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Grain boundaries (GBs) trigger structure-specific chemical segregation of solute atoms. According to the three-dimensional (3D) topology of grains, GBs - although defined as planar defects - cannot be free of curvature. This implies formation of topologically-necessary arrays of secondary GB dislocations. We report here that these pattern-forming secondary GB dislocations can have an additional and, in some cases, even a much stronger effect on GB segregation than defect-free GBs. Using nanoscale correlative tomography combining crystallography and chemical analysis, we quantified the relationship between secondary GB dislocations and their segregation energy spectra for a model Fe-W alloy. This discovery unlocks new design opportunities for advanced materials, leveraging the additional degrees of freedom provided by topologically-necessary secondary GB dislocations to modulate segregation.

In this Letter, we investigate the turbulence and energy injection in the extended nebulae surrounding two luminous obscured quasars, WISEA J100211.29$+$013706.7 ($z=1.5933$) and SDSS J165202.64$+$172852.3 ($z=2.9489$). Utilizing high-resolution data from the NIRSpec IFU onboard the James Webb Space Telescope, we analyze the velocity fields of line-emitting gas in and around these quasars and construct the second-order velocity structure functions (VSFs) to quantify turbulent motions across different spatial scales. Our findings reveal a notable flattening in the VSFs from $\approx\!3$ kpc up to a scale of 10--20 kpc, suggesting that energy injection predominantly occurs at a scale $\lesssim$10 kpc, likely powered by quasar outflows and jet-driven bubbles. The extended spatial range of flat VSFs may also indicate the presence of multiple energy injection sources at these scales. For J1652, the turbulent energy in the host interstellar medium (ISM) is significantly higher than in tidally stripped gas, consistent with the expectation of active galactic nucleus (AGN) activities stirring up the host ISM. Compared to the VSFs observed on spatial scales of 10--50 kpc around lower-redshift UV-bright quasars, these obscured quasars exhibit higher turbulent energies in their immediate surroundings, implying different turbulence drivers between the ISM and halo-scale gas. Future studies with an expanded sample are essential to elucidate further the extent and the pivotal role of AGNs in shaping the gas kinematics of host galaxies and beyond., Comment: 10 pages, 4 figures; submitted; comments welcome!

Hydrogen-rich white dwarfs (WDs) comprise the majority of the WD population, but are only rarely found at the very hot end of the WD cooling sequence. A small subgroup that exhibits both hydrogen and helium lines in their spectra, the so-called hybrid (or DAO) WDs, represents the majority of hydrogen-rich WDs at effective temperatures $T_{eff}$ $\approx$ 100 kK. We aim to understand the spectral evolution of hot hybrid WDs. Although small in number, they represent an evolutionary phase for most ($\approx$ 75 %) WDs. We conducted a nonlocal thermodynamic equilibrium (NLTE) analysis with fully metal line blanketed model atmospheres for the ultraviolet (UV) and optical spectra of a sample of 19 DA and 13 DAO WDs with $T_{eff}$ $>$ 60 kK. The UV spectra allow us to precisely measure the temperature through model fits to metal lines in different ionization stages. This enables us to place the WDs accurately on the cooling sequence. In contrast to earlier studies that typically relied on temperature measurements made from hydrogen lines alone, all DAOs in our sample are clearly hotter than the DAs. DAOs transform into DAs when they cool to $T_{eff}$ $\approx$ 75$-$85 kK, depending on their mass. Along the cooling sequence, we witness a gradual decrease in the abundance of helium and the CNO elements in the DAOs due to gravitational settling. Simultaneously, iron and nickel abundances increase up to the transition region because radiative forces act more efficiently on them. This is followed by a steady decline. We discuss the implications of our results on atomic diffusion theory and on the role of weak radiation-driven winds in hot hydrogen-rich WDs., Comment: Accepted for publication in A&A

