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Energy is a critical driver of modern economic systems. Accurate energy price forecasting plays an important role in supporting decision-making at various levels, from operational purchasing decisions at individual business organizations to policy-making. A significant body of literature has looked into energy price forecasting, investigating a wide range of methods to improve accuracy and inform these critical decisions. Given the evolving landscape of forecasting techniques, the literature lacks a thorough empirical comparison that systematically contrasts these methods. This paper provides an in-depth review of the evolution of forecasting modeling frameworks, from well-established econometric models to machine learning methods, early sequence learners such LSTMs, and more recent advancements in deep learning with transformer networks, which represent the cutting edge in forecasting. We offer a detailed review of the related literature and categorize forecasting methodologies into four model families. We also explore emerging concepts like pre-training and transfer learning, which have transformed the analysis of unstructured data and hold significant promise for time series forecasting. We address a gap in the literature by performing a comprehensive empirical analysis on these four family models, using data from the EU energy markets, we conduct a large-scale empirical study, which contrasts the forecasting accuracy of different approaches, focusing especially on alternative propositions for time series transformers.

In this talk, we discuss the phenomenology of radiative 3-loop seesaw models. The 3-loop suppression allows the new particles to have masses at the TeV scale, along with relatively large Yukawa couplings, while retaining consistency with neutrino masses and mixing, as observed in neutrino oscillation experiments. This leads to a rich phenomenology, especially in searches for charged lepton flavor violation, where the models predict sizable rates, well within future experimental reach. The models provide viable fermionic or scalar dark matter candidates, as is typical within the scotogenic paradigm. We discuss specific realizations in which the W-mass anomaly and the baryon asymmetry of the Universe can be accommodated, while complying with current constraints imposed by electroweak precision observables, charged-lepton flavor violation and neutrinoless double-beta decay., Comment: 6 pages, 4 figures. Talk given at the 42nd International Conference on High Energy Physics - ICHEP2024 (18-24 July 2024, Prague, Czech Republic)

The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on inter-continental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in October 2018. The longest-baseline detections approach 11$\,$G$\lambda$ corresponding to an angular resolution, or fringe spacing, of 19$\mu$as. The Allan deviation of the visibility phase at 870$\mu$m is comparable to that at 1.3$\,$mm on the relevant integration time scales between 2 and 100$\,$s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870$\mu$m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time., Comment: Corresponding author: S. Doeleman

Here we report on the first measurements of the $\gamma$-ray strength functions and nuclear level densities of ${}^{112,114}$Sn performed at the 9~MV Tandem accelerator facilities at IFIN-HH using the Oslo method. We extract thermodynamic properties as well as both gross and fine properties of the pygmy dipole resonance for systematic comparison in the chain of Sn isotopes. The results are compared with microscopic models implemented in the TALYS reaction code, and the fully microscopic quasiparticle-phonon model for the underlying nuclear structure of the dipole strength in ${}^{112,114}$Sn. The experimental data and theoretical results are further included into the cross-section and reaction rate calculations for the $(\mathrm{n},\gamma)$ production reaction of the $p$-process nuclei ${}^{112,114}$Sn showing a significant increase in reaction rates at high temperatures compared to existing nuclear databases., Comment: 21 pages, 17 figures

In recent years there have been a growing interest in online auditing of information flow over social networks with the goal of monitoring undesirable effects, such as, misinformation and fake news. Most previous work on the subject, focus on the binary classification problem of classifying information as fake or genuine. Nonetheless, in many practical scenarios, the multi-class/label setting is of particular importance. For example, it could be the case that a social media platform may want to distinguish between ``true", ``partly-true", and ``false" information. Accordingly, in this paper, we consider the problem of online multiclass classification of information flow. To that end, driven by empirical studies on information flow over real-world social media networks, we propose a probabilistic information flow model over graphs. Then, the learning task is to detect the label of the information flow, with the goal of minimizing a combination of the classification error and the detection time. For this problem, we propose two detection algorithms; the first is based on the well-known multiple sequential probability ratio test, while the second is a novel graph neural network based sequential decision algorithm. For both algorithms, we prove several strong statistical guarantees. We also construct a data driven algorithm for learning the proposed probabilistic model. Finally, we test our algorithms over two real-world datasets, and show that they outperform other state-of-the-art misinformation detection algorithms, in terms of detection time and classification error., Comment: 42 pages

We show that certain moduli spaces of vector bundles over blown-up primary Hopf surfaces admit no compact components. These are the moduli spaces used by Andrei Teleman in his work on the classification of class $VII$ surfaces., Comment: The paper is published

