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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

We report on the realization and characterization of a novel magic-wavelength nanofiber-based two-color optical dipole trap that allows us to generate a periodic one-dimensional array of trapping sites with a spacing significantly smaller than half of the resonant wavelength of the cesium D2-line. To this end, we launch a blue-detuned partial standing wave and two red-detuned light fields through the nanofiber. We demonstrate the trapping of atoms in the array and characterize the resulting trap configuration by measuring the trap frequencies in three directions and observe good agreement with theoretical predictions. The implementation of this nanofiber-based optical interface with magic trapping wavelengths and sub-$\lambda/2$ spacing is an important step towards the exploration of novel collective radiative effects such as selective radiance in 1D atomic arrays., Comment: 5 pages, 4 figures

The Earth is no longer the only known celestial body containing one or more liquid phases. The Cassini spacecraft has discovered seas of hydrocarbons at the surface of Titan, while a series of corroborating evidences argue in favour of the existence of an aqueous ocean beneath the icy crust of several moons. Capillarity embraces a family of physical processes occurring at the free surface of a liquid. These phenomena depend on the liquid properties and on the local planetary conditions. Capillarity may have important direct or indirect implications on the geoscientific and astrobiological points of view. In this paper, we discuss capillarity physics among solar system objects and expected consequences for planetary science., Comment: This paper is accepted in "Journal of Geophysical Research: Planet". Data and softwares are publicly available at https://doi.org/10.5281/zenodo.10391618

Since their first discovery in the late 1960s, Gamma-ray bursts have attracted an exponentially growing interest from the international community due to their central role in the most highly debated open questions of the modern research of astronomy, astrophysics, cosmology, and fundamental physics. These range from the intimate nuclear composition of high density material within the core of ultra-dense neuron stars, to stellar evolution via the collapse of massive stars, the production and propagation of gravitational waves, as well as the exploration of the early Universe by unveiling first stars and galaxies (assessing also their evolution and cosmic re-ionization). GRBs have stimulated in the past $\sim$50 years the development of cutting-edge technological instruments for observations of high energy celestial sources from space, leading to the launch and successful operations of many different scientific missions (several of them still in data taking mode nowadays). In this review, we provide a brief description of the GRB-dedicated missions from space being designed and developed for the future. The list of these projects, not meant to be exhaustive, shall serve as a reference to interested readers to understand what is likely to come next to lead the further development of GRB research and associated phenomenology., Comment: Accepted for publication on Universe. Invited review, contribution to the Universe Special Issue "Recent Advances in Gamma Ray Astrophysics and Future Perspectives", P. Romano eds. (https://www.mdpi.com/journal/universe/special_issues/7299902Z97)

The capability to generate simulation-ready garment models from 3D shapes of clothed humans will significantly enhance the interpretability of captured geometry of real garments, as well as their faithful reproduction in the virtual world. This will have notable impact on fields like shape capture in social VR, and virtual try-on in the fashion industry. To align with the garment modeling process standardized by the fashion industry as well as cloth simulation softwares, it is required to recover 2D patterns. This involves an inverse garment design problem, which is the focus of our work here: Starting with an arbitrary target garment geometry, our system estimates an animatable garment model by automatically adjusting its corresponding 2D template pattern, along with the material parameters of the physics-based simulation (PBS). Built upon a differentiable cloth simulator, the optimization process is directed towards minimizing the deviation of the simulated garment shape from the target geometry. Moreover, our produced patterns meet manufacturing requirements such as left-to-right-symmetry, making them suited for reverse garment fabrication. We validate our approach on examples of different garment types, and show that our method faithfully reproduces both the draped garment shape and the sewing pattern.

This study presents a Bayesian maximum \textit{a~posteriori} (MAP) framework for dynamical system identification from time-series data. This is shown to be equivalent to a generalized Tikhonov regularization, providing a rational justification for the choice of the residual and regularization terms, respectively, from the negative logarithms of the likelihood and prior distributions. In addition to the estimation of model coefficients, the Bayesian interpretation gives access to the full apparatus for Bayesian inference, including the ranking of models, the quantification of model uncertainties and the estimation of unknown (nuisance) hyperparameters. Two Bayesian algorithms, joint maximum \textit{a~posteriori} (JMAP) and variational Bayesian approximation (VBA), are compared to the {LASSO, ridge regression and SINDy algorithms for sparse} regression, by application to several dynamical systems with added {Gaussian or Laplace} noise. For multivariate Gaussian likelihood and prior distributions, the Bayesian formulation gives Gaussian posterior and evidence distributions, in which the numerator terms can be expressed in terms of the Mahalanobis distance or ``Gaussian norm'' $||\vec{y}-\hat{\vec{y}}||^2_{M^{-1}} = (\vec{y}-\hat{\vec{y}})^\top {M^{-1}} (\vec{y}-\hat{\vec{y}})$, where $\vec{y}$ is a vector variable, $\hat{\vec{y}}$ is its estimator and $M$ is the covariance matrix. The posterior Gaussian norm is shown to provide a robust metric for quantitative model selection {for the different systems and noise models examined.}, Comment: Includes supplementary information

