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This study explores the application of a two-level algorithm to enhance the signal-to-noise ratio of glueball calculations in four-dimensional $\mathrm{SU(3)}$ pure gauge theory. Our findings demonstrate that the statistical errors exhibit an exponential reduction, enabling reliable extraction of effective masses at distances where current standard methods would demand exponentially more samples. However, at shorter distances, standard methods prove more efficient due to a saturation of the variance reduction using the multi-level method. We discuss the physical distance at which the multi-level sampling is expected to outperform the standard algorithm, supported by numerical evidence across different lattice spacings and glueball channels. Additionally, we construct a variational basis comprising 35 Wilson loops up to length 12 and 5 smearing sizes each, presenting results for the first state in the spectrum for the scalar, pseudoscalar, and tensor channels., Comment: 12 pages, 7 figures, preprint

This paper introduces CodeGemma, a collection of specialized open code models built on top of Gemma, capable of a variety of code and natural language generation tasks. We release three model variants. CodeGemma 7B pretrained (PT) and instruction-tuned (IT) variants have remarkably resilient natural language understanding, excel in mathematical reasoning, and match code capabilities of other open models. CodeGemma 2B is a state-of-the-art code completion model designed for fast code infilling and open-ended generation in latency-sensitive settings., Comment: v1: 11 pages, 4 figures, 5 tables. v2: Update metadata

In this brief note, we confront our results on diffractive photoproduction of $J/\psi$ mesons with the putative gluon shadowing ratio defined as $R_g= \sqrt{\sigma(\gamma A \to J/\psi A)/\sigma_{\rm IA.}}$, where $\sigma_{\rm IA}$ is the result in impulse approximation. Building on our earlier description of the process in the color-dipole approach, where we took into account the rescattering of $c \bar c$ states only, we demonstrate that the inclusion of $c \bar c g$-Fock states improves the description at small $x$ commonly associated with gluon shadowing., Comment: 8 pages, 2 figures

Molecular Communications (MC) research is increasingly focused on applications within the human body, such as health monitoring and drug delivery. These applications require testing in realistic and living environments. Thus, advancing experimental MC research to the next level requires the development of in vivo experimental testbeds. In this paper, we introduce the Chorioallantoic Membrane ( CAM ) model as a versatile 3D in vivo MC testbed. The CAM is a highly vascularized membrane formed in fertilized chicken eggs and has gained significance in various research fields, including bioengineering, cancer research, and drug development. Its versatility, reproducibility, and realistic biological properties make the CAM model perfectly suited for next-generation MC testbeds, facilitating the transition from proof-of-concept systems to practical applications. We provide a comprehensive introduction to the CAM model, its properties, and its applications in practical research. Additionally, we present a characterization of the CAM model as an MC system. As a preliminary experimental study, we investigate the distribution of fluorescent molecules in the closed-loop vascular system of the CAM model. We also derive an approximate analytical model for the propagation of molecules in closed-loop systems, and show that the proposed model is able to approximate molecule propagation in the CAM model., Comment: 7 pages, 10 figures. This work has been submitted to the 11th ACM International Conference on Nanoscale Computing and Communication, Milan, Italy

The differentiable programming paradigm is a cornerstone of modern scientific computing. It refers to numerical methods for computing the gradient of a numerical model's output. Many scientific models are based on differential equations, where differentiable programming plays a crucial role in calculating model sensitivities, inverting model parameters, and training hybrid models that combine differential equations with data-driven approaches. Furthermore, recognizing the strong synergies between inverse methods and machine learning offers the opportunity to establish a coherent framework applicable to both fields. Differentiating functions based on the numerical solution of differential equations is non-trivial. Numerous methods based on a wide variety of paradigms have been proposed in the literature, each with pros and cons specific to the type of problem investigated. Here, we provide a comprehensive review of existing techniques to compute derivatives of numerical solutions of differential equations. We first discuss the importance of gradients of solutions of differential equations in a variety of scientific domains. Second, we lay out the mathematical foundations of the various approaches and compare them with each other. Third, we cover the computational considerations and explore the solutions available in modern scientific software. Last but not least, we provide best-practices and recommendations for practitioners. We hope that this work accelerates the fusion of scientific models and data, and fosters a modern approach to scientific modelling.

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 535 authors from 84 institutions, 12 pages, 8 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

The Pierre Auger Observatory is the most sensitive instrument to detect photons with energies above $10^{17}$ eV. It measures extensive air showers generated by ultra high energy cosmic rays using a hybrid technique that exploits the combination of a fluorescence detector with a ground array of particle detectors. The signatures of a photon-induced air shower are a larger atmospheric depth of the shower maximum ($X_{max}$) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced cascades. In this work, a new analysis technique in the energy interval between 1 and 30 EeV (1 EeV = $10^{18}$ eV) has been developed by combining the fluorescence detector-based measurement of $X_{max}$ with the specific features of the surface detector signal through a parameter related to the air shower muon content, derived from the universality of the air shower development. No evidence of a statistically significant signal due to photon primaries was found using data collected in about 12 years of operation. Thus, upper bounds to the integral photon flux have been set using a detailed calculation of the detector exposure, in combination with a data-driven background estimation. The derived 95% confidence level upper limits are 0.0403, 0.01113, 0.0035, 0.0023, and 0.0021 km$^{-2}$ sr$^{-1}$ yr$^{-1}$ above 1, 2, 3, 5, and 10 EeV, respectively, leading to the most stringent upper limits on the photon flux in the EeV range. Compared with past results, the upper limits were improved by about 40% for the lowest energy threshold and by a factor 3 above 3 EeV, where no candidates were found and the expected background is negligible. The presented limits can be used to probe the assumptions on chemical composition of ultra-high energy cosmic rays and allow for the constraint of the mass and lifetime phase space of super-heavy dark matter particles., Comment: 19 pages, 22 figures

