affect interlayer coupling and moir\'e effects. Therefore, to access the intrinsic properties of the TMD stack, it is essential to obtain a clean and uniform interface between the layers. Here, we show that this is achieved by ironing with the tip of an atomic force microscope. This post-stacking procedure dramatically improves the homogeneity of the interfaces, which is reflected in the optical response of the interlayer exciton. We demonstrate that ironing improves the layer coupling, enhancing moir\'e effects and reducing disorder. This is crucial for the investigation of TMD heterostructure physics, which currently suffers from low reproducibility.

Convergent-beam electron diffraction (CBED) is a well-established probe for spatial symmetries of crystalline samples, mainly exploiting the well-defined mapping between the diffraction groups (symmetry group of CBED patterns) and the point-group symmetries of the crystalline sample. In this work, we extend CBED to determine magnetic point groups. We construct all magnetic CBED groups, of which there exist 125. Then, we provide the complete mapping of the 122 magnetic point groups to corresponding magnetic CBED groups for all crystal orientations. In order to verify the group-theoretical considerations, we conduct electron-scattering simulations on antiferromagnetic crystals and provide guidelines for the experimental realization. Based on its feasibility using existing technology, as well as on its accuracy, high spatial resolution, and small required sample size, magnetic CBED promises to be become a valuable alternative method for magnetic structure determination.

Measurements of the EMC effect in the tritium and helium-3 mirror nuclei are reported. The data were obtained by the MARATHON Jefferson Lab experiment, which performed deep inelastic electron scattering from deuterium and the three-body nuclei, using a cryogenic gas target system and the High Resolution Spectrometers of the Hall A Facility of the Lab. The data cover the Bjorken $x$ range from 0.20 to 0.83, corresponding to a squared four-momentum transfer $Q^2$ range from 2.7 to $11.9\gevsq$, and to an invariant mass $W$ of the final hadronic state greater than 1.84 GeV/${\it c}^2$. The tritium EMC effect measurement is the first of its kind. The MARATHON experimental results are compared to results from previous measurements by DESY-HERMES and JLab-Hall C experiments, as well as with few-body theoretical predictions., Comment: arXiv admin note: text overlap with arXiv:2104.05850

Unmanned Aerial Vehicles autonomously perform tasks with the use of state-of-the-art control algorithms. These control algorithms rely on the freshness and correctness of sensor readings. Incorrect control actions lead to catastrophic destabilization of the process. In this work, we propose a multi-part \emph{Sensor Deprivation Attacks} (SDAs), aiming to stealthily impact process control via sensor reconfiguration. In the first part, the attacker will inject messages on local buses that connect to the sensor. The injected message reconfigures the sensors, e.g.,~to suspend the sensing. In the second part, those manipulation primitives are selectively used to cause adversarial sensor values at the controller, transparently to the data consumer. In the third part, the manipulated sensor values lead to unwanted control actions (e.g. a drone crash). We experimentally investigate all three parts of our proposed attack. Our findings show that i)~reconfiguring sensors can have surprising effects on reported sensor values, and ii)~the attacker can stall the overall Kalman Filter state estimation, leading to a complete stop of control computations. As a result, the UAV becomes destabilized, leading to a crash or significant deviation from its planned trajectory (over 30 meters). We also propose an attack synthesis methodology that optimizes the timing of these SDA manipulations, maximizing their impact. Notably, our results demonstrate that these SDAs evade detection by state-of-the-art UAV anomaly detectors. Our work shows that attacks on sensors are not limited to continuously inducing random measurements, and demonstrate that sensor reconfiguration can completely stall the drone controller. In our experiments, state-of-the-art UAV controller software and countermeasures are unable to handle such manipulations. Hence, we also discuss new corresponding countermeasures.

A major feature of efflux pumps is multidrug polyspecificity, which to date still eludes some of the traditional dogmas of drug binding within protein science. We propose a combinatorial approach to explore, in the vast sequence space of polypeptide chains, the neighbourhood of some superfamilies of efflux pumps. Creating new functional structures as permutations of existing ones has the potential to unveil some of the hidden mechanisms behind the functionality of efflux pumps., Comment: 3 pages

The interplay between missing data and model uncertainty -- two classic statistical problems -- leads to primary questions that we formally address from an objective Bayesian perspective. For the general regression problem, we discuss the probabilistic justification of Rubin's rules applied to the usual components of Bayesian variable selection, arguing that prior predictive marginals should be central to the pursued methodology. In the regression settings, we explore the conditions of prior distributions that make the missing data mechanism ignorable. Moreover, when comparing multiple linear models, we provide a complete methodology for dealing with special cases, such as variable selection or uncertainty regarding model errors. In numerous simulation experiments, we demonstrate that our method outperforms or equals others, in consistently producing results close to those obtained using the full dataset. In general, the difference increases with the percentage of missing data and the correlation between the variables used for imputation. Finally, we summarize possible directions for future research.

The miniaturisation of transistors is approaching its limits due to challenges in heat management and information transfer speed. To overcome these obstacles, emerging technologies such as spintronics are being developed, which leverage the electron's spin in addition to its charge. Local phenomena at interfaces or structural defects will greatly influence the efficiency of spin-based devices, making the ability to study and control spin wave propagation at the nano- and atomic scales a key challenge. The development of high-spatial-resolution tools to probe spin waves, also called magnons, at relevant lengthscales is thus essential to understand how their properties are affected by such local features. Here, we show the first experimental detection of bulk magnons at the nanoscale using scanning transmission electron microscopy. By employing high-resolution electron energy loss spectroscopy with hybrid-pixel direct electron detectors optimized for low acceleration voltages, we successfully overcome the challenges posed by weak signals and identify magnon excitations in a thin NiO nanocrystal. Advanced inelastic electron scattering simulations corroborate our findings. These results open new avenues for detecting magnons, exploring their dispersions and their modifications arising from nanoscale structural or chemical defects. This marks an important milestone in magnonics and presents exciting opportunities for the future development of spintronic devices.

