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In learning problems, the noise inherent to the task at hand hinders the possibility to infer without a certain degree of uncertainty. Quantifying this uncertainty, regardless of its wide use, assumes high relevance for security-sensitive applications. Within these scenarios, it becomes fundamental to guarantee good (i.e., trustworthy) uncertainty measures, which downstream modules can securely employ to drive the final decision-making process. However, an attacker may be interested in forcing the system to produce either (i) highly uncertain outputs jeopardizing the system's availability or (ii) low uncertainty estimates, making the system accept uncertain samples that would instead require a careful inspection (e.g., human intervention). Therefore, it becomes fundamental to understand how to obtain robust uncertainty estimates against these kinds of attacks. In this work, we reveal both empirically and theoretically that defending against adversarial examples, i.e., carefully perturbed samples that cause misclassification, additionally guarantees a more secure, trustworthy uncertainty estimate under common attack scenarios without the need for an ad-hoc defense strategy. To support our claims, we evaluate multiple adversarial-robust models from the publicly available benchmark RobustBench on the CIFAR-10 and ImageNet datasets.

Recent work has proposed neural network pruning techniques to reduce the size of a network while preserving robustness against adversarial examples, i.e., well-crafted inputs inducing a misclassification. These methods, which we refer to as adversarial pruning methods, involve complex and articulated designs, making it difficult to analyze the differences and establish a fair and accurate comparison. In this work, we overcome these issues by surveying current adversarial pruning methods and proposing a novel taxonomy to categorize them based on two main dimensions: the pipeline, defining when to prune; and the specifics, defining how to prune. We then highlight the limitations of current empirical analyses and propose a novel, fair evaluation benchmark to address them. We finally conduct an empirical re-evaluation of current adversarial pruning methods and discuss the results, highlighting the shared traits of top-performing adversarial pruning methods, as well as common issues. We welcome contributions in our publicly-available benchmark at https://github.com/pralab/AdversarialPruningBenchmark

This paper introduces a framework based on linear splines for 2-dimensional extended object tracking and classification. Unlike state of the art models, linear splines allow to represent extended objects whose contour is an arbitrarily complex curve. An exact likelihood is derived for the case in which noisy measurements can be scattered from any point on the contour of the extended object, while an approximate Monte Carlo likelihood is provided for the case wherein scattering points can be anywhere, i.e. inside or on the contour, on the object surface. Exploiting such likelihood to measure how well the observed data fit a given shape, a suitable estimator is developed. The proposed estimator models the extended object in terms of a kinematic state, providing object position and orientation, along with a shape vector, characterizing object contour and surface. The kinematic state is estimated via a nonlinear Kalman filter, while the shape vector is estimated via a Bayesian classifier so that classification is implicitly solved during shape estimation. Numerical experiments are provided to assess, compared to state of the art extended object estimators, the effectiveness of the proposed one.

The KM3NeT Collaboration has tackled a common challenge faced by the astroparticle physics community, namely adapting the experiment-specific simulation software to work with the CORSIKA air shower simulation output. The proposed solution is an extension of the open-source code gSeaGen, allowing for the transport of muons generated by CORSIKA to a detector of any size at an arbitrary depth. The gSeaGen code was not only extended in terms of functionalities but also underwent a thorough redesign of the muon propagation routine, resulting in a more accurate and efficient simulation. This paper presents the capabilities of the new gSeaGen code as well as prospects for further developments., Comment: 27 pages, 13 figures

Photometric galaxy surveys, despite their limited resolution along the line of sight, encode rich information about the large-scale structure (LSS) of the Universe thanks to the large number density and extensive depth of the data. However, the complicated selection effects in wide and deep surveys will potentially cause significant bias in the angular two-point correlation function (2PCF) measured from those surveys. In this paper, we measure the 2PCF from the newly published KiDS-Legacy sample. Given an $r$-band $5\sigma$ magnitude limit of $24.8$ and survey footprint of $1347$ deg$^2$, it achieves an excellent combination of sky coverage and depth for such a measurement. We find that complex selection effects, primarily induced by varying seeing, introduce over-estimation of the 2PCF by approximately an order of magnitude. To correct for such effects, we apply a machine learning-based method to recover an ``organised random'' (OR) that presents the same selection pattern as the galaxy sample. The basic idea is to find the selection-induced clustering of galaxies using a combination of self-organising maps (SOM) and hierarchical clustering (HC). This unsupervised machine learning method is able to recover complicated selection effects without specifying their functional forms. We validate this ``SOM+HC'' method on mock deep galaxy samples with realistic systematics and selections derived from the KiDS-Legacy catalogue. Using mock data, we demonstrate that the OR delivers unbiased 2PCF cosmological parameter constraints, removing the $27\sigma$ offset in the galaxy bias parameter that is recovered when adopting uniform randoms. Blinded measurements on the real KiDS-Legacy data show that the corrected 2PCF is robust to the SOM+HC configuration near the optimal setup suggested by the mock tests. Our software is open-source for future usage., Comment: 29 pages, 27 figures, 4 tables

