Search

Many active galaxies harbor powerful relativistic jets, however, the detailed mechanisms of their formation and acceleration remain poorly understood. To investigate the area of jet acceleration and collimation with the highest available angular resolution, we study the innermost region of the bipolar jet in the nearby low-ionization nuclear emission-line region (LINER) galaxy NGC 1052. We combined observations of NGC 1052 taken with VLBA, GMVA, and EHT over one week in the spring of 2017. For the first time, NGC 1052 was detected with the EHT, providing a size of the central region in-between both jet bases of 250 RS (Schwarzschild radii) perpendicular to the jet axes. This size estimate supports previous studies of the jets expansion profile which suggest two breaks of the profile at around 300 RS and 10000 RS distances to the core. Furthermore, we estimated the magnetic field to be 1.25 Gauss at a distance of 22 {\mu}as from the central engine by fitting a synchrotron-self absorption spectrum to the innermost emission feature, which shows a spectral turn-over at about 130 GHz. Assuming a purely poloidal magnetic field, this implies an upper limit on the magnetic field strength at the event horizon of 26000 Gauss, which is consistent with previous measurements. The complex, low-brightness, double-sided jet structure in NGC 1052 makes it a challenge to detect the source at millimeter (mm) wavelengths. However, our first EHT observations have demonstrated that detection is possible up to at least 230 GHz. This study offers a glimpse through the dense surrounding torus and into the innermost central region, where the jets are formed. This has enabled us to finally resolve this region and provide improved constraints on its expansion and magnetic field strength., Comment: 22 pages, 10 figures, published in A&A

The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-K\"onigl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.

AGN-launched jets are a crucial element in the study of supermassive black holes (SMBH) and their closest surroundings. The formation of such jets, whether they are launched by magnetic field lines anchored to the accretion disc or directly connected to the black hole's (BH) ergosphere, is the subject of ongoing, extensive research. 3C84, the compact radio source in the central galaxy NGC1275 of the Perseus super-cluster, is a prime laboratory for testing such jet launching scenarios, as well as studying the innermost, sub-parsec AGN structure and jet origin. Very long baseline interferometry (VLBI) offers a unique view into the physical processes in action, in the immediate vicinity of BHs, unparalleled by other observational techniques. With VLBI at short wavelengths particular high angular resolutions are obtained. Utilising such cm and mm-VLBI observations of 3C84 with the European VLBI Network and the Event Horizon Telescope, we study the magnetic field strength and associated accretion flow around its central SMBH. This is possible, as higher frequency VLBI measurements are capable of peering through the accretion flow surrounding the central engine of 3C84, which is known to block the line of sight to the sub-parsec counter-jet via free-free absorption. Furthermore, we study the magnetic field's signature in the core region, as manifested in polarised light. As part of this analysis we compare our observations to relativistic magneto-hydrodynamic simulations. Finally, we investigate the effect of instabilities on the shape of the jet's parsec-scale funnel and try to connect them to its historical evolution., Comment: 4 pages, 4 figures, Proceedings of the 16th European VLBI Network Symposium

Radio searches for single pulses provide the opportunity to discover one-off events, fast transients and some pulsars that might otherwise be missed by conventional periodicity searches. The MeerTRAP real-time search pipeline operates commensally to observations with the MeerKAT telescope. Here, we report on 26 new Galactic radio transients, mostly rotating radio transients (RRATs) and also the detection of one RRAT and two pulsars that were independently discovered by other surveys. The dispersion measures of two of the new sources marginally exceed the Galactic contribution depending on the electron density model used. Using a simple method of fitting a Gaussian function to individual pulses, and obtaining positions of arcsecond accuracy from image-based localisations using channelised voltage data from our transient buffer, we have derived timing solutions spanning multiple years for five sources. The timing parameters imply ages of several Myr and low surface magnetic field strengths which is characteristic of RRATs. We were able to measure spin periods for eight more transients, including one source which appears to rotate every 17.5 seconds. A majority of the sources have only been seen in one observation, sometimes despite multiple return visits to the field. Some sources exhibit complex emission features like component switching and periodic microstructure., Comment: 24 pages, 13 figures, 4 tables. Accepted for publication in Monthly Notices of the Royal Astronomical Society

Millisecond pulsars (MSPs) in binary systems are precise laboratories for tests of gravity and the physics of dense matter. Their orbits can show relativistic effects that provide a measurement of the neutron star mass and the pulsars are included in timing array experiments that search for gravitational waves. Neutron star mass measurements are key to eventually solving the neutron star equation of state and these can be obtained by a measure of the Shapiro delay if the orbit is viewed near edge-on. Here we report on the timing and noise analysis of five MSPs observed with the MeerKAT radio telescope: PSRs J0900$-$3144, J0921$-$5202, J1216$-$6410, J1327$-$0755 and J1543$-$5149. We searched for the Shapiro delay in all of the pulsars and obtain weak detections for PSRs J0900$-$3144, J1216$-$6410, and J1327$-$0755. We report a higher significance detection of the Shapiro delay for PSR J1543$-$5149, giving a precise pulsar mass of $M_{\rm p} = 1.349^{+0.043}_{-0.061}\,$M$_\odot$ and companion white-dwarf mass $M_{\rm c} = 0.223^{+0.005}_{-0.007}\,$M$_\odot$. This is an atypically low mass measurement for a recycled MSP. In addition to these Shapiro delays, we also obtain timing model parameters including proper motions and parallax constraints for most of the pulsars., Comment: 10 pages, 3 figures, 3 tables, accepted for publication in MNRAS

The kinetic Sunyaev-Zel'dovich effect (kSZ) and patchy screening effect are two complementary cosmic microwave background (CMB) probes of the reionization era. The kSZ effect is a relatively strong signal, but is difficult to disentangle from other sources of temperature anisotropy, whereas patchy screening is weaker but can be reconstructed using the cleaner polarization channel. Here, we explore the potential of using upcoming CMB surveys to correlate a reconstructed map of patchy screening with (the square of) the kSZ map, and what a detection of this cross-correlation would mean for reionization science. To do this, we use simulations and theory to quantify the contributions to this signal from different redshifts. We then use the expected survey properties for CMB-S4 and CMB-HD to make detection forecasts before exploring how the signal depends on reionization parameters. We forecast that CMB-S4 will obtain a hint of this signal at up to 1.8$\sigma$ and CMB-HD will detect it at up to 14$\sigma$. We find that this signal contains unique information about the timing and morphology of reionization, particularly sensitivity to the first half of reionization and to the bispectrum of the ionized gas distribution., Comment: 17 pages, 9 figures. To be submitted to ApJ. Comments welcome