The Helix is a visually striking and the nearest planetary nebula, yet any companions responsible for its asymmetric morphology have yet to be identified. In 2020, low-amplitude photometric variations with a periodicity of 2.8 d were reported based on Cycle 1 TESS observations. In this work, with the inclusion of two additional sectors, these periodic light curves are compared with lcurve simulations of irradiated companions in such an orbit. Based on the light curve modelling, there are two representative solutions: i) a Jupiter-sized body with 0.102 Rsol and an arbitrarily small orbital inclination i=1 deg, and ii) a 0.021 Rsol exoplanet with i approx. 25 deg, essentially aligned with the Helix Nebular inclination. Irradiated substellar companion models with equilibrium temperature 4970 K are constructed and compared with existing optical spectra and infrared photometry, where Jupiter-sized bodies can be ruled out, but companions modestly larger than Neptune are still allowed. Additionally, any spatially-unresolved companions are constrained based on the multi-wavelength, photometric spectral energy distribution of the central star. No ultracool dwarf companion earlier than around L5 is permitted within roughly 1200 au, leaving only faint white dwarfs and cold brown dwarfs as possible surviving architects of the nebular asymmetries. While a planetary survivor is a tantalizing possibility, it cannot be ruled out that the light curve modulation is stellar in nature, where any substellar companion requires confirmation and may be possible with JWST observations., Comment: 9 pages, 7 figures, 1 table, accepted to MNRAS

We propose the conjecture that every graph $G$ of order $n$ with less than $3n-6$ edges has a vertex cut that induces a forest. Maximal planar graphs do not have such vertex cuts and show that the density condition would be best possible. We verify the conjecture for planar graphs and show that every graph $G$ of order $n$ with less than $\frac{11}{5}n-\frac{18}{5}$ edges has a vertex cut that induces a forest.

Grain boundaries are dominant imperfections in nanocrystalline materials that form a complex 3-dimensional (3D) network. Solute segregation to grain boundaries is strongly coupled to the grain boundary character, which governs the stability and macroscopic properties of nanostructured materials. Here, we develop a 3-dimensional transmission electron microscopy and atom probe tomography correlation framework to retrieve the grain boundary character and composition at the highest spatial resolution and chemical sensitivity by correlating four-dimensional scanning precession electron diffraction tomography (4D-SPED) and atom probe tomography (APT) on the same sample. We obtain the 3D grain boundary habit plane network and explore the preferential segregation of Cu and Si in a nanocrystalline Ni-W alloy. The correlation of structural and compositional information reveals that Cu segregates predominantly along high angle grain boundaries and incoherent twin boundaries, whereas Si segregation to low angle and incommensurate grain boundaries is observed. The novel full 3D correlative approach employed in this work opens up new possibilities to explore the 3D crystallographic and compositional nature of nanomaterials. This lays the foundation for both probing the true 3D structure-chemistry at the sub-nanometer scale and, consequentially, tailoring the macroscopic properties of advanced nanomaterials.

Human annotators typically provide annotated data for training machine learning models, such as neural networks. Yet, human annotations are subject to noise, impairing generalization performances. Methodological research on approaches counteracting noisy annotations requires corresponding datasets for a meaningful empirical evaluation. Consequently, we introduce a novel benchmark dataset, dopanim, consisting of about 15,750 animal images of 15 classes with ground truth labels. For approximately 10,500 of these images, 20 humans provided over 52,000 annotations with an accuracy of circa 67%. Its key attributes include (1) the challenging task of classifying doppelganger animals, (2) human-estimated likelihoods as annotations, and (3) annotator metadata. We benchmark well-known multi-annotator learning approaches using seven variants of this dataset and outline further evaluation use cases such as learning beyond hard class labels and active learning. Our dataset and a comprehensive codebase are publicly available to emulate the data collection process and to reproduce all empirical results., Comment: Under review @ NeurIPS 2024 (Datasets and Benchmarks Track)