We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV (1 EeV=$10^{18}$ eV) using the distributions of the depth of shower maximum $X_\mathrm{max}$. The analysis relies on ${\sim}50,000$ events recorded by the Surface Detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the data set offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the Fluorescence Detector, this enables the first measurement of the evolution of the mean and the standard deviation of the $X_\mathrm{max}$ distributions up to 100 EeV. Our findings are threefold: (1.) The evolution of the mean logarithmic mass towards a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (2.) The evolution of the fluctuations of $X_\mathrm{max}$ towards a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in $X_\mathrm{max}$ at the highest energies. (3.) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum., Comment: submitted to Phys. Rev. D, 28 pages, 18 figures, 5 tables

We present measurements of the atmospheric depth of the shower maximum $X_\mathrm{max}$, inferred for the first time on an event-by-event level using the Surface Detector of the Pierre Auger Observatory. Using deep learning, we were able to extend measurements of the $X_\mathrm{max}$ distributions up to energies of 100 EeV ($10^{20}$ eV), not yet revealed by current measurements, providing new insights into the mass composition of cosmic rays at extreme energies. Gaining a 10-fold increase in statistics compared to the Fluorescence Detector data, we find evidence that the rate of change of the average $X_\mathrm{max}$ with the logarithm of energy features three breaks at $6.5\pm0.6~(\mathrm{stat})\pm1~(\mathrm{sys})$ EeV, $11\pm 2~(\mathrm{stat})\pm1~(\mathrm{sys})$ EeV, and $31\pm5~(\mathrm{stat})\pm3~(\mathrm{sys})$ EeV, in the vicinity to the three prominent features (ankle, instep, suppression) of the cosmic-ray flux. The energy evolution of the mean and standard deviation of the measured $X_\mathrm{max}$ distributions indicates that the mass composition becomes increasingly heavier and purer, thus being incompatible with a large fraction of light nuclei between 50 EeV and 100 EeV., Comment: submitted to Phys. Rev. Lett., 10 pages, 3 figures, 1 table

Structural modularity is a pervasive feature of biological neural networks, which have been linked to several functional and computational advantages. Yet, the use of modular architectures in artificial neural networks has been relatively limited despite early successes. Here, we explore the performance and functional dynamics of a modular network trained on a memory task via an iterative growth curriculum. We find that for a given classical, non-modular recurrent neural network (RNN), an equivalent modular network will perform better across multiple metrics, including training time, generalizability, and robustness to some perturbations. We further examine how different aspects of a modular network's connectivity contribute to its computational capability. We then demonstrate that the inductive bias introduced by the modular topology is strong enough for the network to perform well even when the connectivity within modules is fixed and only the connections between modules are trained. Our findings suggest that gradual modular growth of RNNs could provide advantages for learning increasingly complex tasks on evolutionary timescales, and help build more scalable and compressible artificial networks.

This paper introduces a novel optically controllable molecular communication (MC) transmitter (TX) design, which is based on a vesicular nanodevice (ND) functionalized for the release of signaling molecules via transmembrane proteins. Due to its optical-to-chemical conversion capability, the ND can be used as an externally controllable TX for several MC applications such as bit transmission and targeted drug delivery. The proposed TX design comprises two cooperating modules, an energizing module and a release module, and depending on the specific choices for the modules allows for the release of different types of signaling molecules. After setting up a general system model for the proposed TX design, we conduct a detailed mathematical analysis of a specific realization. In particular, we derive an exact analytical and an approximate closed-form solution for the concentration of the released signaling molecules and validate our results by comparison with a numerical solution. Moreover, we consider the impact of a buffering medium, which is typically present in experimental and application environments, in both our analytical and numerical analyses to evaluate the feasibility of our proposed TX design for practical chemical implementation. The proposed analytical and closed-form models facilitate system parameter optimization, which can accelerate the experimental development cycle of the proposed ND architecture in the future., Comment: 7 pages double-column, 5 figures, 1 table. This work has been submitted to the 11th ACM International Conference on Nanoscale Computing and Communication, Milan, Italy

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

Magnetron sputtering inherently exhibits the advantage of dislodging particles from the target in a ratio equivalent to the target stoichiometry. Nevertheless, film compositions often deviate due to element-dependent scattering with the working gas, necessitating the adjustment of the sputtering process. In this work, we explore an unconventional approach of addressing this issue, involving the employment of an off-stoichiometric target. The required composition is obtained through an iterative process, which is demonstrated by Fe$_2$VAl and Fe$_2$V$_{0.9}$Ti$_{0.1}$Al films as case studies. Ultimately, the correct stoichiometry is obtained from Fe$_{1.86}$V$_{1.15}$Al$_{0.99}$ and Fe$_{1.88}$V$_{1.02}$Ti$_{0.13}$Al$_{0.97}$ targets, respectively. Despite the thermoelectric properties falling below expectations, mainly due to imperfect film crystallization, the strategy successfully achieved the desired stoichiometry, enabling accurate film synthesis without the need of advanced sputtering setups.