We present a computational study of phonon relaxation in face-centered cubic (fcc) nickel (Ni), focusing on ultra-fast magnetization dynamics. The phonons are excited beyond their thermal equilibrium population, and the relaxation behavior is analyzed as a function of both wave vector ($\vec{q}$) and phonon frequency ($\omega$). To efficiently investigate these excitations, we introduce a trajectory post-processing technique, the frozen-trajectory excitation, which facilitates the $(\vec{q},\omega)$-resolved analysis. Molecular dynamics simulations combined with the frozen-phonon multislice method predict relaxation signatures observable with time-resolved transmission electron microscopy (TEM) at 10 -- 20 fs resolution. Our findings indicate mode dependence in the relaxation processes, highlighting the importance of phonon-specific behavior consideration in ultrafast dynamics., Comment: 10 pages, 8 figures

Uniaxially strained Fe--Co disordered alloys have emerged as promising candidates for cost-effective rare-earth-free permanent magnets due to their high magnetocrystalline anisotropy energy (MAE). Using first-principles, fully relativistic calculations within the coherent potential approximation and PBE exchange-correlation potential, we explore the MAE of tetragonal Fe--Co alloys under uniaxial compression. Our results reveal a previously uncharted high-MAE region, distinct from known structures and accessible through uniaxial compression., Comment: 6 pages, 3 figures

Relative representations are an established approach to zero-shot model stitching, consisting of a non-trainable transformation of the latent space of a deep neural network. Based on insights of topological and geometric nature, we propose two improvements to relative representations. First, we introduce a normalization procedure in the relative transformation, resulting in invariance to non-isotropic rescalings and permutations. The latter coincides with the symmetries in parameter space induced by common activation functions. Second, we propose to deploy topological densification when fine-tuning relative representations, a topological regularization loss encouraging clustering within classes. We provide an empirical investigation on a natural language task, where both the proposed variations yield improved performance on zero-shot model stitching.

This study presents the design, simulation, and experimental characterization of a superconducting transmon qubit circuit prototype for potential applications in dark matter detection experiments. We describe a planar circuit design featuring two non-interacting transmon qubits, one with fixed frequency and the other flux tunable. Finite-element simulations were employed to extract key Hamiltonian parameters and optimize component geometries. The qubit was fabricated and then characterized at $20$ mK, allowing for a comparison between simulated and measured qubit parameters. Good agreement was found for transition frequencies and anharmonicities (within 1\% and 10\% respectively) while coupling strengths exhibited larger discrepancies (30\%). We discuss potential causes for measured coherence times falling below expectations ($T_1\sim\,$1-2 \textmu s) and propose strategies for future design improvements. Notably, we demonstrate the application of a hybrid 3D-2D simulation approach for energy participation ratio evaluation, yielding a more accurate estimation of dielectric losses. This work represents an important first step in developing planar Quantum Non-Demolition (QND) single-photon counters for dark matter searches, particularly for axion and dark photon detection schemes.

We propose HyperSteiner -- an efficient heuristic algorithm for computing Steiner minimal trees in the hyperbolic space. HyperSteiner extends the Euclidean Smith-Lee-Liebman algorithm, which is grounded in a divide-and-conquer approach involving the Delaunay triangulation. The central idea is rephrasing Steiner tree problems with three terminals as a system of equations in the Klein-Beltrami model. Motivated by the fact that hyperbolic geometry is well-suited for representing hierarchies, we explore applications to hierarchy discovery in data. Results show that HyperSteiner infers more realistic hierarchies than the Minimum Spanning Tree and is more scalable to large datasets than Neighbor Joining.

We present a complete analysis of Fermi Large Area Telescope (LAT) data of GRB 221009A, the brightest Gamma-Ray Burst (GRB) ever detected. The burst emission above 30 MeV detected by the LAT preceded by 1 s the low-energy (< 10 MeV) pulse that triggered the Fermi Gamma-Ray Burst Monitor (GBM), as has been observed in other GRBs. The prompt phase of GRB 221009A lasted a few hundred seconds. It was so bright that we identify a Bad Time Interval (BTI) of 64 seconds caused by the extremely high flux of hard X-rays and soft gamma rays, during which the event reconstruction efficiency was poor and the dead time fraction quite high. The late-time emission decayed as a power law, but the extrapolation of the late-time emission during the first 450 seconds suggests that the afterglow started during the prompt emission. We also found that high-energy events observed by the LAT are incompatible with synchrotron origin, and, during the prompt emission, are more likely related to an extra component identified as synchrotron self-Compton (SSC). A remarkable 400 GeV photon, detected by the LAT 33 ks after the GBM trigger and directionally consistent with the location of GRB 221009A, is hard to explain as a product of SSC or TeV electromagnetic cascades, and the process responsible for its origin is uncertain. Because of its proximity and energetic nature, GRB 221009A is an extremely rare event., Comment: 60 pages, 38 figures, 9 tables

