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This paper addresses the problems of conditional variance estimation and confidence interval construction in nonparametric regression using dense networks with the Rectified Linear Unit (ReLU) activation function. We present a residual-based framework for conditional variance estimation, deriving nonasymptotic bounds for variance estimation under both heteroscedastic and homoscedastic settings. We relax the sub-Gaussian noise assumption, allowing the proposed bounds to accommodate sub-Exponential noise and beyond. Building on this, for a ReLU neural network estimator, we derive non-asymptotic bounds for both its conditional mean and variance estimation, representing the first result for variance estimation using ReLU networks. Furthermore, we develop a ReLU network based robust bootstrap procedure (Efron, 1992) for constructing confidence intervals for the true mean that comes with a theoretical guarantee on the coverage, providing a significant advancement in uncertainty quantification and the construction of reliable confidence intervals in deep learning settings.

In this paper, we focus on fully connected deep neural networks utilizing the Rectified Linear Unit (ReLU) activation function for nonparametric estimation. We derive non-asymptotic bounds that lead to convergence rates, addressing both temporal and spatial dependence in the observed measurements. By accounting for dependencies across time and space, our models better reflect the complexities of real-world data, enhancing both predictive performance and theoretical robustness. We also tackle the curse of dimensionality by modeling the data on a manifold, exploring the intrinsic dimensionality of high-dimensional data. We broaden existing theoretical findings of temporal-spatial analysis by applying them to neural networks in more general contexts and demonstrate that our proof techniques are effective for models with short-range dependence. Our empirical simulations across various synthetic response functions underscore the superior performance of our method, outperforming established approaches in the existing literature. These findings provide valuable insights into the strong capabilities of dense neural networks (Dense NN) for temporal-spatial modeling across a broad range of function classes.

Stopword removal is a critical stage in many Machine Learning methods but often receives little consideration, it interferes with the model visualizations and disrupts user confidence. Inappropriately chosen or hastily omitted stopwords not only lead to suboptimal performance but also significantly affect the quality of models, thus reducing the willingness of practitioners and stakeholders to rely on the output visualizations. This paper proposes a novel extraction method that provides a corpus-specific probabilistic estimation of stopword likelihood and an interactive visualization system to support their analysis. We evaluated our approach and interface using real-world data, a commonly used Machine Learning method (Topic Modelling), and a comprehensive qualitative experiment probing user confidence. The results of our work show that our system increases user confidence in the credibility of topic models by (1) returning reasonable probabilities, (2) generating an appropriate and representative extension of common stopword lists, and (3) providing an adjustable threshold for estimating and analyzing stopwords visually. Finally, we discuss insights, recommendations, and best practices to support practitioners while improving the output of Machine Learning methods and topic model visualizations with robust stopword analysis and removal.

GX 339$-$4 is one of the prototypical black hole X-ray transients, exhibiting recurrent outbursts that allow detailed studies of black hole accretion and ejection phenomena. In this work we present four epochs of optical and near-infrared spectroscopy obtained with X-shooter at the Very Large Telescope. The dataset includes two hard state spectra, collected during the 2013 and 2015 outbursts, and two soft state spectra observed during the 2021 outburst. Strong Balmer, Paschen, He I and He II emission lines are consistently observed in all spectra, while Brackett transitions and the Bowen blend are only prominent in the soft state. Although P-Cygni profiles are not identified, the presence of wind signatures, such as extended emission wings, flat-top and asymmetric red-skewed profiles, is consistently observed through most emission lines, suggesting the presence of wind-type ejecta. These features are particularly evident in the hard state, but they are also observed in the soft state, especially in the near-infrared. This strengthens the case for state-independent winds in black hole transients and increases the evidence for wind signatures in low-to-intermediate orbital inclination systems. We also study the spectral energy distribution, which provides evidence for the presence of synchrotron emission during the hard state. The jet significantly affects the near-infrared continuum, greatly diluting the emission features produced in the accretion flow. The simultaneous identification of both jet and wind signatures during the hard state reinforces the idea of a complex outflow scenario, in which different types of ejecta coexist., Comment: Accepted for publication in A&A

The assimilation and prediction of phase-resolved surface gravity waves are critical challenges in ocean science and engineering. Potential flow theory (PFT) has been widely employed to develop wave models and numerical techniques for wave prediction. However, traditional wave prediction methods are often limited. For example, most simplified wave models have a limited ability to capture strong wave nonlinearity, while fully nonlinear PFT solvers often fail to meet the speed requirements of engineering applications. This computational inefficiency also hinders the development of effective data assimilation techniques, which are required to reconstruct spatial wave information from sparse measurements to initialize the wave prediction. To address these challenges, we propose a novel solver method that leverages physics-informed neural networks (PINNs) that parameterize PFT solutions as neural networks. This provides a computationally inexpensive way to assimilate and predict wave data. The proposed PINN framework is validated through comparisons with analytical linear PFT solutions and experimental data collected in a laboratory wave flume. The results demonstrate that our approach accurately captures and predicts irregular, nonlinear, and dispersive wave surface dynamics. Moreover, the PINN can infer the fully nonlinear velocity potential throughout the entire fluid volume solely from surface elevation measurements, enabling the calculation of fluid velocities that are difficult to measure experimentally., Comment: 22 pages, 12 Figures, preprint

Data from the Euclid space telescope will enable cosmic shear measurements with very small statistical errors, requiring corresponding systematic error control level. A common approach to correct for shear biases involves calibrating shape measurement methods using image simulations with known input shear. Given their high resolution, Hubble Space Telescope (HST) galaxies can, in principle, be utilised to emulate Euclid observations. In this work, we employ a GalSim-based testing environment to investigate whether uncertainties in the HST point spread function (PSF) model or in data processing techniques introduce significant biases in weak-lensing (WL) shear calibration. We used single S\'ersic galaxy models to simulate both HST and Euclid observations. We then `Euclidised' our HST simulations and compared the results with the directly simulated Euclid-like images. For this comparison, we utilised a moment-based shape measurement algorithm and galaxy model fits. Through the Euclidisation procedure, we effectively reduced the residual multiplicative biases in shear measurements to sub-percent levels. This achievement was made possible by employing either the native pixel scales of the instruments, utilising the Lanczos15 interpolation kernel, correcting for noise correlations, and ensuring consistent galaxy signal-to-noise ratios between simulation branches. However, the Euclidisation procedure requires further analysis on the impact of the correlated noise, to estimate calibration bias. Additionally, we conducted an in-depth analysis of the accuracy of TinyTim HST PSF models using star fields observed in the F606W and F814W filters. We observe that F606W images exhibit a broader scatter in the recovered best-fit focus, compared to those in the F814W filter., Comment: Accepted by A&A. 23 pages, 20 figures, Euclid pre-launch key paper