Bioacoustic research, vital for understanding animal behavior, conservation, and ecology, faces a monumental challenge: analyzing vast datasets where animal vocalizations are rare. While deep learning techniques are becoming standard, adapting them to bioacoustics remains difficult. We address this with animal2vec, an interpretable large transformer model, and a self-supervised training scheme tailored for sparse and unbalanced bioacoustic data. It learns from unlabeled audio and then refines its understanding with labeled data. Furthermore, we introduce and publicly release MeerKAT: Meerkat Kalahari Audio Transcripts, a dataset of meerkat (Suricata suricatta) vocalizations with millisecond-resolution annotations, the largest labeled dataset on non-human terrestrial mammals currently available. Our model outperforms existing methods on MeerKAT and the publicly available NIPS4Bplus birdsong dataset. Moreover, animal2vec performs well even with limited labeled data (few-shot learning). animal2vec and MeerKAT provide a new reference point for bioacoustic research, enabling scientists to analyze large amounts of data even with scarce ground truth information., Comment: Code available at: https://github.com/livingingroups/animal2vec | Dataset available at: https://doi.org/10.17617/3.0J0DYB

Animals have evolved to rapidly detect and recognise brief and intermittent encounters with odour packages, exhibiting recognition capabilities within milliseconds. Artificial olfaction has faced challenges in achieving comparable results -- existing solutions are either slow; or bulky, expensive, and power-intensive -- limiting applicability in real-world scenarios for mobile robotics. Here we introduce a miniaturised high-speed electronic nose; characterised by high-bandwidth sensor readouts, tightly controlled sensing parameters and powerful algorithms. The system is evaluated on a high-fidelity odour delivery benchmark. We showcase successful classification of tens-of-millisecond odour pulses, and demonstrate temporal pattern encoding of stimuli switching with up to 60 Hz. Those timescales are unprecedented in miniaturised low-power settings, and demonstrably exceed the performance observed in mice. For the first time, it is possible to match the temporal resolution of animal olfaction in robotic systems. This will allow for addressing challenges in environmental and industrial monitoring, security, neuroscience, and beyond.

We report long baseline interferometric observations with the CHARA Array that resolve six previously known double-lined spectroscopic binary systems in the Hyades cluster, with orbital periods ranging from 3 to 358 days: HD 27483, HD 283882, HD 26874, HD 27149, HD 30676, and HD 28545. We combine those observations with new and existing radial-velocity measurements, to infer the dynamical masses for the components as well as the orbital parallaxes. For most stars the masses are determined to better than 1%. Our work significantly increases the number of systems with mass determinations in the cluster. We find that while current models of stellar evolution for the age and metallicity of the Hyades are able to reproduce the overall shape of the empirical mass-luminosity relation, they overestimate the $V$-band fluxes by about 0.1 mag between 0.5 and 1.4 $M_{\odot}$. The disagreement is smaller in $H$, and near zero in $K$, and depends somewhat on the model. We also make use of the TESS light curves to estimate rotation periods for our targets, and detect numerous flares in one of them (HD 283882), estimating an average flaring rate of 0.44 events per day., Comment: 21 pages in two-column emulateapj format, including figures and tables. Accepted for publication in The Astrophysical Journal

Laser-cooled gases of atoms interacting with the field of an optical cavity are a powerful tool for quantum sensing and the simulation of open and closed quantum systems. They can display spontaneous self-organisation phase transitions, time crystals, new lasing mechanisms, squeezed states for quantum sensing, protection of quantum coherence, and dynamical phase transitions. However, all of these phenomena are explored in a discontinuous manner due to the need to stop and reload a new ensemble of atoms. Here we report the observation of hours-long continuous lasing from laser-cooled $^{88}$Sr atoms continuously loaded into a ring cavity. The required inversion to produce lasing arises from inversion in the atomic momentum degree of freedom, a mechanism related directly to self-organization phase transitions and collective atomic recoil lasing, both of which were previously only observed in a cyclic fashion compared to the truly continuous behavior here. Further, the sensitivity of the lasing frequency to cavity frequency changes is 120 fold suppressed due to an atomic loss mechanism, opening an interesting new path to compensate cavity frequency noise for realizing narrow frequency references. This work opens the way for continuous cavity QED quantum simulation experiments as well as continuous superradiant lasers., Comment: 10 pages, 5 figures

With economic development, the complexity of infrastructure has increased drastically. Similarly, with the shift from fossil fuels to renewable sources of energy, there is a dire need for such systems that not only predict and forecast with accuracy but also help in understanding the process of predictions. Artificial intelligence and machine learning techniques have helped in finding out wellperforming solutions to different problems in the energy sector. However, the usage of state-of-the-art techniques like reinforcement learning is not surprisingly convincing. This paper discusses the application of reinforcement techniques in energy systems and how explanations of these models can be helpful

In a physical system, changing parameters such as temperature can induce a phase transition: an abrupt change from one state of matter to another. Analogous phenomena have recently been observed in large language models. Typically, the task of identifying phase transitions requires human analysis and some prior understanding of the system to narrow down which low-dimensional properties to monitor and analyze. Statistical methods for the automated detection of phase transitions from data have recently been proposed within the physics community. These methods are largely system agnostic and, as shown here, can be adapted to study the behavior of large language models. In particular, we quantify distributional changes in the generated output via statistical distances, which can be efficiently estimated with access to the probability distribution over next-tokens. This versatile approach is capable of discovering new phases of behavior and unexplored transitions -- an ability that is particularly exciting in light of the rapid development of language models and their emergent capabilities., Comment: 21 pages, 4 figures

Fiber-based distribution of triggered, entangled, single-photon pairs is a key requirement for the future development of terrestrial quantum networks. In this context, semiconductor quantum dots (QDs) are promising candidates for deterministic sources of on-demand polarization-entangled photon pairs. So far, the best QD polarization-entangled-pair sources emit in the near-infrared wavelength regime, where the transmission distance in deployed fibers is limited. Here, to be compatible with existing fiber network infrastructures, bi-directional polarization-conserving quantum frequency conversion (QFC) is employed to convert the QD emission from \unit[780]{nm} to telecom wavelengths. We show the preservation of polarization entanglement after QFC (fidelity to Bell state $F_{\phi^+, conv}=0.972\pm0.003$) of the biexciton transition. As a step towards real-world applicability, high entanglement fidelities ($F_{\phi^+, loop}=0.945\pm0.005$) after the propagation of one photon of the entangled pair along a \unit[35.8]{km} field installed standard single mode fiber link are reported. Furthermore, we successfully demonstrate a second polarization-conversing QFC step back to \unit[780]{nm} preserving entanglement ($F_{\phi^+, back}=0.903\pm0.005$). This further prepares the way for interfacing quantum light to various quantum memories.