The multipole expansion, a ubiquitous tool in a variety of physical problems, can be formulated in spherical and Cartesian coordinates. By constructing an explicit map linking both formulations in isotropic media, we discover a lack of equivalence between both approaches in anisotropic media. In isotropic media, the Cartesian multipole tensor can be reduced to a spherical tensor containing significantly fewer entries. In anisotropic media, however, the loss of propagation symmetry prevents this reduction. In turn, non-harmonic sources radiate fields that can be projected onto a finite set of Cartesian multipole moments but require (possibly infinitely) many spherical moments. For harmonic sources, the link between both approaches presents a systematic way to construct the spherical multipole expansion from the Cartesian one. The lack of equivalence between both approaches results in physically significant effects wherever the field propagation includes the Laplace operator. We illustrate this issue on an electromagnetic radiation inverse problem in anisotropic media, including an analysis of a large-anisotropy regime. We show that the use of the Cartesian approach significantly increases the efficiency and interpretability of the model. The proposed approach opens the door to wider applications of the multipole expansion in anisotropic media, whose importance is rising in multiple physical systems., Comment: 16 pages, 5 figures

The Blandford-Znajek (BZ) process is electromagnetic energy release from rotating black holes (BHs) along magnetic field lines threading them and widely believed to drive relativistic jets. This process is successfully demonstrated in general relativistic magnetohydrodynamic (MHD) simulations with the coordinate system regular on the event horizon, by which one can estimate the outward Poynting flux, although the direct energy release through the horizon shown in the simulations does not provide an intuitive picture. We revisit the mechanism of BH energy reduction by utilizing the coordinate system singular on the horizon, in which the falling membrane of past accreted matter should exist above the horizon. We find that the Poynting flux is produced at the boundary between the falling membrane and the magnetically-dominated inflow, and the front of the inflow creates the negative electromagnetic energy, which reduces the rotational energy of spacetime. We also clarify that the poloidal electric current does not form a closed circuit within the magnetically-dominated flow. Previous interpretations of the BZ process and possibilities of the ideal MHD violation and BH charging are also discussed., Comment: 14 pages, 2 figures; submitted to PTEP

Traumatic brain injury (TBI) can cause a range of cognitive and communication challenges that negatively affect social participation in both face-to-face interactions and computer-mediated communication. In particular, individuals with TBI report barriers that limit access to participation on social media platforms. To improve access to and use of social media for users with TBI, we introduce the Social Media Accessibility and Rehabilitation Toolkit (\textbf{SMART-TBI}). The toolkit includes five aids (Writing Aid, Interpretation Aid, Filter Mode, Focus Mode, and Facebook Customization) designed to address the cognitive and communicative needs of individuals with TBI. We asked eight users with moderate-severe TBI and five TBI rehabilitation experts to evaluate each aid. Our findings revealed potential benefits of aids and areas for improvement, including the need for psychological safety, privacy control, and balancing business and accessibility needs; and overall mixed reactions among the participants to AI-based aids., Comment: In Proceedings The 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS'24)

We report the first observation of the nearby giant radio galaxy NGC 315 using a global VLBI array consisting of 22 radio antennas located across five continents, including high-sensitivity stations, at 22 GHz. Utilizing the extensive $(u,v)$-coverage provided by the array, coupled with the application of a recently developed super-resolution imaging technique based on the regularized maximum likelihood method, we were able to transversely resolve the NGC 315 jet at parsec scales for the first time. Previously known for its central ridge-brightened morphology at similar scales in former VLBI studies, the jet now clearly exhibits a limb-brightened structure. This finding suggests an inherent limb-brightening that was not observable before due to limited angular resolution. Considering that the jet is viewed at an angle of $\sim50^\circ$, the observed limb-brightening is challenging to reconcile with the magnetohydrodynamic models and simulations, which predict that the Doppler-boosted jet edges should dominate over the non-boosted central layer. The conventional jet model that proposes a fast spine and a slow sheath with uniform transverse emissivity may pertain to our observations. However, in this model, the relativistic spine would need to travel at speeds of $\Gamma\gtrsim6.0-12.9$ along the de-projected jet distance of (2.3-10.8) $\times 10^3$ gravitational radii from the black hole. We propose an alternative scenario that suggests higher emissivity at the jet boundary layer, resulting from more efficient particle acceleration or mass loading onto the jet edges, and consider prospects for future observations with even higher angular resolution., Comment: 25 pages, 12 figures, 1 table, accepted for publication in the Astrophysical Journal Letters

It is shown that the space of finite-to-finite holomorphic correspondences on an OT-manifold is discrete. When the OT-manifold has no proper infinite complex-analytic subsets, it then follows by known model-theoretic results that its cartesian powers have no interesting complex-analytic families of subvarieties. The methods of proof, which are similar to [Moosa, Moraru, and Toma ``An essentially saturated surface not of K\"ahler-type", {\em Bull. of the LMS}, 40(5):845--854, 2008], require studying finite unramified covers of OT-manifolds., Comment: The paper is published