We present the most comprehensive and deepest X-ray study to date of the properties of the richest Wolf-Rayet (WR) population observed in a single stellar cluster, Westerlund 1 (Wd1). This work is based on 36 Chandra observations obtained from the "Extended Westerlund 1 and 2 Open Clusters Survey" (EWOCS) project, plus 8 archival Chandra observations. The overall exposure depth (~1.1 Ms) and baseline of the EWOCS observations extending over more than one year enable us to perform a detailed photometric, colour, and spectral analysis, as well as to search for short- and long-term periodicity. In X-rays, we detect 20 out of the 24 known Wolf-Rayet stars in Wd1 down to an observed luminosity of ~7$\times10^{29}$erg s$^{-1}$ (assuming a distance of 4.23 kpc to Wd1), with 8 WR stars being detected in X-rays for the first time. Nine stars show clear evidence of variability over the year-long baseline, with clear signs of periodicity. The X-ray colours and spectral analysis reveal that the vast majority of the WR stars are hard X-ray sources (kT$\geq$2.0keV). The Fe XXV emission line at ~6.7 keV, which commonly originates from the wind-wind collision zone in binary systems, is detected for the first time in the spectra of 17 WR stars in Wd1. In addition the ~6.4 keV fluorescent line is observed in the spectra of three stars, indicating that dense cold material coexists with the hot gas in these systems. Overall, our X-ray results alone suggest a very high binary fraction ($\geq$80%) for the WR star population in Wd1. When combining our results with properties of the WR population from other wavelengths, we estimate a binary fraction of $\geq$92%, which could even reach unity. This suggests that either all the most massive stars are found in binary systems within Wd1, or that binarity is essential for the formation of such a rich population of WR stars., Comment: 20 pages, 11 figures, 6 tables, accepted for publication in A&A

Peer analysis is a critical component of investment management, often relying on expert-provided categorization systems. These systems' consistency is questioned when they do not align with cohorts from unsupervised clustering algorithms optimized for various metrics. We investigate whether unsupervised clustering can reproduce ground truth classes in a labeled dataset, showing that success depends on feature selection and the chosen distance metric. Using toy datasets and fund categorization as real-world examples we demonstrate that accurately reproducing ground truth classes is challenging. We also highlight the limitations of standard clustering evaluation metrics in identifying the optimal number of clusters relative to the ground truth classes. We then show that if appropriate features are available in the dataset, and a proper distance metric is known (e.g., using a supervised Random Forest-based distance metric learning method), then an unsupervised clustering can indeed reproduce the ground truth classes as distinct clusters., Comment: 9 pages, 4 tables 28 figures

Surrogate models that combine dimensionality reduction and regression techniques are essential to reduce the need for costly high-fidelity computational fluid dynamics data. New approaches using $\beta$-Variational Autoencoder ($\beta$-VAE) architectures have shown promise in obtaining high-quality low-dimensional representations of high-dimensional flow data while enabling physical interpretation of their latent spaces. We propose a surrogate model based on latent space regression to predict pressure distributions on a transonic wing given the flight conditions: Mach number and angle of attack. The $\beta$-VAE model, enhanced with Principal Component Analysis (PCA), maps high-dimensional data to a low-dimensional latent space, showing a direct correlation with flight conditions. Regularization through $\beta$ requires careful tuning to improve overall performance, while PCA preprocessing helps to construct an effective latent space, improving autoencoder training and performance. Gaussian Process Regression is used to predict latent space variables from flight conditions, showing robust behavior independent of $\beta$, and the decoder reconstructs the high-dimensional pressure field data. This pipeline provides insight into unexplored flight conditions. Furthermore, a fine-tuning process of the decoder further refines the model, reducing the dependence on $\beta$ and enhancing accuracy. Structured latent space, robust regression performance, and significant improvements in fine-tuning collectively create a highly accurate and efficient surrogate model. Our methodology demonstrates the effectiveness of $\beta$-VAEs for aerodynamic surrogate modeling, offering a rapid, cost-effective, and reliable alternative for aerodynamic data prediction., Comment: 19 pages, 12 figures

TThe Period-Luminosity (PL) relation for Cepheid variable stars in the Large Magellanic Cloud (LMC) is crucial for distance measurements in astronomy. This study analyzes the impact of using the median rather than the mean on the PL relation's slope and zero point. It also examines the persistence of the break at approximately 10 days and addresses specification issues in the PL relation model. Using $VI$-band median and mean magnitudes from the OGLE-IV survey, corrected for extinction, we fit the PL relation employing robust $MM$-regression, which features a high breakdown point and robust standard errors. Statistical tests and residual analysis are conducted to identify and correct model deficiencies. Our findings indicate a significant change in the PL relation for Cepheids with periods of 10 days or longer, regardless of whether median or mean magnitudes are used. A bias in the zero point and slope estimators is observed when using median magnitudes instead of mean magnitudes, especially in the $V$-band. By identifying and correcting regression issues and considering the period break, our estimators for slope and zero point are more accurate for distance calculations. Comparative analysis of the models for each band quantifies the bias introduced by using median magnitudes, highlighting the importance of considering the Cepheids' period for accurate location measure results, similar to those obtained using mean magnitudes.

In recent years, linear complementary pairs (LCP) of codes and linear complementary dual (LCD) codes have gained significant attention due to their applications in coding theory and cryptography. In this work, we construct explicit LCPs of codes and LCD codes from function fields of genus $g \geq 1$. To accomplish this, we present pairs of suitable divisors giving rise to non-special divisors of degree $g-1$ in the function field. The results are applied in constructing LCPs of algebraic geometry codes and LCD algebraic geometry (AG) codes in Kummer extensions, hyperelliptic function fields, and elliptic curves.

