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The formation time scales of quiescent galaxies can be estimated in two different ways: by their star formation history and by their chemistry. Previously, the methods yielded conflicting results, especially when considering $\alpha$-enhanced objects. This is primarily due to the time resolution limitations of very old stellar populations, which prevent accurately constraining their star formation histories. We analysed the JWST observations of the extremely massive galaxy ZF-UDS-7329 at z$\sim$3.2 and show that the higher time resolution necessary to match the chemical formation time scales using stellar population synthesis can be achieved by studying galaxies at high redshift. We compare the massive galaxy to the well-known relic galaxy NGC~1277, arguing that ZF-UDS-7329 is an early Universe example of the cores of present-day massive elliptical galaxies or, if left untouched, a relic galaxy., Comment: Accepted for publication in A&A, 5 pages, 4 figures

Direct fidelity estimation is a protocol that estimates the fidelity between an experimental quantum state and a target pure state. By measuring the expectation values of Pauli operators selected through importance sampling, the method is exponentially faster than full quantum state tomography. We propose an enhanced direct fidelity estimation protocol that uses fewer copies of the experimental state by grouping Pauli operators before the sampling process. We derive analytical bounds on the measurement cost and estimator variance, showing improvements over the standard method. Numerical simulations validate our approach, demonstrating that for 8-qubit Haar-random states, our method achieves a one-third reduction in the required number of copies and reduces variance by an order of magnitude using only local measurements. These results underscore the potential of our protocol to enhance the efficiency of fidelity estimation in current quantum devices.

We present the design and performance of a four-phased radiofrequency (RF) carpet system for ion transport in high-pressure xenon gas. The RF carpet, designed with a 160 $\mu$m pitch, is applied to the lateral collection of ions in xenon at pressures up to 600 mbar. We demonstrate transport efficiency of caesium ions across varying pressures, and compare with microscopic simulations made in the SIMION package. The novel use of an N-phased RF carpet at high pressure can achieve ion levitation and controlled lateral motion in a denser environment than is typical for RF ion transport in gases. This feature makes such carpets strong candidates for ion transport to single ion sensors envisaged for future neutrinoless double-beta decay experiments in xenon gas.

Multimode cavity optomechanics, where multiple mechanical degrees of freedom couple to optical cavity modes, provides a rich platform for exploring nonlinear dynamics and engineering complex interactions. In this work, we investigate the interplay between two mechanical modes with similar characteristics and a self-induced nonlinear modulation of intra-cavity power (self-pulsing) driven by free-carrier dispersion and thermo-optic effects in silicon. Notably, the self-pulsing dynamics adapts to the optomechanically induced perturbations from both mechanical modes, enabling simultaneous synchronous pumping and driving them into a stable state characterized by high-amplitude, self-sustained, and coherent oscillations. This result effectively overcomes the strong mode competition typically observed in modes with similar spatial distributions and frequency scales. Remarkably, this regime is achieved even when the mechanical frequencies do not satisfy a harmonic relation, leading to quasi-periodic or chaotic intra-cavity power dynamics, while the mechanical modes maintain coherent, high-amplitude oscillations. These results, supported by a numerical model that accurately predicts the dynamics of the system, open new pathways for the generation and control of multi-phonon coherent sources in chip-integrated silicon platforms.

The 2-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission aims at performing an extensive spectroscopic survey of approximately 20--30 million H$\alpha$-emitting galaxies up to about redshift two. This ambitious project seeks to elucidate the nature of dark energy by mapping the 3-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the 3-dimensional 2-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid data set, which involves millions of galaxies. Key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including kd-tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. The results indicate that the software is robust and can reliably estimate the 2-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of the Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission's timeline, highlighting the software's capability to handle large data sets efficiently., Comment: 17 pages, 13 figures, submitted to A&A

The Euclid mission is generating a vast amount of imaging data in four broadband filters at high angular resolution. This will allow the detailed study of mass, metallicity, and stellar populations across galaxies, which will constrain their formation and evolutionary pathways. Transforming the Euclid imaging for large samples of galaxies into maps of physical parameters in an efficient and reliable manner is an outstanding challenge. We investigate the power and reliability of machine learning techniques to extract the distribution of physical parameters within well-resolved galaxies. We focus on estimating stellar mass surface density, mass-averaged stellar metallicity and age. We generate noise-free, synthetic high-resolution imaging data in the Euclid photometric bands for a set of 1154 galaxies from the TNG50 cosmological simulation. The images are generated with the SKIRT radiative transfer code, taking into account the complex 3D distribution of stellar populations and interstellar dust attenuation. We use a machine learning framework to map the idealised mock observational data to the physical parameters on a pixel-by-pixel basis. We find that stellar mass surface density can be accurately recovered with a $\leq 0.130 {\rm \,dex}$ scatter. Conversely, stellar metallicity and age estimates are, as expected, less robust, but still contain significant information which originates from underlying correlations at a sub-kpc scale between stellar mass surface density and stellar population properties.