We analyze the gauge fixing precision dependence of some non-local quark-blinear lattice operators interesting in computing parton physics for several measurements, using 5 lattice spacings ranging from 0.032 fm to 0.121 fm. Our results show that gauge dependent non-local measurements are significantly more sensitive to the precision of gauge fixing than anticipated. The impact of imprecise gauge fixing is significant for fine lattices and long distances. For instance, even with the typically defined precision of Landau gauge fixing of $10^{-8}$, the deviation caused by imprecise gauge fixing can reach 12 percent, when calculating the trace of Wilson lines at 1.2 fm with a lattice spacing of approximately 0.03 fm. Similar behavior has been observed in $\xi$ gauge and Coulomb gauge as well. For both quasi PDFs and quasi TMD-PDFs operators renormalized using the RI/MOM scheme, convergence for different lattice spacings at long distance is only observed when the precision of Landau gauge fixing is sufficiently high. To describe these findings quantitatively, we propose an empirical formula to estimate the required precision., Comment: 16 pages, 15 figures

There are two distinct regimes of Yang-Mills theory where we can demonstrate confinement, the existence of a mass gap, and fractional theta angle dependence using a reliable semi-classical calculation. The two regimes are Yang-Mills theory on $S^1 \times {\mathbb R}^3$ with a small circle and a double-trace deformation, and Yang-Mills theory on $T^2 \times {\mathbb R}^2$ where the torus $T^2$ is small and threaded by a 't Hooft flux. In the first case the confinement mechanism is related to self-dual monopoles, whereas in the second case self-dual center-vortices play a crucial role. These two topological objects are distinct. In particular, they have different mutual statistics with Wilson loops. On the other hand, they carry the same topological charge and action. On ${\mathbb R \times T^2 \times S^1}$, we are able to extrapolate both monopole regime and vortex regime to a quantum mechanical domain, where a cross-over takes place. Both sides of the cross-over are described by a deformed $\mathbb Z_N$ TQFT. On ${\mathbb R^2 \times S^1 \times S^1}$, we derive the effective field theory of vortices from the effective theory of monopoles in the presence of a 't Hooft flux. This results from a two-stage adjoint Higgs mechanism, to $U(1)^{N-1}$ in 3d first and a $\mathbb Z_N$ EFT in 2d second. This proves adiabatic continuity of the two confinement mechanisms across dimensions and shows how monopoles and their magnetic flux transmute into center-vortices. This basic mechanism is flux fractionalization: The magnetic flux of the monopoles fractionalizes and collimates in such a way that 2d Wilson loops detect it as a center vortex., Comment: 30 pages, 5 figures, Minor changes

Recent advancements in electron microscopy have introduced innovative techniques enabling the inelastic interaction of fast electrons with tightly confined and intense light fields. These techniques, commonly summarized under the term photon-induced nearfield electron microscopy now offer unprecedented capabilities for a precise mapping of the characteristics of optical near-fields with remarkable spatial resolution but their spectral resolution were only scarcely investigated. In this study, we employ a strongly chirped and temporally broadband light pulse to investigate the interaction between free electrons and light at the edge of a MoS2 thin film. Our approach unveils the details of electron-light coupling, revealing a pronounced dependence of the coupling strength on both the position and photon energy. Employing numerical simulations of a simplified model system we identify these modulations to be caused by optical interferences between the incident and reflected field as well as an optical mode guided within the transition metal dichalcogenide film., Comment: 19 pages, 3 figures, 40 references

This paper details the efforts of the WisPerMed team in the BioLaySumm2024 Shared Task on automatic lay summarization in the biomedical domain, aimed at making scientific publications accessible to non-specialists. Large language models (LLMs), specifically the BioMistral and Llama3 models, were fine-tuned and employed to create lay summaries from complex scientific texts. The summarization performance was enhanced through various approaches, including instruction tuning, few-shot learning, and prompt variations tailored to incorporate specific context information. The experiments demonstrated that fine-tuning generally led to the best performance across most evaluated metrics. Few-shot learning notably improved the models' ability to generate relevant and factually accurate texts, particularly when using a well-crafted prompt. Additionally, a Dynamic Expert Selection (DES) mechanism to optimize the selection of text outputs based on readability and factuality metrics was developed. Out of 54 participants, the WisPerMed team reached the 4th place, measured by readability, factuality, and relevance. Determined by the overall score, our approach improved upon the baseline by approx. 5.5 percentage points and was only approx 1.5 percentage points behind the first place., Comment: 4 pages, 6 figure, 3 tables, acctepted at: BIONLP 2024 and Shared Tasks @ ACL 2024

In a recently developed methodology termed photon induced near-field electron microscopy (PINEM), the inelastic scattering of electrons off illuminated nanostructures provides direct experimental access to the structure of optical near-field modes and their population. Whereas the inelastic scattering probability can be quantitatively linked to the near field distribution, analytical results for simple light scattering geometries are scarce. Here we derive a fully analytical expression for the coupling strength between free electrons and optical near-fields in planar geometries representing dielectric thin films. Contributions to the overall coupling from the electric field above, below and within the sample are analyzed in detail. By carefully choosing the relative angles between electron beam, light and thin film and by accounting for a broad spectrum of photon energies, we demonstrate that one can imprint optical material properties like the reflectivity onto the electron energy distribution., Comment: 17 pages, 4 figures, 32 references