Among many-body instabilities in correlated quantum systems, electronic nematicity, defined by the spontaneous breaking of rotational symmetry, has emerged as a critical phenomenon, particularly within high-temperature superconductors. Recently, this behavior has been identified in CsTi$_3$Bi$_5$, a member of the AV$_3$Sb$_5$ (A = K, Rb, Cs) kagome family, recognized for its intricate and unconventional quantum phases. Despite accumulating indirect evidence, the fundamental mechanisms driving nematicity in CsTi$_3$Bi$_5$ remain inadequately understood, sparking ongoing debates. In this study, we employ polarization-dependent angle-resolved photoemission spectroscopy to reveal definitive signatures of an orbital-selective nematic deformation in the electronic structure of CsTi$_3$Bi$_5$. This direct experimental evidence underscores the pivotal role of orbital degrees of freedom in symmetry breaking, providing new insights into the complex electronic environment. By applying the functional renormalization group technique to a fully interacting ab initio model, we demonstrate the emergence of a finite angular momentum ($d$-wave) Pomeranchuk instability in CsTi$_3$Bi$_5$, driven by the concomitant action of electronic correlations within specific orbital channels and chemical potential detuning away from Van Hove singularities. By elucidating the connection between orbital correlations and symmetry-breaking instabilities, this work lays a crucial foundation for future investigations into the broader role of orbital selectivity in quantum materials, with far-reaching implications for the design and manipulation of novel electronic phases.

In recent years, the serverless paradigm has been widely adopted to develop cloud applications, as it enables building scalable solutions while delegating operational concerns such as infrastructure management and resource provisioning to the serverless provider. Despite bringing undisputed advantages, the serverless model requires a change in programming paradigm that may add complexity in software development. In particular, in the Function-as-a-Service (FaaS) paradigm, functions are inherently stateless. As a consequence, developers carry the burden of directly interacting with external storage services and handling concurrency and state consistency across function invocations. This results in less time spent on solving the actual business problems they face. Moving from these premises, this paper proposes Histrio, a programming model and execution environment that simplifies the development of complex stateful applications in the FaaS paradigm. Histrio grounds on the actor programming model, and lifts concerns such as state management, database interaction, and concurrency handling from developers. It enriches the actor model with features that simplify and optimize the interaction with external storage. It guarantees exactly-once-processing consistency, meaning that the application always behaves as if any interaction with external clients was processed once and only once, masking failures. Histrio has been compared with a classical FaaS implementation to evaluate both the development time saved due to the guarantees the system offers and the applicability of Histrio in typical applications. In the evaluated scenarios, Histrio simplified the implementation by significantly removing the amount of code needed to handle operational concerns. It proves to be scalable and it provides configuration mechanisms to trade performance and execution costs.

In this paper, we characterize all discrete-time systems in quasi-standard form admitting coalgebra symmetry with respect to the Lie--Poisson algebra $\mathfrak{h}_{6}$. The outcome of this study is a family of systems depending on an arbitrary function of three variables, playing the r\^ole of the potential. Moreover, using a direct search approach, we classify discrete-time systems from this family that admit an additional invariant at most quadratic in the physical variables. We discuss the integrability properties of the obtained cases, their relationship with known systems, and their continuum limits., Comment: 34 pages, 2 tables

We study the reverse mathematics of characterization theorems of regular countable second countable spaces (or $CSCS$ for short). We prove that arithmetic comprehension is equivalent over $\textbf{RCA}_0$ to every $T_3$ $CSCS$ being metrizable, and we characterize the $T_3$ spaces which are metrizable over $\textbf{RCA}_0$. We show that Lynn's theorem for $CSCS$ can be carried out in $\textbf{ACA}_0$, namely that every zero dimensional separable space is homeomorphic to the order topology of a linear order. We also show that arithmetic comprehension is equivalent to every $T_2$ compact $CSCS$ being well-orderable. From general topology, we know that the locally compact $T_2$ $CSCS$ are the well-orderable $CSCS$, and that the $T_3$ scattered $CSCS$ are the completely metrizable $CSCS$. We show that these characterizations and a few others are equivalent to arithmetic transfinite recursion over $\textbf{RCA}_0$. We also find a few statments that are equivalent to $\Pi^1_1$ comprehension. In particular we show that every $T_3$ $CSCS$ has a Cantor Bendixson rank and that every $T_3$ $CSCS$ is the disjoint union of a scattered space and dense in itself space are equivalent to $\Pi^1_1$ comprehension over $\textbf{RCA}_0$.