The Space-based multi-band astronomical Variable Objects Monitor (SVOM) is a Chinese-French mission dedicated to the study of the transient sky. It is scheduled to start operations in 2024. ECLAIRs is a coded-mask telescope with a large field of view. It is designed to detect and localize gamma-ray bursts (GRBs) in the energy range from 4 keV up to 120 keV. In 2021, the ECLAIRs telescope underwent various calibration campaigns in vacuum test-chambers to evaluate its performance. Between 4 and 8 keV, the counting response of the detection plane shows inhomogeneities between pixels from different production batches. The efficiency inhomogeneity is caused by low-efficiency pixels (LEPs) from one of the two batches, together with high-threshold pixels (HTPs) whose threshold was raised to avoid cross-talk effects. In addition, some unexpected noise was found in the detection plane regions close to the heat pipes. We study the impact of these inhomogeneities and of the heat-pipe noise at low energies on the ECLAIRs onboard triggers. We propose different strategies in order to mitigate these impacts and to improve the onboard trigger performance. We analyzed the data from the calibration campaigns and performed simulations with the ground model of the ECLAIRs trigger software in order to design and evaluate the different strategies. Most of the impact of HTPs can be corrected for by excluding HTPs from the trigger processing. To correct for the impact of LEPs, an efficiency correction in the shadowgram seems to be a good solution. An effective solution for the heat-pipe noise is selecting the noisy pixels and ignoring their data in the 4--8 keV band during the data analysis., Comment: Accepted for publication in Astronomy&Astrophysics Accepted for publication in Astronomy&Astrophysics Accepted for publication in Astronomy

We discuss applications of the study of the new and barely explored class of changing-look (CL) narrow-line Seyfert 1 (NLS1) galaxies and comment on their detection with the space mission SVOM (Space Variable Objects Monitor). We highlight the case of NGC 1566, which is outstanding in many respects, for instance as one of the nearest known CL AGN undergoing exceptional outbursts. Its NLS1 nature is discussed, and we take it as a nearby prototype for systems that could be discovered and studied in the near future, including with SVOM. Finally, we briefly examine the broader implications and applications of CL events in NLS1 galaxies and show that such systems, once discovered in larger numbers, will greatly advance our understanding of the physics of the environment of rapidly growing supermassive black holes. This White Paper is part of a sequence of publications which explore aspects of our understanding of (CL) NLS1 galaxy physics with future missions., Comment: 14 pages, 4 figures. Accepted for publication in the Universe Special Issue "A Multimessenger View of Supermassive Black Holes and the Quasar Main Sequence"

This work investigates spanwise wall oscillation (SWO) as a method to preferentially enhance heat transfer over drag in turbulent channel flow. Direct numerical simulations at $Re_\tau=180$ and $\Pr=1$ show set of wall-oscillation parameters reducing drag also decrease heat transfer similarly, maintaining coupled transport. However, large period ($T^+=500$) and amplitude ($W^+=30$) induce substantially greater heat transfer intensification, increasing 15 % versus only 7.7 % drag rise. This Reynolds analogy breaking enables preferential elevation of heat transport over momentum. FIK identity analysis reveals negligible impact of forcing terms on dissimilarity. Instead, differences arise from the solenoidal velocity and linear temperature equations. Both the turbulent shear stress and heat flux are amplified near the wall under oscillation. However, the heat flux intensifies more substantially, especially at its peak. This preferential enhancement of the near-wall heat flux, exceeding the shear stress amplification, facilitates greater thermal transport augmentation relative to the friction increase. Results demonstrate that spanwise wall oscillation can preferentially intensify heat transfer beyond drag, providing a promising technique for improving heat exchanger. Further work should optimize the period and amplitude of the oscillation and elucidate the underlying physics of this dissimilar heat transfer control.