This study aims to leverage state of the art language models to automate generating the "Brief Hospital Course" and "Discharge Instructions" sections of Discharge Summaries from the MIMIC-IV dataset, reducing clinicians' administrative workload. We investigate how automation can improve documentation accuracy, alleviate clinician burnout, and enhance operational efficacy in healthcare facilities. This research was conducted within our participation in the Shared Task Discharge Me! at BioNLP @ ACL 2024. Various strategies were employed, including few-shot learning, instruction tuning, and Dynamic Expert Selection (DES), to develop models capable of generating the required text sections. Notably, utilizing an additional clinical domain-specific dataset demonstrated substantial potential to enhance clinical language processing. The DES method, which optimizes the selection of text outputs from multiple predictions, proved to be especially effective. It achieved the highest overall score of 0.332 in the competition, surpassing single-model outputs. This finding suggests that advanced deep learning methods in combination with DES can effectively automate parts of electronic health record documentation. These advancements could enhance patient care by freeing clinician time for patient interactions. The integration of text selection strategies represents a promising avenue for further research., Comment: 8 pages, 6 tables, 8 figures, submitted to: BioNLP 2024 and Shared Tasks @ ACL 2024

We partially characterize nuclearity for the recently introduced class of hypergraph C*-algebras using a tailor-made hypergraph minor relation. The latter is generated by certain operations on hypergraphs which resemble the moves on directed graphs used by Eilers, Restorff, Ruiz and S{\o}rensen to classify unital graph C*-algebras. In particular, we obtain a new proof of the fact that every graph C*-algebra associated to a finite graph is nuclear.

Automated medical image analysis systems often require large amounts of training data with high quality labels, which are difficult and time consuming to generate. This paper introduces Radiology Object in COntext version 2 (ROCOv2), a multimodal dataset consisting of radiological images and associated medical concepts and captions extracted from the PMC Open Access subset. It is an updated version of the ROCO dataset published in 2018, and adds 35,705 new images added to PMC since 2018. It further provides manually curated concepts for imaging modalities with additional anatomical and directional concepts for X-rays. The dataset consists of 79,789 images and has been used, with minor modifications, in the concept detection and caption prediction tasks of ImageCLEFmedical Caption 2023. The dataset is suitable for training image annotation models based on image-caption pairs, or for multi-label image classification using Unified Medical Language System (UMLS) concepts provided with each image. In addition, it can serve for pre-training of medical domain models, and evaluation of deep learning models for multi-task learning., Comment: Accepted for Scientific Data

The cross-section for the production of an electroweak gauge boson ($G = W^{\pm}, Z^0, \gamma$) at forward rapidities in $pp$ collisions is derived within the color - dipole $S$ - matrix framework. We present the full expressions for the differential cross-section of the $q p \rightarrow G X$ process in the impact parameter and transverse momentum spaces, considering the longitudinal and transverse polarizations of the gauge boson. The particular cases associated with the Drell - Yan process and real photon production are discussed. We demonstrate that the final formulae are expressed in terms of the dipole - proton cross-section or the unintegrated gluon distribution, and can be used to estimate the impact of the saturation effects in the gauge boson production at the LHC and future colliders., Comment: 18 pages, 2 figures, 1 table

This paper proposes a framework for training Reinforcement Learning agents using Python in conjunction with Simulink models. Leveraging Python's superior customization options and popular libraries like Stable Baselines3, we aim to bridge the gap between the established Simulink environment and the flexibility of Python for training bleeding edge agents. Our approach is demonstrated on the Quanser Aero 2, a versatile dual-rotor helicopter. We show that policies trained on Simulink models can be seamlessly transferred to the real system, enabling efficient development and deployment of Reinforcement Learning agents for control tasks. Through systematic integration steps, including C-code generation from Simulink, DLL compilation, and Python interface development, we establish a robust framework for training agents on Simulink models. Experimental results demonstrate the effectiveness of our approach, surpassing previous efforts and highlighting the potential of combining Simulink with Python for Reinforcement Learning research and applications., Comment: Accepted at SMPS2024

Following previous works on that topic, we consider Euclidean hadronic matrix elements in position space of two spatially separated local currents on the lattice, in order to extract the $x$ dependence of parton distribution functions (PDFs). The corresponding approach is often referred to by the term lattice cross section. In this work we will consider valence quark PDFs of an unpolarized proton. We adapt the previously established formalism to our choice of operators. The calculation of the two-current matrix elements requires the evaluation of four-point functions. The corresponding calculation is carried out on a $n_f = 2+1$ gauge ensemble with lattice spacing $a = 0.0856~\mathrm{fm}$ and pseudoscalar masses $m_\pi = 355~\mathrm{MeV}$ and $m_K = 441~\mathrm{MeV}$. The four-point functions have been evaluated in a previous project. The lattice data is converted to the $\overline{\mathrm{MS}}$ scheme at a scale $\mu=2~\mathrm{GeV}$ and improved with respect to lattice artifacts. We use a common model as fit ansatz for the lattice data in order to extract the PDFs., Comment: 11 pages, 6 figures

Cavity quantum materials combine the rich many-body physics of condensed matter systems with strong coupling to the surrounding electromagnetic field, which presents both novel prospects and intricate challenges. One is often interested in the properties of one specific aspect of the material, e.g. the electronic many-body dynamics, subject to a structured bath of phononic and photonic modes. Open quantum systems featuring non-Markovian dynamics are routinely solved using techniques such as the Hierarchical Equations of Motion (HEOM) but their usage of the system density-matrix renders them intractable for many-body systems. Here, we combine the HEOM with the Bogoliubov-Born-Green-Kirkwood-Yvon (BBGKY) hierarchy to reach a consistent and rigorous description of open many-body systems and their quantum dynamics. We demonstrate first the strength and limitations of this stacked hierarchy for superradiant emission and spin-squeezing of established quantum optical models before presenting its full potential for quantum many-body systems. In particular, we explicitly simulate the impact of charge noise on the dynamic of the Fermi-Hubbard model subject to a structured bath comprising cavity and vibro-phononic environment. Strong optical coupling not only modifies the dynamic of the many-body system but serves furthermore as measurement channel providing information about the correlated motion imprinted by charge noise. Our work establishes an accessible, yet rigorous, route between condensed matter and quantum optics, fostering the growth of a new domain at their interface., Comment: This early version will be refined and updated with additional results in the near future