Determining the full five-parameter grain boundary characteristics from experiments is essential for understanding grain boundaries impact on material properties, improving related models, and designing advanced alloys. However, achieving this is generally challenging, in particular at nanoscale, due to their 3D nature. In our study, we successfully determined the grain boundary characteristics of an annealed nickel-tungsten alloy (NiW) nanocrystalline needle-shaped specimen (tip) containing twins using Scanning Precession Electron Diffraction (SPED) Tomography. The presence of annealing twins in this face-centered cubic (fcc) material gives rise to common reflections in the SPED diffraction patterns, which challenges the reconstruction of orientation-specific virtual dark field (VDF) images required for tomographic reconstruction of the 3D grain shapes. To address this, an automated post-processing step identifies and deselects these shared reflections prior to the reconstruction of the VDF images. Combined with appropriate intensity normalization and projection alignment procedures, this approach enables high-fidelity 3D reconstruction of the individual grains contained in the needle-shaped sample volume. To probe the accuracy of the resulting boundary characteristics, the twin boundary surface normal directions were extracted from the 3D voxelated grain boundary map using a 3D Hough transform. For the sub-set of coherent Sigma 3 boundaries, the expected {111} grain boundary plane normals were obtained with an angular error of less than 3{\textdegree} for boundary sizes down to 400 nm${}^2$. This work advances our ability to precisely characterize and understand the complex grain boundaries that govern material properties.

Hot subdwarfs (sdO/B) are the stripped helium cores of red giants formed by binary interactions. Close hot subdwarf binaries with massive white dwarf companions have been proposed as possible progenitors of thermonuclear supernovae type Ia (SN Ia). If the supernova is triggered by stable mass transfer from the helium star, the companion should survive the explosion and should be accelerated to high velocities. The hypervelocity star US 708 is regarded as the prototype for such an ejected companion. To find more of those objects we conducted an extensive spectroscopic survey. Candidates for such fast stars have been selected from the spectroscopic database of the Sloan Digital Sky Survey (SDSS) and several ground-based proper motion surveys. Follow-up spectroscopy has been obtained with several 4m- to 10m-class telescopes. Combining the results from quantitative spectroscopic analyses with space-based astrometry from \textit{Gaia} Early Data Release 3 (EDR3) we determined the atmospheric and kinematic parameters of 53 fast hot subdwarf stars. None of these stars is unbound to the Galaxy, although some have Galactic restframe velocities close to the Galactic escape velocity. 21 stars are apparently single objects, which crossed the Galactic disc within their lifetimes in the sdO/B stage and could be regarded as potential candidates for the SN Ia ejection scenario. However, the properties of the full sample are more consistent with a pure old Galactic halo population. We therefore conclude that the fast sdO/B stars we found are likely to be extreme halo stars., Comment: 22 pages, A&A accepted

Passive acoustic monitoring (PAM) in avian bioacoustics enables cost-effective and extensive data collection with minimal disruption to natural habitats. Despite advancements in computational avian bioacoustics, deep learning models continue to encounter challenges in adapting to diverse environments in practical PAM scenarios. This is primarily due to the scarcity of annotations, which requires labor-intensive efforts from human experts. Active learning (AL) reduces annotation cost and speed ups adaption to diverse scenarios by querying the most informative instances for labeling. This paper outlines a deep AL approach, introduces key challenges, and conducts a small-scale pilot study., Comment: accepted at IAL@ECML-PKDD24

For the precise spectral analysis of hot stars, advanced stellar-atmosphere models that consider deviations from the local thermodynamic equilibrium are mandatory. This requires accurate atomic data to calculate all transition rates and occupation numbers for atomic levels in the considered model atoms, not only for a few prominent lines exhibited in an observation. The critical evaluation of atomic data is a challenge because it requires precise laboratory measurements. Ultraviolet spectroscopy of hot stars with high resolving power provide such "laboratory" spectra. We compare observed, isolated lines of the iron group (here calcium to nickel) with our synthetic line profiles to judge the accuracy of the respective oscillator strengths. This will verify them or yield individual correction values to improve the spectral analysis, i.e., the determination of, e.g., effective temperature and abundances. To minimize the error propagation from uncertainties in effective temperature, surface gravity (g), and abundance determination, we start with a precise reanalysis of three hot subdwarf stars, namely EC 11481-2303, Feige 110, and PG 0909+276. Then, we measure the abundances of the iron-group elements individually. Based on identified, isolated lines of these elements, we compare observation and models to measure their deviation in strength (equivalent width). For EC 11481-2303 and Feige 110, we confirmed the previously determined effective temperatures and log g values within their error limits. For all three stars, we fine-tuned all metal abundances to achieve the best reproduction of the observation. For more than 450 isolated absorption lines of the iron group, we compared modeled and observed line strengths. We selected strong, reliable isolated absorption lines, which we recommend to use as reference lines for abundance determinations in related objects., Comment: 13 pages, 12 figures

