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Context. The complex dynamics of asymptotic giant branch (AGB) stars and the resulting stellar winds have a significant impact on the measurements of stellar parameters and amplify their uncertainties. Three-dimensional (3D) radiative hydrodynamic (RHD) simulations of convection suggest that convection-related structures at the surface of AGB star affect the photocentre displacement and the parallax uncertainty measured by Gaia. Aims. We explore the impact of the convection on the photocentre variability and aim to establish analytical laws between the photocentre displacement and stellar parameters to retrieve such parameters from the parallax uncertainty. Methods. We used a selection of 31 RHD simulations with CO5BOLD and the post-processing radiative transfer code Optim3D to compute intensity maps in the Gaia G band [320-1050 nm]. From these maps, we calculated the photocentre position and temporal fluctuations. We then compared the synthetic standard deviation to the parallax uncertainty of a sample of 53 Mira stars observed with Gaia. Results. The simulations show a displacement of the photocentre across the surface ranging from 4 to 13 % of the corresponding stellar radius, in agreement with previous studies. We provide an analytical law relating the pulsation period of the simulations and the photocentre displacement as well as the pulsation period and stellar parameters. By combining these laws, we retrieve the surface gravity, the effective temperature, and the radius for the stars in our sample. Conclusions. Our analysis highlights an original procedure to retrieve stellar parameters by using both state-of-the-art 3D numerical simulations of AGB stellar convection and parallax observations of AGB stars. This will help us refine our understanding of these giants., Comment: 14 pages, 17 figures

[Abridged] AGB stars are significant contributors to the metal enrichment of the interstellar medium. In this paper, we adapted models from advanced RHD simulations as input for radiative transfer software to create synthetic observables. A major goal is to describe an AGB star's non-sphericity and to simulate its effects on the surrounding dusty envelope. We developed tools to translate models of an AGB star and its dust-driven wind from simulations with CO5BOLD into the format used by RADMC-3D. We preserved the asymmetric shape of the star by including it as a `dust species' and by using temperature data computed in CO5BOLD. Circumstellar dust is included using Mg2SiO4 opacity data with spatially dependent grain sizes. We compared images and SEDs created with RADMC-3D of a model with similar output made with a spherically symmetric star. Our CO5BOLD model features substantial and clumpy dust formation just above 3.4 au from the grid centre, and large-scale structures due to giant convection cells are visible on the stellar surface. With the properties of VLTI as a basis, we have created simple synthetic observables. Such optical interferometers should be able to detect these dust clouds. We find that it is important to include asymmetric stellar models since they even affect the SEDs. Effects on flux levels can be linked to the clumpiness of the circumstellar dust and the angle-dependent illumination resulting from temperature variations on the stellar surface causes shifts in the wavelengths of the flux maximum. The methods presented here are an important step towards producing realistic synthetic observables and testing predictions of advanced 3D RHD models. Taking the angle-dependence of SEDs as a proxy for temporal variations in unresolved data, we conclude that not all variability observed in AGB stars should be interpreted as global changes in the sense of spherical models., Comment: 17 pages, 14 figures, and 5 tables, accepted for publication in A&A in July 2024

Stellar convection plays an important role in atmospheric dynamics, wind formation and the mass-loss processes in Asymptotic Giant Branch (AGB) stars. However, a direct characterization of convective surface structures in terms of size, contrast, and life-span is quite challenging. Spatially resolving these features requires the highest angular resolution. In this work, we aim at characterizing the size of convective structures on the surface of the O-rich AGB star R Car to test different theoretical predictions, based on mixing-length theory from solar models. We used infrared low-spectral resolution (R~35) interferometric data in the H-band (~1.76 $\mu$m) with the instrument PIONIER at the Very Large Telescope Interferometer (VLTI) to image the star's surface at two epochs separated by ~6 years. Using a power spectrum analysis, we estimate the horizontal size of the structures on the surface of R Car. The sizes of the stellar disk, at different phases of a pulsation cycle, were obtained using parametric model-fitting in the Fourier domain. Our analysis supports that the sizes of the structures in R Car are correlated with variations of the pressure scale height in the atmosphere of the target, as predicted by theoretical models based on solar convective processes. We observe that these structures grow in size when the star expands within a pulsation cycle. While the information is still scarce, this observational finding highlights the role of convection in the dynamics of those objects. New interferometric imaging campaigns with the renewed capabilities of the VLTI are envisioned to expand our analysis to a larger sample of objects., Comment: Accepted by A&A on 15/05/2024, 11 pages, 7 figures