The electrocardiogram (ECG) is a ubiquitous diagnostic test. Conventional task-specific ECG analysis models require large numbers of expensive ECG annotations or associated labels to train. Transfer learning techniques have been shown to improve generalization and reduce reliance on labeled data. We present ECG-FM, an open foundation model for ECG analysis, and conduct a comprehensive study performed on a dataset of 1.66 million ECGs sourced from both publicly available and private institutional sources. ECG-FM adopts a transformer-based architecture and is pretrained on 2.5 million samples using ECG-specific augmentations and contrastive learning, as well as a continuous signal masking objective. Our transparent evaluation includes a diverse range of downstream tasks, where we predict ECG interpretation labels, reduced left ventricular ejection fraction, and abnormal cardiac troponin. Affirming ECG-FM's effectiveness as a foundation model, we demonstrate how its command of contextual information results in strong performance, rich pretrained embeddings, and reliable interpretability. Due to a lack of open-weight practices, we highlight how ECG analysis is lagging behind other medical machine learning subfields in terms of foundation model adoption. Our code is available at https://github.com/bowang-lab/ECG-FM/., Comment: 22 pages, 7 figures, 10 tables

We present a study of the scattering of a monochromatic helical laser beam, described by a Laguerre-Gauss solution of the Maxwell equations, on an electron sheet, initially at rest in the focal plane of the laser; the interaction is described in the framework of a local plane wave approximation. We calculate the scattered electromagnetic field observed in an arbitrary point at a large distance from the laser focal spot, by adding coherently the contributions of each electron in the electron sheet. Due to the interference effects, the radiation is emitted only into the forward direction, within a narrow cone, and it has a spatial structure that we analyze theoretically and numerically. For circularly polarized incident fields, the structure is also helical, with a helical index which depends on the helical index of the incident radiation and the harmonic order. These structures can be observed experimentally, as each harmonic order is emitted with a different frequency, and within cones of different opening angles. Our findings are in agreement with experimental results in the literature which demonstrate the generation of OAM carrying photons by radiation scattering on electrons.

While the traditional formulation of machine learning tasks is in terms of performance on average, in practice we are often interested in how well a trained model performs on rare or difficult data points at test time. To achieve more robust and balanced generalization, methods applying sharpness-aware minimization to a subset of worst-case examples have proven successful for image classification tasks, but only using deep neural networks in a scenario where the most difficult points are also the least common. In this work, we show how such a strategy can dramatically break down under more diverse models, and as a more robust alternative, instead of typical sharpness we propose and evaluate a training criterion which penalizes poor loss concentration, which can be easily combined with loss transformations such as CVaR or DRO that control tail emphasis.

The afterglows of gamma-ray bursts are non-thermal electron synchrotron emissions from relativistic shocks. The origin of strong magnetic field in the emission region remains elusive, and two field amplification mechanisms via the plasma kinetic and magnetohydrodynamic instabilities have been discussed. The polarimetric observations are a powerful probe to distinguish these two mechanisms. So far, most theoretical works have focused on the former mechanism and constructed afterglow polarization models with microscopic-scale turbulence whose coherence length is much smaller than the thickness of the blast wave. In this work, focusing on the latter mechanism, we utilize our semi-analytic model of the synchrotron polarization with large-scale turbulence whose coherence length is comparable to the thickness of the blast wave to investigate the effect of magnetic field anisotropy and the observer viewing angle. We find that the polarization in our large-scale turbulence model can exhibit both behaviors characteristic of the microscopic-scale turbulence model and those not seen in the microscopic-scale model. Then we find that the large-scale model could explain all the polarimetric observational data to date that seem to be forward shock emission. We also examine the effect of ordered-field component, and find that polarization degree and polarization angle constant in time are realized only when the energy density ratio of the ordered and fluctuated components is $\gtrsim 50$. In this case, however, the polarization degree is much higher than the observed values., Comment: Submitted to ApJ, comments welcome

We survey old and new results on the existence of moduli spaces of semistable coherent sheaves both in algebraic and in complex geometry.

We study the moduli stacks of slope-semistable torsion-free coherent sheaves that admit reflexive, respectively locally free, Seshadri graduations on a smooth projective variety. We show that they are open in the stack of coherent sheaves and that they admit good moduli spaces when the field characteristic is zero. In addition, in the locally free case we prove that the resulting moduli space is a quasi-projective scheme., Comment: v2: Added remarks 3.1 and 3.2 on openness in the analytic case, small notational change

Automatic cell tracking in dense environments is plagued by inaccurate correspondences and misidentification of parent-offspring relationships. In this paper, we introduce a novel cell tracking algorithm named DenseTrack, which integrates deep learning with mathematical model-based strategies to effectively establish correspondences between consecutive frames and detect cell division events in crowded scenarios. We formulate the cell tracking problem as a deep learning-based temporal sequence classification task followed by solving a constrained one-to-one matching optimization problem exploiting the classifier's confidence scores. Additionally, we present an eigendecomposition-based cell division detection strategy that leverages knowledge of cellular geometry. The performance of the proposed approach has been evaluated by tracking densely packed cells in 3D time-lapse image sequences of bacterial biofilm development. The experimental results on simulated as well as experimental fluorescence image sequences suggest that the proposed tracking method achieves superior performance in terms of both qualitative and quantitative evaluation measures compared to recent state-of-the-art cell tracking approaches.