Synchrotron X-ray emission has been detected from nearly a dozen young supernova remnants (SNRs). X-rays of synchrotron origin exhibit linear polarization in a regular, non-randomly oriented magnetic field. The significant polarized X-ray emission from four such SNRs has already been reported on the basis of observations with the Imaging X-ray Polarimetry Explorer (IXPE). The magnetic-field structure as derived from IXPE observations is radial for Cassiopeia A, Tycho's SNR, and SN 1006, and tangential for RX J1713.7-3946. The latter together with the recent detection of a tangential magnetic field in SNR 1E 0102.2-7219 by the Australia Telescope Compact Array in the radio band shows that tangential magnetic fields can also be present in young SNRs. Thus, the dichotomy in polarization between young and middle-aged SNRs (radial magnetic fields in young SNRs, but tangential magnetic fields in middle-aged SNRs), previously noticed in the radio band, deserves additional attention. The present analysis of IXPE observations determines, for the first time, a magnetic-field structure in the northwestern rim of Vela Jr, also known as RX J0852.0-4622, and provides a new example of a young SNR with a tangential magnetic field., Comment: Accepted for publication in Astronomy and Astrophysics

X-ray polarization is a unique new probe of the particle acceleration in astrophysical jets made possible through the Imaging X-ray Polarimetry Explorer. Here we report on the first dense X-ray polarization monitoring campaign on the blazar Mrk 421. Our observations were accompanied by an even denser radio and optical polarization campaign. We find significant short-timescale variability in both X-ray polarization degree and angle, including a $\sim90^\circ$ angle rotation about the jet axis. We attribute this to random variations of the magnetic field, consistent with the presence of turbulence but also unlikely to be explained by turbulence alone. At the same time, the degree of lower-energy polarization is significantly lower and shows no more than mild variability. Our campaign provides further evidence for a scenario in which energy-stratified shock-acceleration of relativistic electrons, combined with a turbulent magnetic field, is responsible for optical to X-ray synchrotron emission in blazar jets., Comment: 23 pages, including 8 pages of appendices. 12 figures, 3 tables. Submitted to ApJ

Neutrinoless double beta decay ($0 \nu \beta \beta$) provides a way to probe physics beyond the Standard Model of particle physics. The upcoming nEXO experiment will search for $0\nu\beta\beta$ decay in $^{136}$Xe with a projected half-life sensitivity exceeding $10^{28}$ years at the 90\% confidence level using a liquid xenon (LXe) Time Projection Chamber (TPC) filled with 5 tonnes of Xe enriched to $\sim$90\% in the $\beta \beta$-decaying isotope $^{136}$Xe. In parallel, a potential future upgrade to nEXO is being investigated with the aim to further suppress radioactive backgrounds, and to confirm $\beta \beta$-decay events. This technique, known as Ba-tagging, comprises of extracting and identifying the $\beta \beta$-decay daughter $^{136}$Ba ion. One tagging approach being pursued involves extracting a small volume of LXe in the vicinity of a potential $\beta \beta$-decay using a capillary tube and facilitating a liquid to gas phase transition by heating the capillary exit. The Ba ion is then separated from the accompanying Xe gas using a radio-frequency (RF) carpet and RF funnel, conclusively identifying the ion as $^{136}$Ba via laser-fluorescence spectroscopy and mass spectrometry. Simultaneously, an accelerator-driven Ba ion source is being developed to validate and optimize this technique. The motivation for the project, the development of the different aspects along with current status and results are discussed here.

We propose three transition-metal adatom systems on 3C-SiC(111) surfaces as a versatile platform to realize massless Dirac fermions and flat bands with strong electronic correlations. Using density functional theory combined with the constrained random phase approximation and dynamical mean-field theory, we investigate the electronic properties of Ti, V, and Cr adatoms. The triangular surface lattices exhibit narrow bandwidths and effective two-band Hubbard models near the Fermi level, originating from partially filled, localized d-orbitals of the adatoms. Our study reveals a materials trend from a flat band Fermi liquid (Cr) via a paramagnetic Mott insulator with large local moments (V) to a Mott insulator on the verge to a heavy Dirac semimetal (Ti) showcasing the diverse nature of these strongly correlated systems. Specifically, the flat bands in the Cr and the well-defined Dirac cones in the strained metallic~Ti lattice indicate high potential for realizing topological and correlated phases.