Following the EU's decision to ban neonicotinoids, this article investigates the impacts of yellow virus on sugar beet yields under the ban and under current and future climates. Using a model that factors in key variables such as sowing dates, phenological stages, first aphid flight and aphid abundance, simulations are performed using long-period climate datasets as inputs. Coupled with incidence and sugar yield loss assumptions, this model allows to reconstruct the impact of yellow virus on sugar beet yields using a so called 'as if' approach. By simulating the effects of viruses over a longer period of time, as if neonicotinoids weren't used in the past, this methodology allows an accurate assessment of risks associated with yellow viruses, as well as impact of future agroecological mesures. The study eventually provides an actuarial rating for an insurance policy that compensates the losses triggered by those viruses.

Let $K\subset \Rn$, $n\geq 3$, be a convex body. A point $p\in \Rn$ is said to be a \textit{Larman point} of $K$ if, for every hyperplane $\Pi$ passing through $p$, the section $\Pi\cap K$ has a $(n-2)$-plane of symmetry. If a point $p \in \Rn$ is a Larman point and if, in addition, for every hyperplane $\Pi$ passing through $p$, the section $\Pi\cap K$ has a $(n-2)$-plane of symmetry which contains $p$, then we call $p$ a \textit{revolution point} of $K$. In this work we prove that if $K\subset \Rt$ is a strictly convex centrally symmetric body with centre at $o$, $p$ is a Larman point of $K$ and there exists a line $L$ such that $p\notin L$ and, for every plane $\Gamma$ passing through $p$, the section $\Gamma \cap K$ has a line of symmetry which intersects $L$, then $K$ is a body of revolution (in some cases, we conclude that $K$ is a sphere). On the other hand, we also prove that if $p$ is a revolution point such that $p\not=o$, then $K$ is a body of revolution.

Excitons hosted by GaN/(Al,Ga)N quantum wells (QWs) are spatially indirect due to the giant built-in electric field that separates electrons and holes along the growth direction. This electric field, and thus exciton energy, can be reduced by depositing metallic layers on the sample surface. Using spatially-resolved micro-photoluminescence spectroscopy we compare the effects of two different materials, Nickel/Gold (NiAu) and few-layered graphene (FLG), on the potential landscape experienced by the excitons. We are able to (i) determine the potential barriers imposed on QW excitons by deposition of FLG and NiAu to be $14$ and $82$~meV, respectively, and (ii) to evidence their impact on the exciton transport at appropriate densities. Optical losses and inhomogeneous broadening induced by deposition of NiAu and FLG layers are similar, and their joined implementation constitute a promising tool for electrostatic modulation of IX densities even in the absence of any applied electric bias.

The integration of two-dimensional $MoS_{2}$ with $GaN$ recently attracted significant interest for future electronic/optoelectronic applications. However, the reported studies have been mainly carried out using heteroepitaxial $GaN$ templates on sapphire substrates, whereas the growth of $MoS_{2}$ on low-dislocation-density bulk GaN can be strategic for the realization of truly vertical devices. In this paper, we report the growth of ultrathin $MoS_{2}$ films, mostly composed by single-layers ($1L$), onto homoepitaxial $n-GaN$ on $n^{+}$ bulk substrates by sulfurization of a pre-deposited $MoO_{x}$ film. Highly uniform and conformal coverage of the $GaN$ surface was demonstrated by atomic force microscopy, while very low tensile strain (0.05%) and a significant $p^{+}$-type doping ($4.5 \times 10^{12} cm^{-2}$) of $1L-MoS_{2}$ was evaluated by Raman mapping. Atomic resolution structural and compositional analyses by aberration-corrected electron microscopy revealed a nearly-ideal van der Waals interface between $MoS_{2}$ and the $Ga$-terminated $GaN$ crystal, where only the topmost $Ga$ atoms are affected by oxidation. Furthermore, the relevant lattice parameters of the $MoS_{2}/GaN$ heterojunction, such as the van der Waals gap, were measured with high precision. Finally, the vertical current injection across this 2D/3D heterojunction has been investigated by nanoscale current-voltage analyses performed by conductive atomic force microscopy, showing a rectifying behavior with an average turn-on voltage $V_{on}=1.7 V$ under forward bias, consistent with the expected band alignment at the interface between $p^{+}$ doped $1L-MoS_{2}$ and $n-GaN$., Comment: 21 pages, 6 figures