We propose a holistic approach for deploying Small Language Models (SLMs) as function-calling agents within vehicles as edge devices, offering a more flexible and robust alternative to traditional rule-based systems. By leveraging SLMs, we simplify vehicle control mechanisms and enhance the user experience. Given the in-vehicle hardware constraints, we apply state-of-the-art model compression techniques, including structured pruning, healing, and quantization, ensuring that the model fits within the resource limitations while maintaining acceptable performance. Our work focuses on optimizing a representative SLM, Microsoft's Phi-3 mini, and outlines best practices for enabling embedded models, including compression, task-specific fine-tuning, and vehicle integration. We demonstrate that, despite significant reduction in model size which removes up to 2 billion parameters from the original model, our approach preserves the model's ability to handle complex in-vehicle tasks accurately and efficiently. Furthermore, by executing the model in a lightweight runtime environment, we achieve a generation speed of 11 tokens per second, making real-time, on-device inference feasible without hardware acceleration. Our results demonstrate the potential of SLMs to transform vehicle control systems, enabling more intuitive interactions between users and their vehicles for an enhanced driving experience.

Hamiltonian operator inference has been developed in [Sharma, H., Wang, Z., Kramer, B., Physica D: Nonlinear Phenomena, 431, p.133122, 2022] to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. The method constructs a low-dimensional model using only data and knowledge of the functional form of the Hamiltonian. The resulting ROMs preserve the intrinsic structure of the system, ensuring that the mechanical and physical properties of the system are maintained. In this work, we extend this approach to port-Hamiltonian systems, which generalize Hamiltonian systems by including energy dissipation, external input, and output. Based on snapshots of the system's state and output, together with the information about the functional form of the Hamiltonian, reduced operators are inferred through optimization and are then used to construct data-driven ROMs. To further alleviate the complexity of evaluating nonlinear terms in the ROMs, a hyper-reduction method via discrete empirical interpolation is applied. Accordingly, we derive error estimates for the ROM approximations of the state and output. Finally, we demonstrate the structure preservation, as well as the accuracy of the proposed port-Hamiltonian operator inference framework, through numerical experiments on a linear mass-spring-damper problem and a nonlinear Toda lattice problem., Comment: 27 pages, 13 figures

This Letter reports the precise measurement of reactor antineutrino spectrum and flux based on the full data set of 4.7 million inverse-beta-decay (IBD) candidates collected at Daya Bay near detectors. Expressed in terms of the IBD yield per fission, the antineutrino spectra from all reactor fissile isotopes and the specific $\mathrm{^{235}U}$ and $\mathrm{^{239}Pu}$ isotopes are measured with 1.3$\%$, 3$\%$ and 8$\%$ uncertainties respectively near the 3 MeV spectrum peak in reconstructed energy, reaching the best precision in the world. The total antineutrino flux and isotopic $\mathrm{^{235}U}$ and $\mathrm{^{239}Pu}$ fluxes are precisely measured to be $5.84\pm0.07$, $6.16\pm0.12$ and $4.16\pm0.21$ in units of $10^{-43} \mathrm{cm^2/fission}$. These measurements are compared with the Huber-Mueller (HM) model, the reevaluated conversion model based on the Kurchatov Institute (KI) measurement and the latest Summation Model (SM2023). The Daya Bay flux shows good consistency with KI and SM2023 models, but disagrees with HM model. The Daya Bay spectrum, however, disagrees with all model predictions.

This study evaluates the performance of TF-IDF weighting, averaged Word2Vec embeddings, and BERT embeddings for document similarity scoring across two contrasting textual domains. By analysing cosine similarity scores, the methods' strengths and limitations are highlighted. The findings underscore TF-IDF's reliance on lexical overlap and Word2Vec's superior semantic generalisation, particularly in cross-domain comparisons. BERT demonstrates lower performance in challenging domains, likely due to insufficient domainspecific fine-tuning., Comment: 9 pages, 4 figures

We present the first widefield extragalactic continuum catalogue with the MeerKAT S-band (2.5 GHz), of the radio-selected DEEP2 field. The combined image over the S1 (1.96 - 2.84 GHz) and S4 (2.62 - 3.50 GHz) sub-bands has an angular resolution of 6.8''$\times$3.6'' (4.0''$\times$2.4'') at a robust weighting of $R = 0.3$ ($R=-0.5$) and a sensitivity of 4.7 (7.5) $\mu$Jy beam$^{-1}$ with an on-source integration time of 70 minutes and a minimum of 52 of the 64 antennas, for respective observations. We present the differential source counts for this field, as well as a morphological comparison of resolved sources between S-band and archival MeerKAT L-band images. We find consistent source counts with the literature and provide spectral indices fitted over a combined frequency range of 1.8 GHz. These observations provide an important first demonstration of the capabilities of MeerKAT S-band imaging with relatively short integration times, as well as a comparison with existing S-band surveys, highlighting the rich scientific potential with future MeerKAT S-band surveys., Comment: 16 pages, 12 figures, 7 tables, Accepted for publication in MNRAS

We extend the theory of topological recursion by considering Airy structures whose partition functions are highest weight vectors of particular $\mathcal{W}$-algebra representations. Such highest weight vectors arise as partition functions of Airy structures only under certain conditions on the representations. In the spectral curve formulation of topological recursion, we show that this generalization amounts to adding specific terms to the correlators $ \omega_{g,1}$, which leads to a ``shifted topological recursion'' formula. We then prove that the wave-functions constructed from this shifted version of topological recursion are WKB solutions of families of quantizations of the spectral curve with $ \hbar$-dependent terms. In the reverse direction, starting from an $\hbar$-connection, we find that it is of topological type if the exact same conditions that we found for the Airy structures are satisfied. When this happens, the resulting shifted loop equations can be solved by the shifted topological recursion obtained earlier., Comment: 49 pages, 1 figure

Automated segmentation of medical images highly depends on the availability of accurate manual image annotations. Such annotations are very time-consuming and costly to generate, and often require specialized expertise, particularly for cross-sectional images which contain many slices for each patient. It is crucial to ensure the best use of annotation resources. In this paper, we systematically answer the question of how to select slices of cross-sectional medical images in order to maximize performance of the resulting deep learning segmentation models. We conducted experiments on 4 medical imaging segmentation tasks with varying annotation budgets, numbers of annotated cases, numbers of annotated slices per volume, slice selection techniques, and mask interpolations. We found that: 1) It is almost always preferable to annotate fewer slices per volume and more volumes given an annotation budget. 2) Selecting slices for annotation by unsupervised active learning (UAL) is not superior to selecting slices randomly or at fixed intervals, provided that each volume is allocated the same number of annotated slices. 3) Interpolating masks between annotated slices rarely enhances model performance, with exceptions of some specific configuration for 3D models.