Mosaic crystals, with their high integrated reflectivities, are widely-employed in spectrometers used to diagnose high energy density systems. X-ray Thomson scattering (XRTS) has emerged as a powerful diagnostic tool of these systems, providing in principle direct access to important properties such as the temperature via detailed balance. However, the measured XRTS spectrum is broadened by the spectrometer instrument function (IF), and without careful consideration of the IF one risks misdiagnosing system conditions. Here, we consider in detail the IF of 40 $\mu$m and 100 $\mu$m mosaic HAPG crystals, and how the broadening varies across the spectrometer in an energy range of 6.7-8.6 keV. Notably, we find a strong asymmetry in the shape of the IF towards higher energies. As an example, we consider the effect of the asymmetry in the IF on the temperature inferred via XRTS for simulated 80 eV CH plasmas, and find that the temperature can be overestimated if an approximate symmetric IF is used. We therefore expect a detailed consideration of the full IF will have an important impact on system properties inferred via XRTS in both forward modelling and model-free approaches., Comment: 19 pages, 13 figures

Radio galaxies are a subclass of active galactic nuclei that drive relativistic jets from their center and are observed in radio to very-high-energy gamma rays. The emission mechanisms and regions are still unknown. High-energy gamma rays can be explained by the emission from the magnetically arrested disks (MADs) around the central supermassive black hole, for which the magnetic flux threading the black hole is in a saturation level, although the emission from the MADs does not explain the optical and X-ray data. We construct a multi-wavelength emission model in which the optical and X-ray emission is emitted by jets and the gamma rays by MADs. Our model takes into account the particle injection by the magnetic reconnection at the jet base close to the black hole and particle entrainment from the ambient gas at the jet emission zone. We apply our model to M87 and find that our model can explain the simultaneous multi-wavelength data. In our model, the emission from the jets is the synchrotron radiation of the nonthermal electrons accelerated by magnetic reconnection, and the emission from the MADs is the synchrotron radiation mainly of the nonthermal protons accelerated by turbulence. We also find that the strong plasma entrainment is necessary to explain the multi-wavelength data. Our model will be tested by variability analysis among the multi-wavelength data., Comment: 17 pages, 8 figures, 1 table

We consider the moment of quadratic twists of the M\"obius function of the form \[ S_k(X,Y) = \sum_{d\leq X} \left( \sum_{n\leq Y} \left(\frac{8d}{n}\right) \mu(n)\right)^k, \] where $\left(\frac{8d}{\cdot}\right)$ is the Kronecker symbol and $d$ runs over positive, odd and square-free integers. We give unconditional results for their asymptotic behaviors., Comment: 12 pages

In 2016, Cramer, Ducas, Peikert and, Regev proposed an efficient algorithm for recovering short generators of principal ideals in $q$-th cyclotomic fields with $q$ being a prime power. In this paper, we improve their analysis of the dual basis of the log-cyclotomic-unit lattice under the Generalised Riemann Hypothesis and in the case that $q$ is a prime number by the negative square moment of Dirichlet $L$-functions at $s=1$. As an implication, we obtain a better lower bound on the success probability for the algorithm in this special case. In order to prove our main result, we also give an analysis of the behaviour of negative $2k$-th moments of Dirichlet $L$-functions at $s=1$., Comment: 16 pages

The truncated Wigner approximation (TWA) enables us to calculate bosonic quantum many-body dynamics while accounting for the effects of quantum fluctuations. In this work, we formulate the TWA for bosonic Markovian open quantum systems described by the Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation from the coherent-state path-integral approach using the Wigner function. We derive an analytical expression for the GKSL equation in the TWA where we consider a bosonic system with an arbitrary Hamiltonian with jump operators that do not couple different states. We numerically confirm that the time evolution of physical quantities and the non-equal time correlation functions obtained in our formulation agree well with the exact ones in the numerically solvable models., Comment: 33 pages, 4 figures

Radiative seesaw models are examples of interesting and testable extensions of the Standard Model to explain the light neutrino masses. In radiative models at 1-loop level, such as the popular scotogenic model, in order to successfully reproduce neutrino masses and mixing, one has to rely either on unnaturally small Yukawa couplings or on a very small mass splitting between the CP-even and CP-odd components of the neutral scalar mediators. We discuss here scotogenic-like models where light-active neutrino masses arise at the three-loop level, providing a more natural explanation for their smallness. The proposed models are consistent with the neutrino oscillation data and allow to successfully accommodate the measured dark matter relic abundance. Depending on the specific realization, it is also possible to explain the W-mass anomaly and to generate the baryon asymmetry of the Universe via leptogenesis. The models lead to rich phenomenology, predicting sizable charged-lepton flavor violation rates, potentially observable in near future experiments, while satisfying all current constraints imposed by neutrinoless double-beta decay, charged-lepton flavor violation and electroweak precision observables., Comment: 6 pages, 5 figures. Contribution to the 2024 Electroweak session of the 58th Rencontres de Moriond