In this paper, the Ni Schottky barrier on GaN epilayer grown on free standing substrates has been characterized. First, transmission electrical microscopy (TEM) images and nanoscale electrical analysis by conductive atomic force microscopy (C-AFM) of the bare material allowed visualizing structural defects in the crystal, as well as local inhomogeneities of the current conduction. The forward current-voltage (I-V) characteristics of Ni/GaN vertical Schottky diodes fabricated on the epilayer gave average values of the Schottky barrier height of 0.79 eV and ideality factor of 1.14. A statistical analysis over a set of diodes, combined with temperature dependence measurements, confirmed the formation of an inhomogeneous Schottky barrier in this material. From a plot of FB versus n, an ideal homogeneous barrier close to 0.9 eV was estimated, similar to that extrapolated by capacitance-voltage (C-V) analysis. Local I-V curves, acquired by means of C-AFM, displayed the inhomogeneous distribution of the onset of current conduction, which in turn resembles the one observed in the macroscopic Schottky diodes. Finally, the reverse characteristic of the diodes fabricated in the defects-free region have been acquired at different temperature and its behaviour has been described by the thermionic field emission (TFE) model.

Reinforcement learning has been widely adopted to model dialogue managers in task-oriented dialogues. However, the user simulator provided by state-of-the-art dialogue frameworks are only rough approximations of human behaviour. The ability to learn from a small number of human interactions is hence crucial, especially on multi-domain and multi-task environments where the action space is large. We therefore propose to use structured policies to improve sample efficiency when learning on these kinds of environments. We also evaluate the impact of learning from human vs simulated experts. Among the different levels of structure that we tested, the graph neural networks (GNNs) show a remarkable superiority by reaching a success rate above 80% with only 50 dialogues, when learning from simulated experts. They also show superiority when learning from human experts, although a performance drop was observed, indicating a possible difficulty in capturing the variability of human strategies. We therefore suggest to concentrate future research efforts on bridging the gap between human data, simulators and automatic evaluators in dialogue frameworks., Comment: 8 pages, at the EACL2023 conference (Findings)

The potential for data-driven applications to scale-resolving simulations of turbulent flows is assessed herein. Multigrid sequential data assimilation algorithms have been used to calibrate solvers for Large Eddy Simulation for the analysis of the high-Reynolds-number flow around a rectangular cylinder of aspect ratio 5:1. This test case has been chosen because of a number of physical complexities which elude accurate representation using reduced-order numerical simulation. The results for the statistical moments of the velocity and pressure flow field show that the data-driven techniques employed, which are based on the Ensemble Kalman Filter, are able to significantly improve the predictive features of the solver for reduced grid resolution. In addition, it was observed that, despite the sparse and asymmetric distribution of observation in the data-driven process, the data augmented results exhibit perfectly symmetric statistics and a significantly improved accuracy also far from the sensor location.

Controlling the photon statistics of light is paramount for quantum science and technologies. Recently, we demonstrated that transmitting resonant laser light past an ensemble of two-level emitters can result in a stream of single photons or excess photon pairs. This transformation is due to quantum interference between the transmitted and incoherently scattered two-photon component. Here, using the dispersion of the atomic medium, we actively control the relative quantum phase between these two components. We thereby realize a tunable two-photon interferometer and observe interference fringes in the normalized photon coincidence rate, varying from antibunching to bunching. Beyond the fundamental insight that the quantum phase between incoherent and coherent light can be tuned and dictates photon statistics, our results lend themselves to the development of novel quantum light sources.

The Microchannel X-ray Telescope (MXT) will be the first focusing X-ray telescope based on a "Lobster-Eye" optical design to be flown on Sino-French mission SVOM. SVOM will be dedicated to the study of Gamma-Ray Bursts and more generally time-domain astrophysics. The MXT telescope is a compact (focal length ~ 1.15 m) and light (< 42 kg) instrument, sensitive in the 0.2--10 keV energy range. It is composed of an optical system, based on micro-pore optics (MPOs) of 40 micron pore size, coupled to a low-noise pnCDD X-ray detector. In this paper we describe the expected scientific performance of the MXT telescope, based on the End-to-End calibration campaign performed in fall 2021, before the integration of the SVOM payload on the satellite., Comment: 22 pages, 12 figures, accepted for publication in Experimental Astronomy