We have investigated the behaviour of three strong near-infrared diffuse interstellar bands (DIBs) at {\lambda}13177 {\AA}, {\lambda}14680 {\AA}, and {\lambda}15272 {\AA}, on a larger sample of sightlines and over a wider range of extinctions than previously studied, utilizing spectra from three observatories. We applied two telluric correction techniques to reduce atmospheric contamination and have used Gaussian fits to characterise the DIB profiles and measure equivalent widths. We confirmed strong and approximately linear correlations with reddening of the {\lambda}13177 {\AA}, {\lambda}14680 {\AA} and {\lambda}15272 {\AA} DIBs, extending them to higher reddening values and strengthening their link to interstellar matter. Modelling of the {\lambda}14680 {\AA} DIB profiles revealed intrinsic variations, including line broadening, linked to their formation processes. This effect is particularly pronounced in the Galactic Centre (GC) environment, where multiple diffuse molecular clouds along the line of sight contribute to line broadening. We have detected one new DIB candidate at {\lambda}14795 {\AA} on sightlines with high reddening., Comment: Accepted for publication in Monthly Notices of the Royal Astronomical Society (MNRAS)

A flag $C_0 \subsetneq C_1 \cdots \subsetneq C_s \subsetneq {\mathbb F}_q^n $ of linear codes is said to be self-orthogonal if the duals of the codes in the flag satisfy $C_{i}^\perp=C_{s-i}$, and it is said to satisfy the isometry-dual property with respect to an isometry vector ${\bf x}$ if $C_i^\perp={\bf x} C_{s-i}$ for $i=1, \dots, s$. We characterize complete (i.e. $s=n$) flags with the isometry-dual property by means of the existence of a word with non-zero coordinates in a certain linear subspace of ${\mathbb F}_q^n$. For flags of algebraic geometry (AG) codes we prove a so-called translation property of isometry-dual flags and give a construction of complete self-orthogonal flags, providing examples of self-orthogonal flags over some maximal function fields. At the end we characterize the divisors giving the isometry-dual property and the related isometry vectors showing that for each function field there is only a finite number of isometry vectors and that they are related by cyclic repetitions.

The atmospheric response for MeV gamma rays (~ 0.1 - 10 MeV) can be characterized in terms of two observed components. The first component is due to photons that reach the detector without scattering. The second component is due to photons that reach the detector after scattering one or more times. While the former can be determined in a straightforward manner, the latter is much more complex to quantify, as it requires tracking the transport of all source photons that are incident on Earth's atmosphere. The scattered component can cause a significant energy-dependent distortion in the measured spectrum, which is important to account for when making balloon-borne observations. In this work we simulate the full response for gamma-ray transport in the atmosphere. We find that the scattered component becomes increasingly more significant towards lower energies, and at 0.1 MeV it may increase the measured flux by as much as a factor of ~2-4, depending on the photon index and off-axis angle of the source. This is particularly important for diffuse sources, whereas the effect from scattering can be significantly reduced for point sources observed with an imaging telescope., Comment: 24 pages, 18 figures. Accepted to The Astrophysical Journal

Food insecurity is widespread among college students in the United States. Food benefits delivered through the CalFresh program, California's version of the federal Supplemental Nutrition Assistance Program (SNAP), can reduce hunger by helping students pay for groceries, but may not reach all eligible students. To date, higher education systems have lacked good estimates of the share of their students who are eligible for CalFresh and the share who actually receive benefits. To address this information gap, the California Policy Lab (CPL) partnered with the California Community College (CCC) Chancellor's Office, the University of California Office of the President (UCOP), the California Department of Social Services (CDSS), and the California Student Aid Commission (CSAC) to build a linked database of student-level administrative data on college enrollment, financial aid, and CalFresh participation. This database covers all students enrolled at CCC or UC campuses from academic years 2010-11 through 2021-22, along with corresponding FAFSA submissions and CalFresh participation. Using these data, we are able to measure how many college students are likely eligible for CalFresh, and of those how many participate. CalFresh eligibility does not perfectly overlap with student need. Some students who are food insecure may not be eligible for benefits, while some eligible students may not be in great need. This in part reflects the rules of the program, which are designed to capture need but do not always do so perfectly. We attempt to measure eligibility according to the actual rules. Our estimates complement other work that uses survey data to measure students' basic needs (California Community Colleges League, 2022). We estimate that in Fall 2019, on the eve of the COVID pandemic, 16% of California community college students (256,000 students), 31% of UC undergraduate students (69,000 students), and 6% of UC graduate students (3,000 students) were likely eligible for CalFresh benefits. However, the majority of these students did not receive benefits -- only 30% of eligible community college students, 22% of eligible UC undergraduates, and 29% of eligible UC graduate students were actually enrolled in CalFresh. We emphasize that our eligibility determinations are estimates based on information available in existing data, which imperfectly capture some elements of the CalFresh eligibility determination process. They may somewhat overstate or understate student eligibility. However, extensive investigation led us to conclude that the errors are likely not large and that our estimates are a good approximation of the share of students who would be found eligible under individualized determinations. As we discuss below, the higher eligibility rate among UC undergraduates as compared to CCC students reflects program rules that make it easier for UC students to qualify than for CCC students with similar resources. We also find differences in eligibility across groups of students within each segment, reflecting both variation in need and program rules. Among both CCC and UC students, Black and Hispanic students, for example, are more likely to be eligible than are White or Asian American students, and students receiving federal, state, or institutional financial aid are much more likely to be eligible than are students not receiving aid. Benefits receipt generally mirrors this, although there are differences across groups in the share of eligible students who receive benefits. The take-up rate, which is the share of eligible students who participate in CalFresh, is higher for Black students (and, at the UC but not at CCCs, Hispanic students) than for White students, and for students on financial aid than for students who are not. Our report indicates there is much room to improve CalFresh participation among eligible students. Through detailed analyses of the paths to eligibility and of variation in participation rates, we hope to shed light on opportunities for policymakers, higher education administrators, community-based organizations, student groups, and advocates to better connect eligible students to benefits. [Additional support was provided by the Woven Foundation.]

This teaching article describes a simple and low-cost methodology for studying electrical transport and constructing basic sensor devices using everyday stationery items, including pencils, paper, and a handheld multimeter. The approach is designed for high school and undergraduate teachers and offers an easy-to-implement, hands-on method for teaching fundamental concepts in physical electronics. The materials and experiments outlined in this article are widely accessible and can be easily replicated in various teaching labs, even with limited budgets.