Two-dimensional materials, including transition metal dichalcogenides, are attractive for a variety of applications in electronics as well as photonics and have recently been envisioned as an appealing platform for phonon polaritonics. However, their direct characterization in the terahertz spectral region, of interest for retrieving, e.g., their phonon response, represents a major challenge, due to the limited sensitivity of typical terahertz spectroscopic tools and the weak interaction of such long-wavelength radiation with sub-nanometer systems. In this work, by exploiting an ad-hoc engineered metallic surface enabling a ten-thousand-fold local absorption boost, we perform enhanced terahertz spectroscopy of a monolayer transition metal dichalcogenide (tungsten diselenide) and extract its dipole-active phonon resonance features. In addition, we use these data to obtain the monolayer effective permittivity around its phonon resonance. Via the direct terahertz characterization of the phonon response of such two-dimensional systems, this method opens the path to the rational design of phonon polariton devices exploiting monolayer transition metal dichalcogenides.

In this work, we address the impact of a small lepton number violation on charged lepton electric dipole moments - EDMs. Low-scale seesaw models protected by lepton number symmetry and leading to pseudo-Dirac pairs in the neutrino heavy spectrum provide a natural explanation for the smallness of neutrino masses with potentially testable consequences. Among which, it was thought that the small mass gap in each pair of pseudo-Dirac neutrinos may induce important contribution to the charged lepton EDMs. Recently, it has been shown that the contribution from some of the Feynman diagrams to charged lepton EDMs exactly cancel by virtue of the Ward-Takahashi identity in quantum electrodynamics. We thus consider here the Standard Model minimally extended with pairs of pseudo-Dirac sterile fermions and derive the complete analytical formula at two loops for the charged lepton EDMs. In addition, we numerically evaluate the order of the predicted EDMs consistent with the experimental bounds and constraints such as neutrino oscillation data, charged lepton flavour violating processes, sterile neutrino direct searches, meson decays, sterile neutrino decays, and cosmological and astrophysical observations. We find that, in the minimal setup accommodating neutrino data (masses and mixings) with only two pseudo-Dirac pairs, the predicted electron EDM is $\mathcal{O}(10^{-36})~e\hspace{0.05cm}\mathrm{cm}$, at most, which is much smaller than the current experimental bound and even future sensitivity. Hopefully, the electron EDM might reach future sensitivity, once extra pseudo-Dirac neutrinos are taken into account. The analytical formulae we derive are generic to any model involving pseudo-Dirac pairs in the heavy neutrino spectrum., Comment: 18 pages, 7 figures

Medical errors in clinical text pose significant risks to patient safety. The MEDIQA-CORR 2024 shared task focuses on detecting and correcting these errors across three subtasks: identifying the presence of an error, extracting the erroneous sentence, and generating a corrected sentence. In this paper, we present our approach that achieved top performance in all three subtasks. For the MS dataset, which contains subtle errors, we developed a retrieval-based system leveraging external medical question-answering datasets. For the UW dataset, reflecting more realistic clinical notes, we created a pipeline of modules to detect, localize, and correct errors. Both approaches utilized the DSPy framework for optimizing prompts and few-shot examples in large language model (LLM) based programs. Our results demonstrate the effectiveness of LLM based programs for medical error correction. However, our approach has limitations in addressing the full diversity of potential errors in medical documentation. We discuss the implications of our work and highlight future research directions to advance the robustness and applicability of medical error detection and correction systems.

This paper outlines our submission to the MEDIQA2024 Multilingual and Multimodal Medical Answer Generation (M3G) shared task. We report results for two standalone solutions under the English category of the task, the first involving two consecutive API calls to the Claude 3 Opus API and the second involving training an image-disease label joint embedding in the style of CLIP for image classification. These two solutions scored 1st and 2nd place respectively on the competition leaderboard, substantially outperforming the next best solution. Additionally, we discuss insights gained from post-competition experiments. While the performance of these two solutions have significant room for improvement due to the difficulty of the shared task and the challenging nature of medical visual question answering in general, we identify the multi-stage LLM approach and the CLIP image classification approach as promising avenues for further investigation.