We report on the development of a novel pixel charge readout system, Grid Activated Multi-scale pixel readout (GAMPix), which is under development for use in the GammaTPC gamma ray instrument concept. GammaTPC is being developed to optimize the use of liquid argon time projection chamber technology for gamma ray astrophysics, for which a fine grained low power charge readout is essential. GAMPix uses a new architecture with coarse and fine scale instrumented electrodes to solve the twin problems of loss of measured charge after diffusion, and high readout power. Fundamentally, it enables low noise and ultra low power charge readout at the spatial scale limited by diffusion in a time projection chamber, and has other possibly applications, including future DUNE modules., Comment: 23 pages, 18 figures

The evolved stages of massive stars are poorly understood, but invaluable constraints can be derived from spatially resolved observations of nearby red supergiants, such as Betelgeuse. Atacama Large Millimeter/submillimeter Array (ALMA) observations of Betelgeuse showing a dipolar velocity field have been interpreted as evidence for a projected rotation rate of about $5\, \mathrm{km\, s^{-1}}$. This is 2 orders of magnitude larger than predicted by single-star evolution, which led to suggestions that Betelgeuse is a binary merger. We propose instead that large-scale convective motions can mimic rotation, especially if they are only partially resolved. We support this claim with 3D CO5BOLD simulations of nonrotating red supergiants that we postprocessed to predict ALMA images and SiO spectra. We show that our synthetic radial velocity maps have a 90% chance of being falsely interpreted as evidence for a projected rotation rate of $\mathrm{2\, km\, s^{-1}}$ or larger for our fiducial simulation. We conclude that we need at least another ALMA observation to firmly establish whether Betelgeuse is indeed rapidly rotating. Such observations would also provide insight into the role of angular momentum and binary interaction in the late evolutionary stages. The data will further probe the structure and complex physical processes in the atmospheres of red supergiants, which are immediate progenitors of supernovae and are believed to be essential in the formation of gravitational-wave sources., Comment: 14 pages, 10 figures, 2 tables. Published in ApJL. Comments welcome. Animations accessible to general readers and supplementary materials can be found at Zenodo: doi: 10.5281/zenodo.10199936 . Postprocessing packages and Jupiter notebook to reproduce the figures will be available in the same link soon

Surgery for gliomas (intrinsic brain tumors), especially when low-grade, is challenging due to the infiltrative nature of the lesion. Currently, no real-time, intra-operative, label-free and wide-field tool is available to assist and guide the surgeon to find the relevant demarcations for these tumors. While marker-based methods exist for the high-grade glioma case, there is no convenient solution available for the low-grade case; thus, marker-free optical techniques represent an attractive option. Although RGB imaging is a standard tool in surgical microscopes, it does not contain sufficient information for tissue differentiation. We leverage the richer information from hyperspectral imaging (HSI), acquired with a snapscan camera in the 468-787 nm range, coupled to a surgical microscope, to build a deep-learning-based diagnostic tool for cancer resection with potential for intra-operative guidance. However, the main limitation of the HSI snapscan camera is the image acquisition time, limiting its widespread deployment in the operation theater. Here, we investigate the effect of HSI channel reduction and pre-selection to scope the design space for the development of cheaper and faster sensors. Neural networks are used to identify the most important spectral channels for tumor tissue differentiation, optimizing the trade-off between the number of channels and precision to enable real-time intra-surgical application. We evaluate the performance of our method on a clinical dataset that was acquired during surgery on five patients. By demonstrating the possibility to efficiently detect low-grade glioma, these results can lead to better cancer resection demarcations, potentially improving treatment effectiveness and patient outcome., Comment: SPIE Photonics West 2023 conference Optical Biopsy XXI: Toward Real-Time Spectroscopic Imaging and Diagnosis. 18 pages, 11 figures