V2487 Ophiuchi (V2487 Oph) is a recurrent nova with classical nova eruptions in 1900 and 1998, and it is also the most extreme known superflare star. These superflares are roughly-hour-long flares with amplitudes and optical energies reaching up to 1.10 mag and $10^{39.21}$ ergs, with the superflares recurring once-a-day. The V2487 Oph superflares are certainly operating with the same mechanism as all the other types of superflare stars, where magnetic loops are twisted and stretched until reconnection occurs, whereupon ambient electrons are accelerated to relativistic energies and then emitted bremsstrahlung radiation from X-ray to radio. V2487 Oph is unique among known superflare stars in that one of the loop footprints is in an accretion disk. This exact mechanism was theoretically predicted by M. R. Hayashi and colleagues in 1996. Now, I have found two superflares recorded on Harvard archival photographs from the years 1941 and 1942. These two superflares have $B$ magnitude amplitudes of $>$1.83 and $>$2.00 mag and total radiated energies of $10^{42.4}$ and $10^{42.5}$ ergs with bolometric corrections. Each has emitted energies of $\sim$30-billion Carringtons, in units of the most energetic solar flare. Further, I find superflares in the Zwicky Transient Factory light curves, so V2487 Oph has been superflaring from 1941 to 2023. For the observed number distribution of $dN/dE$=$4E^{-2}$ superflares per year, for $E$ in units of $10^{41}$ ergs, the emitted energy in superflare light is $10^{42.1}$ erg in each year, or $10^{44.1}$ ergs from 1941 to 2023., Comment: Astrophysical Journal, in press

This work considers the problem of integrated sensing and communications (ISAC) with a massive number of unsourced and uncoordinated users. In the proposed model, known as the unsourced ISAC system (UNISAC), all active communication and sensing users simultaneously share a short frame to transmit their signals, without requiring scheduling with the base station (BS). Hence, the signal received from each user is affected by significant interference from numerous interfering users, making it challenging to extract the transmitted signals. UNISAC aims to decode the transmitted message sequences from communication users while simultaneously detecting active sensing users and estimating their angles of arrival, regardless of the identity of the senders. In this paper, we derive an approximate achievable result for UNISAC and demonstrate its superiority over conventional approaches such as ALOHA, time-division multiple access, treating interference as noise, and multiple signal classification. Through numerical simulations, we validate the effectiveness of UNISAC's sensing and communication capabilities for a large number of users.

We report on the discovery and validation of a transiting long-period mini-Neptune orbiting a bright (V = 9.0 mag) G dwarf (TOI 4633; R = 1.05 RSun, M = 1.10 MSun). The planet was identified in data from the Transiting Exoplanet Survey Satellite by citizen scientists taking part in the Planet Hunters TESS project. Modeling of the transit events yields an orbital period of 271.9445 +/- 0.0040 days and radius of 3.2 +/- 0.20 REarth. The Earth-like orbital period and an incident flux of 1.56 +/- 0.2 places it in the optimistic habitable zone around the star. Doppler spectroscopy of the system allowed us to place an upper mass limit on the transiting planet and revealed a non-transiting planet candidate in the system with a period of 34.15 +/- 0.15 days. Furthermore, the combination of archival data dating back to 1905 with new high angular resolution imaging revealed a stellar companion orbiting the primary star with an orbital period of around 230 years and an eccentricity of about 0.9. The long period of the transiting planet, combined with the high eccentricity and close approach of the companion star makes this a valuable system for testing the formation and stability of planets in binary systems., Comment: 24 pages, 16 figures, 4 tables

Membraneless droplets formed through liquid-liquid phase separation (LLPS) play a crucial role in mRNA storage, enabling organisms to swiftly respond to environmental changes. However, the mechanisms underlying mRNA integration and protection within droplets remain unclear. Here, we unravel the role of bacterial aggresomes as stress granules (SGs) in safeguarding mRNA during stress. We discovered that upon stress onset, mobile mRNA molecules selectively incorporate into individual proteinaceous SGs based on length-dependent enthalpic gain over entropic loss. As stress prolongs, SGs undergo compaction facilitated by stronger non-specific RNA-protein interactions, thereby promoting recruitment of shorter RNA chains. Remarkably, mRNA ribonucleases are repelled from bacterial SGs, due to the influence of protein surface charge. This exclusion mechanism ensures the integrity and preservation of mRNA within SGs during stress conditions, explaining how mRNA can be stored and protected from degradation. Following stress removal, SGs facilitate mRNA translation, thereby enhancing cell fitness in changing environments. These droplets maintain mRNA physiological activity during storage, making them an intriguing new candidate for mRNA therapeutics manufacturing.

In this paper, the feasibility of implementing a lightweight key distribution scheme using physical layer security for secret key generation (SKG) is explored. Specifically, we focus on examining SKG with the received signal strength (RSS) serving as the primary source of shared randomness. Our investigation centers on a frequency-selective line-of-sight (LoS) multipath channel, with a particular emphasis on assessing SKG rates derived from the distributions of RSS. We derive the received signal distributions based on how the multipath components resolve at the receiver. The mutual information (MI) is evaluated based on LoS 3GPP channel models using a numerical estimator. We study how the bandwidth, delay spread, and Rician K-factor impact the estimated MI. This MI then serves as a benchmark setting bounds for the SKG rates in our exploration.