We present the electrostatic control of photoluminescence of monolayer MoS$_2$ at room temperature via integration of free-standing BaTiO$_3$ (BTO), a ferroelectric perovskite oxide, layers. We show that the use of BTO leads to highly tunable exciton emission of MoS$_2$ in a minimal range of gate voltages, effectively controlling the neutral excitons to charged excitons (trions) conversion. Due to BTO's ferroelectric polarization-induced doping we observe large peak emission shifts as well as a large and tunable A trion binding energy in the range of 40-100 meV. To further investigate the efficacy of electrostatic control, we compared our measurements with those carried out when the BTO is replaced by a hexagonal boron nitride (hBN) dielectric layer of comparable thickness, confirming BTO's superior gating properties and thus lower power consumption. Additionally, we take advantage of the ferroelectric switching of BTO by fabricating devices where the BTO layer is decoupled from the gate electrode with a SiO$_2$ layer. Choosing to isolate the BTO allows us to induce large remanent behavior of MoS$_2$'s excitonic features, observing hysteretic behavior in the peak energy ratio between A exciton and its trion, as well as hysteretic behavior in the doping-related trion energy shift. This study illustrates the rich physics involved in combining free-standing complex oxide layers with two-dimensional materials.

The advent of next-generation survey instruments, such as the Vera C. Rubin Observatory and its Legacy Survey of Space and Time (LSST), is opening a window for new research in time-domain astronomy. The Extended LSST Astronomical Time-Series Classification Challenge (ELAsTiCC) was created to test the capacity of brokers to deal with a simulated LSST stream. We describe ATAT, the Astronomical Transformer for time series And Tabular data, a classification model conceived by the ALeRCE alert broker to classify light-curves from next-generation alert streams. ATAT was tested in production during the first round of the ELAsTiCC campaigns. ATAT consists of two Transformer models that encode light curves and features using novel time modulation and quantile feature tokenizer mechanisms, respectively. ATAT was trained on different combinations of light curves, metadata, and features calculated over the light curves. We compare ATAT against the current ALeRCE classifier, a Balanced Hierarchical Random Forest (BHRF) trained on human-engineered features derived from light curves and metadata. When trained on light curves and metadata, ATAT achieves a macro F1-score of 82.9 +- 0.4 in 20 classes, outperforming the BHRF model trained on 429 features, which achieves a macro F1-score of 79.4 +- 0.1. The use of Transformer multimodal architectures, combining light curves and tabular data, opens new possibilities for classifying alerts from a new generation of large etendue telescopes, such as the Vera C. Rubin Observatory, in real-world brokering scenarios.

Inclusive electron scattering at carefully chosen kinematics can isolate scattering from short-range correlations (SRCs), produced through hard, short-distance interactions of nucleons in the nucleus. Because the two-nucleon (2N) SRCs arise from the same N-N interaction in all nuclei, the cross section in the SRC-dominated regime is identical up to an overall scaling factor, and the A/2H cross section ratio is constant in this region. This scaling behavior has been used to identify SRC dominance and to map out the contribution of SRCs for a wide range of nuclei. We examine this scaling behavior at lower momentum transfers using new data on $^2$H, $^3$H, and $^3$He which show that the scaling region is larger than in heavy nuclei. Based on the improved scaling, especially for $^3$H/$^3$He, we examine the ratios at kinematics where three-nucleon SRCs may play an important role. The data for the largest initial nucleon momenta are consistent with isolation of scattering from 3N-SRCs, and suggest that the very-highest momentum nucleons in $^3$He have a nearly isospin-independent momentum configuration, or a small enhancement of the proton distribution.

Molecular-scale diodes made from self-assembled monolayers (SAMs) could complement silicon-based technologies with smaller, cheaper, and more versatile devices. However, advancement of this emerging technology is limited by insufficient electronic performance exhibited by the molecular current rectifiers. We overcome this barrier by exploiting the charge-transfer state that results from co-assembling SAMs of molecules with strong electron donor and acceptor termini. We obtain a substantial enhancement in current rectification, which correlates with the degree of charge transfer, as confirmed by several complementary techniques. These findings provide a previously unexplored method for manipulating the properties of molecular electronic devices by exploiting donor/acceptor interactions. They also serve as a model test platform for the study of doping mechanisms in organic systems. Our devices have the potential for fast widespread adoption due to their low-cost processing and self-assembly onto silicon substrates, which could allow seamless integration with current technologies.

For many transitions, atomic data, such as the oscillator strength (log(gf)) and the central wavelength of the line, are poorly constrained or even unknown. We present and test a new inversion method that infers atomic line parameters and the height stratification of the atmospheric parameters from spatially resolved spectropolarimetric observations of the Sun. This method is implemented in the new inversion code $\texttt{globin}$. The new method imposes a spatial coupling in inversion parameters common to all pixels, such as the atomic parameters of the observed spectral lines, and infers atmospheric parameters for each spatial pixel individually. The uniqueness of this method lies in its ability to retrieve reliable atomic parameters even for heavily blended spectral lines. We tested the method by applying it to a set of 18 spectral lines between 4015 \r{A} and 4017 \r{A}, synthesized from a 3D magnetohydrodynamic simulation containing a sunspot and the quiet Sun region around it. The results were then compared with a previously used inversion method where atomic parameters were determined for every pixel independently (pixel-by-pixel method). The new method was able to retrieve the log(gf) values of all lines to an accuracy of 0.004 dex, while the pixel-by-pixel method retrieved the same parameter to an accuracy of only 0.025 dex. The largest differences between the two methods are evident for the heavily blended lines, with the former method performing better than the latter. In addition, the new method is also able to infer reliable atmospheric parameters in all the inverted pixels by successfully disentangling the degeneracies between the atomic and atmospheric parameters. The new method is well suited for the reliable determination of both atomic and atmospheric parameters and works well on all spectral lines, including those that are weak and/or severely blended., Comment: Accepted for publication in A&A; 16 pages and 10 figures