In this paper, we address the problem of manipulating multi-particle aggregates using a bimanual robotic system. Our approach enables the autonomous transport of dispersed particles through a series of shaping and pushing actions using robotically-controlled tools. Achieving this advanced manipulation capability presents two key challenges: high-level task planning and trajectory execution. For task planning, we leverage Vision Language Models (VLMs) to enable primitive actions such as tool affordance grasping and non-prehensile particle pushing. For trajectory execution, we represent the evolving particle aggregate's contour using truncated Fourier series, providing efficient parametrization of its closed shape. We adaptively compute trajectory waypoints based on group cohesion and the geometric centroid of the aggregate, accounting for its spatial distribution and collective motion. Through real-world experiments, we demonstrate the effectiveness of our methodology in actively shaping and manipulating multi-particle aggregates while maintaining high system cohesion.

Multi-modal Large Language Models (MLLMs) have achieved remarkable success by integrating visual and textual modalities. However, they incur significant computational overhead due to the large number of vision tokens processed, limiting their practicality in resource-constrained environments. We introduce Language-Guided Vision Token Pruning (LVPruning) for MLLMs, an effective yet simple method that significantly reduces the computational burden while preserving model performance. LVPruning employs cross-attention modules to compute the importance of vision tokens based on their interaction with language tokens, determining which to prune. Importantly, LVPruning can be integrated without modifying the original MLLM parameters, which makes LVPruning simple to apply or remove. Our experiments show that LVPruning can effectively reduce up to 90% of vision tokens by the middle layer of LLaVA-1.5, resulting in a 62.1% decrease in inference Tera Floating-Point Operations Per Second (TFLOPs), with an average performance loss of just 0.45% across nine multi-modal benchmarks.

Field dwarf galaxies not actively forming stars are relatively rare in the local Universe, but are present in cosmological hydrodynamical simulations. We use the TNG50 simulation to investigate their origin and find that they all result from environmental effects that have removed or reduced their gas content. Quenched field dwarfs consist of either backsplash objects ejected from a massive host or of systems that have lost their gas after crossing overdense regions such as filaments or sheets (``cosmic web stripping''). Quenched fractions rise steeply with decreasing stellar mass, with quenched systems making up roughly $\sim 15\%$ of all field dwarfs (i.e., excluding satellites) with stellar masses $10^{7}10^9\, M_{\odot}$ within {$1.5$} Mpc is applied. Of these isolated dwarfs, $\sim 6\%$ are backsplash, while the other $\sim 94\%$ have been affected by the cosmic web. Backsplash systems are more deficient in dark matter, have retained less or no gas, and have stopped forming stars earlier than cosmic web-stripped systems. The discovery of deeply isolated dwarf galaxies which were quenched relatively recently would lend observational support to the prediction that the cosmic web is capable of inducing the cessation of star formation in dwarfs., Comment: 8 Figures, submitted to ApJ

A method based on Generative Adversaria! Networks (GANs) is developed for disentangling the physical (effective temperature and gravity) and chemical (metallicity, overabundance of a-elements with respect to iron) atmospheric properties in astronomical spectra. Using a projection of the stellar spectra, commonly called latent space, in which the contribution dueto one or several main stellar physicochemical properties is minimised while others are enhanced, it was possible to maximise the information related to certain properties, which can then be extracted using artificial neural networks (ANN) as regressors with higher accuracy than a reference method based on the use of ANN trained with the original spectra. Methods. Our model utilises autoencoders, comprising two artificial neural networks: an encoder anda decoder which transform input data into a low-dimensional representation known as latent space. It also uses discriminators, which are additional neural networks aimed at transforming the traditional autoencoder training into an adversaria! approach, to disentangle or reinforce the astrophysical parameters from the latent space. The GANDALF tool is described. It was developed to define, train, and test our GAN model with a web framework to show how the disentangling algorithm works visually. It is open to the community in Github. Results. The performance of our approach for retrieving atmospheric stellar properties from spectra is demonstrated using Gaia Radial Velocity Spectrograph (RVS) data from DR3. We use a data-driven perspective and obtain very competitive values, ali within the literature errors, and with the advantage of an important dimensionality reduction of the data to be processed., Comment: 9 pages, 8 figures