This article introduces a new asynchronous Byzantine-tolerant asset transfer system (cryptocurrency) with three noteworthy properties: quasi-anonymity, lightness, and consensus-freedom. Quasi-anonymity means no information is leaked regarding the receivers and amounts of the asset transfers. Lightness means that the underlying cryptographic schemes are \textit{succinct}, and each process only stores data polylogarithmic in the number of its own transfers.Consensus-freedom means the system does not rely on a total order of asset transfers. The proposed algorithm is the first asset transfer system that simultaneously fulfills all these properties in the presence of asynchrony and Byzantine processes. To obtain them, the paper adopts a modular approach combining a new distributed object called agreement proofs and well-known techniques such as vector commitments, universal accumulators, and zero-knowledge proofs. The paper also presents a new non-trivial universal accumulator implementation that does not need knowledge of the underlying accumulated set to generate (non-)membership proofs, which could benefit other crypto-based applications.

VBFNLO is a flexible parton level Monte Carlo program for the simulation of vector boson fusion (VBF), QCD-induced single and double vector boson production plus two jets, and double and triple vector boson production (plus jet) in hadronic collisions at next-to-leading order (NLO) in the strong coupling constant, as well as Higgs boson plus two and three jet production via gluon fusion at the one-loop level. For the new version -- Version 3.0 -- several major enhancements have been included. An interface according to the Binoth Les Houches Accord (BLHA) has been added for all VBF and di/tri-boson processes including fully leptonic decays. For all dimension-8 operators affecting vector boson scattering (VBS) processes, a modified T-matrix unitarization procedure has been implemented. Several new production processes have been added, namely the VBS $Z\gamma jj$ and $\gamma \gamma jj$ processes at NLO, $\gamma \gamma jj $, $WWj$ and $ZZj$ production at NLO including the loop-induced gluon-fusion contributions and the gluon-fusion one-loop induced $\Phi jjj$ ($\Phi$ is a CP-even or CP-odd scalar boson) process at LO, retaining the full top-mass dependence. Finally, the code has been parallelized using OpenMPI., Comment: 16 pages, 3 figures; new code available at http://ific.uv.es/vbfnlo/. arXiv admin note: text overlap with arXiv:1107.4038

Deep learning models have significantly advanced acoustic bird monitoring by being able to recognize numerous bird species based on their vocalizations. However, traditional deep learning models are black boxes that provide no insight into their underlying computations, limiting their usefulness to ornithologists and machine learning engineers. Explainable models could facilitate debugging, knowledge discovery, trust, and interdisciplinary collaboration. This study introduces AudioProtoPNet, an adaptation of the Prototypical Part Network (ProtoPNet) for multi-label bird sound classification. It is an inherently interpretable model that uses a ConvNeXt backbone to extract embeddings, with the classification layer replaced by a prototype learning classifier trained on these embeddings. The classifier learns prototypical patterns of each bird species' vocalizations from spectrograms of training instances. During inference, audio recordings are classified by comparing them to the learned prototypes in the embedding space, providing explanations for the model's decisions and insights into the most informative embeddings of each bird species. The model was trained on the BirdSet training dataset, which consists of 9,734 bird species and over 6,800 hours of recordings. Its performance was evaluated on the seven test datasets of BirdSet, covering different geographical regions. AudioProtoPNet outperformed the state-of-the-art model Perch, achieving an average AUROC of 0.90 and a cmAP of 0.42, with relative improvements of 7.1% and 16.7% over Perch, respectively. These results demonstrate that even for the challenging task of multi-label bird sound classification, it is possible to develop powerful yet inherently interpretable deep learning models that provide valuable insights for ornithologists and machine learning engineers., Comment: Work in progress