We present a simulation-based method to explore the optimum tomographic redshift binning strategy for 3x2pt analyses with Euclid, focusing on the expected configuration of its first major data release (DR1). To do this, we 1) simulate a Euclid-like observation and generate mock shear catalogues from multiple realisations of the 3x2pt fields on the sky, and 2) measure the 3x2pt Pseudo-Cl power spectra for a given tomographic configuration and derive the constraints that they place on the standard dark energy equation of state parameters (w0, wa). For a simulation including Gaussian-distributed photometric redshift uncertainty and shape noise under a LambdaCDM cosmology, we find that bins equipopulated with galaxies yield the best constraints on (w0, wa) for an analysis of the full 3x2pt signal, or the angular clustering component only. For the cosmic shear component, the optimum (w0, wa) constraints are achieved by bins equally spaced in fiducial comoving distance. However, the advantage with respect to alternative binning choices is only a few percent in the size of the $1\,\sigma\,$(w0, wa) contour, and we conclude that the cosmic shear is relatively insensitive to the binning methodology. We find that the information gain extracted on (w0, wa) for any 3x2pt component starts to saturate at $\gtrsim$ 7-8 bins. Any marginal gains resulting from a greater number of bins is likely to be limited by additional uncertainties present in a real measurement, and the increasing demand for accuracy of the covariance matrix. Finally, we consider a 5% contamination from catastrophic photometric redshift outliers and find that, if these errors are not mitigated in the analysis, the bias induced in the 3x2pt signal for 10 equipopulated bins results in dark energy constraints that are inconsistent with the fiducial LambdaCDM cosmology at $>5\,\sigma$., Comment: Euclid Consortium paper. 28 pages, 17 figures. For submission to A&A

The CIELO project introduces a novel set of chemo-dynamical zoom-in simulations designed to simultaneously resolve galaxies and their nearby environments. The initial conditions include a diverse range of cosmic structures, such as local groups, filaments, voids, and walls, allowing for a detailed exploration of galaxies within the broader context of the cosmic web. This study presents the initial conditions and characterizes the global properties of CIELO galaxies and their environments. It focuses on galaxies with stellar masses ranging from log [8,11] solar masses and examines key scaling relations, including the mass-size relation, the Tully-Fisher relation, and the mass-metallicity relation for both stars and star-forming gas. The DisPerSe algorithm was used to determine the positions of CIELO galaxies within the cosmic web, with a specific focus on the Pehuen haloes. The selection of local group volumes was guided by criteria based on the relative positions and velocities of the two primary galaxies. The Pehuen regions were chosen to map walls, filaments, and voids. Synthetic images in the SDSS i, r, and g bands were generated using the SKIRT radiative transfer code. Additionally, a dynamical decomposition was performed to classify galaxy morphologies into bulge, disc, and stellar halo components (abridged)., Comment: 13 pages, 12 figures, submitted. Comments are welcomed

The ESA Euclid mission will survey more than 14,000 deg$^2$ of the sky in visible and near-infrared wavelengths, mapping the extra-galactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 deg from the ecliptic, it should allow for the detection of more than about $10^5$ Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1-10 arcsec/h, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on Sourcextractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class., Comment: Accepted for publication on Astronomy and Astrophysics. 15 Pages, 11 Figures

In this work, we present a detailed procedure of computer implementation of the laws of refraction and reflection on an arbitrary surface with rotational symmetry with respect to the propagation axis. The goal is to facilitate the understanding and application of these physical principles in a computational context. This enables students and instructors alike to develop simulations and interactive applications that faithfully replicate the behavior of light and sound propagating in a diversity of media separated by arbitrary surfaces. In particular it can help to explore freeform optics. Additionally, we include a practical example demonstrating these implementations using either Matlab or open-source Octave programming language., Comment: Article accepted for publication in Revista Mexicana de F\'isica E

We present a detailed study of SN 2024ahr, a hydrogen-poor superluminous supernova (SLSN-I), for which we determine a redshift of $z=0.0861$. SN 2024ahr has a peak absolute magnitude of $M_g\approx M_r\approx -21$ mag, rest-frame rise and decline times (50$\%$ of peak) of about 40 and 80 days, respectively, and typical spectroscopic evolution in the optical band. Similarly, modeling of the UV/optical light curves with a magnetar spin-down engine leads to typical parameters: an initial spin period of $\approx 3.3$ ms, a magnetic field strength of $\approx 6\times 10^{13}$ G, and an ejecta mass of $\approx 9.5$ M$_\odot$. Due to its relatively low redshift we obtained a high signal-to-noise ratio near-IR spectrum about 43 rest-frame days post-peak to search for the presence of helium. We do not detect any significant feature at the location of the He I $\,\lambda 2.058$ $\mu$m feature, and place a conservative upper limit of $\sim 0.05$ M$_\odot$ on the mass of helium in the outer ejecta. We detect broad features of Mg I $\,\lambda 1.575$ $\mu$m and a blend of Co II $\,\lambda 2.126$ $\mu$m and Mg II, $\lambda 2.136$ $\mu$m, which are typical of Type Ic SNe, but with higher velocities. Examining the sample of SLSNe-I with NIR spectroscopy, we find that, unlike SN 2024ahr, these events are generally peculiar. This highlights the need for a large sample of prototypical SLSNe-I with NIR spectroscopy to constrain the fraction of progenitors with helium (Ib-like) and without helium (Ic-like) at the time of the explosion, and hence the evolutionary path(s) leading to the rare outcome of SLSNe-I., Comment: 20 pages, 7 figures

Blazars are often observed to flare across multiple wavelengths. Orphan flares from blazars have been only detected a few times, providing an opportunity to understand the structure of the jet in the accreting system. We report a remarkable orphan X-ray flare from a blazar candidate EP240709a, detected by Einstein Probe (EP) in July 2024. The multi-band spectral properties and variability support EP240709a as a high-energy peaked BL Lacertae-type object. The flux in 0.5-10 keV increases by at least 28 times to the value of low state in 2020, with non-detection of remarkable flaring in other bands during the same period. EP240709a exhibits the harder-when-brighter tendency in the X-ray band during the orphan flare, while its infrared-optical spectra are featureless. We employ one-zone and two-zone leptonic synchrotron self-Compton models to perform the spectral energy distribution fitting. Detecting this rare orphan flare shows the potential of EP in discovering peculiar activities from AGN in high-cadence X-ray sky surveys., Comment: 14 pages, 4 figures, submitted to ApJ