Essential features of the Multigrid Ensemble Kalman Filter (G. Moldovan, G. Lehnasch, L. Cordier, M. Meldi, A multigrid/ensemble Kalman filter strategy for assimilation of unsteady flows, Journal of Computational Physics 443-110481) recently proposed for Data Assimilation of fluid flows are investigated and assessed in this article. The analysis is focused on the improvement in performance due to the inner loop. In this step, data from solutions calculated on the higher resolution levels of the multigrid approach are used as surrogate observations to improve the model prediction on the coarsest levels of the grid. The latter represents the level of resolution used to run the ensemble members for global Data Assimilation. The method is tested over two classical one-dimensional problems, namely the linear advection problem and the Burgers' equation. The analyses encompass a number of different aspects, such as different grid resolutions. The results indicate that the contribution of the inner loop is essential in obtaining accurate flow reconstruction and global parametric optimization. These findings open exciting perspectives of application to grid-dependent reduced-order models extensively used in fluid mechanics applications for complex flows, such as Large Eddy Simulation (LES).

Task-oriented dialogue systems are designed to achieve specific goals while conversing with humans. In practice, they may have to handle simultaneously several domains and tasks. The dialogue manager must therefore be able to take into account domain changes and plan over different domains/tasks in order to deal with multidomain dialogues. However, learning with reinforcement in such context becomes difficult because the state-action dimension is larger while the reward signal remains scarce. Our experimental results suggest that structured policies based on graph neural networks combined with different degrees of imitation learning can effectively handle multi-domain dialogues. The reported experiments underline the benefit of structured policies over standard policies.

Machine Learning models are prone to fail when test data are different from training data, a situation often encountered in real applications known as distribution shift. While still valid, the training-time knowledge becomes less effective, requiring a test-time adaptation to maintain high performance. Following approaches that assume batch-norm layer and use their statistics for adaptation, we propose a Test-Time Adaptation with Principal Component Analysis (TTAwPCA), which presumes a fitted PCA and adapts at test time a spectral filter based on the singular values of the PCA for robustness to corruptions. TTAwPCA combines three components: the output of a given layer is decomposed using a Principal Component Analysis (PCA), filtered by a penalization of its singular values, and reconstructed with the PCA inverse transform. This generic enhancement adds fewer parameters than current methods. Experiments on CIFAR-10-C and CIFAR- 100-C demonstrate the effectiveness and limits of our method using a unique filter of 2000 parameters., Comment: 7 pages, 2 figures, 2 tables, accepted at Workshop on Trustworthy Artificial Intelligence in conjunction with ECML/PKDD 22

The interaction of light with a single two-level emitter is the most fundamental process in quantum optics, and is key to many quantum applications. As a distinctive feature, two photons are never detected simultaneously in the light scattered by the emitter. This is commonly interpreted by saying that a single two-level quantum emitter can only absorb and emit single photons. However, it has been theoretically proposed that the photon anti-correlations can be thought to arise from quantum interference between two possible two-photon scattering amplitudes, which one refers to as coherent and incoherent. This picture is in stark contrast to the aforementioned one, in that it assumes that the atom even has two different mechanisms at its disposal to scatter two photons at the same time. Here, we validate the interference picture by experimentally verifying the 40-year-old conjecture that, by spectrally rejecting only the coherent component of the fluorescence light of a single two-level atom, the remaining light consists of photon pairs that have been simultaneously scattered by the atom. Our results offer fundamental insights into the quantum-mechanical interaction between light and matter and open up novel approaches for the generation of highly non-classical light fields., Comment: 9 pages, 7 figures, updated Methods section

Camera traps have revolutionized the animal research of many species that were previously nearly impossible to observe due to their habitat or behavior. They are cameras generally fixed to a tree that take a short sequence of images when triggered. Deep learning has the potential to overcome the workload to automate image classification according to taxon or empty images. However, a standard deep neural network classifier fails because animals often represent a small portion of the high-definition images. That is why we propose a workflow named Weakly Object Detection Faster-RCNN+FPN which suits this challenge. The model is weakly supervised because it requires only the animal taxon label per image but doesn't require any manual bounding box annotations. First, it automatically performs the weakly-supervised bounding box annotation using the motion from multiple frames. Then, it trains a Faster-RCNN+FPN model using this weak supervision. Experimental results have been obtained with two datasets from a Papua New Guinea and Missouri biodiversity monitoring campaign, then on an easily reproducible testbed.