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Pyrochlore magnets have proven to provide an excellent arena for the realization of a variety of many-body phenomena such as classical and quantum order-by-disorder, as well as spin liquid phases described by emergent gauge field theories. These phenomena arise from the competition between different symmetry-breaking magnetic orders. In this work, we consider a subspace of the most general bilinear nearest-neighbor Hamiltonian on the pyrochlore lattice, parameterized by the local interaction parameter $J_{z\pm}$, where three symmetry-breaking phases converge. We demonstrate that for small values of $|J_{z\pm}|$, a conventional $\mathbf q=0$ ordered phase is selected by a thermal order-by-disorder mechanism. For $|J_{z\pm}|$ above a certain finite threshold, a novel spin-nematic phase is stabilized at low temperatures. Instead of the usual Bragg peaks, the spin-nematic phase features lines of high intensity in the spin structure factor. At intermediate temperatures above the low-temperature orders, a rank-2 U(1) classical spin liquid is realized for all $J_{z\pm} \neq 0$. We fully characterize all phases using classical Monte-Carlo simulations and a self-consistent Gaussian approximation., Comment: 17 pages, 17 figures

MICADO is a first light instrument for the Extremely Large Telescope (ELT), set to start operating later this decade. It will provide diffraction limited imaging, astrometry, high contrast imaging, and long slit spectroscopy at near-infrared wavelengths. During the initial phase operations, adaptive optics (AO) correction will be provided by its own natural guide star wavefront sensor. In its final configuration, that AO system will be retained and complemented by the laser guide star multi-conjugate adaptive optics module MORFEO (formerly known as MAORY). Among many other things, MICADO will study exoplanets, distant galaxies and stars, and investigate black holes, such as Sagittarius A* at the centre of the Milky Way. After their final design phase, most components of MICADO have moved on to the manufacturing and assembly phase. Here we summarize the final design of the instrument and provide an overview about its current manufacturing status and the timeline. Some lessons learned from the final design review process will be presented in order to help future instrumentation projects to cope with the challenges arising from the substantial differences between projects for 8-10m class telescopes (e.g. ESO-VLT) and the next generation Extremely Large Telescopes (e.g. ESO-ELT). Finally, the expected performance will be discussed in the context of the current landscape of astronomical observatories and instruments. For instance, MICADO will have similar sensitivity as the James Webb Space Telescope (JWST), but with six times the spatial resolution., Comment: Proceedings of the SPIE, Volume 13096, id. 1309611 11 pp. (2024)

Cell motility in dense cell collectives is pivotal in various diseases like cancer metastasis and asthma. A central aspect in these phenomena is the heterogeneity in cell motility, but identifying the motility of individual cells is challenging. Previous work has established the importance of the average cell shape in predicting cell dynamics. Here, we aim to identify the importance of individual cell shape features, rather than collective features, to distinguish between high-motility (active) and low-motility (passive) cells in heterogeneous cell layers. Employing the Cellular Potts Model, we generate simulation snapshots and extract static features as inputs for a simple machine-learning model. Our results show that when the passive cells are non-motile, this machine-learning model can accurately predict whether a cell is passive or active using only single-cell shape features. Furthermore, we explore scenarios where passive cells also exhibit some degree of motility, albeit less than active cells. In such cases, our findings indicate that a neural network trained on shape features can accurately classify cell motility, particularly when the number of active cells is low, and the motility of active cells is significantly higher compared to passive cells. This work offers potential for physics-inspired predictions of single-cell properties with implications for inferring cell dynamics from static histological images.

The mode-coupling theory (MCT) of the glass transition ranks among the most successful first-principles kinetic theories to describe glassy dynamics. However, MCT does not fully account for crucial aspects of the dynamics near the glass transition. To facilitate improving the theory, we critically test the approximations inherent in MCT for a supercooled mixture using Brownian dynamics simulations. Although each MCT approximation significantly impacts the predicted dynamics, our findings show that long-time cancellations of errors occur due to static and dynamic approximations of four-point correlation functions, with the validity of these approximations remaining relatively constant across different temperatures. Notably, the MCT form of the memory functional maintains remarkably high accuracy even in the supercooled regime when evaluated with the intermediate scattering function from simulations. The primary discrepancies between theoretical predictions and experimental results arise from the self-consistent nature of the MCT equations, which amplify minor errors in the memory kernel. This suggests that minor corrections to the memory functional could substantially enhance the theory's predictive accuracy.

Principal component analysis (PCA) is one of the most popular dimension reduction techniques in statistics and is especially powerful when a multivariate distribution is concentrated near a lower-dimensional subspace. Multivariate extreme value distributions have turned out to provide challenges for the application of PCA since their constraint support impedes the detection of lower-dimensional structures and heavy-tails can imply that second moments do not exist, thereby preventing the application of classical variance-based techniques for PCA. We adapt PCA to max-stable distributions using a regression setting and employ max-linear maps to project the random vector to a lower-dimensional space while preserving max-stability. We also provide a characterization of those distributions which allow for a perfect reconstruction from the lower-dimensional representation. Finally, we demonstrate how an optimal projection matrix can be consistently estimated and show viability in practice with a simulation study and application to a benchmark dataset., Comment: 34 pages, 11 Figures