Deep active learning (AL) seeks to minimize the annotation costs for training deep neural networks. BAIT, a recently proposed AL strategy based on the Fisher Information, has demonstrated impressive performance across various datasets. However, BAIT's high computational and memory requirements hinder its applicability on large-scale classification tasks, resulting in current research neglecting BAIT in their evaluation. This paper introduces two methods to enhance BAIT's computational efficiency and scalability. Notably, we significantly reduce its time complexity by approximating the Fisher Information. In particular, we adapt the original formulation by i) taking the expectation over the most probable classes, and ii) constructing a binary classification task, leading to an alternative likelihood for gradient computations. Consequently, this allows the efficient use of BAIT on large-scale datasets, including ImageNet. Our unified and comprehensive evaluation across a variety of datasets demonstrates that our approximations achieve strong performance with considerably reduced time complexity. Furthermore, we provide an extensive open-source toolbox that implements recent state-of-the-art AL strategies, available at https://github.com/dhuseljic/dal-toolbox., Comment: Accepted at ECML PKDD 2024

We report the discovery of large ionized, [O II] emitting circumgalactic nebulae around the majority of thirty UV luminous quasars at $z=0.4-1.4$ observed with deep, wide-field integral field spectroscopy (IFS) with the Multi-Unit Spectroscopy Explorer (MUSE) by the Cosmic Ultraviolet Baryon Survey (CUBS) and MUSE Quasar Blind Emitters Survey (MUSEQuBES). Among the 30 quasars, seven (23%) exhibit [O II] emitting nebulae with major axis sizes greater than 100 kpc, twenty greater than 50 kpc (67%), and 27 (90%) greater than 20 kpc. Such large, optically emitting nebulae indicate that cool, dense, and metal-enriched circumgalactic gas is common in the halos of luminous quasars at intermediate redshift. Several of the largest nebulae exhibit morphologies that suggest interaction-related origins. We detect no correlation between the sizes and cosmological dimming corrected surface brightnesses of the nebulae and quasar redshift, luminosity, black hole mass, or radio-loudness, but find a tentative correlation between the nebulae and rest-frame [O II] equivalent width in the quasar spectra. This potential trend suggests a relationship between ISM content and gas reservoirs on CGM scales. The [O II]-emitting nebulae around the $z\approx1$ quasars are smaller and less common than Ly$\alpha$ nebulae around $z\approx3$ quasars. These smaller sizes can be explained if the outer regions of the Ly$\alpha$ halos arise from scattering in more neutral gas, by evolution in the cool CGM content of quasar host halos, by lower-than-expected metallicities on $\gtrsim50$ kpc scales around $z\approx1$ quasars, or by changes in quasar episodic lifetimes between $z=3$ and $1$., Comment: 18 pages, 5 figures, 2 tables. Accepted for publication in the Astrophysical Journal

Highly integrated multichannel readout electronics is crucial in contemporary particle physics experiments. A novel silicon photomultiplier readout system based on the VMM3a ASIC was developed, for the first time exploiting this chip for calorimetric purposes. To extend the dynamic range the signal from each SiPM channel was processed by two electronics channels with different gain. A fully operational prototype system with 256 SiPM readout channels allowed the collection of data from a prototype of the ALICE Forward Hadron Calorimeter (FoCal-H). The design and the test beam results using high energy hadron beams are presented and discussed, confirming the applicability of VMM3a-based solutions for energy measurements in a high rate environment., Comment: 12 pages, 10 figures