The modeling of nonlinear dynamics based on Koopman operator theory, which is originally applicable only to autonomous systems with no control, is extended to non-autonomous control system without approximation to input matrix B. Prevailing methods using a least square estimate of the B matrix may result in an erroneous input matrix, misinforming the controller about the structure of the input matrix in a lifted space. Here, a new method for constructing a Koopman model that comprises the exact input matrix B is presented. A set of state variables are introduced so that the control inputs are linearly involved in the dynamics of actuators. With these variables, a lifted linear model with the exact control matrix, called a Control-Coherent Koopman Model, is constructed by superposing control input terms, which are linear in local actuator dynamics, to the Koopman operator of the associated autonomous nonlinear system. The proposed method is applied to multi degree-of-freedom robotic arms and multi-cable manipulation systems. Model Predictive Control is applied to the former. It is demonstrated that the prevailing Dynamic Mode Decomposition with Control (DMDc) using an approximate control matrix B does not provide a satisfactory result, while the Control-Coherent Koopman Model performs well with the correct B matrix., Comment: Accepted at the Conference on Decision and Control (CDC 2024)

This manuscript considers the problem of ensuring stability and safety during formation control with distributed multi-agent systems in the presence of parametric uncertainty in the dynamics and limited communication. We propose an integrative approach that combines Control Barrier Functions, Adaptive Control, and connected graphs. A reference model is designed so as to ensure a safe and stable formation control strategy. This is combined with a provably correct adaptive control design that includes the use of a CBF-based safety filter that suitably generates safe reference commands. Numerical examples are provided to support the theoretical derivations., Comment: Under Review - American Control Conference 2025

We present a catalog that we named MODEST containing depth-dependent information on the atmospheric conditions inside sunspot groups of all types. The catalog is currently composed of 942 observations of 117 individual active regions with sunspots that cover all types of features observed in the solar photosphere. We use the SPINOR-2D code to perform spatially coupled inversions of the Stokes profiles observed by Hinode/SOT-SP at high spatial resolution. SPINOR-2D accounts for the unavoidable degradation of the spatial information due to the point spread function of the telescope. The sunspot sample focuses on complex sunspot groups, but simple sunspots are also part of the catalog for completeness. Sunspots were observed from 2006 to 2019, covering parts of solar cycles 23 and 24. The catalog is a living resource, as with time, more sunspot groups will be included., Comment: Accepted for publication in A&A

In this work, we study the angular momentum transfer from a single swift electron to non-spherical metallic nanoparticles, specifically investigating spheroidal and polyhedral (Platonic Solids) shapes. While previous research has predominantly focused on spherical nanoparticles, our work expands the knowledge by exploring various geometries. Employing classical electrodynamics and the small particle limit, we calculate the angular momentum transfer by integrating the spectral density, ensuring causality through Fourier-transform analysis. Our findings demonstrate that prolate spheroidal nanoparticles exhibit a single blueshifted plasmonic resonance, compared to spherical nanoparticles of equivalent volume, resulting in lower angular momentum transfer. Conversely, oblate nanoparticles display two resonances (one blueshifted and one redshifted) resulting in a higher angular momentum transfer than their spherical counterparts. Additionally, Platonic Solids with fewer faces exhibit significant redshifts in plasmonic resonances, leading to higher angular momentum transfer due to edge effects. We also observe resonances and angular momentum transfers with similar characteristics in specific pairs of Platonic Solids, known as duals. These results highlight promising applications, particularly in electron tweezers technology.

In 2018, the E12-17-003 experiment was conducted at the Thomas Jefferson National Accelerator Facility (JLab) to explore the possible existence of an nnLambda state in the reconstructed missing mass distribution from a tritium gas target [K. N. Suzuki et al., Prog. Theor. Exp. Phys. 2022, 013D01 (2022), B. Pandey et al., Phys. Rev. C 105, L051001 (2022)]. As part of this investigation, data was also collected using a gaseous hydrogen target, not only for a precise absolute mass scale calibration but also for the study of Lambda/Sigma^0 electroproduction. This dataset was acquired at Q^2~0.5 (GeV/c)^2, W=2.14 GeV, and theta_{gamma K}^{c.m.}~8 deg. It covers forward angles where photoproduction data is scarce and a low-Q^2 region that is of interest for hypernuclear experiments. On the other hand, this kinematic region is at a slightly higher Q^2 than previous hypernuclear experiments, thus providing crucial information for understanding the Q^2 dependence of the differential cross sections for Lambda/Sigma^0 hyperon electroproduction. This paper reports on the Q^2 dependence of the differential cross section for the e + p -> e' + K^+ + Lambda/Sigma^0 reaction in the 0.2-0.8 (GeV/c)^2, and provides comparisons with the currently available theoretical models., Comment: 11 pages, 15 figures

We present a method for computing angle-resolved electron-energy-loss and gain spectroscopies for phonon and magnon excitations in transmission electron microscopy. Fractional scattering intensities are derived from the temperature-dependent time auto-correlation of the electron beam wave function. This method captures both single and multiple scattering processes, as well as dynamical diffraction effects. Our method remains computationally efficient, and it is easy to parallelize., Comment: We include simulations of relevant systems and compare with existing experimental results