Critical single-particle fluctuations associated with particle displacements are inherent to simple glass-forming liquids in the limit of large dimensions and leave a pseudo-critical trace across all finite dimensions. This characteristic could serve as a crucial test for distinguishing between theories of glass formation. We here examine these critical fluctuations, as captured by the well-established non-Gaussian parameter, within both mode-coupling theory (MCT) and dynamical mean-field theory (DMFT) across dimensions for hard sphere liquids and for the minimally structured Mari--Kurchan model. We establish general scaling laws relevant to any liquid dynamics theory in large dimensions and show that the dimensional scalings predicted by MCT are inconsistent with those from DMFT. Simulation results for hard spheres in moderately high dimensions align with the DMFT scenario, reinforcing the relevance of mean-field theory for capturing glass physics in finite dimensions. We identify potential adjustments to MCT to account for certain mean-field physics. Our findings also highlight that local structure and spatial dimensionality can affect single-particle critical fluctuations in non-trivial ways., Comment: 42 pages, 9 figures

In this study, we focus on different strategies drivers use in terms of interleaving between driving and non-driving related tasks (NDRT) while taking back control from automated driving. We conducted two driving simulator experiments to examine how different cognitive demands of texting, priorities, and takeover time budgets affect drivers' takeover strategies. We also evaluated how different takeover strategies affect takeover performance. We found that the choice of takeover strategy was influenced by the priority and takeover time budget but not by the cognitive demand of the NDRT. The takeover strategy did not have any effect on takeover quality or NDRT engagement but influenced takeover timing.

$\delta$-Covering, for some covering range $\delta>0$, is a continuous facility location problem on undirected graphs where all edges have unit length. The facilities may be positioned on the vertices as well as on the interior of the edges. The goal is to position as few facilities as possible such that every point on every edge has distance at most $\delta$ to one of these facilities. For large $\delta$, the problem is similar to dominating set, which is hard to approximate, while for small $\delta$, say close to $1$, the problem is similar to vertex cover. In fact, as shown by Hartmann et al. [Math. Program. 22], $\delta$-Covering for all unit-fractions $\delta$ is polynomial time solvable, while for all other values of $\delta$ the problem is NP-hard. We study the approximability of $\delta$-Covering for every covering range $\delta>0$. For $\delta \geq 3/2$, the problem is log-APX-hard, and allows an $\mathcal O(\log n)$ approximation. For every $\delta < 3/2$, there is a constant factor approximation of a minimum $\delta$-cover (and the problem is APX-hard when $\delta$ is not a unit-fraction). We further study the dependency of the approximation ratio on the covering range $\delta < 3/2$. By providing several polynomial time approximation algorithms and lower bounds under the Unique Games Conjecture, we narrow the possible approximation ratio, especially for $\delta$ close to the polynomial time solvable cases., Comment: 22 pages, 6 figures, extended abstract accepted at WAOA24

The Probe far-Infrared Mission for Astrophysics (PRIMA) is a proposed space observatory which will use arrays of thousands of kinetic inductance detectors (KIDs) to perform low- and moderate-resolution spectroscopy throughout the far-infrared. The detectors must have noise equivalent powers (NEPs) at or below 0.1 aW/sqrt(Hz) to be subdominant to noise from sky backgrounds and thermal noise from PRIMA's cryogenically cooled primary mirror. Using a Radio Frequency System on a Chip for multitone readout, we measure the NEPs of detectors on a flight-like array designed to observe at a wavelength of 210 microns. We find that 92% of the KIDs measured have an NEP below 0.1 aW/sqrt(Hz) at a noise frequency of 10 Hz., Comment: 7 pages, 7 figures

Ultra diffuse galaxies, characterized by their low surface brightness and large physical size, constitute a subclass of dwarf galaxies that challenge our current understanding of galaxy formation and evolution. In this paper, we probe the properties of 74 UDGs, identified in the MATLAS survey, based on a comprehensive study of their globular cluster (GC) populations. We obtained high resolution HST imaging of these galaxies using the ACS F606W and F814W filters, allowing us to select GCs based on color and concentration index. After background subtraction and completeness correction, we calculate an overall total of 387 GCs. The number of GCs per galaxy ranges from 0 to 38, with the majority (64%) having low counts (0-2 GCs). On average, the more massive UDGs host a larger number of GCs. We find that our UDGs have specific frequencies (S_N) ranging from 0 to 91, with a small population (9%) with S_N > 30. The median S_N of our sample is similar to the one for the Perseus cluster UDGs, despite the fact that our UDGs are found in lower density environments. The S_N measurements for individual galaxies can extend beyond those found in Perseus, but remain below the values found for UDGs in the Virgo and Coma cluster. Based on a trending analysis of the S_N values with the host galaxy properties, we find trends with host galaxy size, roundness, color, and local density. For the UDGs with sufficiently high statistics, we study 2D density maps of the GC distributions, which show a variety of appearances: symmetric, asymmetric, off-center, and elongated. The UDGs with disturbed density maps also show disturbed stellar light morphologies. We further quantify the distribution by modeling it with a Sersic profile, finding R_{e,GC}/R_{e,gal} ~ 1.0, which indicates that the GCs follow the stellar light of the host galaxy., Comment: 20 pages, 17 figures, 2 tables, accepted for publication in A&A

We show that the Kontsevich-Segal-Witten (KSW) criterion applied to the no-boundary state constrains anisotropic deformations of de Sitter space. We consider squashed $S^3$ and $S^1 \times S^2$ boundaries and find that in both models, the KSW criterion excludes a significant range of homogeneous but anisotropic configurations. For squashed $S^3$ boundaries, the excluded range includes all surface geometries with negative scalar curvature, in line with dS/CFT reasoning. For $S^1 \times S^2$ boundaries, we find that KSW selects the low-temperature regime of configuration space where the $S^1$ is sufficiently large compared to the $S^2$. In both models, the KSW criterion renders the semiclassical wave function normalizable, up to one-loop effects., Comment: 33 pages