Monolayer hexagonal boron nitride (hBN) has recently become the focus of intense research as a material to host quantum emitters. Although it is well known that such emission is associated with point defects, so far no conclusive correlation between the spectra and specific defects has been demonstrated. Here, we prepare atomically clean suspended hBN samples and subject them to low-energy ion irradiation. The samples are characterized before and after irradiation via automated scanning transmission electron microscopy imaging to assess the defect concentrations and distributions. We find an intrinsic defect concentration of ca. 0.03/nm2 (with ca. 55% boron and 8% nitrogen single vacancies, 20% double vacancies and 16% more complex vacancy structures). To be able to differentiate between these and irradiation-induced defects, we create a significantly higher (but still moderate) concentration of defects with the ions (0.30/nm2), and now find ca. 55% boron and 12% nitrogen single vacancies, 14% double vacancies, and 18% more complex vacancy structures. The results demonstrate that already the simplest irradiation provides selectivity for the defect types, and open the way for future experiments to explore changing the selectivity by modifying the irradiation parameters., Comment: 7 pages, 4 figures

We prove uniform boundedness statements for semistable pure sheaves on projective manifolds. For example, we prove that the set of isomorphism classes of pure sheaves of dimension 2 that are slope semistable with respect to ample classes that vary in a compact set $K$ are bounded. We also prove uniform boundedness for pure sheaves of higher dimension, but with restrictions on the compact set $K$. As applications we get new statements about moduli spaces of semistable sheaves, and the wall-chamber structure that governs their variation., Comment: 24 pages, 1 figure

Many modern manufacturing companies have evolved from a single production site to a multi-factory production environment that must handle both geographically dispersed production orders and their multi-site production steps. The availability of a range of machines in different locations capable of performing the same operation and shipping times between factories have transformed planning systems from the classic Job Shop Scheduling Problem (JSSP) to Distributed Flexible Job Shop Scheduling Problem (DFJSP). As a result, the complexity of production planning has increased significantly. In our work, we use Quantum Annealing (QA) to solve the DFJSP. In addition to the assignment of production orders to production sites, the assignment of production steps to production sites also takes place. This requirement is based on a real use case of a wool textile manufacturer. To investigate the applicability of this method to large problem instances, problems ranging from 50 variables up to 250 variables, the largest problem that could be embedded into a D-Wave quantum annealer Quantum Processing Unit (QPU), are formulated and solved. Special attention is dedicated to the determination of the Lagrange parameters of the Quadratic Unconstrained Binary Optimization (QUBO) model and the QPU configuration parameters, as these factors can significantly impact solution quality. The obtained solutions are compared to solutions obtained by Simulated Annealing (SA), both in terms of solution quality and calculation time. The results demonstrate that QA has the potential to solve large problem instances specific to the industry., Comment: This work has been submitted to the IEEE for possible publication

We present SpaceHopper, a three-legged, small-scale robot designed for future mobile exploration of asteroids and moons. The robot weighs 5.2kg and has a body size of 245mm while using space-qualifiable components. Furthermore, SpaceHopper's design and controls make it well-adapted for investigating dynamic locomotion modes with extended flight-phases. Instead of gyroscopes or fly-wheels, the system uses its three legs to reorient the body during flight in preparation for landing. We control the leg motion for reorientation using Deep Reinforcement Learning policies. In a simulation of Ceres' gravity (0.029g), the robot can reliably jump to commanded positions up to 6m away. Our real-world experiments show that SpaceHopper can successfully reorient to a safe landing orientation within 9.7 degree inside a rotational gimbal and jump in a counterweight setup in Earth's gravity. Overall, we consider SpaceHopper an important step towards controlled jumping locomotion in low-gravity environments., Comment: To be published in the 2024 IEEE International Conference on Robotics and Automation

Long gamma ray bursts (GRBs) are produced by the collapse of some very massive stars, which emit ultra-relativistic jets. When the jets collide with the interstellar medium they decelerate and generate the so-called afterglow emission, which has been observed to be polarised. In this work we study the polarimetric evolution of GRB 210610B afterglow, at $z = 1.1341$. This allows to evaluate the role of geometric and/or magnetic mechanisms in the GRB afterglow polarisation. We observed GRB 210610B using imaging polarimetry with CAFOS on the 2.2 m Calar Alto Telescope and FORS2 on the 4 $\times$ 8.1 m Very Large Telescope. Complementary optical spectroscopy was obtained with OSIRIS on the 10.4 m Gran Telescopio Canarias. We study the GRB light-curve from X-rays to optical bands and the Spectral Energy Distribution (SED). This allows us to strongly constrain the line-of-sight extinction. Finally, we study the GRB host galaxy using optical/NIR data to fit the SED and derive its integrated properties. GRB 210610B had a bright afterglow with a negligible line-of-sight extinction. Polarimetry was obtained at three epochs: during an early plateau phase, at the time when the light curve breaks, and after the light curve steepened. We observe an initial polarisation of $\sim 4\%$ that goes to zero at the time of the break, and then increases again to $\sim 2\%$ with a change of the position angle of $54 \pm 9$ deg. The spectrum show features with very low equivalent widths, indicating a small amount of material in the line-of-sight within the host. The lack of dust and the low amount of material on the line-of-sight to GRB 210610B allow us to study the intrinsic polarisation of the GRB optical afterglow. We find the GRB polarisation signals are consistent with ordered magnetic fields in refreshed shock or/and hydrodynamics-scale turbulent fields in the forward shock., Comment: 17 pages, 7 figures, 5 tables. Accepted for publication in Astronomy and Astrophysics 23 Feb 2024