We estimate both the polarization of spin $1/2$ baryons and the spin density matrix coefficients of spin $1$ mesons using a thermal model that incorporates vorticity and polarization to describe quarks, along with a coalescence formalism where spin and vorticity are not in equilibrium. We find that while our model is not predictive due to its considerable number of free parameters, it has the potential to explain several seemingly puzzling features of experimental spin measurements, such as the absence of baryon polarization alongside significant vector meson spin alignment. We suggest the measuring meson spin off-diagonal matrix elements, and examining the dependence of polarization observables on azimuthal angles, as methods to falsify this model and gain insights into the freezeout details of baryon and meson spin structure.

We introduce a novel approach for detecting gravitational waves through their influence on the shape of resolved astronomical objects. This method, complementary to pulsar timing arrays and astrometric techniques, explores the time-dependent distortions caused by gravitational waves on the shapes of celestial bodies, such as galaxies or any resolved extended object. By developing a formalism based on that adopted in the analysis of weak lensing effects, we derive the response functions for gravitational wave-induced distortions and compute their angular correlation functions. Our results highlight the sensitivity of these distortions to the lowest frequencies of the gravitational wave spectrum and demonstrate how they produce distinct angular correlation signatures, including null and polarisation-sensitive correlations. These findings pave the way for future high-resolution surveys to exploit this novel observable, potentially offering new insights into the stochastic gravitational wave background and cosmological models., Comment: 12 pages, 2 figures

Developing novel protocols for hydrogen (H) loading is crucial for furthering the investigation of hydrides as potential high-temperature superconductors at lower pressures compared to recent discoveries. Ionic gating-induced protonation (IGP) has emerged as a promising technique for H loading due to its inherent simplicity, but it can be limited in the maximum density of injected H when ionic liquids are used as a gating medium. Here, we demonstrate that large H concentrations can be successfully injected in both palladium (Pd) bulk foils and thin films (up to a stoichiometry PdH$_{0.89}$) by using a choline chloride-glycerol deep eutectic solvent (DES) as gate electrolyte and applying gate voltages in excess of the cathodic stability limit. The attained H concentrations are large enough to induce superconductivity in Pd, albeit with an incomplete resistive transition which suggests a strongly inhomogeneous H incorporation in the Pd matrix. This DES-based IGP protocol can be used as a guideline for maximizing H loading in different materials, although specific details of the applied voltage profile might require adjustments based on the material under investigation., Comment: 12 pages, 5 figures

Time Division Multiplexing (TDM) of cryogenic signal lines is a promising technique that can significantly reduce the required space, minimize the cooldown time, and increase the number of measurable quantum devices per cooldown. Here, we report the TDM of supercurrent with a 1-input-8-outputs voltage-actuated hybrid superconducting demultiplexer for the first time. The device comprises 14 ON/OFF InAsOI-based superconducting Josephson Field Effect Transistors (JoFETs) routed with Al traces. Each JoFET features Al as a superconductor and HfO2 as a gate insulator, and it can entirely suppress the switching current and increase the normal-state resistance by 20 times with a gate voltage of -4.5 V. The superconducting demultiplexer operates up to 100 MHz at 50 mK, features an insertion loss of ~ 0 dB in the superconducting state, and an OFF/ON ratio of ~ 17.5 dB in a 50-Ohm-matched cryogenic measurement setup. The frequency operation range can be extended by designing the demultiplexer with a proper microwave signal transport layout minimizing, at the same time, the impact of the parasitic electrical elements. These achievements open up the practical implementation of superconducting TDM as a key to drastically reducing I/O lines, costs, and space occupation in a cryostat, enabling the scalability of superconducting electronics., Comment: 13 pages, 5 figures, supporting information at the end of the paper. arXiv admin note: text overlap with arXiv:2405.07630

We study the sensitivity of the eigenvectors of random matrices, showing that even small perturbations make the eigenvectors almost orthogonal. More precisely, we consider two deformed Wigner matrices $W+D_1$, $W+D_2$ and show that their bulk eigenvectors become asymptotically orthogonal as soon as $\mathrm{Tr}(D_1-D_2)^2\gg 1$, or their respective energies are separated on a scale much bigger than the local eigenvalue spacing. Furthermore, we show that quadratic forms of eigenvectors of $W+D_1$, $W+D_2$ with any deterministic matrix $A\in\mathbf{C}^{N\times N}$ in a specific subspace of codimension one are of size $N^{-1/2}$. This proves a generalization of the Eigenstate Thermalization Hypothesis to eigenvectors belonging to two different spectral families., Comment: 47 pages, 1 figure