Our understanding of the $\gamma$-ray sky has improved dramatically in the past decade, however, the unresolved $\gamma$-ray background (UGRB) still has a potential wealth of information about the faintest $\gamma$-ray sources pervading the Universe. Statistical cross-correlations with tracers of cosmic structure can indirectly identify the populations that most characterize the $\gamma$-ray background. In this study, we analyze the angular correlation between the $\gamma$-ray background and the matter distribution in the Universe as traced by gravitational lensing, leveraging more than a decade of observations from the Fermi-Large Area Telescope (LAT) and 3 years of data from the Dark Energy Survey (DES). We detect a correlation at signal-to-noise ratio of 8.9. Most of the statistical significance comes from large scales, demonstrating, for the first time, that a substantial portion of the UGRB aligns with the mass clustering of the Universe as traced by weak lensing. Blazars provide a plausible explanation for this signal, especially if those contributing to the correlation reside in halos of large mass ($\sim 10^{14} M_{\odot}$) and account for approximately 30-40 % of the UGRB above 10 GeV. Additionally, we observe a preference for a curved $\gamma$-ray energy spectrum, with a log-parabolic shape being favored over a power-law. We also discuss the possibility of modifications to the blazar model and the inclusion of additional $gamma$-ray sources, such as star-forming galaxies or particle dark matter., Comment: 34 pages, 15 figures

The physical and orbital parameters of Trans-Neptunian Objects (TNOs) provide valuable information about the Solar System's formation and evolution. In particular, the characterization of binaries provides insights into the formation mechanisms that may be playing a role at such large distances from the Sun. Studies show two distinct populations, and (38628) Huya occupies an intermediate position between the unequal-size binaries and those with components of roughly equal sizes. In this work, we predicted and observed three stellar occultation events by Huya. Huya and its satellite - S/2012 (38628) 1 - were detected during occultations in March 2021 and again in June 2023. Additionally, an attempt to detect Huya in February 2023 resulted in an additional single-chord detection of the secondary. A spherical body with a minimum diameter of D = 165 km can explain the three single-chord observations and provide a lower limit for the satellite size. The astrometry of Huya's system, as derived from the occultations and supplemented by observations from the Hubble Space Telescope and Keck Observatory, provided constraints on the satellite orbit and the mass of the system. Therefore, assuming the secondary is in an equatorial orbit around the primary, the limb fitting was constrained by the satellite orbit position angle. The system density, calculated by summing the most precise measurement of Huya's volume to the spherical satellite average volume, is $\rho_{1}$ = 1073 $\pm$ 66 kg m$^{-3}$. The density that the object would have assuming a Maclaurin equilibrium shape with a rotational period of 6.725 $\pm$ 0.01 hours is $\rho_{2}$ = 768 $\pm$ 42 kg m$^{-3}$. This difference rules out the Maclaurin equilibrium assumption for the main body shape., Comment: Manuscript accepted by Planetary Science Journal (PSJ)

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

Ewing's sarcoma (ES), characterized by a high density of small round blue cells without structural organization, presents a significant health concern, particularly among adolescents aged 10 to 19. Artificial intelligence-based systems for automated analysis of histopathological images are promising to contribute to an accurate diagnosis of ES. In this context, this study explores the feature extraction ability of different pre-training strategies for distinguishing ES from other soft tissue or bone sarcomas with similar morphology in digitized tissue microarrays for the first time, as far as we know. Vision-language supervision (VLS) is compared to fully-supervised ImageNet pre-training within a multiple instance learning paradigm. Our findings indicate a substantial improvement in diagnostic accuracy with the adaption of VLS using an in-domain dataset. Notably, these models not only enhance the accuracy of predicted classes but also drastically reduce the number of trainable parameters and computational costs., Comment: 11 pages, 5 figures, 2 tables. Oral presentation at KES-InMed 2024 held in Madeira, Portugal

The avoidance of water freezing is the holy grail in the cryopreservation of biological samples, food, and organs. Fast cooling rates are used to beat ice nucleation and avoid cell damage. This strategy can be enhanced by applying high pressures to decrease the nucleation rate, but the physics behind this procedure has not been fully understood yet. We perform computer experiments to investigate ice nucleation at high pressures consisting in embedding ice seeds in supercooled water. We find that the slowing down of the nucleation rate is mainly due to an increase of the ice I-water interfacial free energy with pressure. Our work also clarifies the molecular mechanism of ice nucleation for a wide pressure range. This study is not only relevant to cryopreservation, but also to water amorphization and climate change modeling., Comment: 6 pages and 3 figures

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.

We revise the role that ultraviolet divergences of quantum fields play in slow-roll inflation, and discuss the renormalization of cosmological observables from a space-time perspective, namely the angular power spectrum. We first derive an explicit expression for the multipole coefficients $C_{\ell}$ in the Sachs-Wolfe regime in terms of the two-point function of primordial perturbations. We then analyze the ultraviolet behavior, and point out that the standard result in the literature is equivalent to a renormalization of $C_{\ell}$ at zero ``adiabatic'' order. We further argue that renormalization at second ``adiabatic'' order may be more appropriate from the viewpoint of standard quantum field theory. This may change significantly the predictions for $C_{\ell}$, while maintaining scale invariance., Comment: Proceedings of the "Spanish Relativity Meeting (ERE 2014): almost 100 years after Einstein's revolution"