Deep surveys reveal tidal debris and associated compact stellar systems. Euclid's unique combination of capabilities (spatial resolution, depth, and wide sky coverage) will make it a groundbreaking tool for galactic archaeology in the local Universe, bringing low surface brightness (LSB) science into the era of large-scale astronomical surveys. Euclid's Early Release Observations (ERO) demonstrate this potential with a field of view that includes several galaxies in the Dorado group. In this paper, we aim to derive from this image a mass assembly scenario for its main galaxies: NGC 1549, NGC 1553, and NGC 1546. We detect internal and external diffuse structures, and identify candidate globular clusters (GCs). By analysing the colours and distributions of the diffuse structures and candidate GCs, we can place constraints on the galaxies' mass assembly and merger histories. The results show that feature morphology, surface brightness, colours, and GC density profiles are consistent with galaxies that have undergone different merger scenarios. We classify NGC 1549 as a pure elliptical galaxy that has undergone a major merger. NGC 1553 appears to have recently transitioned from a late-type galaxy to early type, after a series of radial minor to intermediate mergers. NGC 1546 is a rare specimen of galaxy with an undisturbed disk and a prominent diffuse stellar halo, which we infer has been fed by minor mergers and then disturbed by the tidal effect from NGC 1553. Finally, we identify limitations specific to the observing conditions of this ERO, in particular stray light in the visible and persistence in the near-infrared bands. Once these issues are addressed and the extended emission from LSB objects is preserved by the data-processing pipeline, the Euclid Wide Survey will allow studies of the local Universe to be extended to statistical ensembles over a large part of the extragalactic sky., Comment: 25 pages, 20 figures

The survival of the domestic cat (Felis catus) in various ecosystems has become increasingly relevant due to its impact on wildlife, public health, and society. In countries like Mexico, social factors such as abandonment have led to the feralization of the species and an unexpected increase in its population in urban areas. To design and implement effective population control methods, a thorough analysis of the species' population dynamics, along with the social factors influencing it, is necessary. We propose a reaction-diffusion model to simulate the natural dispersal of the population within a bounded domain. After exploring the species' spreading ability, we construct a complex dynamical system based on the biological characteristics of cats and their intraspecific and interspecific interactions, which we explain and study in detail. Both deterministic and stochastic parameters are considered to enhance the realism of the simulations. Our results indicate that the population reaches equilibrium, highlighting the need for control methods combined with social regulations to achieve sustainability in the system.

We generalise the $\eta$ regularisation scheme in order to develop a framework for systematically studying regularisation of loops in quantum field theory. This allows us to "solve" a set of gauge consistency conditions for families of gauge invariant regularisation schemes. We recover several known examples such as dimensional and denominator regularisations, as well as some more general solutions. We also study anomalies in chiral theories in order to carefully describe how our formalism should be properly implemented., Comment: 20 pages

A primary target of the \Euclid space mission is to constrain early-universe physics by searching for deviations from a primordial Gaussian random field. A significant detection of primordial non-Gaussianity would rule out the simplest models of cosmic inflation and transform our understanding of the origin of the Universe. This paper forecasts how well field-level inference of galaxy redshift surveys can constrain the amplitude of local primordial non-Gaussianity ($f_{NL}$), within a Bayesian hierarchical framework, in the upcoming \Euclid data. We design and simulate mock data sets and perform Markov chain Monte Carlo analyses using a full-field forward modelling approach. By including the formation history of the cosmic matter field in the analysis, the method takes into account all available probes of primordial non-Gaussianity, and goes beyond statistical summary estimators of $f_{NL}$. Probes include, for example, two-point and higher-order statistics, peculiar velocity fields, and scale-dependent galaxy biases. Furthermore, the method simultaneously handles systematic survey effects, such as selection effects, survey geometries, and galaxy biases. The forecast shows that the method can reach precision levels of up to $\sigma (f_{NL}) = 2.3$ (68.3\% CI, and at the grid resolution $\Delta L = 62.5\,h^{-1}$Mpc) with \Euclid data. We also provide data products, including realistic $N$-body simulations with nonzero values of $f_{NL}$ and maps of adiabatic curvature fluctuations. The results underscore the feasibility and advantages of field-level inference to constrain $f_{NL}$ in galaxy redshift surveys. Our approach consistently captures all the information available in the large-scale structure to constrain $f_{NL}$, and resolves the degeneracy between early-universe physics and late-time gravitational effects, while mitigating the impact of systematic and observational effects., Comment: 31 pages and 26 figures, 3 tables. Comments are welcome!

Low-mass X-ray binaries with a neutron star as the primary object show a complex array of phenomenology during outbursts. The observed variability in X-ray emission primarily arises from changes in the innermost regions of the accretion disk, neutron star surface, and corona. In this work, we present the results of a comprehensive X-ray spectral and timing analysis of the neutron star transient MAXI J1807+132 during its 2023 outburst using data from the NICER observatory. The outburst is marked by a very rapid rise in the count rate by about a factor of 20 in a day. The source undergoes full state transitions and displays hysteresis effect in the hardness and rms intensity diagrams. Spectral analysis with a three-component model is consistent with disk truncation during the hard states and reaching the last stable orbit during the intermediate and soft states. We discuss the different values of the last stable radius in the context of possible distance of the source and magnetic field strength. The characteristic frequencies throughout the hard and intermediate states are found to be strongly correlated with the inner radius of the disk. Together with the spectral and fast variability properties, we attempt to trace the evolution of the size of the corona along the outburst. Following the main outburst, the source undergoes a high amplitude reflare wherein it shows a complex behavior with relatively high variability (10 %), but low hardness., Comment: ApJ (in press)

A recent report on the detection of very-high-energy gamma rays from V4641 Sagittarii (V4641 Sgr) up to ~0.8 peta-electronvolt has made it the second confirmed "PeVatron" microquasar. Here we report on the observation of V4641 Sgr with X-Ray Imaging and Spectroscopy Mission (XRISM) in September 2024. Thanks to the large field of view and low background, the CCD imager Xtend successfully detected for the first time X-ray extended emission around V4641 Sgr with a significance of > 4.5 sigma and > 10 sigma based on our imaging and spectral analysis, respectively. The spatial extent is estimated to have a radius of $7 \pm 3$ arcmin ($13 \pm 5$ pc at a distance of 6.2 kpc) assuming a Gaussian-like radial distribution, which suggests that the particle acceleration site is within ~10 pc of the microquasar. If the X-ray morphology traces the diffusion of accelerated electrons, this spatial extent can be explained by either an enhanced magnetic field (~80 uG) or a suppressed diffusion coefficient (~$10^{27}$ cm$^2$ s$^{-1}$ at 100 TeV). The integrated X-ray flux, (4-6)$\times 10^{-12}$ erg s$^{-1}$ cm$^{-2}$ (2-10 keV), would require a magnetic field strength higher than the galactic mean (> 8 uG) if the diffuse X-ray emission originates from synchrotron radiation and the gamma-ray emission is predominantly hadronic. If the X-rays are of thermal origin, the measured extension, temperature, and plasma density can be explained by a jet with a luminosity of ~$2\times 10^{39}$ erg s$^{-1}$, which is comparable to the Eddington luminosity of this system., Comment: 9 pages, 5 figures, accepted for publication in ApJL