We prove that the mapping class group of a sphere with five punctures admits uncountably many non-equivalent, coarsely equivariant coarse median structures, falsifying a folklore belief. The same is shown for right-angled Artin groups whose defining graphs are connected, triangle- and square-free, and have at least three vertices. Remarkably, in the latter case the coarse medians we produce are not induced by cocompact cubulations. In the process, we develop the theory of short hierarchically hyperbolic groups (HHGs), which also include Artin groups of large and hyperbolic type, graph manifolds groups, and extensions of Veech groups. We develop tools to modify their hierarchical structure, including using quasimorphisms to construct quasilines that serve as coordinate spaces, and this is where the abundance of coarse median structures comes from. These techniques are of independent interest, and we use them in a forthcoming paper to study quotients of short HHGs., Comment: V2: Main theorem extended to many Right-angled Artin and Coxeter groups, for which we construct uncountably many coarse median structures not coming from cocompact cubulations. Improved exposition in the introduction. Now 54 pages, 7 figures. Any feedback is gladly welcome!

We show that the Gross-Pitaevskii equation coupled with the wave equation for a wire (GP-W) provides a natural theoretical framework for understanding recent experiments employing a nanowire to detect a single quantum vortex in superfluid $^4 {\rm He}$. We uncover the complete spatiotemporal evolution of such wire-based vortex detection via direct numerical simulations of the GP-W system. Furthermore, by computing the spatiotemporal spectrum, we obtain the vortex-capture-induced change in the oscillation frequency of the wire. We quantify this frequency shift by plotting the wire's oscillation frequency versus time and obtain results that closely match experimental observations. In addition, we provide analytical support for our numerical results by deriving the dispersion relation for the oscillating wire, with and without a trapped vortex., Comment: 7 pages, 3 figures

Real-world systems are shaped by both their complex internal interactions and the changes in their noisy environments. In this work, we study how a shared active bath affects the statistical dependencies between two interacting Brownian particles by evaluating their mutual information. We decompose the mutual information into three terms: information stemming from the internal interactions between the particles; information induced by the shared bath, which encodes environmental changes; a term describing information interference that quantifies how the combined presence of both internal interactions and environment either masks (destructive interference) or boosts (constructive interference) information. By studying exactly the case of linear interactions, we find that the sign of information interference depends solely on that of the internal coupling. However, when internal interactions are described by a nonlinear activation function, we show that both constructive and destructive interference appear depending on the interplay between the timescale of the active environment, the internal interactions, and the environmental coupling. Finally, we show that our results generalize to hierarchical systems where asymmetric couplings to the environment mimic the scenario where the active bath is only partially accessible to one particle. This setting allows us to quantify how this asymmetry drives information interference. Our work underscores how information and functional relationships in complex multi-scale systems are fundamentally shaped by the environmental context.

Tape diagrams provide a convenient notation for arrows of rig categories, i.e., categories equipped with two monoidal products, $\oplus$ and $\otimes$, where $\otimes$ distributes over $\oplus $. In this work, we extend tape diagrams with traces over $\oplus$ in order to deal with iteration in imperative programming languages. More precisely, we introduce Kleene-Cartesian bicategories, namely rig categories where the monoidal structure provided by $\otimes$ is a cartesian bicategory, while the one provided by $\oplus$ is what we name a Kleene bicategory. We show that the associated language of tape diagrams is expressive enough to deal with imperative programs and the corresponding laws provide a proof system that is at least as powerful as the one of Hoare logic., Comment: arXiv admin note: text overlap with arXiv:2210.09950

Neutrinos described as an open quantum system may interact with the environment which introduces stochastic perturbations to their quantum phase. This mechanism leads to a loss of coherence along the propagation of the neutrino $-$ a phenomenon commonly referred to as decoherence $-$ and ultimately, to a modification of the oscillation probabilities. Fluctuations in space-time, as envisaged by various theories of quantum gravity, are a potential candidate for a decoherence-inducing environment. Consequently, the search for decoherence provides a rare opportunity to investigate quantum gravitational effects which are usually beyond the reach of current experiments. In this work, quantum decoherence effects are searched for in neutrino data collected by the KM3NeT/ORCA detector from January 2020 to November 2021. The analysis focuses on atmospheric neutrinos within the energy range of a few GeV to $100\,\mathrm{GeV}$. Adopting the open quantum system framework, decoherence is described in a phenomenological manner with the strength of the effect given by the parameters $\Gamma_{21}$ and $\Gamma_{31}$. Following previous studies, a dependence of the type $\Gamma_{ij} \propto (E/E_0)^n$ on the neutrino energy is assumed and the cases $n = -2,-1$ are explored. No significant deviation with respect to the standard oscillation hypothesis is observed. Therefore, $90\,\%$ CL upper limits are estimated as $\Gamma_{21} < 4.6\cdot 10^{-21}\,$GeV and $\Gamma_{31} < 8.4\cdot 10^{-21}\,$GeV for $n = -2$, and $\Gamma_{21} < 1.9\cdot 10^{-22}\,$GeV and $\Gamma_{31} < 2.7\cdot 10^{-22}\,$GeV for $n = -1$, respectively., Comment: 17 pages, 5 figures