We have conducted a GPU accelerated reprocessing of $\sim 87\%$ of the archival data from the High Time Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey by implementing a pulsar search pipeline that was previously used to reprocess the Parkes Multibeam pulsar survey (PMPS). We coherently searched the full 72-min observations of the survey with an acceleration search range up to $|50|\, \rm m\,s^{-2}$, which is most sensitive to binary pulsars experiencing nearly constant acceleration during 72 minutes of their orbital period. Here we report the discovery of 71 pulsars, including 6 millisecond pulsars (MSPs) of which five are in binary systems, and seven pulsars with very high dispersion measures (DM $>800 \, \rm pc \, cm^{-3}$). These pulsar discoveries largely arose by folding candidates to a much lower spectral signal-to-noise ratio than previous surveys, and exploiting the coherence of folding over the incoherent summing of the Fourier components to discover new pulsars as well as candidate classification techniques. We show that these pulsars could be fainter and on average more distant as compared to both the previously reported 100 HTRU-S LowLat pulsars and background pulsar population in the survey region. We have assessed the effectiveness of our search method and the overall pulsar yield of the survey. We show that through this reprocessing we have achieved the expected survey goals including the predicted number of pulsars in the survey region and discuss the major causes as to why these pulsars were missed in previous processings of the survey., Comment: 18 Pages, 12 figures, 9 tables. Accepted for publication in MNRAS

Astrometry of pulsars, particularly their distances, serves as a critical input for various astrophysical experiments using pulsars. Pulsar timing is a primary approach for determining a pulsar's position, parallax, and distance. In this paper, we explore the influence of the solar wind on astrometric measurements obtained through pulsar timing, focusing on its potential to affect the accuracy of these parameters. Using both theoretical calculation and mock-data simulations, we demonstrate a significant correlation between the pulsar position, annual parallax and the solar-wind density parameters. This correlation strongly depends on the pulsar's ecliptic latitude. We show that fixing solar-wind density to an arbitrary value in the timing analysis can introduce significant bias in the estimated pulsar position and parallax, and its significance is highly dependent on the ecliptic latitude of the pulsar and the timing precision of the data. For pulsars with favourable ecliptic latitude and timing precision, the astrometric and solar-wind parameters can be measured jointly with other timing parameters using single-frequency data. The parameter correlation can be mitigated by using multi-frequency data, which also significantly improves the measurement precision of these parameters; this is particularly important for pulsars at a medium or high ecliptic latitude. Additionally, for a selection of pulsars we reprocess their EPTA Data Release 2 data to include modelling of solar-wind effect in the timing analysis. This delivers significant measurements of both parallax and solar-wind density, the latter of which are consistent with those obtained at low-frequency band. In the future, combining pulsar timing data at gigahertz and lower frequencies will probably deliver the most robust and precise measurements of astrometry and solar wind properties in pulsar timing., Comment: 15 pages, 15 figures, 1 table, accepted for publication in MNRAS

We consider algorithmic problems motivated by modular robotic reconfiguration, for which we are given $n$ square-shaped modules (or robots) in a (labeled or unlabeled) start configuration and need to find a schedule of sliding moves to transform it into a desired goal configuration, maintaining connectivity of the configuration at all times. Recent work from Computational Geometry has aimed at minimizing the total number of moves, resulting in schedules that can perform reconfigurations in $\mathcal{O}(n^2)$ moves, or $\mathcal{O}(nP)$ for an arrangement of bounding box perimeter size $P$, but are fully sequential. Here we provide first results in the sliding square model that exploit parallel robot motion, resulting in an optimal speedup to achieve reconfiguration in worst-case optimal makespan of $\mathcal{O}(P)$. We also provide tight bounds on the complexity of the problem by showing that even deciding the possibility of reconfiguration within makespan $1$ is NP-complete in the unlabeled case; for the labeled case, deciding reconfiguration within makespan $2$ is NP-complete, while makespan $1$ can be decided in polynomial time., Comment: 38 pages, 35 figures

Spinal ligaments are crucial elements in the complex biomechanical simulation models as they transfer forces on the bony structure, guide and limit movements and stabilize the spine. The spinal ligaments encompass seven major groups being responsible for maintaining functional interrelationships among the other spinal components. Determination of the ligament origin and insertion points on the 3D vertebrae models is an essential step in building accurate and complex spine biomechanical models. In our paper, we propose a pipeline that is able to detect 66 spinal ligament attachment points by using a step-wise approach. Our method incorporates a fast vertebra registration that strategically extracts only 15 3D points to compute the transformation, and edge detection for a precise projection of the registered ligaments onto any given patient-specific vertebra model. Our method shows high accuracy, particularly in identifying landmarks on the anterior part of the vertebra with an average distance of 2.24 mm for anterior longitudinal ligament and 1.26 mm for posterior longitudinal ligament landmarks. The landmark detection requires approximately 3.0 seconds per vertebra, providing a substantial improvement over existing methods. Clinical relevance: using the proposed method, the required landmarks that represent origin and insertion points for forces in the biomechanical spine models can be localized automatically in an accurate and time-efficient manner.

Patient-specific 3D spine models serve as a foundation for spinal treatment and surgery planning as well as analysis of loading conditions in biomechanical and biomedical research. Despite advancements in imaging technologies, the reconstruction of complete 3D spine models often faces challenges due to limitations in imaging modalities such as planar X-Ray and missing certain spinal structures, such as the spinal or transverse processes, in volumetric medical images and resulting segmentations. In this study, we present a novel accurate and time-efficient method to reconstruct complete 3D lumbar spine models from incomplete 3D vertebral bodies obtained from segmented magnetic resonance images (MRI). In our method, we use an affine transformation to align artificial vertebra models with patient-specific incomplete vertebrae. The transformation matrix is derived from vertebra landmarks, which are automatically detected on the vertebra endplates. The results of our evaluation demonstrate the high accuracy of the performed registration, achieving an average point-to-model distance of 1.95 mm. Additionally, in assessing the morphological properties of the vertebrae and intervertebral characteristics, our method demonstrated a mean absolute error (MAE) of 3.4{\deg} in the angles of functional spine units (FSUs), emphasizing its effectiveness in maintaining important spinal features throughout the transformation process of individual vertebrae. Our method achieves the registration of the entire lumbar spine, spanning segments L1 to L5, in just 0.14 seconds, showcasing its time-efficiency. Clinical relevance: the fast and accurate reconstruction of spinal models from incomplete input data such as segmentations provides a foundation for many applications in spine diagnostics, treatment planning, and the development of spinal healthcare solutions.