This work introduces Dareplane, a modular and broad technology agnostic open source software platform for brain-computer interface research with an application focus on adaptive deep brain stimulation (aDBS). While the search for suitable biomarkers to inform aDBS has provided rich results over the last two decades, development of control strategies is not progressing at the same pace. One difficulty for investigating control approaches resides with the complex setups required for aDBS experiments. The Dareplane platform supports aDBS setups, and more generally brain computer interfaces, by providing a modular, technology-agnostic, and easy-to-implement software platform to make experimental setups more resilient and replicable. The key features of the platform are presented and the composition of modules into a full experimental setup is discussed in the context of a Python-based orchestration module. The performance of a typical experimental setup on Dareplane for aDBS is evaluated in three benchtop experiments, covering (a) an easy-to-replicate setup using an Arduino microcontroller, (b) a setup with hardware of an implantable pulse generator, and (c) a setup using an established and CE certified external neurostimulator. Benchmark results are presented for individual processing steps and full closed-loop processing. The results show that the microcontroller setup in (a) provides timing comparable to the realistic setups in (b) and (c). The Dareplane platform was successfully used in a total of 19 open-loop DBS sessions with externalized DBS and electrocorticography (ECoG) leads. In addition, the full technical feasibility of the platform in the aDBS context is demonstrated in a first closed-loop session with externalized leads on a patient with Parkinson's disease receiving DBS treatment.

By 2050, the global population will exceed 9 billion, demanding a 70% increase in food production. Animal proteins alone may not suffice and contribute to global warming. Alternative proteins such as legumes, algae, and insects are being explored, but their health impacts are largely unknown. For this, three-week-old rats were fed diets containing 20% protein from various sources for six weeks. A casein-based control diet was compared to soy isolate, spirulina powder, chickpea isolate, chickpea flour, and fly larvae powder. Except for spirulina, alternative protein groups showed comparable growth patterns to the casein group. Morphological and mechanical tests of femur bones matched growth patterns. Caecal 16S analysis highlighted the impact on gut microbiota diversity. Chickpea flour showed significantly lower $\alpha$-diversity compared with casein and chickpea isolate groups while chickpea flour, had the greatest distinction in $\beta$-diversity. Alternative protein sources supported optimal growth, but quality and health implications require further exploration.

The Ornstein-Zernike equation is a powerful tool in liquid state theory for predicting structural and thermodynamic properties of fluids. Combined with a suitable closure, it has been shown to reproduce e.g. the static structure factor, pressure, and compressibility of liquids to a great degree of accuracy. However, out of the multitude of closures that exist for the Ornstein-Zernike equation, it is hard to predict a priori which closure will give the most accurate predictions for the system at hand. To alleviate this problem, we compare the predictive power of many closures on a curated set of representative benchmark systems, including those with hard-sphere, inverse power-law, Gaussian core, and Lennard-Jones particles, in three and two dimensions. For example, we find that the well-known and highly used Percus-Yevick closure gives significantly worse predictions than lesser-known closures of equal complexity in all cases studied. We anticipate that the trends observed in our results will aid in making more informed decisions regarding closure choices. To facilitate the adoption of more modern closure theories, we also have packaged, documented, and distributed the code necessary to numerically solve the equations for a given closure and pair interaction potential.

We report on the effects of cosmic ray interactions with the Kinetic Inductance Detector (KID) based focal plane array for the Terahertz Intensity Mapper (TIM). TIM is a NASA-funded balloon-borne experiment designed to probe the peak of the star formation in the Universe. It employs two spectroscopic bands, each equipped with a focal plane of four $\sim\,$900-pixel, KID-based array chips. Measurements of an 864-pixel TIM array shows 791 resonators in a 0.5$\,$GHz bandwidth. We discuss challenges with resonator calibration caused by this high multiplexing density. We robustly identify the physical positions of 788 (99.6$\,$%) detectors using a custom LED-based identification scheme. Using this information we show that cosmic ray events occur at a rate of 2.1$\,\mathrm{events/min/cm^2}$ in our array. 66$\,$% of the events affect a single pixel, and another 33$\,$% affect $<\,$5 KIDs per event spread over a 0.66$\,\mathrm{cm^2}$ region (2 pixel pitches in radius). We observe a total cosmic ray dead fraction of 0.0011$\,$%, and predict that the maximum possible in-flight dead fraction is $\sim\,$0.165$\,$%, which demonstrates our design will be robust against these high-energy events., Comment: 14 pages, 5 figures. Accepted for the publication in Journal of Low Temperature Physics (2024)

Self-calibration methods with the CLEAN algorithm have been widely employed in Very Long Baseline Interferometry (VLBI) data processing in order to correct antenna-based amplitude and phase corruptions present in the data. However, human interaction during the conventional CLEAN self-calibration process can impose a strong effective prior, which in turn may produce artifacts within the final image and hinder the reproducibility of final results. In this work, we aim to demonstrate a combined self-calibration and imaging method for VLBI data in a Bayesian inference framework. The method corrects for amplitude and phase gains for each antenna and polarization mode by inferring the temporal correlation of the gain solutions. We use Stokes I data of M87 taken with the Very Long Baseline Array (VLBA) at 43GHz, pre-calibrated using the rPICARD CASA-based pipeline. For antenna-based gain calibration and imaging, we use the Bayesian imaging software resolve. To estimate gain and image uncertainties, we use a Variational Inference method. We obtain a high-resolution M87 Stokes I image at 43GHz in conjunction with antenna-based gain solutions using our Bayesian self-calibration and imaging method. The core with counter-jet structure is better resolved, and extended jet emission is better described compared to the CLEAN reconstruction. Furthermore, uncertainty estimation of the image and antenna-based gains allows us to quantify the reliability of the result. Our Bayesian self-calibration and imaging method is able to reconstruct robust and reproducible Stokes I images and gain solutions with uncertainty estimation by taking into account the uncertainty information in the data., Comment: accepted for publication in A&A