A key processing step in ground-based astronomy involves combining multiple noisy and blurry exposures to produce an image of the night sky with improved signal-to-noise ratio. Typically, this is achieved via image coaddition, and can be undertaken such that the resulting night sky image has enhanced spatial resolution. Yet, this task remains a formidable challenge despite decades of advancements. In this paper, we introduce ImageMM: a new framework based on the majorization-minimization algorithm for joint multi-frame astronomical image restoration and super-resolution. ImageMM uses multiple registered astronomical exposures to produce a non-parametric latent image of the night sky, prior to the atmosphere's impact on the observed exposures. Our framework also features a novel variational approach to compute refined point-spread functions of arbitrary resolution for the restoration and super-resolution procedure. Our algorithms, implemented in TensorFlow, leverage Graphics Processing Unit acceleration to produce latent images in near real-time, even when processing high-resolution exposures. We tested ImageMM on Hyper Suprime-Cam (HSC) exposures, which are a precursor for upcoming imaging data from the Rubin Observatory. The results are encouraging: ImageMM produces sharp latent images, in which spatial features of bright sources are revealed in unprecedented detail (e.g. the structure of spiral galaxies), and where faint sources that are usually indistinguishable from the noisy sky-background also become discernible, thus pushing the detection limits. Moreover, aperture photometry performed on the HSC pipeline coadd and ImageMM's latent images yielded consistent source detection and flux measurements, thereby demonstrating ImageMM's suitability for cutting-edge photometric studies with state-of-the-art astronomical imaging data.

We report, for the first time, the detection of a sample of quenched and isolated dwarf galaxies (with 8.9 $<$ log(M$_{\rm \star}$/M$_{\rm \odot}$) $<$ 9.5) in the least dense regions of the cosmic web, including voids, filaments, and walls. These dwarfs have no neighbouring galaxy within 1.0~Mpc in projected distance. Based on the full spectral fitting of their central spectra using Sloan Digital Sky Survey data, these galaxies are gas-deprived, exhibit stellar mass assembly very similar to dwarfs in the central regions of galaxy clusters, and have experienced no significant star formation in the past 2 Gyr. Additionally, analysis of r-band images from the Dark Energy Camera Legacy Survey showed that these dwarf galaxies host a central Nuclear Star Cluster (NSC). Detecting quenched, isolated dwarf galaxies in cosmic voids indicates that environmental factors are not the sole drivers of their quenching. Internal mechanisms, such as feedback from in-situ star formation, also contributing to the NSC formation, black holes, or variations in conditions during their formation, offer potential explanations for star formation suppression in these galaxies. These findings highlight the need for a significant revision in our understanding of baryonic physics, particularly concerning the formation and evolution of low-mass galaxies., Comment: 9 pages, 5 figures, accepted as a Letter to the Editor in Astronomy & Astrophysics

The ability to automatically encircle boundaries with mobile robots is crucial for tasks such as border tracking and object enclosing. Previous research has primarily focused on regular boundaries, often assuming that their geometric equations are known in advance, which is not often the case in practice. In this paper, we investigate a more general case and propose an algorithm that addresses geometric irregularities of boundaries without requiring prior knowledge of their analytical expressions. To achieve this, we develop a Fourier-based curve fitting method for boundary approximation using sampled points, enabling parametric characterization of general 2-D boundaries. This approach allows star-shaped boundaries to be fitted into polar-angle-based parametric curves, while boundaries of other shapes are handled through decomposition. Then, we design a vector field (VF) to achieve the encirclement of the parameterized boundary, wherein a polar radius error is introduced to measure the robot's ``distance'' to the boundary. The controller is finally synthesized using a control barrier function and quadratic programming to mediate some potentially conflicting specifications: boundary encirclement, obstacle avoidance, and limited actuation. In this manner, the VF-guided reference control not only guides the boundary encircling action, but can also be minimally modified to satisfy obstacle avoidance and input saturation constraints. Simulations and experiments are presented to verify the performance of our new method, which can be applied to mobile robots to perform practical tasks such as cleaning chemical spills and environment monitoring., Comment: 11 pages, submitted to IEEE/ASME Transactions on Mechatronics

Antimicrobial resistance (AMR) is a global threat and combating its spread is of paramount importance. AMR often results from a cooperative behaviour with shared protection against drugs. Microbial communities generally evolve in volatile environments and spatial structures. Migration, fluctuations, and environmental variability thus have significant impacts on AMR, whose maintenance in static environments is generally promoted by migration. Here, we demonstrate that this picture changes dramatically in time-fluctuating spatially structured environments. To this end, we consider a two-dimensional metapopulation model consisting of demes in which drug-resistant and sensitive cells evolve in a time-changing environment in the presence of a toxin against which protection can be shared. Cells migrate between neighbouring demes and hence connect them. When the environment varies neither too quickly nor too slowly, the dynamics is characterised by bottlenecks causing fluctuation-driven local extinctions, a mechanism countered by migration that rescues AMR. Through simulations and mathematical analysis, we investigate how migration and environmental variability influence the probability of resistance eradication. We determine the near-optimal conditions for the fluctuation-driven AMR eradication, and show that slow but non-zero migration speeds up the clearance of resistance and can enhance its eradication probability. We discuss our study's impact on laboratory-controlled experiments., Comment: 24+9 pages, 8+3 figures, 1 table. Simulation data and codes for all figures, as well as all 5 Supplementary Movies, are electronically available from the Open Science Framework (OSF) repository. DOI: https://doi.org/10.17605/OSF.IO/EPB28