Segment Anything Model (SAM) has shown impressive performance in interactive and zero-shot segmentation across diverse domains, suggesting that they have learned a general concept of "objects" from their large-scale training. However, we observed that SAM struggles with certain types of objects, particularly those featuring dense, tree-like structures and low textural contrast from their surroundings. These failure modes are critical for understanding its limitations in real-world use. In order to systematically examine this issue, we propose metrics to quantify two key object characteristics: tree-likeness and textural separability. Through extensive controlled synthetic experiments and testing on real datasets, we demonstrate that SAM's performance is noticeably correlated with these factors. We link these behaviors under the concept of "textural confusion", where SAM misinterprets local structure as global texture, leading to over-segmentation, or struggles to differentiate objects from similarly textured backgrounds. These findings offer the first quantitative framework to model SAM's challenges, providing valuable insights into its limitations and guiding future improvements for vision foundation models., Comment: Code: https://github.com/mazurowski-lab/SAM-TexturalConfusion-Metrics

Ultra-light axion-like particles (ALPs) can be a viable solution to the dark matter problem. The scalar field associated with ALPs, coupled to the electromagnetic field, acts as an active birefringent medium, altering the polarisation properties of light through which it propagates. In particular, oscillations of the axionic field induce monochromatic variations of the plane of linearly polarised radiation of astrophysical signals. The radio emission of millisecond pulsars provides an excellent tool to search for such manifestations, given their high fractional linear polarisation and negligible fluctuations of their polarisation properties. We have searched for the evidence of ALPs in the polarimetry measurements of pulsars collected and preprocessed for the European Pulsar Timing Array (EPTA) campaign. Focusing on the twelve brightest sources in linear polarisation, we searched for an astrophysical signal from axions using both frequentist and Bayesian statistical frameworks. For the frequentist analysis, which uses Lomb-Scargle periodograms at its core, no statistically significant signal has been found. The model used for the Bayesian analysis has been adjusted to accommodate multiple deterministic systematics that may be present in the data. A statistically significant signal has been found in the dataset of multiple pulsars with common frequency between $10^{-8}$ Hz and $2\times10^{-8}$ Hz, which can most likely be explained by the residual Faraday rotation in the terrestrial ionosphere. Strong bounds on the coupling constant $g_{a\gamma}$, in the same ballpark as other searches, have been obtained in the mass range between $6\times10^{-24}$ eV and $5\times10^{-21}$ eV. We conclude by discussing problems that can limit the sensitivity of our search for ultra-light axions in the polarimetry data of pulsars, and possible ways to resolve them., Comment: 24 pages, 15 figures

In an accompanying publication, the MeerKAT Pulsar Timing Array (MPTA) collaboration reports tentative evidence for the presence of a stochastic gravitational-wave background, following observations of similar signals from the European and Indian Pulsar Timing Arrays, NANOGrav, the Parkes Pulsar Timing Array and the Chinese Pulsar Timing Array. If such a gravitational-wave background signal originates from a population of inspiraling supermassive black-hole binaries, the signal may be anisotropically distributed on the sky. In this Letter we evaluate the anisotropy of the MPTA signal using a spherical harmonic decomposition. We discuss complications arising from the covariance between pulsar pairs and regularisation of the Fisher matrix. Applying our method to the 4.5 yr dataset, we obtain two forms of sky maps for the three most sensitive MPTA frequency bins between 7 -21 nHz. Our "clean maps'' estimate the distribution of gravitational-wave strain power with minimal assumptions. Our radiometer maps answer the question: is there a statistically significant point source? We find a noteworthy hotspot in the 7 nHz clean map with a $p$-factor of $p=0.015$ (not including trial factors). Future observations are required to determine if this hotspot is of astrophysical origin.

Pulsar Timing Arrays search for nanohertz-frequency gravitational waves by regularly observing ensembles of millisecond pulsars over many years to look for correlated timing residuals. Recently the first evidence for a stochastic gravitational wave background has been presented by the major Arrays, with varying levels of significance ($\sim$2-4$\sigma$). In this paper we present the results of background searches with the MeerKAT Pulsar Timing Array. Although of limited duration (4.5 yr), the $\sim$ 250,000 arrival times with a median error of just $3 \mu$s on 83 pulsars make it very sensitive to spatial correlations. Detection of a gravitational wave background requires careful modelling of noise processes to ensure that any correlations represent a fit to the underlying background and not other misspecified processes. Under different assumptions about noise processes we can produce either what appear to be compelling Hellings-Downs correlations of high significance (3-3.4$\sigma$) with a spectrum close to that which is predicted, or surprisingly, under slightly different assumptions, ones that are insignificant. This appears to be related to the fact that many of the highest precision MeerKAT Pulsar Timing Array pulsars are in close proximity and dominate the detection statistics. The sky-averaged characteristic strain amplitude of the correlated signal in our most significant model is $h_{c, {\rm yr}} = 7.5^{+0.8}_{-0.9} \times 10^{-15}$ measured at a spectral index of $\alpha=-0.26$, decreasing to $h_{c, {\rm yr}} = 4.8^{+0.8}_{-0.9} \times 10^{-15}$ when assessed at the predicted $\alpha=-2/3$. These data will be valuable as the International Pulsar Timing Array project explores the significance of gravitational wave detections and their dependence on the assumed noise models.

Pulsar timing arrays are ensembles of regularly observed millisecond pulsars timed to high precision. Each pulsar in an array could be affected by a suite of noise processes, most of which are astrophysically motivated. Analysing them carefully can be used to understand these physical processes. However, the primary purpose of these experiments is to detect signals that are common to all pulsars, in particular signals associated with a stochastic gravitational wave background. To detect this, it is paramount to appropriately characterise other signals that may otherwise impact array sensitivity or cause a spurious detection. Here we describe the second data release and first detailed noise analysis of the pulsars in the MeerKAT Pulsar Timing Array, comprising high-cadence and high-precision observations of $83$ millisecond pulsars over $4.5$ years. We use this analysis to search for a common signal in the data, finding a process with an amplitude of $\log_{10}\mathrm{A_{CURN}} = -14.25^{+0.21}_{-0.36}$ and spectral index $\gamma_\mathrm{CURN} = 3.60^{+1.31}_{-0.89}$. Fixing the spectral index at the value predicted for a background produced by the inspiral of binary supermassive black holes, we measure the amplitude to be $\log_{10}\mathrm{A_{CURN}} = -14.28^{+0.21}_{-0.21}$ at a significance expressed as a Bayes factor of $\ln(\mathcal{B}) = 4.46$. Under both assumptions, the amplitude that we recover is larger than those reported by other PTA experiments. We use the results of this analysis to forecast our sensitivity to a gravitational wave background possessing the spectral properties of the common signal we have measured.