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

Asymmetric partition of fate determinants during cell division is a hallmark of cell differentiation. Recent works suggested that such a mechanism is hijacked by cancer cells to increase both their phenotypic heterogeneity and plasticity and in turn their fitness. To quantify fluctuations in the partitioning of cellular elements, imaging-based approaches are used, whose accuracy is limited by the difficulty of detecting cell divisions. Our work addresses this gap proposing a general method based on high-throughput flow cytometry measurements coupled with a theoretical frameworks. We applied our method to a panel of both normal and cancerous human colon cells, showing that different kinds of colon adenocarcinoma cells display very distinct extents of fluctuations in their cytoplasm partition, explained by an asymmetric division of their size. To test the accuracy of our population-level protocol, we directly measure the inherited fractions of cellular elements from extensive time-lapses of live-cell laser scanning microscopy, finding excellent agreement across the cell types. Ultimately, our flow cytometry-based method promise to be accurate and easily applicable to a wide range of biological systems where the quantification of partition fluctuations would help accounting for the observed phenotypic heterogeneity and plasticity, Comment: 17 pages, 4 figures

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

Less than 10 meters deep, shallow landslides are rapidly moving and strongly dangerous slides. In the present work, the probabilistic distribution of the landslide detachment points within a valley is modelled as a spatial Poisson point process, whose intensity depends on geophysical predictors according to a generalized additive model. Modelling the intensity with a generalized additive model jointly allows to obtain good predictive performance and to preserve the interpretability of the effects of the geophysical predictors on the intensity of the process. We propose a novel workflow, based on Random Forests, to select the geophysical predictors entering the model for the intensity. In this context, the statistically significant effects are interpreted as activating or stabilizing factors for landslide detachment. In order to guarantee the transferability of the resulting model, training, validation, and test of the algorithm are performed on mutually disjoint valleys in the Alps of Lombardy (Italy). Finally, the uncertainty around the estimated intensity of the process is quantified via semiparametric bootstrap.

For general large non-Hermitian random matrices $X$ and deterministic normal deformations $A$, we prove that the local eigenvalue statistics of $A+X$ close to the critical edge points of its spectrum are universal. This concludes the proof of the third and last remaining typical universality class for non-Hermitian random matrices, after bulk and sharp edge universalities have been established in recent years., Comment: 31 pages, 3 figures

The Lattice Boltzmann Method (LBM) is a computational technique of Computational Fluid Dynamics (CFD) that has gained popularity due to its high parallelism and ability to handle complex geometries with minimal effort. Although LBM frameworks are increasingly important in various industries and research fields, their complexity makes them difficult to modify and can lead to suboptimal performance. This paper presents miniLB, the first, to the best of our knowledge, SYCL-based LBM mini-app.miniLB addresses the need for a performance-portable LBM proxy app capable of abstracting complex fluid dynamics simulations across heterogeneous computing systems. We analyze SYCL semantics for performance portability and evaluate miniLB on multiple GPU architectures using various SYCL implementations. Our results, compared against a manually-tuned FORTRAN version, demonstrate effectiveness of miniLB in assessing LBM performance across diverse hardware, offering valuable insights for optimizing large-scale LBM frameworks in modern computing environments., Comment: 12 pages, conference

Though parameter shift rules have drastically improved gradient estimation methods for several types of quantum circuits, leading to improved performance in downstream tasks, so far they have not been transferable to linear optics with single photons. In this work, we derive an analytical formula for the gradients in these circuits with respect to phaseshifters via a generalized parameter shift rule, where the number of parameter shifts depends linearly on the total number of photons. Experimentally, this enables access to derivatives in photonic systems without the need for finite difference approximations. Building on this, we propose two strategies through which one can reduce the number of shifts in the expression, and hence reduce the overall sample complexity. Numerically, we show that this generalized parameter-shift rule can converge to the minimum of a cost function with fewer parameter update steps than alternative techniques. We anticipate that this method will open up new avenues to solving optimization problems with photonic systems, as well as provide new techniques for the experimental characterization and control of linear optical systems., Comment: 13 + 11 pages, 7 figures