The evolution of Cataclysmic Variables (CVs) is driven by period-changes ($\dot{P}$), for which the long-venerable consensus is the Magnetic Braking Model (MBM). The MBM has its only distinctive assumption being a power-law `recipe' describing the angular momentum loss (AML) in the binary, producing a single unique evolutionary track with $\dot{P}$ as a function of the orbital period. This required prediction can be used to test the most-fundamental assumption of MBM, but it has never been tested previously. In this paper, I collect $\dot{P}$ measures for 52 CVs of all types. First, 44 per cent of the CVs have positive-$\dot{P}$, with such being impossible in MBM. Second, even amongst the CVs with negative-$\dot{P}$, their $\dot{P}$ measures are always more-negative than required by MBM, with an average deviation of 110$\times$. Third, three CVs have large chaotic variations in $\dot{P}$ that are impossible for MBM, proving that some unknown mechanism exists and is operating that dominates for these systems. Fourth, the MBM does not account for the long-term effects on evolution arising from the large sudden period decreases seen across many nova events, with this unaccounted effect dominating for the majority of nova systems and changing the sign of the overall evolutionary $\dot{P}$. Fifth, three recurrent novae are observed to suddenly change $\dot{P}$ by an order-of-magnitude across a nova event, with this being impossible in the MBM. In all, the required MBM $\dot{P}$ predictions all fail for my 52 CVs, usually by orders-of-magnitude, so the MBM AML-recipe is wrong by orders-of-magnitude., Comment: ApJ in press

We study collective light scattering from linear crystals with up to twelve $^{40}\text{Ca}^+$ ions, acting as coherent single photon emitters. Light-scattering is induced by two-photon laser excitation, starting from the S$_{1/2}$ to D$_{5/2}$ quadrupole transition at 729~nm in combination with laser excitation of the D$_{5/2}$ to P$_{3/2}$ dipole transition at 854~nm, followed by a decay back to S$_{1/2}$ via a single photon emission near 393~nm. The scattered intensity is recorded in the far field, featuring the interference of emitted light fields of the entire crystal. Furthermore, we demonstrate spin-dependent coherent scattering and unveil the time evolution of a previously encoded spin texture in a crystal employing the recorded dynamics of the spatial frequency components of the fringe pattern.

The zonotope containment problem, i.e., whether one zonotope is contained in another, is a central problem in control theory. Applications include detecting faults and robustifying controllers by computing invariant sets, and obtain fixed points in reachability analysis. Despite the inherent co-NP-hardness of this problem, an approximation algorithm developed by S. Sadraddini and R. Tedrake has gained widespread recognition for its swift execution and consistent reliability in practice. In our study, we substantiate the precision of the algorithm with a definitive proof, elucidating the empirical accuracy observed in practice. Our proof hinges on establishing a connection between the containment problem and the computation of matrix norms, thereby enabling the extension of the approximation algorithm to encompass ellipsotopes -- a broader class of sets derived from zonotopes. We also explore the computational complexity of the ellipsotope containment problem with a focus on approximability. Finally, we present new methods to compute safe sets for linear dynamical systems, demonstrating the practical relevance of approximating the ellipsotope containment problem.

Using elementary techniques from Geometric Analysis, Partial Differential Equations, and Abelian $C^*$ Algebras, we uncover a novel, yet familiar, global geometric invariant -- namely the indexed set of integrals of triple products of eigenfunctions of the Laplace-Beltrami operator, to precisely characterize which isospectral closed Riemannian manifolds are isometric., Comment: 8 pages, no figures

Bosonic quantum devices offer a novel approach to realize quantum computations, where the quantum two-level system (qubit) is replaced with the quantum (an)harmonic oscillator (qumode) as the fundamental building block of the quantum simulator. The simulation of chemical structure and dynamics can then be achieved by representing or mapping the system Hamiltonians in terms of bosonic operators. In this perspective, we review recent progress and future potential of using bosonic quantum devices for addressing a wide range of challenging chemical problems, including the calculation of molecular vibronic spectra, the simulation of gas-phase and solution-phase adiabatic and nonadiabatic chemical dynamics, the efficient solution of molecular graph theory problems, and the calculations of electronic structure., Comment: 40 pages including references, 13 figures, revised

In mutation testing, the quality of a test suite is evaluated by introducing faults into a program and determining whether the program's tests detect them. Most existing approaches for mutation testing involve the application of a fixed set of mutation operators, e.g., replacing a "+" with a "-" or removing a function's body. However, certain types of real-world bugs cannot easily be simulated by such approaches, limiting their effectiveness. This paper presents a technique where a Large Language Model (LLM) is prompted to suggest mutations by asking it what placeholders that have been inserted in source code could be replaced with. The technique is implemented in LLMorpheus, a mutation testing tool for JavaScript, and evaluated on 13 subject packages, considering several variations on the prompting strategy, and using several LLMs. We find LLMorpheus to be capable of producing mutants that resemble existing bugs that cannot be produced by StrykerJS, a state-of-the-art mutation testing tool. Moreover, we report on the running time, cost, and number of mutants produced by LLMorpheus, demonstrating its practicality.

Silicon carbide (SiC) is the leading wide-bandgap semiconductor material, providing mature doping and device fabrication. Additionally, SiC hosts a multitude of optically active point defects (color centers), it is an excellent material for optical resonators due to its high refractive index and an outstanding material for mechanical resonators due to its high Q/f product. Moreover, epitaxial graphene layers can be grown as ultrathin electrodes and provide the potential to fine-tune color center resonances. These characteristics render SiC an ideal platform for experiments with single color centers towards quantum technologies including coupling color centers towards cooperative effects. A crucial step towards harnessing the full potential of the SiC platform includes technologies to create color centers with defined localization and density, e.g.\ to facilitate their coupling to nano-photonic structures and to observe cooperative effects. Here, silicon vacancy centers (V$_{Si}$) stand out as no impurity atom is needed and high-thermal budget annealing steps can be avoided. We characterize the effect of localized, femtosecond laser irradiation of SiC, investigating surface modifications and photoluminescence including Raman spectroscopy and optical lifetime measurements., Comment: 7 pages, 6 figures