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

This paper presents the results of a joint radio and gamma-ray timing campaign on the nine millisecond pulsars (MSPs) discovered as part of the L-band targeted survey of Fermi-LAT sources performed in the context of the Transients and Pulsars with MeerKAT (TRAPUM) Large Survey Project. Out of these pulsars, eight are members of binary systems; of these eight, two exhibit extended eclipses of the radio emission. Using an initial radio timing solution, pulsations were found in the gamma rays for six of the targets. For these sources, a joint timing analysis of radio times of arrival and gamma-ray photons was performed, using a newly developed code that optimises the parameters through a Markov chain Monte Carlo (MCMC) technique. This approach has allowed us to precisely measure both the short- and long-term timing parameters. This study includes a proper motion measurement for four pulsars, which a gamma ray-only analysis would not have been sensitive to, despite the 15-year span of Fermi data., Comment: 20 pages, 5 figures

Context: Timing of pulsar PSR J0337+1715 provides a unique opportunity to test the strong equivalence principle (SEP) with a strongly self-gravitating object. This is due to its unique situation in a triple stellar system with two white dwarfs. Aims: Our previous study suggested the presence of a strong low-frequency signal in the timing residuals. We set out to model it on a longer dataset in order to determine its nature and improve accuracy. Methods: Three models are considered: chromatic or achromatic red-noise, and a small planet in a hierarchical orbit with the triple stellar system. These models are implemented in our numerical timing model. We perform Bayesian inference of posterior distributions. Best fits are compared using information-theoretic criteria. Results: Chromatic red noise from dispersion-measure variations is ruled out. Achromatic red noise or a planet in keplerian orbit provide the best fits. If it is red noise then it appears exceptionally strong. Assuming the presence of a planet, we obtain a marginal detection of mutual interactions which allows us to constrain its mass to $\sim 0.5 M_{\rm Moon}$ as well as its inclination. The latter is intriguingly coincident with a Kozai resonance. We show that a longer observation span will ultimately lead to a clear signature of the planet model due to its mutual interactions with the triple system. We produce new limits on SEP violation: $|\Delta| < 1.5\cdot 10^{-6}$ or $|\Delta| < 2.3\cdot 10^{-6}$ at 95% confidence level under the planet or red-noise hypothesis, respectively. This model dependence emphasises the need for additional data and model selection. As a by-product, we estimate a rather low supernova kick velocity of $\sim 110-125 \rm km/s$, strengthening the idea that it is a necessary condition for the formation of pulsar triple systems.

We propose soft Hoeffding trees (SoHoT) as a new differentiable and transparent model for possibly infinite and changing data streams. Stream mining algorithms such as Hoeffding trees grow based on the incoming data stream, but they currently lack the adaptability of end-to-end deep learning systems. End-to-end learning can be desirable if a feature representation is learned by a neural network and used in a tree, or if the outputs of trees are further processed in a deep learning model or workflow. Different from Hoeffding trees, soft trees can be integrated into such systems due to their differentiability, but are neither transparent nor explainable. Our novel model combines the extensibility and transparency of Hoeffding trees with the differentiability of soft trees. We introduce a new gating function to regulate the balance between univariate and multivariate splits in the tree. Experiments are performed on 20 data streams, comparing SoHoT to standard Hoeffding trees, Hoeffding trees with limited complexity, and soft trees applying a sparse activation function for sample routing. The results show that soft Hoeffding trees outperform Hoeffding trees in estimating class probabilities and, at the same time, maintain transparency compared to soft trees, with relatively small losses in terms of AUROC and cross-entropy. We also demonstrate how to trade off transparency against performance using a hyperparameter, obtaining univariate splits at one end of the spectrum and multivariate splits at the other.

We propose a novel technique for optimizing a modular fault-tolerant quantum computing architecture, taking into account any desired space-time trade--offs between the number of physical qubits and the fault-tolerant execution time of a quantum algorithm. We consider a concept architecture comprising a dedicated zone as a multi-level magic state factory and a core processor for efficient logical operations, forming a supply chain network for production and consumption of magic states. Using a heuristic algorithm, we solve the multi-objective optimization problem of minimizing space and time subject to a user-defined error budget for the success of the computation, taking the performance of various fault-tolerant protocols such as quantum memory, state preparation, magic state distillation, code growth, and logical operations into account. As an application, we show that physical quantum resource estimation reduces to a simple model involving a small number of key parameters, namely, the circuit volume, the error prefactors ($\mu$) and error suppression rates ($\Lambda$) of the fault-tolerant protocols, and an allowed slowdown factor ($\beta$). We show that, in the proposed architecture, $10^5$--$10^8$ physical qubits are required for quantum algorithms with $T$-counts in the range $10^6$--$10^{15}$ and logical qubit counts in the range $10^2$--$10^4$, when run on quantum computers with quantum memory $\Lambda$ in the range 3--10, for all slowdown factors $\beta \geq 0.2$., Comment: 21 pages, 6 figures

We develop two novel couplings between general pure-jump L\'evy processes in $\R^d$ and apply them to obtain upper bounds on the rate of convergence in an appropriate Wasserstein distance on the path space for a wide class of L\'evy processes attracted to a multidimensional stable process in the small-time regime. We also establish general lower bounds based on certain universal properties of slowly varying functions and the relationship between the Wasserstein and Toscani--Fourier distances of the marginals. Our upper and lower bounds typically have matching rates. In particular, the rate of convergence is polynomial for the domain of normal attraction and slower than a slowly varying function for the domain of non-normal attraction., Comment: 42 pages, 2 figures, for a short YouTube video describing the results, see https://youtu.be/76eJD6a8Kko?si=5OkdWw4AiNp0P1po

Idiomatic expressions are an integral part of human languages, often used to express complex ideas in compressed or conventional ways (e.g. eager beaver as a keen and enthusiastic person). However, their interpretations may not be straightforwardly linked to the meanings of their individual components in isolation and this may have an impact for compositional approaches. In this paper, we investigate to what extent word representation models are able to go beyond compositional word combinations and capture multiword expression idiomaticity and some of the expected properties related to idiomatic meanings. We focus on noun compounds of varying levels of idiomaticity in two languages (English and Portuguese), presenting a dataset of minimal pairs containing human idiomaticity judgments for each noun compound at both type and token levels, their paraphrases and their occurrences in naturalistic and sense-neutral contexts, totalling 32,200 sentences. We propose this set of minimal pairs for evaluating how well a model captures idiomatic meanings, and define a set of fine-grained metrics of Affinity and Scaled Similarity, to determine how sensitive the models are to perturbations that may lead to changes in idiomaticity. The results obtained with a variety of representative and widely used models indicate that, despite superficial indications to the contrary in the form of high similarities, idiomaticity is not yet accurately represented in current models. Moreover, the performance of models with different levels of contextualisation suggests that their ability to capture context is not yet able to go beyond more superficial lexical clues provided by the words and to actually incorporate the relevant semantic clues needed for idiomaticity.