Gravitational waves offer an unprecedented opportunity to look into the violent high-energy processes happening during the reheating phase of our Universe. We consider a Hubble-induced phase transition scenario as a source of a post-inflationary stochastic background of gravitational waves and analyse the main characteristics of its spectrum for the first time via numerical methods. The output of a large number of fully-fledged classical lattice simulations is condensed in a set of parametric formulas that describe key features of the gravitational wave spectrum, such as its peak amplitude and characteristic frequency, and avoid the need for further time-consuming simulations. The signal from such stochastic background is compared to the prospective sensitivity of future gravitational-wave detectors., Comment: 17 pages

In this paper we analyse the spectro-photometric properties of the Type II supernova \sn, exploded at a distance of $19.9\,\rm{Mpc}$, in NGC~3206. Its early spectra are characterised by narrow high-ionisation emission lines, often interpreted as signatures of ongoing interaction between rapidly expanding ejecta and a confined dense circumstellar medium. However, we provide a model of the bolometric light curve of the transient that does not require sources of energy different than the H recombination and radioactive decays. Our model can reproduce the bolometric light curve of SN~2024bch adopting an ejected mass of $M_{bulk}\simeq5$\msun~surrounded by an extended envelope of only 0.2\msun~with an outer radius $R_{env}=7.0\times10^{13}\,\rm{cm}$. An accurate modelling focused on the radioactive part of the light curve, which accounts for incomplete $\gamma-$ray trapping, gives a $^{56}\rm{Ni}$ mass of 0.048\msun. We propose narrow lines to be powered by Bowen fluorescence induced by scattering of \ion{He}{II} Ly$\alpha$ photons, resulting in the emission of high-ionisation resonance lines. Simple light travel time calculations based on the maximum phase of the narrow emission lines place the inner radius of the H-rich, un-shocked shell at a radius $\simeq4.4\times10^{15}\,\rm{cm}$, compatible with an absence of ejecta-CSM interaction during the first weeks of evolution. Possible signatures of interaction appear only $\sim69\,\rm{days}$ after explosion, although the resulting conversion of kinetic energy into radiation does not seem to contribute significantly to the total luminosity of the transient., Comment: 13 pages, 11 figures, submitted to A&A

The superradiance instability of rotating black holes leads to the formation of an ultralight boson cloud with distinctive observational signatures, making black holes an effective probe of ultralight dark matter. However, around black holes in a binary system, the superradiance effect of such clouds can be terminated by tidal perturbations from the companion, leading to cloud depletion. In this study, we perform the first analysis of the impact of this termination effect on superradiant black hole binaries which are realistically modelled after their statistics in our Galaxy. Working with a dataset of approximately $10^7$ black hole binaries simulated using the Stellar EVolution for N-body (SEVN) population synthesis code, we identify the superradiant candidates and those that manage to survive the termination effect. We then calculate the cloud survival rate for various boson masses and black hole spin models. Our findings reveal that the $l=m=1$ cloud modes are generally stable against termination, whereas the $l=m=2$ modes can be significantly affected, with survival rates dropping below $10\%$ for boson masses below approximately $0.5\times 10^{-12}$ eV. In addition, our analysis indicates that clouds that overcome termination typically exhibit a higher superradiant growth rate and therefore a higher detectability., Comment: 13 pages, 10 figures

Traditional speech enhancement methods often oversimplify the task of restoration by focusing on a single type of distortion. Generative models that handle multiple distortions frequently struggle with phone reconstruction and high-frequency harmonics, leading to breathing and gasping artifacts that reduce the intelligibility of reconstructed speech. These models are also computationally demanding, and many solutions are restricted to producing outputs in the wide-band frequency range, which limits their suitability for professional applications. To address these challenges, we propose Hi-ResLDM, a novel generative model based on latent diffusion designed to remove multiple distortions and restore speech recordings to studio quality, sampled at 48kHz. We benchmark Hi-ResLDM against state-of-the-art methods that leverage GAN and Conditional Flow Matching (CFM) components, demonstrating superior performance in regenerating high-frequency-band details. Hi-ResLDM not only excels in non-instrusive metrics but is also consistently preferred in human evaluation and performs competitively on intrusive evaluations, making it ideal for high-resolution speech restoration.