While the subclass of interacting supernovae with narrow hydrogen emission lines (SNe IIn) consists of some of the longest-lasting and brightest SNe ever discovered, their progenitors are still not well understood. Investigating SNe IIn as they emit across the electromagnetic spectrum is the most robust way to understand the progenitor evolution before the explosion. This work presents X-Ray, optical, infrared, and radio observations of the strongly interacting Type IIn SN 2020ywx covering a period $>1200$ days after discovery. Through multiwavelength modeling, we find that the progenitor of 2020ywx was losing mass at $\sim10^{-2}$--$10^{-3} \mathrm{\,M_{\odot}\,yr^{-1}}$ for at least 100 yr pre-explosion using the circumstellar medium (CSM) speed of $120$ km/s measured from our optical and NIR spectra. Despite the similar magnitude of mass-loss measured in different wavelength ranges, we find discrepancies between the X-ray and optical/radio-derived mass-loss evolution, which suggest asymmetries in the CSM. Furthermore, we find evidence for dust formation due to the combination of a growing blueshift in optical emission lines and near-infrared continuum emission which we fit with blackbodies at $\sim$ 1000 K. Based on the observed elevated mass loss over more than 100 years and the configuration of the CSM inferred from the multiwavelength observations, we invoke binary interaction as the most plausible mechanism to explain the overall mass-loss evolution. SN 2020ywx is thus a case that may support the growing observational consensus that SNe IIn mass loss is explained by binary interaction., Comment: Submitted to ApJ, 31 pages, 19 figures

Investigating the assembly history of the most massive and passive galaxies will enhance our understanding of why galaxies exhibit such a remarkable diversity in structure and morphology. In this paper, we simultaneously investigate the assembly history and redshift evolution of semi-analytically modelled galaxy properties of central galaxies between 0.56 < z < 4.15, alongside their connection to their halos as a function of large-scale environment. We extract sub-samples of galaxies from a mock catalogue representative for the BOSS-CMASS sample, which includes the most massive and passively evolving system known today. Utilising typical galaxy properties such as star formation rate, (g-i) colour, or cold gas-phase metallicity (Zcold), we track the redshift evolution of these properties across the main progenitor trees. We present results on galaxy and halo properties, including their growth and clustering functions. Our findings indicate that galaxies in the highest stellar and halo mass regimes are least metal-enriched (using Zcold as a proxy) and consistently exhibit significantly larger black hole masses and higher clustering amplitudes compared to sub-samples selected by e.g. colour or star formation rate. This population forms later and also retains large reservoirs of cold gas. In contrast, galaxies in the intermediate and lower stellar/halo mass regimes consume their cold gas at higher redshift and were among the earliest and quickest to assemble. We observe a clear trend where the clustering of the galaxies selected according to their Zcold-values (either low-Zcold or high-Zcold) depends on the density of their location within the large-scale environment. We assume that in particular galaxies in the low/high-Zcold sub-samples form and evolve through distinct evolutionary channels, which are predetermined by their location within the large-scale environment of the cosmic web., Comment: 21 pages, 12 figures, accepted for publication in A&A

Quantum entanglement is an essential resource for several branches of quantum science and technology, however, entanglement detection can be a challenging task, specifically, if typical entanglement measures such as linear entanglement entropy or negativity are the metrics of interest. Here we propose a protocol to detect bipartite entanglement in a system of $N$ qubits inspired by the concept of monogamy of entanglement. We argue that given a total system with some bipartite entanglement between two subsystems, subsequent unitary evolution, and measurement of one of the individual subsystems might be used to quantify the entanglement between the two. To address the difficulty of detection, we propose to use spin squeezing to quantify the entanglement within the individual subsystem, knowing that the relation between spin squeezing and some entanglement measures is not one-to-one, we give some suggestions on how a clever choice of squeezing Hamiltonian can lead to better results in our protocol. For systems with a small number of qubits, we derive analytical results and show how our protocol can work optimally for GHZ states, moreover, for larger systems we show how the accuracy of the protocol can be improved by a proper choice of the squeezing Hamiltonian. Our protocol presents an alternative for entanglement detection in platforms where state tomography is inaccessible (in widely separated entangled systems, for example) or hard to perform, additionally, the ideas presented here can be extended beyond spin-only systems to expand its applicability., Comment: 11 pages, 9 figures

Transfer learning enhances model performance in a target population with limited samples by leveraging knowledge from related studies. While many works focus on improving predictive performance, challenges of statistical inference persist. Bayesian approaches naturally offer uncertainty quantification for parameter estimates, yet existing Bayesian transfer learning methods are typically limited to single-source scenarios or require individual-level data. We introduce TRansfer leArning via guideD horseshoE prioR (TRADER), a novel approach enabling multi-source transfer through pre-trained models in high-dimensional linear regression. TRADER shrinks target parameters towards a weighted average of source estimates, accommodating sources with different scales. Theoretical investigation shows that TRADER achieves faster posterior contraction rates than standard continuous shrinkage priors when sources align well with the target while preventing negative transfer from heterogeneous sources. The analysis of finite-sample marginal posterior behavior reveals that TRADER achieves desired frequentist coverage probabilities, even for coefficients with moderate signal strength--a scenario where standard continuous shrinkage priors struggle. Extensive numerical studies and a real-data application estimating the association between blood glucose and insulin use in the Hispanic diabetic population demonstrate that TRADER improves estimation and inference accuracy over continuous shrinkage priors using target data alone, while outperforming a state-of-the-art transfer learning method that requires individual-level data., Comment: 40 pages, 4 figures, 1 Table

Earthquake early warning systems are crucial for protecting areas that are subject to these natural disasters. An essential part of these systems is the detection procedure. Traditionally these systems work with seismograph data, but high rate GNSS data has become a promising alternative for the usage in large earthquake early warning systems. Besides traditional methods, deep learning approaches have gained recent popularity in this field, as they are able to leverage the large amounts of real and synthetic seismic data. Nevertheless, the usage of deep learning on GNSS data remains a comparatively new topic. This work contributes to the field of early warning systems by proposing an autoencoder based deep learning pipeline that aims to be lightweight and customizable for the detection of anomalies viz. high magnitude earthquakes in GNSS data. This model, DetEQ, is trained using the noise data recordings from nine stations located in Chile. The detection pipeline encompasses: (i) the generation of an anomaly score using the ground truth and reconstructed output from the autoencoder, (ii) the detection of relevant seismic events through an appropriate threshold, and (iii) the filtering of local events, that would lead to false positives. Robustness of the model was tested on the HR GNSS real data of 2011 Mw 6.8 Concepcion earthquake recorded at six stations. The results highlight the potential of GNSS based deep learning models for effective earthquake detection.