This work presents a design under uncertainty approach for a char combustion process in a limited-data setting, where simulations of the fluid-solid coupled system are computationally expensive. We integrate a polynomial dimensional decomposition (PDD) surrogate model into the design optimization and induce computational efficiency in three key areas. First, we transform the input random variables to have fixed probability measures, which eliminates the need to recalculate the PDD's basis functions associated with these probability quantities. Second, using the limited available data from a physics-based high-fidelity solver, we estimate the PDD coefficients via sparsity-promoting diffeomorphic modulation under observable response preserving homotopy regression. Third, we propose a single-pass surrogate model training process that avoids the need to generate new training data and update the PDD coefficients during the derivative-free optimization process. The results provide insights for optimizing process parameters to ensure consistently high energy production from char combustion., Comment: 19 pages, 6 figures

Externally driven dense packings of particles can exhibit nonlinear wave phenomena that are not described by effective medium theory or linearized approximate models. Such nontrivial wave responses can be exploited to design sound-focusing/scrambling devices, acoustic filters, and analog computational units. At high amplitude vibrations or low confinement pressures, the effect of nonlinear particle contacts becomes increasingly noticeable, and the interplay of nonlinearity, disorder, and discreteness in the system gives rise to remarkable properties, particularly useful in designing structures with exotic properties. In this paper, we build upon the data-driven methods in dynamical system analysis and show that the Koopman spectral theory can be applied to granular crystals, enabling their phase space analysis beyond the linearizable regime and without recourse to any approximations considered in the previous works. We show that a deep neural network can map the dynamics to a latent space where the essential nonlinearity of the granular system unfolds into a high-dimensional linear space. As a proof of concept, we use data from numerical simulations of a two-particle system and evaluate the accuracy of the trajectory predictions under various initial conditions. By incorporating data from experimental measurements, our proposed framework can directly capture the underlying dynamics without imposing any assumptions about the physics model. Spectral analysis of the trained surrogate system can help bridge the gap between the simulation results and the physical realization of granular crystals and facilitate the inverse design of materials with desired behaviors.

We present a scalable tensor-based approach to computing input-normal/output-diagonal nonlinear balancing transformations for control-affine systems with polynomial nonlinearities. This transformation is necessary to determine the states that can be truncated when forming a reduced-order model. Given a polynomial representation for the controllability and observability energy functions, we derive the explicit equations to compute a polynomial transformation to induce input-normal/output-diagonal structure in the energy functions in the transformed coordinates. The transformation is computed degree-by-degree, similar to previous Taylor-series approaches in the literature. However, unlike previous works, we provide a detailed analysis of the transformation equations in Kronecker product form to enable a scalable implementation. We derive the explicit algebraic structure for the equations, present rigorous analyses for the solvability and algorithmic complexity of those equations, and provide general purpose open-source software implementations for the proposed algorithms to stimulate broader use of nonlinear balanced truncation model. We demonstrate that with our efficient implementation, computing the nonlinear transformation is approximately as expensive as computing the energy functions., Comment: 11 pages, 6 figures

We consider the optimal regulation problem for nonlinear control-affine dynamical systems. Whereas the linear-quadratic regulator (LQR) considers optimal control of a linear system with quadratic cost function, we study polynomial systems with polynomial cost functions; we call this problem the polynomial-polynomial regulator (PPR). The resulting polynomial feedback laws provide two potential improvements over linear feedback laws: 1) they more accurately approximate the optimal control law, resulting in lower control costs, and 2) for some problems they can provide a larger region of stabilization. We derive explicit formulas -- and a scalable, general purpose software implementation -- for computing the polynomial approximation to the value function that solves the optimal control problem. The method is illustrated first on a low-dimensional aircraft stall stabilization example, for which PPR control recovers the aircraft from more severe stall conditions than LQR control. Then we demonstrate the scalability of the approach on a semidiscretization of dimension $n=129$ of a partial differential equation, for which the PPR control reduces the control cost by approximately 75% compared to LQR for the initial condition of interest., Comment: 8 pages, 4 figures; accepted to 63rd IEEE Conference on Decision and Control

The interstellar medium of the Milky Way contains turbulent plasma with structures driven by energetic processes that fuel star formation and shape the evolution of our Galaxy. Radio waves from pulsars are scattered off the small (au-scale and below) structures, resulting in frequency-dependent interference patterns that are modulated in time because of the relative motions of the pulsar, Earth, and plasma. Power spectral analyses of these patterns show parabolic arcs with curvatures that encode the locations and kinematics of individual structures. Here we report the discovery of at least 25 distinct plasma structures in the direction of the brilliant millisecond pulsar, PSR J0437$-$4715, in observations obtained with the MeerKAT radio telescope. Four arcs reveal structures within 5000 au of the pulsar, from a series of shocks induced as the pulsar and its wind interact with the ambient insterstellar medium. The measured radial distance and velocity of the main shock allows us to solve the shock geometry and space velocity of the pulsar in three dimensions, while the velocity of another structure unexpectedly indicates a back flow from the direction of the shock or pulsar-wind tail. The remaining 21 arcs represent a surprising abundance of structures sustained by turbulence within the Local Bubble -- a region of the interstellar medium thought to be depleted of gas by a series of supernova explosions about 14 Myr ago., Comment: 46 pages, 10 figures, 1 table, submitted to Nature Astronomy

GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs and outputs are processed by the same neural network. GPT-4o can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50\% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models. In line with our commitment to building AI safely and consistent with our voluntary commitments to the White House, we are sharing the GPT-4o System Card, which includes our Preparedness Framework evaluations. In this System Card, we provide a detailed look at GPT-4o's capabilities, limitations, and safety evaluations across multiple categories, focusing on speech-to-speech while also evaluating text and image capabilities, and measures we've implemented to ensure the model is safe and aligned. We also include third-party assessments on dangerous capabilities, as well as discussion of potential societal impacts of GPT-4o's text and vision capabilities.