Context: The C-19 stellar stream is the most metal-poor stream known to date. While its width and velocity dispersion indicate a dwarf galaxy origin, its metallicity spread and abundance patterns are more similar to those of globular clusters (GCs). If it is indeed of GC origin, its extremely low metallicity ([Fe/H]=-3.4, estimated from giant stars) implies that these stellar systems can form out of gas that is as extremely poor in metals as this. Previously, only giant stream stars were observed spectroscopically, although the majority of stream stars are unevolved stars. Aims: We pushed the spectroscopic observations to the subgiant branch stars ($G\approx 20$) in order to consolidate the chemical and dynamical properties of C-19. Methods: We used the high-efficiency spectrograph X-shooter fed by the ESO 8.2 m VLT telescope to observe 15 candidate subgiant C-19 members. The spectra were used to measure radial velocities and to determine chemical abundances using the \mygi\ code. Results; We developed a likelihood model that takes metallicity and radial velocities into account. We conclude that 12 stars are likely members of C-19, while 3 stars (S05, S12, and S13) are likely contaminants. When these 3 stars are excluded, our model implies a mean metallicity $\rm \langle [Fe/H]\rangle = -3.1\pm 0.1$, the mean radial velocity is $\langle v_r\rangle = -192\pm3$ kms$^{-1}$, and the velocity dispersion is $\sigma_{vr} = 5.9^{+3.6}_{-5.9}$ kms$^{-1}$. This all agrees within errors with previous studies. The A(Mg) of a sample of 15 C-19 members, including 6 giant stars, shows a standard deviation of 0.44 dex, and the mean uncertainty on Mg is 0.25 dex. Conclusions: Our preferred interpretation of the current data is that C-19 is a disrupted GC. We cannot completely rule out the possibility that the GC could have belonged to a dwarf galaxy that contained more metal-rich stars, however. This scenario would explain the radial velocity members at higher metallicity, as well as the width and velocity dispersion of the stream. In either case, a GC formed out of gas as poor in metals as these stars seems necessary to explain the existence of C-19. The possibility that no GC was associated with C-19 cannot be ruled out either., Comment: Astronomy & Astrophysics - A&A, In press

We study ultrafilters from the perspective of the algebra in the \v{C}ech-Stone compactification of the natural numbers, and idempotent elements therein. The first two results that we prove establish that, if $p$ is a Q-point (resp. a selective ultrafilter) and $\mathscr F^p$ (resp. $\mathscr G^p$) is the smallest family containing $p$ and closed under iterated sums (resp. closed under Blass--Frol\'{\i}k sums and Rudin--Keisler images), then $\mathscr F^p$ (resp. $\mathscr G^p$) contains no idempotent elements. The second of these results about a selective ultrafilter has the following interesting consequence: assuming a conjecture of Blass, in models of the form $\mathbf{L}(\mathbb R)[p]$ where $\mathbf{L}(\mathbb R)$ is a Solovay model (of $\mathsf{ZF}$ without choice) and $p$ is a selective ultrafilter, there are no idempotent elements. In particular, the theory $\mathsf{ZF}$ plus the existence of a nonprincipal ultrafilter on $\omega$ does not imply the existence of idempotent ultrafilters, which answers a question of DiNasso and Tachtsis (Proc. Amer. Math. Soc. 146, 397-411). Following the line of obtaining independence results in $\mathsf{ZF}$, we finish the paper by proving that $\mathsf{ZF}$ plus "every additive filter can be extended to an idempotent ultrafilter" does not imply the Ultrafilter Theorem over $\mathbb R$, answering another question of DiNasso and Tachtsis from the same paper., Comment: 27 pages

The prominence of artificial intelligence and machine learning in everyday life has led to efforts to foster AI literacy for all K-12 students. In this paper, we review how Hour of Code activities engage with the five big ideas of AI, in particular with machine learning and societal impact. We found that a large majority of activities focus on perception and machine learning, with little attention paid to representation and other topics. A surprising finding was the increased attention paid to critical aspects of computing. However, we also observed a limited engagement with hands-on activities. In the discussion, we address how future introductory activities could be designed to offer a broader array of topics, including the development of tools to introduce novices to artificial intelligence and machine learning and the design of more unplugged and collaborative activities.