Heterogeneous multilayered solid-state electrolyte (HMSSE) has been widely explored for their broadened working voltage range and compatibility with electrodes. However, due to the limitations of traditional manufacturing methods such as casting, the interface between electrolyte layers in HMSSE can decrease the ionic conductivity severely. Here, a novel combinatory aerosol jet printing (CAJP) is introduced to fabricate functionally graded solid-state electrolyte (FGSSE) without sharp interface. Owing to the unique ability of CAJP (in-situ mixing and instantaneous tuning of the mixing ratio), FGSSE with smooth microscale compositional gradation is achieved. Electrochemical tests show that FGSSE has excellent oxidative stability exceeding 5.5 V and improved conductivity (>7 times of an analogous HMSSE). By decoupling the total resistance, we show that the resistance from the electrolyte/electrolyte interface of HMSSE is 5.7 times of the total resistance of FGSSE. The Li/FGSSE/NCM622 cell can be stably run for more than 200 cycles along with improved rate performance.

With the STAR experiment at the BNL Relativisic Heavy Ion Collider, we characterize $\sqrt{s_\mathrm{NN}}$ = 200 GeV p+Au collisions by event activity (EA) measured within the pseudorapidity range $eta$ $in$ [-5, -3.4] in the Au-going direction and report correlations between this EA and hard- and soft- scale particle production at midrapidity ($\eta$ $\in$ [-1, 1]). At the soft scale, charged particle production in low-EA p+Au collisions is comparable to that in p+p collisions and increases monotonically with increasing EA. At the hard scale, we report measurements of high transverse momentum (pT) jets in events of different EAs. In contrast with the soft particle production, high-pT particle production and EA are found to be inversely related. To investigate whether this is a signal of jet quenching in high-EA events, we also report ratios of pT imbalance and azimuthal separation of dijets in high- and low-EA events. Within our measurement precision, no significant differences are observed, disfavoring the presence of jet quenching in the highest 30% EA p+Au collisions at $\sqrt{s_\mathrm{NN}}$ = 200 GeV., Comment: 12 page, 9 figures

We introduce a coarse algebraic invariant for coarse groups and use it to differentiate various coarsifications of the group of integers. This lets us answer two questions posed by Leitner and the second author. The invariant is obtained by considering the set of exponents n such that taking n-th powers defines a coarse equivalence of the coarse group., Comment: 14 pages

Multilinguality is crucial for extending recent advancements in language modelling to diverse linguistic communities. To maintain high performance while representing multiple languages, multilingual models ideally align representations, allowing what is learned in one language to generalise to others. Prior research has emphasised the importance of parallel data and shared vocabulary elements as key factors for such alignment. In this study, we investigate an unintuitive novel driver of cross-lingual generalisation: language imbalance. In controlled experiments on perfectly equivalent cloned languages, we observe that the existence of a predominant language during training boosts the performance of less frequent languages and leads to stronger alignment of model representations across languages. Furthermore, we find that this trend is amplified with scale: with large enough models or long enough training, we observe that bilingual training data with a 90/10 language split yields better performance on both languages than a balanced 50/50 split. Building on these insights, we design training schemes that can improve performance in all cloned languages, even without altering the training data. As we extend our analysis to real languages, we find that infrequent languages still benefit from frequent ones, yet whether language imbalance causes cross-lingual generalisation there is not conclusive.

Tokenisation is a core part of language models (LMs). It involves splitting a character sequence into subwords which are assigned arbitrary indices before being served to the LM. While typically lossless, however, this process may lead to less sample efficient LM training: as it removes character-level information, it could make it harder for LMs to generalise across similar subwords, such as now and Now. We refer to such subwords as near duplicates. In this paper, we study the impact of near duplicate subwords on LM training efficiency. First, we design an experiment that gives us an upper bound to how much we should expect a model to improve if we could perfectly generalise across near duplicates. We do this by duplicating each subword in our LM's vocabulary, creating perfectly equivalent classes of subwords. Experimentally, we find that LMs need roughly 17% more data when trained in a fully duplicated setting. Second, we investigate the impact of naturally occurring near duplicates on LMs. Here, we see that merging them considerably hurts LM performance. Therefore, although subword duplication negatively impacts LM training efficiency, naturally occurring near duplicates may not be as similar as anticipated, limiting the potential for performance improvements.

Resonant planetary migration in protoplanetary discs can lead to an interplay between the resonant interaction of planets and their disc torques called overstability. While theoretical predictions and N-body simulations hinted at its existence, there was no conclusive evidence until hydrodynamical simulations were performed. Our primary purpose is to find a hydrodynamic setup that induces overstability in a planetary system with two moderate-mass planets in a first-order 2:1 mean motion resonance. We also aim to analyse the impact of key disc parameters, namely the viscosity, surface density, and aspect ratio, on the occurrence of overstability in this planetary system when the masses of the planets are kept constant. We performed 2D locally isothermal hydrodynamical simulations of two planets, with masses of 5 and 10 $M_{\oplus}$, in a 2:1 resonance. Upon identifying the fiducial model in which the system exhibits overstability, we performed simulations with different disc parameters to explore the effects of the disc on the overstability of the system. We observe an overstable planetary system in our hydrodynamic simulations. In the parameter study, we note that overstability occurs in discs characterised by low surface density and low viscosity. Increasing the surface density reduces the probability of overstability within the system. A limit cycle was observed in a specific viscous model with $\alpha_{\nu} = 10^{-3}$. In almost all our models, planets create partial gaps in the disc, which affects both the migration timescale and structure of the planetary system. We demonstrate the existence of overstability using hydrodynamic simulations but find deviations from the analytic approximation and show that the main contribution to this deviation can be attributed to dynamic gap opening., Comment: 16 pages (including appendices), 27 figures, 3 tables, accepted for publication by A&A