Convection and mass loss by stellar winds are two dynamical processes that shape asymptotic giant branch (AGB) stars and their evolution. Observations and earlier 3D models indicate that giant convection cells cause high-contrast surface intensity patterns, and contribute to the origin of clumpy dust clouds. We study the formation and resulting properties of dust-driven winds from AGB stars, using new global 3D simulations. The dynamical stellar interiors, atmospheres, and wind acceleration zones of two M-type AGB stars were modeled with the CO5BOLD code. These first global 3D simulations are based on frequency-dependent gas opacities, and they feature time-dependent condensation and evaporation of silicate grains. Convection and pulsations emerge self-consistently, allowing us to derive wind properties (e.g., mass-loss rates and outflow velocities), without relying on parameterized descriptions of these processes. In contrast to 1D models with purely radial pulsations, the shocks induced by convection and pulsation in the 3D models cover large parts, but not the entirety, of the sphere, leading to a patchy, nonspherical structure of the atmosphere. Since dust condensation critically depends on gas density, new dust clouds form mostly in the dense wakes of atmospheric shocks, where the grains can grow efficiently. The resulting clumpy distribution of newly formed dust leads to a complex 3D morphology of the extended atmosphere and wind-acceleration zone, with simultaneous infall and outflow regions close to the star. Highly nonspherical isotherms and short-lived cool pockets of gas in the stellar vicinity are prominent features. Efficient dust formation sets in closer to the star than spherical averages of the temperature indicate, in dense regions where grain growth rates are higher than average.

In recent years, neural network based image denoising approaches have revolutionized the analysis of biomedical microscopy data. Self-supervised methods, such as Noise2Void (N2V), are applicable to virtually all noisy datasets, even without dedicated training data being available. Arguably, this facilitated the fast and widespread adoption of N2V throughout the life sciences. Unfortunately, the blind-spot training underlying N2V can lead to rather visible checkerboard artifacts, thereby reducing the quality of final predictions considerably. In this work, we present two modifications to the vanilla N2V setup that both help to reduce the unwanted artifacts considerably. Firstly, we propose a modified network architecture, i.e., using BlurPool instead of MaxPool layers throughout the used U-Net, rolling back the residual U-Net to a non-residual U-Net, and eliminating the skip connections at the uppermost U-Net level. Additionally, we propose new replacement strategies to determine the pixel intensity values that fill in the elected blind-spot pixels. We validate our modifications on a range of microscopy and natural image data. Based on added synthetic noise from multiple noise types and at varying amplitudes, we show that both proposed modifications push the current state-of-the-art for fully self-supervised image denoising., Comment: 16 pages, 7 figures, 5 page supplement, 4 supplementary figures, accepted at BIC workshop at ECCV 2022

The characteristic variability of cool giants and supergiants is attributed to a combination of stellar pulsation and large-scale convective flows. Full 3D radiation-hydrodynamical modelling is an essential tool for understanding the nature of these dynamical processes. The parameter space in our 3D model grid of red giants has expanded in recent years. These models can provide many insights on the nature and properties of the pulsations, including the interplay between convection and pulsations. We treat 3D dynamical models of asymptotic giant branch (AGB) stars and red supergiants similar to observational data. We aim to explore the relation between stellar parameters and the properties of the self-excited pulsations. Output from global 'star-in-a-box' models computed with the CO5BOLD radiation-hydrodynamics code were analysed, particularly in regards to the pulsation properties, to find possible correlations with input and emergent stellar parameters. The fast Fourier transform was applied to spherically averaged mass flows to identify possible radial pulsation periods beneath the photosphere of the modelled stars. Stellar parameters were investigated for correlations with the extracted pulsation periods. We find that the pulsation periods varied with the stellar parameters in good agreement with the current expectations. The pulsation periods follow Ritter's period-mean density relation well and our AGB models agree with period-luminosity relations derived from observations. A mass estimate formula was derived from the 3D models, relating the stellar mass to the fundamental mode pulsation period and the stellar radius. While the non-linearity of the interplay between the self-excited pulsations and the self-consistent convection complicates analyses, the resulting correlations are in good agreement with respect to current theoretical and observational understandings., Comment: 15 pages, 14 figures, 1 appendix, accepted for publication in A&A. New version corrected a typo in equation (5)