The increasing demand for wireless data transfer has been the driving force behind the widespread adoption of Massive MIMO (multiple-input multiple-output) technology in 5G. The next-generation MIMO technology is now being developed to cater to the new data traffic and performance expectations generated by new user devices and services in the next decade. The evolution towards "ultra-massive MIMO (UM-MIMO)" is not only about adding more antennas but will also uncover new propagation and hardware phenomena that can only be treated by jointly utilizing insights from the communication, electromagnetic (EM), and circuit theory areas. This article offers a comprehensive overview of the key benefits of the UM-MIMO technology and the associated challenges. It explores massive multiplexing facilitated by radiative near-field effects, characterizes the spatial degrees-of-freedom, and practical channel estimation schemes tailored for massive arrays. Moreover, we provide a tutorial on EM theory and circuit theory, and how it is used to obtain physically consistent antenna and channel models. Subsequently, the article describes different ways to implement massive and dense antenna arrays, and how to co-design antennas with signal processing. The main open research challenges are identified at the end., Comment: Submitted to Proceedings of the IEEE, 36 pages, 23 figures

Data depth is a statistical function that generalizes order and quantiles to the multivariate setting and beyond, with applications spanning over descriptive and visual statistics, anomaly detection, testing, etc. The celebrated halfspace depth exploits data geometry via an optimization program to deliver properties of invariances, robustness, and non-parametricity. Nevertheless, it implicitly assumes convex data supports and requires exponential computational cost. To tackle distribution's multimodality, we extend the halfspace depth in a Reproducing Kernel Hilbert Space (RKHS). We show that the obtained depth is intuitive and establish its consistency with provable concentration bounds that allow for homogeneity testing. The proposed depth can be computed using manifold gradient making faster than halfspace depth by several orders of magnitude. The performance of our depth is demonstrated through numerical simulations as well as applications such as anomaly detection on real data and homogeneity testing., Comment: 30 pages

Context. With a mass exceeding several 10^4 solar masses and a rich and dense population of massive stars, supermassive young star clusters represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions among stars. Aims. In this paper we present the "Extended Westerlund 1 and 2 Open Clusters Survey" (EWOCS) project, which aims to investigate the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars. The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun. Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically, the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec. Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation were carried out using the ACIS-Extract software. Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a photon flux threshold of approximately 2x10^-8 photons/cm^2/s. The X-ray sources exhibit a highly concentrated spatial distribution, with 1075 sources located within the central 1 arcminute. We have successfully detected X-ray emissions from 126 out of the 166 known massive stars of the cluster, and we have collected over 71000 photons from the magnetar CXO J164710.20-455217, Comment: The paper has been accepted for publication by Astronomy and Astrophysics

The identification of preexisting near-surface faults represents a piece of crucial information needed to correctly assess the seismic hazard of any area. The mapping of these structures is particularly challenging in densely populated and heavily urbanized areas. We use ambient seismic noise recorded by a dense array in Seal Beach, California, to image shallow fault lines via a reflected surface wave analysis. Our results highlight the presence of previously unknown shallow faults that correlate remarkably well with shallow seismicity and active survey images.

The pion decay constant $F_{\pi}$ plays an important role in QCD and in Chiral Perturbation Theory. It is hardly known, however, that a corresponding constant exists in the Schwinger model with $N_{\rm f} \geq 2$ degenerate fermion flavors. In this case, the ``pion'' does not decay and $F_{\pi}$is dimensionless. Still, $F_{\pi}$ can be defined by 2d analogies to the Gell-Mann--Oakes--Renner relation, the Witten--Veneziano formula and the residual ``pion'' mass in the $\delta$-regime. With suitable assumptions, and by inserting simulation data, these QCD-inspired relations are all compatible with $F_{\pi} \simeq 1/\sqrt{2\pi}$ at zero fermion mass, as we observe for $N_{\rm f} = 2, \dots , 6$. We conclude that this is a meaningful constant in the multi-flavor Schwinger model., Comment: 7 pages, LaTex, 4 figures, talk presented at the 40th International Symposium on Lattice Field Theory (Lattice 2023), July 31st - August 4th, 2023, Fermi National Accelerator Laboratory

We present a study of the 3d O(2) non-linear $\sigma$-model on the lattice, which exhibits topological defects in the form of vortices. They tend to organize into vortex lines that bear close analogies with global cosmic strings. Therefore, this model serves as a testbed for studying the dynamics of topological defects. It undergoes a second order phase transition, hence it is appropriate for investigating the Kibble-Zurek mechanism. In this regard, we explore the persistence of topological defects when the temperature is rapidly reduced from above to below the critical temperature; this cooling (or "quenching") process takes the system out of equilibrium. We probe a wide range of inverse cooling rates $\tau_{\rm Q}$ and final temperatures, employing distinct Monte Carlo algorithms. The results consistently show that the density of persisting topological defects follows a power-law in $\tau_{\rm Q}$, in agreement with Zurek's conjecture. On the other hand, at this point our results do not confirm Zurek's prediction for the exponent in this power-law, but its final test is still under investigation., Comment: 7 pages, LaTex, 3 figures, talk presented at the 40th International Symposium on Lattice Field Theory (Lattice 2023), July 31st - August 4th, 2023, Fermi National Accelerator Laboratory

In this work, using maximal elements in generalized Weierstrass semigroups and its relationship with pure gaps, we extend the results in \cite{CMT2024} and provide a way to completely determine the set of pure gaps at several rational places in an arbitrary function field $F$ over a finite field and its cardinality. As an example, we determine the cardinality and a simple explicit description of the set of pure gaps at several rational places distinct to the infinity place on Kummer extensions, which is a different characterization from that presented by Hu and Yang in \cite{HY2018}. Furthermore, we present some applications in coding theory and AG codes with good parameters.