Considered a pair of random lifetimes whose dependence is described by a Time Transformed Exponential model, we provide analytical expressions for the distribution of their sum. These expressions are obtained by using a representation of the joint distribution in terms of multivariate distortions, which is an alternative approach to the classical copula representation. Since this approach allows to obtain conditional distributions and their inverses in simple form, then it is also shown how it can be used to predict the value of the sum from the value of one of the variables (or vice versa) by using quantile regression techniques.

The coherent systems are basic concepts in reliability theory and survival analysis. They contain as particular cases the popular series, parallel and $k$-ou-of-$n$ systems (order statistics). Many results have been obtained for them by assuming that the component lifetimes are independent. In many practical cases, this assumption is unrealistic. In this paper we study them by assuming a Time Transformed Exponential (TTE) model for the joint distribution of the component lifetimes. This model is equivalent to the frailty model which assumes that they are conditionally independent given a common risk parameter (which represents the common environment risk). Under this model, we obtain explicit expressions for the system reliability functions and comparison results for the main stochastic orders. The system residual lifetime (under different assumptions) is studied as well.

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3$\times$2pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining $\Lambda$CDM parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure $\Omega_\mathrm{m}=0.300\pm0.017$ and $\sigma_8=0.797\pm0.026$. Compared to constraints from Planck primary CMB anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 ($1.2\sigma$) for the two-parameter difference. We further obtain $S_8\equiv\sigma_8(\Omega_\mathrm{m}/0.3)^{0.5}=0.796\pm0.013$ which is lower than the Planck measurement at the $1.6\sigma$ level. The combined SPT cluster, DES 3$\times$2pt, and Planck datasets mildly prefer a non-zero positive neutrino mass, with a 95% upper limit $\sum m_\nu<0.25~\mathrm{eV}$ on the sum of neutrino masses. Assuming a $w$CDM model, we constrain the dark energy equation of state parameter $w=-1.15^{+0.23}_{-0.17}$ and when combining with Planck primary CMB anisotropies, we recover $w=-1.20^{+0.15}_{-0.09}$, a $1.7\sigma$ difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology., Comment: Submitted to Phys. Rev. D

Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However, accurately predicting surgical outcomes remains a significant challenge. This study introduces a novel biomarker derived from brain connectivity changes caused by TLE surgery, analyzed using hyperbolic graph embeddings, to predict surgical success. Using structural and diffusion magnetic resonance imaging (MRI) data from 51 patients, we examined differences in structural connectivity networks associated to surgical outcomes. Our approach uniquely leveraged hyperbolic Poincare disk embeddings of pre- and post-surgery brain networks, successfully distinguishing patients with favorable outcomes from those with poor outcomes. Notably, the method identified regions in the contralateral hemisphere relative to the epileptogenic zone, whose connectivity patterns emerged as a potential biomarker for favorable surgical outcomes. To validate the model, we employed a leave-one-out cross-validation approach, achieving an area under the curve (AUC) of 0.86 and a balanced accuracy of 0.81. These results underscore the predictive capability of our model and its effectiveness in individual outcome forecasting based on structural network changes. Our findings highlight the use of non-Euclidean hyperbolic graph embeddings to analyze brain networks, offering deeper insights into connectivity alterations in epilepsy, and advancing personalized prediction of surgical outcomes in TLE.

In this article we briefly review the adiabatic renormalization program for spin 1/2 fields in expanding universes. We introduce the method and provide explicit expressions for the renormalized vacuum expectation value of the stress-energy tensor. Then, we discuss its application to some cosmological scenario of physical interest. We end up sketching out the proof that adiabatic and DeWitt-Schwinger point-splitting schemes provide the same renormalized expectation values of the stress-energy tensor for Dirac fields., Comment: Proceedings of the 14th Marcel Grossmann Meeting, 2816-2821 (2017)

While there is widespread interest in supporting young people to critically evaluate machine learning-powered systems, there is little research on how we can support them in inquiring about how these systems work and what their limitations and implications may be. Outside of K-12 education, an effective strategy in evaluating black-boxed systems is algorithm auditing-a method for understanding algorithmic systems' opaque inner workings and external impacts from the outside in. In this paper, we review how expert researchers conduct algorithm audits and how end users engage in auditing practices to propose five steps that, when incorporated into learning activities, can support young people in auditing algorithms. We present a case study of a team of teenagers engaging with each step during an out-of-school workshop in which they audited peer-designed generative AI TikTok filters. We discuss the kind of scaffolds we provided to support youth in algorithm auditing and directions and challenges for integrating algorithm auditing into classroom activities. This paper contributes: (a) a conceptualization of five steps to scaffold algorithm auditing learning activities, and (b) examples of how youth engaged with each step during our pilot study.