With a rapidly rising number of transients detected in astronomy, classification methods based on machine learning are increasingly being employed. Their goals are typically to obtain a definitive classification of transients, and for good performance they usually require the presence of a large set of observations. However, well-designed, targeted models can reach their classification goals with fewer computing resources. This paper presents SNGuess, a model designed to find young extragalactic nearby transients with high purity. SNGuess works with a set of features that can be efficiently calculated from astronomical alert data. Some of these features are static and associated with the alert metadata, while others must be calculated from the photometric observations contained in the alert. Most of the features are simple enough to be obtained or to be calculated already at the early stages in the lifetime of a transient after its detection. We calculate these features for a set of labeled public alert data obtained over a time span of 15 months from the Zwicky Transient Facility (ZTF). The core model of SNGuess consists of an ensemble of decision trees, which are trained via gradient boosting. Approximately 88% of the candidates suggested by SNGuess from a set of alerts from ZTF spanning from April 2020 to August 2021 were found to be true relevant supernovae (SNe). For alerts with bright detections, this number ranges between 92% and 98%. Since April 2020, transients identified by SNGuess as potential young SNe in the ZTF alert stream are being published to the Transient Name Server (TNS) under the AMPEL_ZTF_NEW group identifier. SNGuess scores for any transient observed by ZTF can be accessed via a web service. The source code of SNGuess is publicly available., Comment: 14 pages, 10 figures, Astronomy & Astrophysics (A&A), Forthcoming article, source code https://github.com/nmiranda/SNGuess

Red supergiant (RSGs) are cool massive stars in a late phase of their evolution when the stellar envelope becomes fully convective. They are the brightest stars in the universe at infrared light and can be detected in galaxies far beyond the Local Group, allowing for accurate determination of chemical composition of galaxies. The study of their physical properties is extremely important for various phenomena including the final fate of massive stars as type II supernovae and gravitational wave progenitors. We explore the well-studied nearby young stellar cluster chi Per. Using Gaia EDR3 data, we find the distance of the cluster (d = 2.260+-0.020 kpc). We then investigate the variability of the convection-related surface structure as a source for parallax measurement uncertainty. We use state-of-the-art 3D radiative hydrodynamics simulations with CO5BOLD and the post-processing radiative transfer code OPTIM3D to compute intensity maps in the Gaia G photometric system. We calculate the variabiltiy, as a function of time, of the intensity-weighted mean from the synthetic maps. We then select the RSG stars in the cluster and compare their uncertainty on parallaxes to the predictions of photocentre displacements. The synthetic maps of RSG show extremely irregular and temporal variable surfaces due to convection-related dynamics. Consequentially, the position of the photo-center varies during Gaia measurements between 0.033 and 0.130 AU (up to 5% of the corresponding simulation stellar radius). We argue that the variability of the convection-related surface structures accounts for a substantial part of the Gaia EDR3 parallax error of the RSG sample. We suggest that the variation of the uncertainty on Gaia parallax could be exploited quantitatively using appropriate 3D simulations to extract, in a unique way, important information about the stellar dynamics and parameters of RSG stars., Comment: Press-release: https://www.mpa-garching.mpg.de/1054448/news20220530

The winds observed around asymptotic giant branch (AGB) stars are generally attributed to radiation pressure on dust, which is formed in the extended dynamical atmospheres of these pulsating, strongly convective stars. Current radiation-hydrodynamical models can explain many of the observed features, and they are on the brink of delivering a predictive theory of mass loss. This review summarizes recent results and ongoing work on winds of AGB stars, discussing critical ingredients of the driving mechanism, and first results of global 3D RHD star-and-wind-in-a-box simulations. With such models it becomes possible to follow the flow of matter, in full 3D geometry, all the way from the turbulent, pulsating interior of an AGB star, through its atmosphere and dust formation zone into the region where the wind is accelerated by radiation pressure on dust. Advanced instruments, which can resolve the stellar atmospheres, where the winds originate, provide essential data for testing the models., Comment: Accepted for publication in "The Origin of Outflows in Evolved Stars", Proceedings of IAU Symposium 366 (8 pages, 2 figures)