The wavelength dependent refraction of light in the atmosphere causes the chromatic dispersion of a target on the focal plane of an instrument. This is known as atmospheric dispersion, with one of the consequences being wavelength dependent flux losses which are difficult to minimise, requiring analysis in both instrument design and operations. We present Atmosphyre, a novel python package developed to characterise the impact of atmospheric dispersion on a spectrograph, with a focus on fibre multi-object spectrographs (MOS) which will be at the forefront of ground-based astronomy for the next few decades. We show example simulations and provide recommendations for minimising fibre MOS flux losses. We conclude that the guiding wavelength should typically be bluer than the observing band mid-wavelength, around 25-45% of the way through the band. The aperture should be centred on this wavelength's location on the focal plane. This wavelength/position remains constant for all reasonable declinations and target hour angles. We also present an application of the package to MOSAIC, the ELT's multi-object spectrograph. We find that differential losses greater than 10% are unavoidable for 1h observations that are a) after a local hour angle of 2.5h, or b) at declinations below -60 degrees and above 10 degrees. We identify that the introduction of an atmospheric dispersion corrector (ADC) would result in the significant reduction of spectral distortions, a gain in survey speed for many observations, and enable the implementation of wider visible observing bands; as a result, there has been a proposal to adopt ADCs at a positioner level for MOSAIC. Future work includes adding field differential refraction to Atmosphyre, important for future wide-field multi-object spectrograph projects such as the proposed WST., Comment: 10 pages, 6 figures, submitted to SPIE Astronomical Telescopes & Instrumentation, Ground-based and Airborne Instrumentation for Astronomy X (Conference 13096, Paper 219)

We use large-scale fermion quantum Monte Carlo simulations to study metallic and deconfined quantum phase transitions in a bilayer honeycomb model, focusing on their quantum critical and finite-temperature properties. At weak interaction, a fully symmetric Dirac semimetal state is realized. At intermediate and strong interaction, respectively, two long-range-ordered phases that break different symmetries are stabilized. The ordered phases feature partial and full, respectively, gap openings in the fermion spectrum. We clarify the symmetries of the different zero-temperature phases and the symmetry breaking patterns across the two quantum phase transitions between them. The first transition between the disordered and long-range-ordered semimetallic phases has previously been argued to be described by the $(2+1)$-dimensional Gross-Neveu-SO(3) field theory. By performing simulations with an improved symmetric Trotter decomposition, we further substantiate this claim by computing the critical exponents $1/\nu$, $\eta_\phi$, and $\eta_\psi$, which turn out to be consistent with the field-theoretical expectation within numerical and analytical uncertainties. The second transition between the two long-range-ordered phases has previously been proposed as a possible instance of a metallic deconfined quantum critical point. We further develop this scenario by analyzing the spectral functions in the single-particle, particle-hole, and particle-particle channels. Our results indicate gapless excitations with a unique velocity, supporting the emergence of Lorentz symmetry at criticality. We also determine the finite-temperature phase boundaries above the fully gapped state at large interaction, which smoothly vanish near the putative metallic deconfined quantum critical point, consistent with a continuous or weakly first-order transition., Comment: 13 pages, 9 figures

Circulating tumor cell clusters play an important role in the metastatic cascade. These clusters can acquire a migratory and more invasive phenotype, and coordinate their motion to migrate as a collective. Before such clusters can form by collectively detaching from a primary tumor, however, the cluster must first aggregate in the tumor interior. The mechanism of this cluster formation process is still poorly understood. One of the possible ways for cells to cluster is by aligning their direction of motion with their neighboring cells. This work aims to investigate the role of this cell-cell alignment interaction on the formation of motile cell clusters inside the bulk of a tumor using computer simulations. We employ a Cellular Potts model in which we model a two-dimensional heterogeneous confluent layer containing both motile and non-motile cells. Our results indicate that the degree of clustering is governed by two distinct processes: the formation of clusters due to the presence of cell-cell alignment interactions among motile cells, and the suppression of clustering due to the presence of the dynamic cellular environment (comprised of the non-motile cells). We find that the largest motile clusters are formed for intermediate alignment strengths, contrary to what is observed for motile cells in free space (that is, unimpeded by a dense cellular environment), in which case stronger cell-cell alignment always leads to larger clustering. Our findings suggest that the presence of a densely-packed cellular environment and strong cell-cell alignment inhibits the formation of large migratory clusters within the primary tumor, providing physical insight into potential factors at play during the early stages of metastasis., Comment: 11 pages, 6 figures

We extend the analytic description of complex no-boundary solutions in the context of inflation to large field models. We discuss the Kontsevich-Segal-Witten (KSW) criterion and find it is satisfied in small field models, while in large field models it depends on an integral involving $V'(\phi)$ over the range of inflation. It follows that the criterion does not truly constrain inflationary phenomenology since one can complete any inflaton potential beyond observable scales so as to satisfy KSW., Comment: 15 pages

We consider a recently proposed approach to graph signal processing based on graphons. We show how the graphon-based approach to GSP applies to graphs sampled from a stochastic block model. We obtain a basis for the graphon Fourier transform on such samples directly from the link probability matrix and the block sizes of the model. This formulation allows us to bound the sensitivity of the Fourier transform to small changes in block sizes. We then focus on the case where the probability matrix corresponds to a (weighted) Cayley graph. If block sizes are equal, a nice Fourier basis can be derived from the underlying group. We explore how, in the case where block sizes are not equal, some or all nice properties of the group basis can be maintained. We complement the theoretical results with simulations., Comment: 23 pages

Differential Evolution (DE) is a highly successful population based global optimisation algorithm, commonly used for solving numerical optimisation problems. However, as the complexity of the objective function increases, the wall-clock run-time of the algorithm suffers as many fitness function evaluations must take place to effectively explore the search space. Due to the inherently parallel nature of the DE algorithm, graphics processing units (GPU) have been used to effectively accelerate both the fitness evaluation and DE algorithm. This work reviews the main architectural choices made in the literature for GPU based DE algorithms and introduces a new GPU based numerical optimisation benchmark to evaluate and compare GPU based DE algorithms.