Pulsar Timing Array (PTA) collaborations gather high-precision timing measurements of pulsars with the aim of detecting gravitational wave (GW) signals. A major challenge lies in the identification and characterization of the different sources of noise that may hamper their sensitivity to GWs. The presence of time-correlated noise that resembles the target signal might give rise to degeneracies that can directly impact the detection statistics. In this work, we focus on the covariance that exists between a "chromatic" dispersion measure (DM) noise and an "achromatic" stochastic gravitational wave background (GWB). "Chromatic" associated to the DM noise means that its amplitude depends on the frequency of the incoming pulsar photons measured by the radio-telescope. Several frequency channels are then required to accurately characterise its chromatic features and when the coverage of incoming frequency is poor, it becomes impossible to disentangle chromatic and achromatic noise contributions. In this paper, we explore this situation by injecting realistic GWB into 100 realizations of two mock versions of the second data release (DR2) of the European PTA (EPTA), characterized by different frequency coverage. The first dataset is a faithful copy of DR2, in which the first half of the data is dominated by only one frequency channel of observation; the second one is identical except for a more homogeneous frequency coverage across the full dataset. We show that for 91% of the injections, a better frequency coverage leads to an improved statistical significance (~1.3dex higher log Bayes factor on average) of the GWB and a better characterization of its properties. We propose a metric to quantify the degeneracy between DM and GWB parameters and show that it is correlated with a loss of significance for the recovered GWB and an increase in the GWB bias towards a higher and flatter spectral shape.

Van der Waals (vdW) homo-/hetero-structures are ideal systems for studying interfacial tribological properties such as structural superlubricity. Previous studies concentrated on the mechanism of translational motion in vdW interfaces. However, detailed mechanisms and general properties of the rotational motion are barely explored. Here, we combine experiments and simulations to reveal the twisting dynamics of the MoS$_2$/graphite heterostructure. Unlike the translational friction falling into the superlubricity regime with no twist angle dependence, the dynamic rotational resistances highly depend on twist angles. Our results show that the periodic rotational resistance force originates from structural potential energy changes during the twisting. The structural potential energy of MoS$_2$/graphite heterostructure increases monotonically from0 to 30 degrees twist angles, and the estimated relative energy barrier is (1.43 +/- 0.36) x 10 J/m. The formation of Moir\'e superstructures in the graphene layer is the key to controlling the structural potential energy of the MoS$_2$/graphene heterostructure. Our results suggest that in twisting 2D heterostructures, even if the interface sliding friction is negligible, the evolving potential energy change results in a non-vanishing rotational resistance force. The structural change of the heterostructure can be an additional pathway for energy dissipation in the rotational motion, further enhancing the rotational friction force., Comment: Published in ACS Appl. Mater. Interfaces 2023, 15, 15, 19616-19623

Tensegrity robots are composed of rigid struts and flexible cables. They constitute an emerging class of hybrid rigid-soft robotic systems and are promising systems for a wide array of applications, ranging from locomotion to assembly. They are difficult to control and model accurately, however, due to their compliance and high number of degrees of freedom. To address this issue, prior work has introduced a differentiable physics engine designed for tensegrity robots based on first principles. In contrast, this work proposes the use of graph neural networks to model contact dynamics over a graph representation of tensegrity robots, which leverages their natural graph-like cable connectivity between end caps of rigid rods. This learned simulator can accurately model 3-bar and 6-bar tensegrity robot dynamics in simulation-to-simulation experiments where MuJoCo is used as the ground truth. It can also achieve higher accuracy than the previous differentiable engine for a real 3-bar tensegrity robot, for which the robot state is only partially observable. When compared against direct applications of recent mesh-based graph neural network simulators, the proposed approach is computationally more efficient, both for training and inference, while achieving higher accuracy. Code and data are available at https://github.com/nchen9191/tensegrity_gnn_simulator_public

PSR J0737$-$3039A/B is unique among double neutron star systems. Its near-perfect edge-on orbit causes the fast spinning pulsar A to be eclipsed by the magnetic field of the slow spinning pulsar B. Using high-sensitivity MeerKAT radio observations combined with updated constraints on the system geometry, we studied the impact of these eclipses on the incident polarization properties of pulsar A. Averaging light curves together after correcting for the rotation of pulsar B revealed enormous amounts of circular polarization and rapid changes in the linear polarization position angle, which occur at phases where emission from pulsar A is partially transmitted through the magnetosphere of pulsar B. These behaviours confirm that the eclipse mechanism is the result of synchrotron absorption in a relativistic pair-plasma confined to the closed-field region of pulsar B's truncated dipolar magnetic field. We demonstrate that changes in circular polarization handedness throughout the eclipses are directly tied to the average line of sight magnetic field direction of pulsar B, from which we unambiguously determine the complete magnetic and viewing geometry of the pulsar., Comment: 8 pages, 6 figures. Accepted for publication in MNRAS

Having a detailed knowledge of the intracluster medium (ICM) to infer the exact cluster physics such as the cluster dynamical state is crucial for cluster-based cosmological studies. This knowledge limits the accuracy and precision of mass estimation, a key parameter for such studies. In this paper, we conduct an in-depth analysis of cluster ACT-CL J0240.0+0116 using a multi-wavelength approach, with a primary focus on high angular resolution Sunyaev-Zeldovich (SZ) thermal component observations obtained under the NIKA2 Sunyaev-Zeldovich Large Programme (LPSZ). We create composite images using NIKA2, X-ray, and optical galaxy number density maps. The results reveal distinct signs of disturbance within the cluster with the distributions of gas and member galaxies that do not overlap. We also find suggestions of an inflow of matter onto the cluster from the southwestern direction. Ultimately, we classify the cluster as disturbed, using morphological indicators derived from its SZ, X-ray, and optical image. The cluster SZ signal is also contaminated by a strong central point source. We adopt different approaches to handling this contaminant and find the estimates of our pressure and hydrostatic mass profiles robust to the point source mitigation model. The cluster hydrostatic mass is estimated at $4.25^{+0.50}_{-0.45\, } \times 10^{14} \,\mathrm{M}_{\odot}$ for the case where the point source was masked. These values are consistent with the mass estimated using only X-ray data and with those from previous SZ studies of the Atacama cosmology telescope (ACT) survey, with improved precision on the mass estimate. Our findings strongly suggest that ACT-CL J0240.0+0116 is a disturbed cluster system, and the detailed observations and derived values serve as a compelling case study for the capabilities of the LPSZ in mapping the cluster ICM with high precision., Comment: 13 pages, 7 figures, submitted to A&A