Context. VX Sgr is a cool, evolved, and luminous red star whose stellar parameters are difficult to determine, which affects its classification. Aims. We aim to spatially resolve the photospheric extent as well as the circumstellar environment. Methods. We used interferometric observations obtained with the MATISSE instrument in the L (3 to 4 {\mu}m), M (4.5 to 5 {\mu}m), and N (8 to 13 {\mu}m) bands. We reconstructed monochromatic images using the MIRA software. We used 3D radiation-hydrodynamics (RHD) simulations carried out with CO5BOLD and a uniform disc model to estimate the apparent diameter and interpret the stellar surface structures. Moreover, we employed the radiative transfer codes Optim3D and Radmc3D to compute the spectral energy distribution for the L, M, and N bands, respectively. Results. MATISSE observations unveil, for the first time, the morphology of VX Sgr across the L, M, and N bands. The reconstructed images show a complex morphology with brighter areas whose characteristics depend on the wavelength probed. We measured the angular diameter as a function of the wavelength and showed that the photospheric extent in the L and M bands depends on the opacity through the atmosphere. In addition to this, we also concluded that the observed photospheric inhomogeneities can be interpreted as convection-related surface structures. The comparison in the N band yielded a qualitative agreement between the N band spectrum and simple dust radiative transfer simulations. However, it is not possible to firmly conclude on the interpretation of the current data because of the difficulty in constraing the model parameters using the limited accuracy of our absolute flux calibration. Conclusions. MATISSE observations and the derived reconstructed images unveil the appearance of the stellar surface and circumstellar environment across a very large spectral domain for the first time., Comment: Accepted for publication on Astronomy and Astrophysics

Accelerator magnet test facilities frequently need to measure different magnets on differently equipped test stands and with different instrumentation. Designing a modular and highly reusable system that combines flexibility built-in at the architectural level as well as on the component level addresses this need. Specification of the backbone of the system, with the interfaces and dataflow for software components and core hardware modules, serves as a basis for building such a system. The design process and implementation of an extensible magnetic measurement data acquisition and control system are described, including techniques for maximizing the reuse of software. The discussion is supported by showing the application of this methodology to constructing two dissimilar systems for rotating coil measurements, both based on the same architecture and sharing core hardware modules and many software components. The first system is for production testing 10 m long cryo-assemblies containing two MQXFA quadrupole magnets for the high-luminosity upgrade of the Large Hadron Collider and the second for testing IQC conventional quadrupole magnets in support of the accelerator system at Fermilab.

The Join operator, as one of the most expensive and commonly used operators in database systems, plays a substantial role in Database Management System (DBMS) performance. Among the many different Join algorithms studied over the last decades, Hybrid Hash Join (HHJ) has proven to be one of the most efficient and widely-used join algorithms. While the performance of HHJ depends largely on accurate statistics and information about the input relations, it may not always be practical or possible for a system to have such information available. The design of HHJ depends on many details to perform well. This paper is an experimental and analytical study of the trade-offs in designing a robust and dynamic HHJ operator. We revisit the design and optimization techniques suggested by previous studies through extensive experiments, comparing them with other algorithms designed by us or used in related studies. We explore the impact of the number of partitions on the performance of HHJ and propose a lower bound and a default value for the number of partitions. We continue by designing and evaluating different partition insertion techniques to maximize memory utilization with the least CPU cost. In addition, we consider a comprehensive set of algorithms for dynamically selecting a partition to spill and compare the results against previously published studies. We then present two alternative growth policies for spilled partitions and study their effectiveness using experimental and model-based analyses. These algorithms have been implemented in the context of Apache AsterixDB and evaluated under different scenarios such as variable record sizes, different distributions of join attributes, and different storage types, including HDD, SSD, and Amazon Elastic Block Store (Amazon EBS).