Antenna behaviors such as mutual coupling, near-field propagation, and polarization cannot be neglected in signal and channel models for wireless communication. We present an electromagnetic-based array manifold that accounts for several complicated behaviors and can model arbitrary antenna configurations. We quantize antennas into a large number of Hertzian dipoles to develop a model for the radiated array field. The resulting abstraction provides a means to predict the electric field for general non-homogeneous array geometries through a linear model that depends on the point source location, the position of each Hertzian dipole, and a set of coefficients obtained from electromagnetic simulation. We then leverage this model to formulate a beamforming gain optimization that can be adapted to account for polarization of the receive field as well as constraints on the radiated power density. Numerical results demonstrate that the proposed method achieves accuracy that is close to that of electromagnetic simulations. By leveraging the developed array manifold for beamforming, systems can achieve higher beamforming gains compared to beamforming with less accurate models.

Space exploration and establishing human presence on other planets demand advanced technology and effective collaboration between robots and astronauts. Efficient space resource utilization is also vital for extraterrestrial settlements. The Collaborative In-Situ Resources Utilisation (CISRU) project has developed a software suite comprising five key modules. The first module manages multi-agent autonomy, facilitating communication between agents and mission control. The second focuses on environment perception, employing AI algorithms for tasks like environment segmentation and object pose estimation. The third module ensures safe navigation, covering obstacle avoidance, social navigation with astronauts, and cooperation among robots. The fourth module addresses manipulation functions, including multi-tool capabilities and tool-changer design for diverse tasks in In-Situ Resources Utilization (ISRU) scenarios. Finally, the fifth module controls cooperative behaviour, incorporating astronaut commands, Mixed Reality interfaces, map fusion, task supervision, and error control. The suite was tested using an astronaut-rover interaction dataset in a planetary environment and GMV SPoT analogue environments. Results demonstrate the advantages of E4 autonomy and AI in space systems, benefiting astronaut-robot collaboration. This paper details CISRU's development, field test preparation, and analysis, highlighting its potential to revolutionize planetary exploration through AI-powered technology., Comment: 9 pages, conference paper for IAC 23

The CISRU project has focused on the development of a software suite for planetary (and terrestrial) robotics, fully abstracted from the robotic platform and enabling interaction between rovers and astronauts in complex tasks and non-structured scenarios. To achieve this, a high level of autonomy is required, powered by AI and multi-agent autonomous planning systems inherited from ERGO/ADE and the PERASPERA program. This communication presents the system developed in CISRU, focusing on the modules of AI-based perception and the interaction between astronauts and robots., Comment: Conference paper for ASTRA 2023

In 2016 the Compton Spectrometer and Imager (COSI) had a successful 46-day flight onboard NASA's Super Pressure Balloon platform. In this work we report measurements of the Galactic diffuse continuum emission (GDCE) observed towards the inner Galaxy during the flight, which in the COSI energy band (0.2 - 5 MeV) is primarily generated from inverse Compton radiation. Within uncertainties we find overall good agreement with previous measurements from INTEGRAL/SPI and COMPTEL. Based on these initial findings, we discuss the potential for further probing the GDCE with the 2016 COSI balloon data, as well as prospects for the upcoming satellite mission., Comment: 14 pages, 4 figures, 2 tables. Accepted for publication in the Astrophysical Journal

Impedance-matching networks affect power transfer from the radio frequency (RF) chains to the antennas. Their design impacts the signal to noise ratio (SNR) and the achievable rate. In this paper, we maximize the information-theoretic achievable rate of a multiple-input-single-output (MISO) system with wideband matching constraints. Using a multiport circuit theory approach with frequency-selective scattering parameters, we propose a general framework for optimizing the MISO achievable rate that incorporates Bode-Fano wideband matching theory. We express the solution to the achievable rate optimization problem in terms of the optimized transmission coefficient and the Lagrangian parameters corresponding to the Bode-Fano inequality constraints. We apply this framework to a single electric Chu's antenna and an array of two electric Chu's antennas. We compare the optimized achievable rate obtained numerically with other benchmarks like the ideal achievable rate computed by disregarding matching constraints and the achievable rate obtained by using sub-optimal matching strategies like conjugate matching and frequency-flat transmission. We also propose a practical methodology to approximate the achievable rate bound by using the optimal transmission coefficient to derive a physically realizable matching network through the ADS software.

In this paper, we assess the efficacy of ChatGPT (version Feb 2023), a large-scale language model, in solving probability problems typically presented in introductory computer engineering exams. Our study comprised a set of 23 probability exercises administered to students at Rey Juan Carlos University (URJC) in Madrid. The responses produced by ChatGPT were evaluated by a group of five statistics professors, who assessed them qualitatively and assigned grades based on the same criteria used for students. Our results indicate that ChatGPT surpasses the average student in terms of phrasing, organization, and logical reasoning. The model's performance remained consistent for both the Spanish and English versions of the exercises. However, ChatGPT encountered difficulties in executing basic numerical operations. Our experiments demonstrate that requesting ChatGPT to provide the solution in the form of an R script proved to be an effective approach for overcoming these limitations. In summary, our results indicate that ChatGPT surpasses the average student in solving probability problems commonly presented in introductory computer engineering exams. Nonetheless, the model exhibits limitations in reasoning around certain probability concepts. The model's ability to deliver high-quality explanations and illustrate solutions in any programming language, coupled with its performance in solving probability exercises, suggests that large language models have the potential to serve as learning assistants., Comment: 10 pages, 6 figures, 4 tables

In this paper a framework for solving the time optimal control (TOC) using Galerkin's Weighted Residuals Method (GWRM) and Sequential Convex Programming (SCP) is proposed. The proposed method solves the two-point boundary value problem, avoiding the use of shooting methods that rely heavily on the appropriate initialization of the adjoint state and optimal time. Since TOC yields an open-loop controller, a Model Predictive Control (MPC) scheme is employed to track both the optimal trajectory and controller, allowing the system to reject disturbances. The approach is validated using the Dubins' car dynamics for optimal time trajectory generation.