The ability to wield tools was once considered exclusive to human intelligence, but it's now known that many other animals, like crows, possess this capability. Yet, robotic systems still fall short of matching biological dexterity. In this paper, we investigate the use of Large Language Models (LLMs), tool affordances, and object manoeuvrability for non-prehensile tool-based manipulation tasks. Our novel method leverages LLMs based on scene information and natural language instructions to enable symbolic task planning for tool-object manipulation. This approach allows the system to convert the human language sentence into a sequence of feasible motion functions. We have developed a novel manoeuvrability-driven controller using a new tool affordance model derived from visual feedback. This controller helps guide the robot's tool utilization and manipulation actions, even within confined areas, using a stepping incremental approach. The proposed methodology is evaluated with experiments to prove its effectiveness under various manipulation scenarios.

Strong degeneracy exists between some modified gravity (MG) models and massive neutrinos because the enhanced structure growth produced by modified gravity can be suppressed due to the free-streaming massive neutrinos. Previous works showed this degeneracy can be broken with non-Gaussian or velocity information. Therefore in this work, we focus on the large-scale structure (LSS) in redshift space and investigate for the first time the possibility of using the non-Gaussian information and velocity information captured by the 3D scalar Minkowski functionals (MFs) and the 3D Minkowski tensors (MTs) to break this degeneracy. Based on the Quijote and Quijote-MG simulations, we find the imprints on redshift space LSS left by the Hu-Sawicki $f(R)$ gravity can be discriminated from those left by massive neutrinos with these statistics. With the Fisher information formalism, we first show how the MTs extract information with their perpendicular and parallel elements for both low- and high-density regions; then we compare constraints from the power spectrum monopole and MFs in real space with those in redshift space, and investigate how the constraining power is further improved with anisotropies captured by the quadrupole and hexadecapole of the power spectrum and the MTs; finally, we combine the power spectrum multipoles with MFs plus MTs and find the constraints from the power spectrum multipoles on $\Omega_{\mathrm{m}}, h, \sigma_8$, $M_\nu$, and $f_{R_0}$ can be improved, because they are complemented with non-Gaussian information, by a factor of 3.4, 3.0, 3.3, 3.3, and 1.9 on small scales ($k_{\rm{max}}=0.5~h\rm{Mpc}^{-1},\ R_G=5~h^{-1}\rm{Mpc}$), and 2.8, 2.2, 3.4, 3.4, and 1.5 on large scales ($k_{\rm{max}}=0.25~h\rm{Mpc}^{-1},\ R_G=10~h^{-1}\rm{Mpc}$)., Comment: 41 pages, 15 figures, submitted to JCAP

The circumgalactic medium (CGM) around massive galaxies plays a crucial role in regulating star formation and feedback. Using the CAMELS simulation suite, we develop emulators for the X-ray surface brightness profile and the X-ray luminosity--stellar mass scaling relation to investigate how stellar and AGN feedback shape the X-ray properties of the hot CGM. Our analysis shows that at CGM scales ($10^{12} \lesssim M_{\rm halo}/M_\odot \lesssim 10^{13}$, $10\lesssim r/{\rm kpc} \lesssim 400$), stellar feedback more significantly impacts the X-ray properties than AGN feedback within the parameters studied. Comparing the emulators to recent eROSITA All-Sky Survey observations, it was found that stronger feedback than currently implemented in the IllustrisTNG, SIMBA, and Astrid simulations is required to match observed CGM properties. However, adopting these enhanced feedback parameters causes deviations in the stellar-mass-halo-mass relations from observational constraints below the group mass scale. This tension suggests possible unaccounted systematics in X-ray CGM observations or inadequacies in the feedback models of cosmological simulations., Comment: 13 pages, 6 figures, submitted to ApJ

Purpose: The purpose of this paper is to examine how a clinical interview protocol with failure artifact scenarios can capture changes in high school students' explanations of troubleshooting processes in physical computing activities. We focus on physical computing since finding and fixing hardware and software bugs is a highly contextual practice that involves multiple interconnected domains and skills. Approach: We developed and piloted a "failure artifact scenarios" clinical interview protocol. Youth were presented with buggy physical computing projects over video calls and asked for suggestions on how to fix them without having access to the actual project or its code. We applied this clinical interview protocol before and after an eight-week-long physical computing (more specifically, electronic textiles) unit. We analyzed matching pre- and post-interviews from 18 students at four different schools. Findings: Our findings demonstrate how the protocol can capture change in students' thinking about troubleshooting by eliciting students' explanations of specificity of domain knowledge of problems, multimodality of physical computing, iterative testing of failure artifact scenarios, and concreteness of troubleshooting and problem solving processes. Originality: Beyond tests and surveys used to assess debugging, which traditionally focus on correctness or student beliefs, our "failure artifact scenarios" clinical interview protocol reveals student troubleshooting-related thinking processes when encountering buggy projects. As an assessment tool, it may be useful to evaluate the change and development of students' abilities over time., Comment: arXiv admin note: text overlap with arXiv:2311.17212