This work reports the testing of a Forward Calorimeter (FoCal) prototype based on an n-type Si pad array detector at the CERN PS accelerator. The FoCal is a proposed upgrade in the ALICE detector operating within the pseudorapidity range of 3.2 < $\mathrm{\eta}$ < 5.8. It aims to measure direct photons, neutral hadrons, vector mesons, and jets for the study of gluon saturation effects in the unexplored region of low momentum fraction x ($\mathrm{\sim10^{-5} - 10^{-6}}$). The prototype is a $\mathrm{8\times9}$ n-type Si pad array detector with each pad occupying one cm$^2$ area, fabricated on a 6-in, 325~$\mathrm{\pm 10 \thinspace \mu}$m thick, and high-resistivity ($\sim$7 k$\Omega \thinspace$ cm) Si wafer which is readout using HGCROCv2 chip. The detector is tested using pion beams of energy 10~GeV and electron beams of energy 1-5~GeV. The measurements of the Minimum Ionizing Particle (MIP) response of pions and the shower profiles of electrons are reported., Comment: 14 pages, 13 figures

Deep learning (DL) has greatly advanced audio classification, yet the field is limited by the scarcity of large-scale benchmark datasets that have propelled progress in other domains. While AudioSet aims to bridge this gap as a universal-domain dataset, its restricted accessibility and lack of diverse real-world evaluation use cases challenge its role as the primary resource. Therefore, we introduce $\texttt{BirdSet}$, a large-scale benchmark dataset for audio classification focusing on avian bioacoustics. $\texttt{BirdSet}$ surpasses AudioSet with over 6,800 recording hours ($\uparrow\!17\%$) from nearly 10,000 classes ($\uparrow\!18\times$) for training and more than 400 hours ($\uparrow\!7\times$) across eight strongly labeled evaluation datasets. It serves as a versatile resource for use cases such as multi-label classification, covariate shift or self-supervised learning. We benchmark six well-known DL models in multi-label classification across three distinct training scenarios and outline further evaluation use cases in audio classification. We host our dataset on Hugging Face for easy accessibility and offer an extensive codebase to reproduce our results., Comment: Under review

In this study, the impact of turbulent diffusion on mixing of biochemical reaction models is explored by implementing and validating different models. An original codebase called CHAD (Coupled Hydrodynamics and Anaerobic Digestion) is extended to incorporate turbulent diffusion and validate it against results from OpenFOAM with 2D Rayleigh-Taylor Instability and lid-driven cavity simulations. The models are then tested for the applications with Anaerobic Digestion - a widely used wastewater treatment method. The findings demonstrate that the implemented models accurately capture turbulent diffusion when provided with an accurate flow field. Specifically, a minor effect of chemical turbulent diffusion on biochemical reactions within the anaerobic digestion tank is observed, while thermal turbulent diffusion significantly influences mixing. By successfully implementing turbulent diffusion models in CHAD, its capabilities for more accurate anaerobic digestion simulations are enhanced, aiding in optimizing the design and operation of anaerobic digestion reactors in real-world wastewater treatment applications.

Standard methods for modeling anaerobic digestion processes assume homogeneous conditions inside the tank and thus suffer from the negligence of hydrodynamics. In this work, we present the software toolbox Coupled Hydrodynamics and Anaerobic Digestion (CHAD), a novel parallelized solver that is capable of utilizing CFD results as the basis for Anaerobic digestion model No.1 (ADMno1) simulations. CHAD uses a particle-based Lagrangian CFD solver i.e., DualSPHysics (DSPH) as input and provides for a parallelized, C++ code implementation of the standard ADMno1. This paper demonstrates a conceptual and numerical verification of the toolbox and outlines the future pathway to enhance the approach., Comment: conference paper