Cluster cosmology can benefit from combining multi-wavelength studies, which can benefit from characterising the correlation coefficients between different mass-observable relations. In this work, we aim to provide information on the scatter, the skewness, and the covariance of various mass-observable relations in galaxy clusters in cosmological hydrodynamic simulations. This information will help future analyses to better tackle accretion histories and projection effects and model mass observable relations for cosmology studies.We identify galaxy clusters in Magneticum Box2b simulations with mass $M_{\rm 200c}>10^{14} {\rm M}_\odot$ at redshift $z=0.24$ and $z=0.90$. Our analysis includes \Euclid-derived properties such as richness, stellar mass, lensing mass, and concentration. Additionally, we investigate complementary multi-wavelength data, including X-ray luminosity, integrated Compton-$y$ parameter, gas mass, and temperature. The impact of projection effects on mass-observable residuals and correlations is then examined. At intermediate redshift ($z=0.24$), projection effects impact lensing concentration, richness, and gas mass the most in terms of scatter and skewness of log-residuals of scaling relations. The contribution of projection effects can be significant enough to boost a spurious hot- vs. cold-baryons correlation and consequently hide underlying correlations due to halo accretion histories. At high redshift ($z=0.9$), the richness has a much lower scatter (of log-residuals), and the quantity that is most impacted by projection effects is the lensing mass. Lensing concentration reconstruction, in particular, is affected by deviations of the reduced-shear profile shape from the one derived by an NFW profile rather than interlopers in the line of sight., Comment: 26 pages, 22 figures, submitted to A&A, replied to referee comments

The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg^2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. Machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. We select all sources with VIS IE < 23 mag from the Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just 11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artefacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected 10^5 lensing systems in Euclid, this implies 10^6 objects for human classification, which while very large is not in principle intractable and not without precedent., Comment: 22 pages, 11 figures, Euclid consortium paper, A&A submitted

The aim of this study is to identify quiescent galaxies in the 2-deg$^2$ COSMOS field at $z \sim 3.1$ and analyze their environment. Using data from the ODIN survey and COSMOS2020 catalog, we identify 24 massive quiescent galaxies (MQGs) with stellar masses $\geq 10^{10.6}$ and derive their star formation histories and quenching timescales using SED fitting with BAGPIPES. Voronoi-based density maps trace local and large-scale environments using Lyman-$\alpha$ Emitters and photometric galaxies. Results indicate uniformly short quenching timescales ($<$500 Myr) independent of environmental density, suggesting rapid internal mechanisms such as AGN feedback dominate over environmental factors. MQGs do not correlate with protoclusters or filaments, although some are near gas-rich filaments but show no rejuvenation. These findings suggest quenching at high redshift is driven primarily by internal processes rather than environmental interactions.

Neural quantum states (NQS) have emerged as a powerful ansatz for variational quantum Monte Carlo studies of strongly-correlated systems. Here, we apply recurrent neural networks (RNNs) and autoregressive transformer neural networks to the Fermi-Hubbard and the (non-Hermitian) Hatano-Nelson-Hubbard models in one and two dimensions. In both cases, we observe that the convergence of the RNN ansatz is challenged when increasing the interaction strength. We present a physically-motivated and easy-to-implement strategy for improving the optimization, namely, by ramping of the model parameters. Furthermore, we investigate the advantages and disadvantages of the autoregressive sampling property of both network architectures. For the Hatano-Nelson-Hubbard model, we identify convergence issues that stem from the autoregressive sampling scheme in combination with the non-Hermitian nature of the model. Our findings provide insights into the challenges of the NQS approach and make the first step towards exploring strongly-correlated electrons using this ansatz., Comment: 14 pages, 13 figures

We propose a scenario of a de Sitter universe living on an End-of-the-World brane. Motivated by the Swampland programme and in particular the Cobordism Conjecture, we consider a compact region of AdS$_5$ nucleating from nothing, with a dS$_4$ living on its boundary. We show that it can equivalently be interpreted as an up-tunnelling from AdS$_5$ with cosmological constant $\Lambda\to -\infty$, following Brown and Dahlen's proposal for 'nothing'. Their picture naively leads to the conclusion that the brane has infinite negative tension. But we show that it becomes finite and positive once we employ holographic renormalization, recovering the Bubble of Something where the domain wall becomes a boundary of spacetime. The same holds true in any number of dimensions and, moreover, at the level of metric perturbations. This provides motivation for alternative routes of obtaining cosmology from quantum gravity or string theory using domain walls, departing from conventional vacuum approaches., Comment: 31 pages, 1 figure

We advance the study of pure de Sitter supergravity by introducing a finite formulation of unimodular supergravity via the super-St\"uckelberg mechanism. Building on previous works, we construct a complete four-dimensional action of spontaneously broken ${\cal N}\!\!=\!\!1$ supergravity to all orders, which allows for de Sitter solutions. The introduction of finite supergravity transformations extends the super-St\"uckelberg procedure beyond the second order, offering a recursive solution to all orders in the goldstino sector. This work bridges the earlier perturbative approaches and the complete finite theory, opening new possibilities for de Sitter vacua in supergravity models and eventually string theory., Comment: 23 pages

With the growing availability of quantitative forecasts from various sources, effectively communicating these multiple forecasts has become increasingly crucial. Recent advances have explored using Multiple-Forecast Visualizations (MFVs) to display multiple time-series forecasts. However, how to systematically sample from a pool of disparate forecasts to create MFVs that effectively facilitate decision-making requires further investigation. To address this challenge, we examine two cluster-based sampling strategies for creating MFVs and three designs for visualizing them to assist people in decision-making with forecasts. Through two online studies (Experiment 1 n = 711 and Experiment 2 n = 400) and over 15 decision-making-related metrics, we evaluated participants' perceptions of eight visualization designs using historical COVID-19 forecasts as a test bed. Our findings revealed that one sampling method significantly enhanced participants' ability to predict future outcomes, thereby reducing their surprise when confronted with the actual outcomes. Importantly, since no approach excels in all metrics, we advise choosing different visualization designs based on communication goals. Furthermore, qualitative response data demonstrate a correlation between response consistency and people's inclination to extrapolate from the forecast segment of the visualization. This research offers insights into how to improve visualizations of multiple forecasts using an automated and empirically validated technique for selecting forecasts that outperform common techniques on several key metrics and reduce overplotting.