Large-scale vision language models (LVLMs) are language models that are capable of processing images and text inputs by a single model. This paper explores the use of LVLMs to generate review texts for images. The ability of LVLMs to review images is not fully understood, highlighting the need for a methodical evaluation of their review abilities. Unlike image captions, review texts can be written from various perspectives such as image composition and exposure. This diversity of review perspectives makes it difficult to uniquely determine a single correct review for an image. To address this challenge, we introduce an evaluation method based on rank correlation analysis, in which review texts are ranked by humans and LVLMs, then, measures the correlation between these rankings. We further validate this approach by creating a benchmark dataset aimed at assessing the image review ability of recent LVLMs. Our experiments with the dataset reveal that LVLMs, particularly those with proven superiority in other evaluative contexts, excel at distinguishing between high-quality and substandard image reviews., Comment: 9pages, under reviewing

We study a class of semistability conditions defined by a system of ample classes for coherent sheaves over a smooth projective variety. Under some necessary boundedness assumptions, we show the existence of a well-behaved chamber structure for the variation of moduli spaces of sheaves with respect to the change of semistability., Comment: 21 pages, v2: Mistake corrected in the proof of the HN property

Equation of state measurements at Jovian or stellar conditions are currently conducted by dynamic shock compression driven by multi-kilojoule multi-beam nanosecond-duration lasers. These experiments require precise design of the target and specific tailoring of the spatial and temporal laser profiles to reach the highest pressures. At the same time, the studies are limited by the low repetition rate of the lasers. Here, we show that by the irradiation of a thin wire with single beam Joule-class short-pulse laser, a converging cylindrical shock is generated compressing the wire material to conditions relevant for the above applications. The shockwave was observed using Phase Contrast Imaging employing a hard X-ray Free Electron Laser with unprecedented temporal and spatial sensitivity. The data collected for Cu wires is in agreement with hydrodynamic simulations of an ablative shock launched by a highly-impulsive and transient resistive heating of the wire surface. The subsequent cylindrical shockwave travels towards the wire axis and is predicted to reach a compression factor of 9 and pressures above 800 Mbar. Simulations for astrophysical relevant materials underline the potential of this compression technique as a new tool for high energy density studies at high repetition rates.

Let $N$ be a prime and $\phi$ be a Hecke-Maass cuspidal newform for the Hecke congruence subgroup $\Gamma_0(N)$ in $\operatorname{SL}_n(\mathbb{R})$. Let $\Omega$ be an adelic compactum and let $\Omega_N$ be its projection to $\Gamma_0(N) \backslash \operatorname{SL}_n(\mathbb{R}) / \operatorname{SO}(n)$. For any prime $n$, we prove sub-baseline bounds for the sup-norm of $\phi$ restricted to $\Omega_N$. Conditionally on GRH, we generalise this result to all $n \geq 2$. The methods involve a new reduction theory with level structure, based on generalisations of Atkin-Lehner operators., Comment: 46 pages

Radiation therapy is a primary and effective NasoPharyngeal Carcinoma (NPC) treatment strategy. The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis. Previously, the delineation of GTVs and OARs was performed by experienced radiation oncologists. Recently, deep learning has achieved promising results in many medical image segmentation tasks. However, for NPC OARs and GTVs segmentation, few public datasets are available for model development and evaluation. To alleviate this problem, the SegRap2023 challenge was organized in conjunction with MICCAI2023 and presented a large-scale benchmark for OAR and GTV segmentation with 400 Computed Tomography (CT) scans from 200 NPC patients, each with a pair of pre-aligned non-contrast and contrast-enhanced CT scans. The challenge's goal was to segment 45 OARs and 2 GTVs from the paired CT scans. In this paper, we detail the challenge and analyze the solutions of all participants. The average Dice similarity coefficient scores for all submissions ranged from 76.68\% to 86.70\%, and 70.42\% to 73.44\% for OARs and GTVs, respectively. We conclude that the segmentation of large-size OARs is well-addressed, and more efforts are needed for GTVs and small-size or thin-structure OARs. The benchmark will remain publicly available here: https://segrap2023.grand-challenge.org, Comment: A challenge report of SegRap2023 (organized in conjunction with MICCAI2023)

Recently, computers have diversified architectures. To achieve high numerical calculation software performance, it is necessary to tune the software according to the target computer architecture. However, code optimization for each environment is difficult unless it is performed by a specialist who knows computer architectures well. By applying autotuning (AT), the tuning effort can be reduced. Optimized implementation by AT that enhances computer performance can be used even by non-experts. In this research, we propose a technique for AT for programs using open multi-processing (OpenMP). We propose an AT method using an AT language that changes the OpenMP optimized loop and dynamically changes the number of threads in OpenMP according to computational kernels. Performance evaluation was performed using the Fujitsu PRIMEHPC FX100, which is a K-computer type supercomputer installed at the Information Technology Center, Nagoya University. As a result, we found there was a performance increase of 1.801 times that of the original code in a plasma turbulence analysis.