The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime factor for patient risk stratification, although it suffers from inconsistencies and variations among pathologists. Moreover, absence of annotations in medical imaging difficults training deep learning models. To address these challenges, we introduce a pipeline designed for bladder cancer grading using histological slides. First, it extracts urothelium tissue tiles at different magnification levels, employing a convolutional neural network for processing for feature extraction. Then, it engages in the slide-level prediction process. It employs a nested multiple instance learning approach with attention to predict the grade. To distinguish different levels of malignancy within specific regions of the slide, we include the origins of the tiles in our analysis. The attention scores at region level is shown to correlate with verified high-grade regions, giving some explainability to the model. Clinical evaluations demonstrate that our model consistently outperforms previous state-of-the-art methods., Comment: https://github.com/Biomedical-Data-Analysis-Laboratory/GradeMIL

We present a pioneering investigation into the application of deep learning techniques to analyze histopathological images for addressing the substantial challenge of automated prognostic prediction. Prognostic prediction poses a unique challenge as the ground truth labels are inherently weak, and the model must anticipate future events that are not directly observable in the image. To address this challenge, we propose a novel three-part framework comprising of a convolutional network based tissue segmentation algorithm for region of interest delineation, a contrastive learning module for feature extraction, and a nested multiple instance learning classification module. Our study explores the significance of various regions of interest within the histopathological slides and exploits diverse learning scenarios. The pipeline is initially validated on artificially generated data and a simpler diagnostic task. Transitioning to prognostic prediction, tasks become more challenging. Employing bladder cancer as use case, our best models yield an AUC of 0.721 and 0.678 for recurrence and treatment outcome prediction respectively., Comment: https://github.com/Biomedical-Data-Analysis-Laboratory/HistoPrognostics

Extragalactic globular clusters (EGCs) are an abundant and powerful tracer of galaxy dynamics and formation, and their own formation and evolution is also a matter of extensive debate. The compact nature of globular clusters means that they are hard to spatially resolve and thus study outside the Local Group. In this work we have examined how well EGCs will be detectable in images from the Euclid telescope, using both simulated pre-launch images and the first early-release observations of the Fornax galaxy cluster. The Euclid Wide Survey will provide high-spatial resolution VIS imaging in the broad IE band as well as near-infrared photometry (YE, JE, and HE). We estimate that the galaxies within 100 Mpc in the footprint of the Euclid survey host around 830 000 EGCs of which about 350 000 are within the survey's detection limits. For about half of these EGCs, three infrared colours will be available as well. For any galaxy within 50Mpc the brighter half of its GC luminosity function will be detectable by the Euclid Wide Survey. The detectability of EGCs is mainly driven by the residual surface brightness of their host galaxy. We find that an automated machine-learning EGC-classification method based on real Euclid data of the Fornax galaxy cluster provides an efficient method to generate high purity and high completeness GC candidate catalogues. We confirm that EGCs are spatially resolved compared to pure point sources in VIS images of Fornax. Our analysis of both simulated and first on-sky data show that Euclid will increase the number of GCs accessible with high-resolution imaging substantially compared to previous surveys, and will permit the study of GCs in the outskirts of their hosts. Euclid is unique in enabling systematic studies of EGCs in a spatially unbiased and homogeneous manner and is primed to improve our understanding of many understudied aspects of GC astrophysics., Comment: Submitted to A&A

We make use of the unprecedented depth, spatial resolution, and field of view of the Euclid Early Release Observations of the Perseus galaxy cluster to detect and characterise the dwarf galaxy population in this massive system. The Euclid high resolution VIS and combined VIS+NIR colour images were visually inspected and dwarf galaxy candidates were identified. Their morphologies, the presence of nuclei, and their globular cluster (GC) richness were visually assessed, complementing an automatic detection of the GC candidates. Structural and photometric parameters, including Euclid filter colours, were extracted from 2-dimensional fitting. Based on this analysis, a total of 1100 dwarf candidates were found across the image, with 638 appearing to be new identifications. The majority (96%) are classified as dwarf ellipticals, 53% are nucleated, 26% are GC-rich, and 6% show disturbed morphologies. A relatively high fraction of galaxies, 8%, are categorised as ultra-diffuse galaxies. The majority of the dwarfs follow the expected scaling relations. Globally, the GC specific frequency, S_N, of the Perseus dwarfs is intermediate between those measured in the Virgo and Coma clusters. While the dwarfs with the largest GC counts are found throughout the Euclid field of view, those located around the east-west strip, where most of the brightest cluster members are found, exhibit larger S_N values, on average. The spatial distribution of the dwarfs, GCs, and intracluster light show a main iso-density/isophotal centre displaced to the west of the bright galaxy light distribution. The ERO imaging of the Perseus cluster demonstrates the unique capability of Euclid to concurrently detect and characterise large samples of dwarfs, their nuclei, and their GC systems, allowing us to construct a detailed picture of the formation and evolution of galaxies over a wide range of mass scales and environments., Comment: 44 pages, 24 figures, 5 tables, paper submitted to A&A as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