We present a comprehensive multi-epoch photometric and spectroscopic study of SN 2024bch, a nearby (19.9 Mpc) Type II supernova (SN) with prominent early high ionization emission lines. Optical spectra from 2.9 days after the estimated explosion reveal narrow lines of H I, He II, C IV, and N IV that disappear by day 6. High cadence photometry from the ground and TESS show that the SN brightened quickly and reached a peak M$_V \sim$ $-$17.8 mag within a week of explosion, and late-time photometry suggests a $^{56}$Ni mass of 0.050 M$_{\odot}$. High-resolution spectra from day 8 and 43 trace the unshocked circumstellar medium (CSM) and indicate a wind velocity of 30--40 km s$^{-1}$, a value consistent with a red supergiant (RSG) progenitor. Comparisons between models and the early spectra suggest a pre-SN mass-loss rate of $\dot{M} \sim 10^{-3}-10^{-2}\ M_\odot\ \mathrm{yr}^{-1}$, which is too high to be explained by quiescent mass loss from RSGs, but is consistent with some recent measurements of similar SNe. Persistent blueshifted H I and [O I] emission lines seen in the optical and NIR spectra could be produced by asymmetries in the SN ejecta, while the multi-component H$\alpha$ may indicate continued interaction with an asymmetric CSM well into the nebular phase. SN 2024bch provides another clue to the complex environments and mass-loss histories around massive stars., Comment: Submitted to ApJ

We present supernova (SN) 2023ufx, a unique Type IIP SN with the shortest known plateau duration ($t_\mathrm{PT}$ $\sim$47 days), a luminous V-band peak ($M_{V}$ = $-$18.42 $\pm$ 0.08 mag), and a rapid early decline rate ($s1$ = 3.47 $\pm$ 0.09 mag (50 days)$^{-1}$). By comparing observed photometry to a hydrodynamic MESA+STELLA model grid, we constrain the progenitor to be a massive red supergiant with M$_\mathrm{ZAMS}$ $\simeq$19 - 25 M$_{\odot}$. Independent comparisons with nebular spectral models also suggest an initial He-core mass of $\sim$6 M$_{\odot}$, and thus a massive progenitor. For a Type IIP, SN 2023ufx produced an unusually high amount of nickel ($^{56}$Ni) $\sim$0.14 $\pm$ 0.02 M$_{\odot}$, during the explosion. We find that the short plateau duration in SN 2023ufx can be explained with the presence of a small hydrogen envelope (M$_\mathrm{H_\mathrm{env}}$ $\simeq$1.2 M$_{\odot}$), suggesting partial stripping of the progenitor. About $\simeq$0.09 M$_{\odot}$ of CSM through mass loss from late-time stellar evolution of the progenitor is needed to fit the early time ($\lesssim$10 days) pseudo-bolometric light curve. Nebular line diagnostics of broad and multi-peak components of [O I] $\lambda\lambda$6300, 6364, H$\alpha$, and [Ca II] $\lambda \lambda$7291, 7323 suggest that the explosion of SN 2023ufx could be inherently asymmetric, preferentially ejecting material along our line-of-sight., Comment: Submitted to ApJ, 30 pages, 19 figures

The instruments at the focus of the Euclid space observatory offer superb, diffraction-limited imaging over an unprecedented (from space) wide field of view of 0.57 deg$^2$. This exquisite image quality has the potential to produce high-precision astrometry for point sources once the undersampling of Euclid's cameras is taken into account by means of accurate, effective point spread function (ePSF) modelling. We present a complex, detailed workflow to simultaneously solve for the geometric distortion (GD) and model the undersampled ePSFs of the Euclid detectors. Our procedure was successfully developed and tested with data from the Early Release Observations (ERO) programme focused on the nearby globular cluster NGC 6397. Our final one-dimensional astrometric precision for a well-measured star just below saturation is 0.7 mas (0.007 pixel) for the Visible Instrument (VIS) and 3 mas (0.01 pixel) for the Near-Infrared Spectrometer and Photometer (NISP). Finally, we present a specific scientific application of this high-precision astrometry: the combination of Euclid and Gaia data to compute proper motions and study the internal kinematics of NGC 6397. Future work, when more data become available, will allow for a better characterisation of the ePSFs and GD corrections that are derived here, along with assessment of their temporal stability, and their dependencies on the spectral energy distribution of the sources as seen through the wide-band filters of Euclid., Comment: 23 pages, 21 figures. Accepted for publication in A&A on October 24, 2024. Astro-photometric catalogs and stacked images will be available at the CDS after the paper will be published

Core ellipticals, massive early-type galaxies have an almost constant inner surface brightness profile. The size of the core region correlates with the mass of the finally merged black hole. Here we report the first Euclid-based dynamical mass determination of a supermassive black hole. We study the centre of NGC 1272, the second most luminous elliptical galaxy in the Perseus cluster, combining the Euclid VIS photometry coming from the Early Release Observations of the Perseus cluster with VIRUS spectroscopic observations at the Hobby-Eberly Telescope. The core of NGC 1272 is detected on the Euclid VIS image. Its size is $1.29\pm 0.07''$ or 0.45 kpc, determined by fitting PSF-convolved core-S\'ersic and Nuker-law functions. The two-dimensional stellar kinematics of the galaxy is measured from the VIRUS spectra by deriving optimally regularized non-parametric line-of-sight velocity distributions. Dynamical models of the galaxy are constructed using our axisymmetric and triaxial Schwarzschild codes. We measure a black hole mass of $(5\pm3) \times 10^9 M_\odot$, in line with the expectation from the $M_{\rm BH}$-$r_{\rm b}$ correlation, but eight times larger than predicted by the $M_{\rm BH}$-$\sigma$ correlation (at $1.8\sigma$ significance). The core size, rather than the velocity dispersion, allows one to select galaxies harboring the most massive black holes. The spatial resolution, wide area coverage, and depth of the \Euclid (Wide and Deep) surveys allow us to find cores of passive galaxies larger than 2 kpc up to redshift 1., Comment: Accepted for publication in A&A

Lifelong reinforcement learning (RL) has been developed as a paradigm for extending single-task RL to more realistic, dynamic settings. In lifelong RL, the "life" of an RL agent is modeled as a stream of tasks drawn from a task distribution. We propose EPIC (\underline{E}mpirical \underline{P}AC-Bayes that \underline{I}mproves \underline{C}ontinuously), a novel algorithm designed for lifelong RL using PAC-Bayes theory. EPIC learns a shared policy distribution, referred to as the \textit{world policy}, which enables rapid adaptation to new tasks while retaining valuable knowledge from previous experiences. Our theoretical analysis establishes a relationship between the algorithm's generalization performance and the number of prior tasks preserved in memory. We also derive the sample complexity of EPIC in terms of RL regret. Extensive experiments on a variety of environments demonstrate that EPIC significantly outperforms existing methods in lifelong RL, offering both theoretical guarantees and practical efficacy through the use of the world policy.