Double $L$-functions are the generalization of Dirichlet $L$-functions to two variable functions. We investigate the order estimation of double $L$-functions, and give upper bounds which are explicit in conductor aspect., Comment: 12 pages

OpenAI's large multimodal model, GPT-4V(ision), was recently developed for general image interpretation. However, less is known about its capabilities with medical image interpretation and diagnosis. Board-certified physicians and senior residents assessed GPT-4V's proficiency across a range of medical conditions using imaging modalities such as CT scans, MRIs, ECGs, and clinical photographs. Although GPT-4V is able to identify and explain medical images, its diagnostic accuracy and clinical decision-making abilities are poor, posing risks to patient safety. Despite the potential that large language models may have in enhancing medical education and delivery, the current limitations of GPT-4V in interpreting medical images reinforces the importance of appropriate caution when using it for clinical decision-making.

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE) providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe-Salpeter Equation (BSE), variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn-Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support of GPU acceleration has been achieved with minor modifications of the GPAW code thanks to the CuPy library. We end the review with an outlook describing some future plans for GPAW.

In the absence of a sufficient amount of plasma injection into the black hole (BH) magnetosphere, the force-free state of the magnetosphere cannot be maintained, leading to the emergence of strong, time-dependent, longitudinal electric field (spark gap). Recent studies of supermassive BH magnetospheres by using analytical methods and particle-in-cell (PIC) simulations propose the possibility of the efficient particle acceleration and consequent gamma-ray emissions in the spark gap. In this work, we perform one-dimensional general relativistic PIC simulations to examine the gamma-ray emission from stellar-mass BH magnetospheres. We find that intermittent spark gaps emerge and particles are efficiently accelerated, in a similar manner to the supermassive BH case. We build a semi-analytic model of the plasma dynamics and radiative processes which reproduces the maximum electron energies and peak gamma-ray luminosities in the simulation results. Based on this model, we show that gamma-ray signals from stellar-mass BHs wandering through the interstellar medium could be detected by gamma-ray telescopes such as the Fermi Large Area Telescope, or the Cherenkov Telescope Array., Comment: 17 pages, 9 figures, 1 table, accepted in ApJ

Mesoscale simulations of fission gas release (FGR) in nuclear fuel provide a powerful tool for understanding how microstructure evolution impacts FGR, but they are computationally intensive. In this study, we present an alternate, data-driven approach, using deep learning to predict instantaneous FGR flux from 2D nuclear fuel microstructure images. Four convolutional neural network (CNN) architectures with multiscale regression are trained and evaluated on simulated FGR data generated using a hybrid phase field/cluster dynamics model. All four networks show high predictive power, with $R^{2}$ values above 98%. The best performing network combine a Convolutional Block Attention Module (CBAM) and InceptionNet mechanisms to provide superior accuracy (mean absolute percentage error of 4.4%), training stability, and robustness on very low instantaneous FGR flux values., Comment: Submitted at Journal of Nuclear Materials, 20 pages, 10 figures, 3 tables

X-rays have been observed in natural downward cloud-to-ground lightning for over twenty years and in rocket-triggered lightning for slightly less. In both cases, this energetic radiation has been detected during the stepped and dart leader phases of downward negative flashes. More recently, X-rays have also been reported during the dart leader phase of upward negative flashes. In this study, we present the observations of four upward positive lightning flashes from the S\"antis Tower (2.5 km ASL) in Switzerland. These consist of the simultaneous records of electric current passing through the tower, and electric field strength and X-ray flux 20 meters from the tower base. One of the flashes was captured by a high-speed camera operating at 24,000 frames per second, stills from which are also presented. We detected X-rays during the initial phase of upward negative leader propagation, which can be associated with the leader-stepping process from electric field and current waveforms. To the best of our knowledge, this is the first time that such measurements are reported in the literature. The obtained time-synchronised data confirm that the X-ray emissions detected are associated with the initial steps of the upward negative leader. The frequency and energy of X-ray pulses appear to decrease as a function of time, with pulses disappearing altogether within the first millisecond of the leader initiation. The X-ray pulse energy appears to increase with the maximum current-derivative and the electric field change of its associated leader step. These observations contribute to improving the currently lackluster understanding of upward lightning, which is a primary source of damage to tall structures such as telecommunications towers and wind turbines, as well as airplanes during take-off and landing.