The millimeter continuum emission from galaxies provides important information about cold dust, its distribution, heating, and role in their InterStellar Medium (ISM). This emission also carries an unknown portion of the free-free and synchrotron radiation. The IRAM 30m Guaranteed Time Large Project, Interpreting Millimeter Emission of Galaxies with IRAM and NIKA2 (IMEGIN) provides a unique opportunity to study the origin of the millimeter emission on angular resolutions of <18" in a sample of nearby galaxies. As a pilot study, we present millimeter observations of two IMEGIN galaxies, NGC 2146 (starburst) and NGC 2976 (peculiar dwarf) at 1.15 mm and 2 mm. Combined with the data taken with Spitzer, Herschel, Plank, WSRT, and the 100m Effelsberg telescopes, we model the infrared-to-radio Spectral Energy Distribution (SED) of these galaxies, both globally and at resolved scales, using a Bayesian approach to 1) dissect different components of the millimeter emission, 2) investigate the physical properties of dust, and 3) explore correlations between millimeter emission, gas, and Star Formation Rate (SFR). We find that cold dust is responsible for most of the 1.15 mm emission in both galaxies and at 2 mm in NGC 2976. The free-free emission emits more importantly in NGC 2146 at 2 mm. The cold dust emissivity index is flatter in the dwarf galaxy ($\beta = 1.3\pm 0.1$) compared to the starburst galaxy ($\beta = 1.7\pm 0.1$). Mapping the dust-to-gas ratio, we find that it changes between 0.004 and 0.01 with a mean of $0.006\pm0.001$ in the dwarf galaxy. In addition, no global balance holds between the formation and dissociation of H$_2$ in this galaxy. We find tight correlations between the millimeter emission and both the SFR and molecular gas mass in both galaxies., Comment: Accepted for publication in Astronomy & Astrophysics

The Small and Large Magellanic Clouds are the only galaxies outside our own in which radio pulsars have been discovered to date. The sensitivity of the MeerKAT radio interferometer offers an opportunity to search for a population of more distant extragalactic pulsars. The TRAPUM (TRansients And PUlsars with MeerKAT) collaboration has performed a radio-domain search for pulsars and transients in the dwarf star-forming galaxies Sextans A and B, situated at the edge of the local group 1.4 Mpc away. We conducted three 2-hour multi-beam observations at L-band (856-1712 MHz) with the full array of MeerKAT. No pulsars were found down to a radio pseudo-luminosity upper limit of 7.9$\pm$0.4 Jy kpc$^{2}$ at 1400 MHz, which is 28 times more sensitive than the previous limit from the Murriyang telescope. This luminosity is 30 per cent greater than that of the brightest known radio pulsar and sets a cut-off on the luminosity distributions of the entire Sextans A and B galaxies for unobscured radio pulsars beamed in our direction. A Fast Radio Burst was detected in one of the Sextans A observations at a Dispersion Measure (DM) of 737 pc cm$^{-3}$. We believe this is a background event not associated with the dwarf galaxy due to its large DM and its S/N being strongest in the wide-field incoherent beam of MeerKAT., Comment: 11 pages, 9 figures, 5 tables. Accepted for publication in Monthly Notices of the Royal Astronomical Society

We propose cognitive prompting as a novel approach to guide problem-solving in large language models (LLMs) through structured, human-like cognitive operations, such as goal clarification, decomposition, filtering, abstraction, and pattern recognition. By employing systematic, step-by-step reasoning, cognitive prompting enables LLMs to tackle complex, multi-step tasks more efficiently. We introduce three variants: a deterministic sequence of cognitive operations, a self-adaptive variant in which the LLM dynamically selects the sequence of cognitive operations, and a hybrid variant that uses generated correct solutions as few-shot chain-of-thought prompts. Experiments with LLaMA, Gemma~2, and Qwen models in each two sizes on the arithmetic reasoning benchmark GSM8K demonstrate that cognitive prompting significantly improves performance compared to standard question answering., Comment: 6 pages, submitted to ESANN 2025

This paper investigates the enhancement of spatial resolution in Sentinel-2 bands that contain spectral information using advanced super-resolution techniques by a factor of 2. State-of-the-art CNN models are compared with enhanced GAN approaches in terms of quality and feasibility. Therefore, a representative dataset comprising Sentinel-2 low-resolution images and corresponding high-resolution aerial orthophotos is required. Literature study reveals no feasible dataset for the land type of interest (forests), for which reason an adequate dataset had to be generated in addition, accounting for accurate alignment and image source optimization. The results reveal that while CNN-based approaches produce satisfactory outcomes, they tend to yield blurry images. In contrast, GAN-based models not only provide clear and detailed images, but also demonstrate superior performance in terms of quantitative assessment, underlying the potential of the framework beyond the specific land type investigated., Comment: This work has been submitted to the IEEE for possible publication

Work of Glover and Huneke shows that a cubic graph embeds into the real projective plane if and only if it does not contain one of six topological minors called cubic projective plane obstructions. Here we classify up to equivalence the embeddings of these graphs into the torus.

Latest advances in the field of natural language processing (NLP) enable new use cases for different domains, including the medical sector. In particular, transcription can be used to support automation in the nursing documentation process and give nurses more time to interact with the patients. However, different challenges including (a) data privacy, (b) local languages and dialects, and (c) domain-specific vocabulary need to be addressed. In this case study, we investigate the case of home care nursing documentation in Switzerland. We assessed different transcription tools and models, and conducted several experiments with OpenAI Whisper, involving different variations of German (i.e., dialects, foreign accent) and manually curated example texts by a domain expert of home care nursing. Our results indicate that even the used out-of-the-box model performs sufficiently well to be a good starting point for future research in the field.

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

This paper presents surface acoustic wave (SAW) acoustic delay lines (ADL) for studying propagation loss mechanisms in Lithium Niobate (LN). Devices were fabricated by depositing 50 nm aluminum patterns on 600 nm X-Cut LN on amorphous silicon on silicon carbide, where longitudinally dominant SAW was targeted. Upon fabrication, higher-order thickness-based cross-sectional Lam\'e modes and Rayleigh modes were studied for their Q factors using acoustic delay lines. Utilizing bi-directional electrodes, ADL with lateral lambda values ranging from 0.4 um to 0.6 um were measured. Higher order Lame modes were found to have consistently higher Q factors than their Rayleigh mode counterpart, on the order of 1000-3000, showing high-frequency SAW devices as still viable candidates for frequency scaling without a substantial increase in loss., Comment: 4 pages, 7 figures, accepted by IEEE UFFC-JS

We introduce a novel strategy for multi-robot sorting of waste objects using Reinforcement Learning. Our focus lies on finding optimal picking strategies that facilitate an effective coordination of a multi-robot system, subject to maximizing the waste removal potential. We realize this by formulating the sorting problem as an OpenAI gym environment and training a neural network with a deep reinforcement learning algorithm. The objective function is set up to optimize the picking rate of the robotic system. In simulation, we draw a performance comparison to an intuitive combinatorial game theory-based approach. We show that the trained policies outperform the latter and achieve up to 16% higher picking rates. Finally, the respective algorithms are validated on a hardware setup consisting of a two-robot sorting station able to process incoming waste objects through pick-and-place operations.