Graph Neural Networks (GNNs) have emerged as a promising tool to handle data exhibiting an irregular structure. However, most GNN architectures perform well on homophilic datasets, where the labels of neighboring nodes are likely to be the same. In recent years, an increasing body of work has been devoted to the development of GNN architectures for heterophilic datasets, where labels do not exhibit this low-pass behavior. In this work, we create a new graph in which nodes are connected if they share structural characteristics, meaning a higher chance of sharing their labels, and then use this new graph in the GNN architecture. To do this, we compute the k-nearest neighbors graph according to distances between structural features, which are either (i) role-based, such as degree, or (ii) global, such as centrality measures. Experiments show that the labels are smoother in this newly defined graph and that the performance of GNN architectures improves when using this alternative structure., Comment: Presented as a conference paper in the Asilomar Conference on Signals, Systems, and Computers 2024

The adiabatic regularization method is likely the most direct and intuitive renormalization scheme for FLRW cosmologies. The method requires one to start with a nonvanishing mass, but massless theories can be studied by taking the massless limit at the end of the calculations. For spin-$1$, however, this limit changes the number of degrees of freedom, so it cannot be performed directly. In this work, we show a direct approach that begins with the canonical quantization of the physical degrees of freedom of a massive Proca field. We give the details of the construction and show that, in the massless limit, the renormalized stress-energy tensor of the Proca field is closely related to that of a minimally coupled scalar field. For completeness and pedagogical purposes, we also include a brief orientation to the adiabatic method for scalar fields. The construction of the adiabatic subtractions in momentum space is compared with that of the BPHZ method for renormalizing Feynman loop integrals., Comment: Accepted to appear in the Proceedings of the 17th Marcel Grossmann Meeting (MG17)

Tidal disruption events (TDEs) of giant stars by supermassive black holes (SMBH) differ significantly from those of main sequence ones. Most (all for SMBH of more than a~ few times 10^5 m_\odot) giant-TDEs are partial: only a fraction of the envelope is torn apart. The dense stellar core and the rest of the envelope remain intact. In this work, we explore, using the stellar evolution code MESA, the fate of the remnants. We find that after a short period, comparable to the thermal time scale, the remnant returns to a giant structure with a radius comparable to the progenitor giant one, a slightly larger luminosity (as compared with a regular giant with the same mass), and a comparable lifetime until it collapses to a white dwarf. If such a giant with a mass less than approx 0.9 m_\odot is discovered, it can be identified as an outlier - a giant that is too light for the current age of the Universe. If the remnant orbit is not perturbed significantly during the encounter, the remnant will undergo successive partial tidal disruptions until its mass is $0.6-0.7 m_\odot$. We expect a few dozen to a few hundred such remnants in the Galactic nucleus.

In this article, we describe the components and procedures for building a drone ready for networking experimentation. In particular, our drone design includes multiple technologies and elements such as 4G/5G connectivity for real-time data transmission, a 360-degree camera for immersive vision and AR/VR, precise GPS for navigation, and a powerful Linux-based system with GPU for computer vision experiments and applications. Component selection and assembly techniques are included, along with software integration for a smooth, seamless operation of advanced edge applications.

Flat elastic sheets tend to display wrinkles and folds. From pieces of clothing down to two-dimensional crystals, these corrugations appear in response to strain generated by sheet compression or stretching, thermal or mechanical mismatch with other elastic layers, or surface tension. Extensively studied in metals, polymers and, more recently, in van der Waals exfoliated layers, with the advent of thin single crystal freestanding films of complex oxides, researchers are now paying attention to novel microstructural effects induced by bending ferroelectric-ferroelastics, where polarization is strongly coupled to lattice deformation. Here we show that wrinkle undulations in BaTiO3 sheets bonded to a viscoelastic substrate transform into a buckle delamination geometry when transferred onto a rigid substrate. Using spatially resolved techniques at different scales (Raman, scanning probe and electron microscopy), we show how these delaminations in the free BaTiO3 sheets display a self-organization of ferroelastic domains along the buckle profile that strongly differs from the more studied sinusoidal wrinkle geometry. Moreover, we disclose the hierarchical distribution of a secondary set of domains induced by the misalignment of these folding structures from the preferred in-plane crystallographic orientations. Our results disclose the relevance of the morphology and orientation of buckling instabilities in ferroelectric free sheets, for the stabilization of different domain structures, pointing to new routes for domain engineering of ferroelectrics in flexible oxide sheets.

The contribution to pushing the boundaries of knowledge is a critical metric for evaluating the research performance of countries and institutions, which in many cases is not revealed by common bibliometric indicators. The Rk-index was specifically designed to assess such contributions, and the Rn-index is a variant that corrects the weakness of the Rk-index, particularly in the evaluation of countries that produce a high proportion of global advancements. This is the case of the USA and China in many technological fields. Additionally, the Rn-index is simple to calculate and understand, as it involves only summing the ratios between the local and global ranks of papers, ordered by their citation count. Moreover, the Rn-index may also be fractionally counted., Comment: 6 pages; 2 figures; 4 tables