The One-hundred-deg$^2$ DECam Imaging in Narrowbands (ODIN) survey is carrying out a systematic search for protoclusters during Cosmic Noon, using Ly$\alpha$-emitting galaxies (LAEs) as tracers. Once completed, ODIN aims to identify hundreds of protoclusters at redshifts of 2.4, 3.1, and 4.5 across seven extragalactic fields, covering a total area of up to 91~deg$^2$. In this work, we report strong clustering of high-redshift protoclusters through the protocluster-LAE cross-correlation function measurements of 150 protocluster candidates at $z~=~2.4$ and 3.1, identified in two ODIN fields with a total area of 13.9 deg$^2$. At $z~=~2.4$ and 3.1, respectively, the inferred protocluster biases are $6.6^{+1.3}_{-1.1}$ and $6.1^{+1.3}_{-1.1}$, corresponding to mean halo masses of $\log \langle M /M_\odot\rangle = 13.53^{+0.21}_{-0.24}$ and $12.96^{+0.28}_{-0.33}$. By the present day, these protoclusters are expected to evolve into virialized galaxy clusters with a mean mass of $\sim$ $10^{14.5}~M_\odot$. By comparing the observed number density of protoclusters to that of halos with the measured clustering strength, we find that our sample is highly complete. Finally, the similar descendant masses derived for our samples at $z=2.4$ and 3.1 assuming that the halo number density remains constant suggest that they represent similar structures observed at different cosmic epochs. As a consequence, any observed differences between the two samples can be understood as redshift evolution. The ODIN protocluster samples will thus provide valuable insights into the cosmic evolution of cluster galaxies., Comment: 12 pages, 5 figures, submitted to ApJ

We describe the cryogenic system being developed for Taurus: a super-pressure balloon-borne microwave polarimeter scheduled to fly in 2027. The Taurus cryogenic system consists of a 660L liquid helium cryostat which achieves a base temperature of <100mK with the help of a capillary-fed superfluid tank and a closed cycle dilution refrigerator. The main tank is supported with fiberglass flexures and is encased in two layers of vapor-cooled shields which allow Taurus to make full use of the extended flight time offered by the super-pressure balloon platform. The Taurus cryostat is projected to hold for over 50 days while weighing under 1000lbs. We present the design, testing, and thermal analysis of the Taurus cryogenic systems.

In this paper, we look at the nonlinear bending theory for thin prestrained elastic sheets with an oscillating periodic structure. We show that all limiting (in the sense of $\Gamma-$convergence) energy functionals which formally correspond to an infinite thickness-to-period ratio are equivalent. In contrast, there are several different limit models that formally correspond to a $0$ thickness-to-period ratio.

We investigate the physical properties and redshift evolution of simulated galaxies residing in protoclusters at cosmic noon, to understand the influence of the environment on galaxy formation. This work is to build clear expectations for the ongoing ODIN survey, devoted to mapping large-scale structures at z=2.4, 3.1, and 4.5 using Ly$\alpha$-emitting galaxies (LAEs) as tracers. From the IllustrisTNG simulations, we define subregions centered on the most massive clusters ranked by total stellar mass at z=0 and study the properties of galaxies within, including LAEs. To model the LAE population, we take a semi-analytical approach that assigns Ly$\alpha$ luminosity and equivalent width based on the UV luminosities to galaxies in a probabilistic manner. We investigate stellar mass, star formation rate, major mergers, and specific star formation rate of the population of star-forming galaxies and LAEs in the field and protocluster environment and trace their evolution. We find that the overall shape of the UV luminosity function (LF) in simulated protocluster environments is characterized by a shallower faint-end slope and an excess on the bright end, signaling different formation histories for galaxies therein. The difference is milder for the Ly$\alpha$ LF. While protocluster galaxies follow the same SFR-$M_{\odot}$ scaling relation as average field galaxies, a larger fraction appears to have experienced major mergers in the last 200 Myr and as a result shows enhanced star formation at a ~60% level, leading to a flatter distribution in both SFR and $M_{\odot}$ relative to galaxies in the average field. We find that protocluster galaxies, including LAEs, begin to quench much earlier (z~0.8-1.6) than field galaxies (z~0.5-0.9); our result is in agreement with recent observational results and highlights the importance of large-scale environment on the overall formation history of galaxies., Comment: 18 pages, 13 figures, to be submitted to Astronomy & Astrophysics, the abstract was reduced to meet character requirements; edits include: updating coauthor list and affiliations, updating citations in Sec 2.1

We present multi-epoch optical spectropolarimetric and imaging polarimetric observations of the nearby Type II supernova (SN) 2023ixf discovered in M101 at a distance of 6.85 Mpc. The first imaging polarimetric observations were taken +2.33 days (60085.08 MJD) after the explosion, while the last imaging polarimetric data points (+73.19 and +76.19 days) were acquired after the fall from the light curve plateau. At +2.33 days there is strong evidence of circumstellar material (CSM) interaction in the spectra and the light curve. A significant level of polarization $P_r = 0.88\pm 0.06 \% $ seen during this phase indicates that this CSM is aspherical. We find that the polarization evolves with time toward the interstellar polarization level ($0.35\%$) during the photospheric phase, which suggests that the recombination photosphere is spherically symmetric. There is a jump in polarization ($P_r =0.65 \pm 0.08 \% $) at +73.19 days when the light curve falls from the plateau. This is a phase where polarimetric data is sensitive to non-spherical inner ejecta or a decrease in optical depth into the single scattering regime. We also present spectropolarimetric data that reveal line (de)polarization during most of the observed epochs. In addition, at +14.50 days we see an "inverse P Cygn" profile in the H and He line polarization, which clearly indicates the presence of asymmetrically distributed material overlying the photosphere. The overall temporal evolution of polarization is typical for Type II SNe, but the high level of polarization during the rising phase has only been observed in SN 2023ixf., Comment: 14 pages, 7 figures, submitted to ApJL, comments welcome

Gravitational redshift and Doppler effects give rise to an antisymmetric component of the galaxy correlation function when cross-correlating two galaxy populations or two different tracers. In this paper, we assess the detectability of these effects in the Euclid spectroscopic galaxy survey. We model the impact of gravitational redshift on the observed redshift of galaxies in the Flagship mock catalogue using a Navarro-Frenk-White profile for the host haloes. We isolate these relativistic effects, largely subdominant in the standard analysis, by splitting the galaxy catalogue into two populations of faint and bright objects and estimating the dipole of their cross-correlation in four redshift bins. In the simulated catalogue, we detect the dipole signal on scales below $30\,h^{-1}{\rm Mpc}$, with detection significances of $4\,\sigma$ and $3\,\sigma$ in the two lowest redshift bins, respectively. At higher redshifts, the detection significance drops below $2\,\sigma$. Overall, we estimate the total detection significance in the Euclid spectroscopic sample to be approximately $6\,\sigma$. We find that on small scales, the major contribution to the signal comes from the nonlinear gravitational potential. Our study on the Flagship mock catalogue shows that this observable can be detected in Euclid Data Release 2 and beyond., Comment: 21 pages, 11 figures, 1 appendix; submitted on behalf of the Euclid Collaboration

Given a filtration of simplicial complexes, one usually applies persistent homology and summarizes the results in barcodes. Then, in order to extract statistical information from these barcodes, one needs to compute statistical indicators over the bars of the barcode. An issue with this approach is that usually infinite bars must be deleted or cut to finite ones; however, so far there is no consensus on how to perform this procedure. In this work we propose for the first time a systematic way to analyze barcodes through the use of statistical indicators. Our approach is based on the minimization of a divergence measure that generalizes the standard Wasserstein or bottleneck distance to a new asymmetric distance-like function that we introduce and which is interesting on its own. In particular, we analyze the topology induced by this divergence and the stability of known vectorizations with respect to this topology.