The Euclid ERO programme targeted the Perseus cluster of galaxies, gathering deep data in the central region of the cluster over 0.7 square degree, corresponding to approximately 0.25 r_200. The data set reaches a point-source depth of IE=28.0 (YE, JE, HE = 25.3) AB magnitudes at 5 sigma with a 0.16" and 0.48" FWHM, and a surface brightness limit of 30.1 (29.2) mag per square arcsec. The exceptional depth and spatial resolution of this wide-field multi-band data enable the simultaneous detection and characterisation of both bright and low surface brightness galaxies, along with their globular cluster systems, from the optical to the NIR. This study advances beyond previous analyses of the cluster and enables a range of scientific investigations summarised here. We derive the luminosity and stellar mass functions (LF and SMF) of the Perseus cluster in the Euclid IE band, thanks to supplementary u,g,r,i,z and Halpha data from the CFHT. We adopt a catalogue of 1100 dwarf galaxies, detailed in the corresponding ERO paper. We identify all other sources in the Euclid images and obtain accurate photometric measurements using AutoProf or AstroPhot for 138 bright cluster galaxies, and SourceExtractor for half a million compact sources. Cluster membership for the bright sample is determined by calculating photometric redshifts with Phosphoros. Our LF and SMF are the deepest recorded for the Perseus cluster, highlighting the groundbreaking capabilities of the Euclid telescope. Both the LF and SMF fit a Schechter plus Gaussian model. The LF features a dip at M(IE)=-19 and a faint-end slope of alpha_S = -1.2 to -1.3. The SMF displays a low-mass-end slope of alpha_S = -1.2 to -1.35. These observed slopes are flatter than those predicted for dark matter halos in cosmological simulations, offering significant insights for models of galaxy formation and evolution., Comment: Submitted to A&A, 44 pages, 35 figures, Part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

We present an analysis of Euclid observations of a 0.5 deg$^2$ field in the central region of the Fornax galaxy cluster that were acquired during the performance verification phase. With these data, we investigate the potential of Euclid for identifying GCs at 20 Mpc, and validate the search methods using artificial GCs and known GCs within the field from the literature. Our analysis of artificial GCs injected into the data shows that Euclid's data in $I_{\rm E}$ band is 80% complete at about $I_{\rm E} \sim 26.0$ mag ($M_{V\rm } \sim -5.0$ mag), and resolves GCs as small as $r_{\rm h} = 2.5$ pc. In the $I_{\rm E}$ band, we detect more than 95% of the known GCs from previous spectroscopic surveys and GC candidates of the ACS Fornax Cluster Survey, of which more than 80% are resolved. We identify more than 5000 new GC candidates within the field of view down to $I_{\rm E}$ mag, about 1.5 mag fainter than the typical GC luminosity function turn-over magnitude, and investigate their spatial distribution within the intracluster field. We then focus on the GC candidates around dwarf galaxies and investigate their numbers, stacked luminosity distribution and stacked radial distribution. While the overall GC properties are consistent with those in the literature, an interesting over-representation of relatively bright candidates is found within a small number of relatively GC-rich dwarf galaxies. Our work confirms the capabilities of Euclid data in detecting GCs and separating them from foreground and background contaminants at a distance of 20 Mpc, particularly for low-GC count systems such as dwarf galaxies., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

We present a quantum algorithm for computational fluid dynamics based on the Lattice-Boltzmann method. Our approach involves a novel encoding strategy and a modified collision operator, assuming full relaxation to the local equilibrium within a single time step. Our quantum algorithm enables the computation of multiple time steps in the linearized case, specifically for solving the advection-diffusion equation, before necessitating a full state measurement. Moreover, our formulation can be extended to compute the non-linear equilibrium distribution function for a single time step prior to measurement, utilizing the measurement as an essential algorithmic step. However, in the non-linear case, a classical postprocessing step is necessary for computing the moments of the distribution function. We validate our algorithm by solving the one dimensional advection-diffusion of a Gaussian hill. Our results demonstrate that our quantum algorithm captures non-linearity.

Deep Neural Networks (DNNs) share important similarities with structural glasses. Both have many degrees of freedom, and their dynamics are governed by a high-dimensional, non-convex landscape representing either the loss or energy, respectively. Furthermore, both experience gradient descent dynamics subject to noise. In this work we investigate, by performing quantitative measurements on realistic networks trained on the MNIST and CIFAR-10 datasets, the extent to which this qualitative similarity gives rise to glass-like dynamics in neural networks. We demonstrate the existence of a Topology Trivialisation Transition as well as the previously studied under-to-overparameterised transition analogous to jamming. By training DNNs with overdamped Langevin dynamics in the resulting disordered phases, we do not observe diverging relaxation times at non-zero temperature, nor do we observe any caging effects, in contrast to glass phenomenology. However, the weight overlap function follows a power law in time, with an exponent of approximately -0.5, in agreement with the Mode-Coupling Theory of structural glasses. In addition, the DNN dynamics obey a form of time-temperature superposition. Finally, dynamic heterogeneity and ageing are observed at low temperatures. These results highlight important and surprising points of both difference and agreement between the behaviour of DNNs and structural glasses.