XL-Calibur is a balloon-borne Compton polarimeter for X-rays in the $\sim$15-80 keV range. Using an X-ray mirror with a 12 m focal length for collecting photons onto a beryllium scattering rod surrounded by CZT detectors, a minimum-detectable polarization as low as $\sim$3% is expected during a 24-hour on-target observation of a 1 Crab source at 45$^{\circ}$ elevation. Systematic effects alter the reconstructed polarization as the mirror focal spot moves across the beryllium scatterer, due to pointing offsets, mechanical misalignment or deformation of the carbon-fiber truss supporting the mirror and the polarimeter. Unaddressed, this can give rise to a spurious polarization signal for an unpolarized flux, or a change in reconstructed polarization fraction and angle for a polarized flux. Using bench-marked Monte-Carlo simulations and an accurate mirror point-spread function characterized at synchrotron beam-lines, systematic effects are quantified, and mitigation strategies discussed. By recalculating the scattering site for a shifted beam, systematic errors can be reduced from several tens of percent to the few-percent level for any shift within the scattering element. The treatment of these systematic effects will be important for any polarimetric instrument where a focused X-ray beam is impinging on a scattering element surrounded by counting detectors., Comment: Submitted to Astroparticle Physics

We perform nonlocal thermodynamic equilibrium (NLTE) model atmosphere analyses of the three hottest hypervelocity stars (space velocities between $\approx$ 1500-2800 km s$^{-1}$) known to date, which were recently discovered spectroscopically and identified as runaways from Type Ia supernovae. The hottest of the three (J0546$+$0836, effective temperature $T_\mathrm{eff}$ = 95,000 $\pm$ 15,000 K, surface gravity log g = $5.5 \pm 0.5$) has an oxygen-dominated atmosphere with a significant amount of carbon (C = $0.10 \pm 0.05$, O = $0.90 \pm 0.05$, mass fractions). Its mixed absorption+emission line spectrum exhibits photospheric absorption lines from O V and O VI as well as O III and O IV emission lines that are formed in a radiation-driven wind with a mass-loss rate of the order of $10^{-8}$ $M_\odot$ yr$^{-1}$. Spectroscopically, J0546$+$0836 is a [WC]-PG1159 transition-type pre-white dwarf. The second object (J0927$-$6335) is a PG1159-type white dwarf with a pure absorption-line spectrum dominated by C III/C IV and O III/O IV. We find $T_\mathrm{eff}$ = 60,000 $\pm$ 5000 K, log g = $7.0 \pm 0.5$, and a carbon- and oxygen-dominated atmosphere with C = $0.47 \pm 0.25$, O = $0.48 \pm 0.25$, and possibly a minute amount of helium (He = $0.05 \pm 0.05$). Comparison with post-AGB evolutionary tracks suggests a mass of $M\approx0.5$ $M_\odot$ for both objects, if such tracks can safely be applied to these stars. We find the third object (J1332$-$3541) to be a relatively massive ($M=0.89 M_\odot$) hydrogen-rich (DAO) white dwarf with $T_\mathrm{eff}$ = 65,657 $\pm$ 2390 K, log g = $8.38 \pm 0.08$, and abundances H = $0.65 \pm 0.04$ and He = $0.35 \pm 0.04$. We discuss our results in the context of the "dynamically driven double-degenerate double-detonation" (D$^6$) scenario proposed for the origin of these stars., Comment: Accepted for publication in A&A

We present the performance of a full-length prototype of the ALICE Forward Calorimeter (FoCal). The detector is composed of a silicon-tungsten electromagnetic sampling calorimeter with longitudinal and transverse segmentation (FoCal-E) of about 20$X_0$ and a hadronic copper-scintillating-fiber calorimeter (FoCal-H) of about 5$\lambda_{\rm int}$. The data were taken between 2021 and 2023 at the CERN PS and SPS beam lines with hadron (electron) beams up to energies of 350 (300) GeV. Regarding FoCal-E, we report a comprehensive analysis of its response to minimum ionizing particles across all pad layers. The longitudinal shower profile of electromagnetic showers is measured with a layer-wise segmentation of 1$X_0$. As a projection to the performance of the final detector in electromagnetic showers, we demonstrate linearity in the full energy range, and show that the energy resolution fulfills the requirements for the physics needs. Additionally, the performance to separate two-showers events was studied by quantifying the transverse shower width. Regarding FoCal-H, we report a detailed analysis of the response to hadron beams between 60 and 350 GeV. The results are compared to simulations obtained with a Geant4 model of the test beam setup, which in particular for FoCal-E are in good agreement with the data. The energy resolution of FoCal-E was found to be lower than 3% at energies larger than 100 GeV. The response of FoCal-H to hadron beams was found to be linear, albeit with a significant intercept that is about factor 2 larger than in simulations. Its resolution, which is non-Gaussian and generally larger than in simulations, was quantified using the FWHM, and decreases from about 16% at 100 GeV to about 11% at 350 GeV. The discrepancy to simulations, which is particularly evident at low hadron energies, needs to be further investigated., Comment: 57 pages (without acronyms), 45 captioned figures