Massive stars end their life as core-collapse supernovae, amongst which some extremes are Type Ic broad-lined supernovae associated with long-duration gamma-ray bursts (LGRBs) having powerful relativistic jets. Their less-extreme brethren make unsuccessful jets that are choked inside the stars, appearing as X-ray flashes or low-luminosity GRBs. On the other hand, there exists a population of extragalactic fast X-ray transients (EFXTs) with timescales ranging from seconds to thousands of seconds, whose origins remain obscure. Known sources that contribute to the observed EFXT population include the softer analogs of LGRBs, shock breakouts of supernovae, or unsuccessful jets. Here, we report the discovery of the bright X-ray transient EP240414a detected by the Einstein Probe (EP), which is associated with the Type Ic supernova SN 2024gsa at a redshift of 0.401. The X-ray emission evolution is characterised by a very soft energy spectrum peaking at < 1.3 keV, which makes it distinct from known LGRBs, X-ray flashes, or low-luminosity GRBs. Follow-up observations at optical and radio bands revealed the existence of a weak relativistic jet that interacts with an extended shell surrounding the progenitor star. Located on the outskirts of a massive galaxy, this event reveals a new population of explosions of Wolf-Rayet stars characterised by a less powerful engine that drives a successful but weak jet, possibly owing to a progenitor star with a smaller core angular momentum than in traditional LGRB progenitors., Comment: 43 pages, 9 figures, 4 tables, submitted. Comments are welcome

Measurements of galaxy clustering are affected by RSD. Peculiar velocities, gravitational lensing, and other light-cone projection effects modify the observed redshifts, fluxes, and sky positions of distant light sources. We determine which of these effects leave a detectable imprint on several 2-point clustering statistics extracted from the EWSS on large scales. We generate 140 mock galaxy catalogues with the survey geometry and selection function of the EWSS and make use of the LIGER method to account for a variable number of relativistic RSD to linear order in the cosmological perturbations. We estimate different 2-point clustering statistics from the mocks and use the likelihood-ratio test to calculate the statistical significance with which the EWSS could reject the null hypothesis that certain relativistic projection effects can be neglected in the theoretical models. We find that the combined effects of lensing magnification and convergence imprint characteristic signatures on several clustering observables. Their S/N ranges between 2.5 and 6 (depending on the adopted summary statistic) for the highest-redshift galaxies in the EWSS. The corresponding feature due to the peculiar velocity of the Sun is measured with a S/N of order one or two. The $P_{\ell}(k)$ from the catalogues that include all relativistic effects reject the null hypothesis that RSD are only generated by the variation of the peculiar velocity along the line of sight with a significance of 2.9 standard deviations. As a byproduct of our study, we demonstrate that the mixing-matrix formalism to model finite-volume effects in the $P_{\ell}(k)$ can be robustly applied to surveys made of several disconnected patches. Our results indicate that relativistic RSD, the contribution from weak gravitational lensing in particular, cannot be disregarded when modelling 2-point clustering statistics extracted from the EWSS., Comment: 23 pages, 14 figures

Liquid crystal elastomers (LCEs) marry the large deformation response of a cross-linked polymer network with the nematic order of liquid crystals pendent to the network. Of particular interest is the actuation of LCE sheets where the nematic order, modeled by a unit vector called the director, is specified heterogeneously in the plane of the sheet. Heating such a sheet leads to a large spontaneous deformation, coupled to the director design through a metric constraint that is now well-established by the literature. Here we go beyond the metric constraint and identify the full plate theory that underlies this phenomenon. Starting from a widely used bulk model for LCEs, we derive a plate theory for the pure bending deformations of patterned LCE sheets in the limit that the sheet thickness tends to zero using the framework of $\Gamma$-convergence. Specifically, after dividing the bulk energy by the cube of the thickness to set a bending scale, we show that all limiting midplane deformations with bounded energy at this scale satisfy the aforementioned metric constraint. We then identify the energy of our plate theory as an ansatz-free lower bound of the limit of the scaled bulk energy, and construct a recovery sequence that achieves this plate energy for all smooth enough midplane deformations. We conclude by applying our plate theory to a variety of examples., Comment: 35 pages, 4 figures

XMMSL1 J171900.4-353217 is a very-faint X-ray transient that was discovered in 2010 March when it exhibited an outburst. We report on 7 observations, obtained with the X-Ray Telescope (XRT) aboard the Neil Gehrels {\it{Swift}} Observatory between 2010 May to October. By fitting a single absorbed power-law model to the XRT spectra, we infer power-law indices of $\Gamma = 1.8-2.7$ and an absorption column density of $\mathrm{N}_{\mathrm{H}}=(4.6-7.9)\times 10^{22}~\mathrm{cm}^{-2}$. The inferred $0.5-10$~keV luminosity fluctuated irregularly and peaked at $\mathrm{L}_\mathrm{X}\simeq 10^{35}-10^{36} ~\mathrm{erg~s^{-1}}$ for a distance of $4-12$~kpc. Based on the evolution of the power-law index with varying luminosity, we propose that the source most likely is a transient neutron star low-mass X-ray binary located at several kpc. If true, it would be a good candidate to search for coherent millisecond pulsations when it enters a new accretion outburst., Comment: 18 pages, 3 figures, 4 tables, Research article accepted for publication in: Revista Mexicana de Astronomia y Astrofisica (RMxAA)

We present cosmological parameter forecasts for the Euclid 6x2pt statistics, which include the galaxy clustering and weak lensing main probes together with previously neglected cross-covariance and cross-correlation signals between imaging/photometric and spectroscopic data. The aim is understanding the impact of such terms on the Euclid performance. We produce 6x2pt cosmological forecasts, considering two different techniques: the so-called harmonic and hybrid approaches, respectively. In the first, we treat all the different Euclid probes in the same way, i.e. we consider only angular 2pt-statistics for spectroscopic and photometric clustering, as well as for weak lensing, analysing all their possible cross-covariances and cross-correlations in the spherical harmonic domain. In the second, we do not account for negligible cross-covariances between the 3D and 2D data, but consider the combination of their cross-correlation with the auto-correlation signals. We find that both cross-covariances and cross-correlation signals, have a negligible impact on the cosmological parameter constraints and, therefore, on the Euclid performance. In the case of the hybrid approach, we attribute this result to the effect of the cross-correlation between weak lensing and photometric data, which is dominant with respect to other cross-correlation signals. In the case of the 2D harmonic approach, we attribute this result to two main theoretical limitations of the 2D projected statistics implemented in this work according to the analysis of official Euclid forecasts: the high shot noise and the limited redshift range of the spectroscopic sample, together with the loss of radial information from subleading terms such as redshift-space distortions and lensing magnification. Our analysis suggests that 2D and 3D Euclid data can be safely treated as independent, with a great saving in computational resources., Comment: 32 pages, 20 figures. Comments are welcome