In this paper, we describe the wide-field spectroscopic survey telescope (WST) project. WST is a 12-metre wide-field spectroscopic survey telescope with simultaneous operation of a large field-of-view (3 sq. degree), high-multiplex (20,000) multi-object spectrograph (MOS), with both a low and high-resolution modes, and a giant 3x3 arcmin2 integral field spectrograph (IFS). In scientific capability, these specifications place WST far ahead of existing and planned facilities. In only 5 years of operation, the MOS would target 250 million galaxies and 25 million stars at low spectral resolution, plus 2 million stars at high resolution. Without need for pre-imaged targets, the IFS would deliver 4 billion spectra offering many serendipitous discoveries. Given the current investment in deep imaging surveys and noting the diagnostic power of spectroscopy, WST will fill a crucial gap in astronomical capability and work in synergy with future ground and space-based facilities. We show how it can address outstanding scientific questions in the areas of cosmology; galaxy assembly, evolution, and enrichment, including our own Milky Way; the origin of stars and planets; and time domain and multi-messenger astrophysics. WST's uniquely rich dataset may yield unforeseen discoveries in many of these areas. The telescope and instruments are designed as an integrated system and will mostly use existing technology, with the aim to minimise the carbon footprint and environmental impact. We will propose WST as the next European Southern Observatory (ESO) project after completion of the 39-metre ELT., Comment: 15 pages, 15 figures

We study the constraints imposed on the electromagnetic response of general media by microcausality (commutators of local fields vanish outside the light cone) and positivity of the imaginary parts (the medium can only absorb energy from the external field). The equations of motion for the average electromagnetic field in a medium -- the macroscopic Maxwell equations -- can be derived from the in-in effective action and the effect of the medium is encoded in the electric and magnetic permeabilities $\varepsilon(\omega,|\boldsymbol{k}|)$ and $\mu(\omega,|\boldsymbol{k}|)$. Microcausality implies analyticity of the retarded Green's functions when the imaginary part of the $4$-vector $(\omega,\boldsymbol{k})$ lies in forward light cone. With appropriate assumptions about the behavior of the medium at high frequencies one derives dispersion relations, originally studied by Leontovich. In the case of dielectrics these relations, combined with the positivity of the imaginary parts, imply bounds on the low-energy values of the response, $\varepsilon(0,0)$ and $\mu(0,0)$. In particular the quantities $\varepsilon(0,0)-1$ and $\varepsilon(0,0) - 1/\mu(0,0)$ are constrained to be positive and equal to integrals over the imaginary parts of the response. We discuss various improvements of these bounds in the case of non-relativistic media and with additional assumptions about the UV behavior., Comment: 27 pages + appendices, 7 figures

The measurement of pulsar pulse times-of-arrival (ToAs) is a crucial step in detecting low-frequency gravitational waves. To determine ToAs, we can use template-matching to compare each observed pulse profile with a standard template. However, using different combinations of templates and template-matching methods (TMMs) without careful consideration may lead to inconsistent results. In pulsar timing array (PTA) experiments, distinct ToAs from the same observations can be obtained, due to the use of diverse templates and TMMs. In other words, employing diverse approaches can yield different timing results and would thus have a significant impact on subsequent gravitational wave searches. In this paper, we examine several commonly used combinations to analyze their effect on pulse ToAs. we evaluate the potential impact of template and TMM selection on thirteen typical millisecond pulsars within the European PTA. We employ pulsar timing methods, specifically the root mean square and reduced chi-square $\chi_r^2$ of the residuals of the best timing solution to assess the outcomes. Additionally, we evaluate the system-limited noise floor (SLNF) for each pulsar at various telescopes operating around 1.4~GHz using frequency-resolved templates. Our findings suggest that utilizing data-derived and smoothed templates in conjunction with the Fourier-domain with Markov-chain Monte Carlo (FDM) TMM is generally the most effective approach, though there may be exceptions that require further attention. Furthermore, we determine that pulse phase jitter noise does not significantly limit the current precision of the European PTA's timing, as jitter levels derived from other studies are much smaller than the SLNF., Comment: Accepted by A&A

Pulsar Timing Array (PTA) collaborations recently reported evidence for the presence of a gravitational wave background (GWB) in their datasets. The main candidate that is expected to produce such a GWB is the population of supermassive black hole binaries (SMBHB). Some analyses showed that the recovered signal may exhibit time-dependent properties, i.e. non-stationarity. In this paper, we propose an approximated non-stationary Gaussian process (GP) model obtained from the perturbation of stationary processes. The presented method is applied to the second data release of the European pulsar timing array to search for non-stationary features in the GWB. We analyzed the data in different time slices and showed that the inferred properties of the GWB evolve with time. We find no evidence for such non-stationary behavior and the Bayes factor in favor of the latter is $\mathcal{B}^{NS}_{S} = 1.5$. We argue that the evolution of the GWB properties most likely comes from the \mf{improvement of the observation cadence} with time and \mf{better} characterization of the noise of individual pulsars. Such non-stationary GWB could also be produced by the leakage of non-stationary features in the noise of individual pulsars or by the presence of an eccentric single source., Comment: 14 pages, 14 figures

Fine-resolution spatial patterns of water table depth (WTD) play a crucial role in shaping ecological resilience, hydrological connectivity, and anthropocentric objectives. Generally, a large-scale (e.g., continental or global) spatial map of static WTD can be simulated using either physically-based (PB) or machine learning-based (ML) models. We construct three fine-resolution (500 m) ML simulations of WTD, using the XGBoost algorithm and more than 20 million real and proxy observations of WTD, across the United States and Canada. The three ML models were constrained using known physical relations between WTD's drivers and WTD and were trained by sequentially adding real and proxy observations of WTD. We interpret the black box of our physically constrained ML models and compare it against available literature in groundwater hydrology. Through an extensive (pixel-by-pixel) evaluation, we demonstrate that our models can more accurately predict unseen real and proxy observations of WTD across most of North America's ecoregions compared to three available PB simulations of WTD. However, we still argue that large-scale WTD estimation is far from being a solved problem. We reason that due to biased observational data mainly collected from low-elevation floodplains, the misspecification of equations within physically-based models, and the over-flexibility of machine learning models, verifiably accurate simulations of WTD do not yet exist. Ultimately, we thoroughly discuss future directions that may help hydrogeologists decide how to proceed with WTD estimations, with a particular focus on the application of machine learning and the use of proxy satellite data.