The stability of Reissner-N\"ordstrom black holes with an extremal mass-charge relation was determined by calculating the propagation speed of gravitational waves on this background in an effective field theory (EFT) of gravity. New results for metric components are shown, along with the corresponding new extremal relation, part of which differs by a global factor of 2 from the past published work. This new relation further develops the existing constraints on EFT parameters. The radial propagation speed for gravitational waves in the Regge-Wheeler gauge was calculated linearly for all perturbations, yielding exact luminality for all dimension-4 operators. The dimension-6 radial speed modifications introduce no constraints on the sign of the modified theory parameters from causality arguments, while the deviation from classical theories vanishes at both horizons. The angular speed was found to be altered for the dimension-4 operators, with possible new constraints on the modified theory being suggested from causality arguments. Results are consistent existing literature on Schwarzschild black hole backgrounds, with some EFT terms becoming active only in non-vacuum spacetimes such as Reissner-N\"ordstrom black holes., Comment: 22 pages, 1 figure

Detailed measurements of the spectral structure of cosmic-ray electrons and positrons from 10.6 GeV to 7.5 TeV are presented from over 7 years of observations with the CALorimetric Electron Telescope (CALET) on the International Space Station. Because of the excellent energy resolution (a few percent above 10 GeV) and the outstanding e/p separation (10$^5$), CALET provides optimal performance for a detailed search of structures in the energy spectrum. The analysis uses data up to the end of 2022, and the statistics of observed electron candidates has increased more than 3 times since the last publication in 2018. By adopting an updated boosted decision tree analysis, a sufficient proton rejection power up to 7.5 TeV is achieved, with a residual proton contamination less than 10%. The observed energy spectrum becomes gradually harder in the lower energy region from around 30 GeV, consistently with AMS-02, but from 300 to 600 GeV it is considerably softer than the spectra measured by DAMPE and Fermi-LAT. At high energies, the spectrum presents a sharp break around 1 TeV, with a spectral index change from -3.15 to -3.91, and a broken power law fitting the data in the energy range from 30 GeV to 4.8 TeV better than a single power law with 6.9 sigma significance, which is compatible with the DAMPE results. The break is consistent with the expected effects of radiation loss during the propagation from distant sources (except the highest energy bin). We have fitted the spectrum with a model consistent with the positron flux measured by AMS-02 below 1 TeV and interpreted the electron + positron spectrum with possible contributions from pulsars and nearby sources. Above 4.8 TeV, a possible contribution from known nearby supernova remnants, including Vela, is addressed by an event-by-event analysis providing a higher proton-rejection power than a purely statistical analysis., Comment: main text: 7 pages, 4 figures; supplemental material: 10 pages, 8 figures, 1 table

In this paper, we describe the capabilities and constraints of Large Language Models (LLMs) within disparate academic disciplines, aiming to delineate their strengths and limitations with precision. We examine how LLMs augment scientific inquiry, offering concrete examples such as accelerating literature review by summarizing vast numbers of publications, enhancing code development through automated syntax correction, and refining the scientific writing process. Simultaneously, we articulate the challenges LLMs face, including their reliance on extensive and sometimes biased datasets, and the potential ethical dilemmas stemming from their use. Our critical discussion extends to the varying impacts of LLMs across fields, from the natural sciences, where they help model complex biological sequences, to the social sciences, where they can parse large-scale qualitative data. We conclude by offering a nuanced perspective on how LLMs can be both a boon and a boundary to scientific progress.