The spatial scales of relativistic radio jets, probed by relativistic magneto-hydrodynamic jet launching simulations (RMHDs) and by most very-long-baseline interferometry (VLBI) observations differ by an order of magnitude. Bridging the gap between these RMHD simulations and VLBI observations requires selecting nearby active galactic nuclei (AGN), the parsec-scale region of which can be resolved. 3C 84 is a nearby bright AGN fulfilling the necessary requirements: it is launching a powerful, relativistic jet powered by a central supermassive black hole, while also being very bright. Using 22 GHz global VLBI measurements of 3C 84 we aim to study its sub-parsec region in both total intensity and linear polarisation, to explore the properties of this jet, with a linear resolution of $\sim0.1$ parsec. We test different simulation setups by altering the bulk Lorentz factor $\Gamma$ of the jet, as well as the magnetic field configuration (toroidal, poloidal, helical). We confirm the persistence of a limb brightened structure, which reaches deep into the sub-parsec region. The corresponding electric vector position angles (EVPAs) follow the bulk jet flow inside but tend to be orthogonal to it near the edges. Our state-of-the-art RMHD simulations show that this geometry is consistent with a spine-sheath model, associated with a mildly relativistic flow and a toroidal magnetic field configuration., Comment: 10 pages, 8 figures, accepted for publication in Astronomy and Astrophysics

We study single-interface solutions to a free boundary problem that couples bilinear bulk diffusion to the Stefan condition and a hysteretic flow rule for phase boundaries. We introduce a time-discrete approximation scheme and establish its convergence in the limit of vanishing step size. The main difficulty in our proof are strong microscopic oscillations which are produced by a propagating phase interface and need to be controlled on the macroscopic scale. We also present numerical simulations and discuss the link to the viscous regularization of ill-posed diffusion equations., Comment: 29 pages, several figures

We report measurements characterizing the performance of a kinetic inductance detector array designed for a wavelength of 25 microns and very low optical background level suitable for applications such as a far-infrared instrument on a cryogenically cooled space telescope. In a pulse counting mode of operation at low optical flux, the detectors can resolve individual 25-micron photons. In an integrating mode, the detectors remain photon noise limited over more than six orders of magnitude in absorbed power from 70 zW to 200 fW, with a limiting NEP of 4.6 x 10^-20 W/rtHz at 1 Hz. In addition, the detectors are highly stable with flat power spectra under optical load down to 1 mHz. Operational parameters of the detector are determined including the efficiency of conversion of the incident optical power into quasiparticles in the aluminum absorbing element and the quasiparticle self-recombination constant., Comment: 35 pages, 18 figures

Artificial Intelligence (AI) will change human work by taking over specific job tasks, but there is a debate which tasks are susceptible to automation, and whether AI will augment or replace workers and affect wages. By combining data on job tasks with a measure of AI susceptibility, we show that more highly skilled workers are more susceptible to AI automation, and that analytical non-routine tasks are at risk to be impacted by AI. Moreover, we observe that wage growth premiums for the lowest and the highest required skill level appear unrelated to AI susceptibility and that workers in occupations with many routine tasks saw higher wage growth if their work was more strongly susceptible to AI. Our findings imply that AI has the potential to affect human workers differently than canonical economic theories about the impact of technology on work these theories predict., Comment: main text 18 pages, 4 figures, 4 tables, robustness checks included

The physical link between AGN activity and the suppression of star formation in their host galaxies is one of the major open questions of AGN feedback. The Spitzer space mission revealed a subset of nearby radio galaxies with unusually bright line emission from warm ($T\ge 100$ K) H$_2$, while typical star-formation tracers were exceptionally faint or undetected. We present JWST NIRSpec and MIRI IFU observations of 3C 326 N at z=0.09 and identify 19 ro-vibrational H$_2$ emission lines that probe hot ($T\sim 1000$ K) gas as well as the rotational lines of H$_2$ 0--0 S(3), S(5), and S(6) which probe most of the $2\times 10^9$ M$_\odot$ of warm H$_2$ in this galaxy. CO band heads show a stellar component consistent with a "slow-rotator", typical of a massive $3\times10^{11}$ M$_\odot$ galaxy, and provide us with a reliable redshift of $z=0.08979\pm 0.0003$. Extended line emission shows a bipolar bubble expanding through the molecular disk at velocities of up to 380 km s$^{-1}$, delineated by several bright clumps along the Northern outer rim, potentially from gas fragmentation. Throughout the disk, the H$_2$ is very broad, FWHM ~100-1300 km s$^{-1}$, and shows dual-component Gaussian line profiles. [FeII]$\lambda$1.644 and Pa$\alpha$ follow the same morphology, however [NeIII]$\lambda$15.56 is more symmetric about the nucleus. We show that the gas, with the exception of [NeIII]$\lambda$15.56, is predominantly heated by shocks driven by the radio jet and that the accompanying line broadening is sufficient to suppress star formation. We also compare the rotational and ro-vibrational lines, finding that the latter can be a good proxy to the global morphology and kinematic properties of the former in strongly turbulent environments. This enables studies of turbulence in galaxies at intermediate and high redshifts while most rotational lines are redshifted out of the MIRI bandpass for $z$>1.5., Comment: Accepted with comments by A&A, 14 Figures, 5 Tables