Recent advances in Natural Language Interfaces (NLIs) and Large Language Models (LLMs) have transformed our approach to NLP tasks, shifting the focus towards a more Pragmatics-based approach. This shift enables more natural interactions between humans and voice assistants, which have been historically difficult to achieve. Pragmatics involves understanding how users often talk out of turn, interrupt one another, or provide relevant information without being explicitly asked (maxim of quantity). To explore this, we developed a digital assistant that continuously listens to conversations and proactively generates relevant visualizations during data exploration tasks. In a within-subject study, participants interacted with both proactive and non-proactive versions of a voice assistant while exploring the Hawaii Climate Data Portal (HCDP). Results suggest that the proactive assistant enhanced user engagement and facilitated quicker insights. Our study highlights the potential of Pragmatic, proactive AI in NLIs and identifies key challenges in its implementation, offering insights for future research., Comment: 14 pages, 8 figures, 1 table

We study numerically the Hessian of low-lying minima of vector spin glass models defined on random regular graphs. We consider the two-component (XY) and three-component (Heisenberg) spin glasses at zero temperature, subjected to the action of a randomly oriented external field. Varying the intensity of the external field, these models undergo a zero temperature phase transition from a paramagnet at high field to a spin glass at low field. We study how the spectral properties of the Hessian depend on the magnetic field. In particular, we study the shape of the spectrum at low frequency and the localization properties of low energy eigenvectors across the transition. We find that in both phases the edge of the spectral density behaves as $\lambda^{3/2}$: such a behavior rules out the presence of a diverging spin-glass susceptibility $\chi_{SG}=\langle 1/\lambda^2 \rangle$. As to low energy eigenvectors, we find that the softest eigenmodes are always localized in both phases of the two models. However, by studying in detail the geometry of low energy eigenmodes across different energy scales close to the lower edge of the spectrum, we find a different behavior for the two models at the transition: in the XY case, low energy modes are typically localized; at variance, in the Heisenberg case low-energy eigenmodes with a multi-modal structure (sort of ``delocalization'') appear at an energy scale that vanishes in the infinite size limit. These geometrically non-trivial excitations, which we call Concentrated and Delocalised Low Energy Modes (CDLEM), coexist with trivially localised excitations: we interpret their existence as a sign of critical behavior related to the onset of the spin glass phase., Comment: 15 pages, 8 figures

ANNZ is a fast and simple algorithm which utilises artificial neural networks (ANNs), it was known as one of the pioneers of machine learning approaches to photometric redshift estimation decades ago. We enhanced the algorithm by introducing new activation functions like tanh, softplus, SiLU, Mish and ReLU variants; its new performance is then vigorously tested on legacy samples like the Luminous Red Galaxy (LRG) and Stripe-82 samples from SDSS, as well as modern galaxy samples like the Physics of the Accelerating Universe Survey (PAUS). This work focuses on testing the robustness of activation functions with respect to the choice of ANN architectures, particularly on its depth and width, in the context of galaxy photometric redshift estimation. Our upgraded algorithm, which we named ANNZ+, shows that the tanh and Leaky ReLU activation functions provide more consistent and stable results across deeper and wider architectures with > 1 per cent improvement in root-mean-square error ($\sigma_{\textrm{RMS}}$) and 68th percentile error ($\sigma_{68}$) when tested on SDSS data sets. While assessing its capabilities in handling high dimensional inputs, we achieved an improvement of 11 per cent in $\sigma_{\textrm{RMS}}$ and 6 per cent in $\sigma_{68}$ with the tanh activation function when tested on the 40-narrowband PAUS dataset; it even outperformed ANNZ2, its supposed successor, by 44 per cent in $\sigma_{\textrm{RMS}}$. This justifies the effort to upgrade the 20-year-old ANNZ, allowing it to remain viable and competitive within the photo-z community today. The updated algorithm ANNZ+ is publicly available at https://github.com/imdadmpt/ANNzPlus., Comment: 37 pages, 9 figures, submitted to JCAP

We characterize the domain of the Schr\"odinger operators $S=-\Delta+c|x|^{-\alpha}$ in $L^p(\mathbb{R}^N)$, with $0<\alpha<2$ and $c\in\mathbb{R}$. When $\alpha p< N$, the domain characterization is essentially known and can be proved using different tools, for instance kernel estimates and potentials in the Kato class or in the reverse H\"older class. However,the other cases seem not to be known, so far.In this paper, we give the explicit description of the domain of $S$ for all range of parameters $p,\alpha$ and $c$., Comment: 20 pages

Two-dimensional crystals stack together through weak van der Waals (vdW) forces, offering unlimited possibilities to play with layer number, order and twist angle in vdW heterostructures (HSs). The realisation of high-performance optoelectronic devices, however, requires the achievement of specific band alignments, $k$-space matching between conduction band minima and valence band maxima, as well as efficient charge transfer between the constituent layers. Fine tuning mechanisms to design ideal HSs are lacking. Here, we show that layer-selective strain engineering can be exploited as an extra degree of freedom in vdW HSs to tailor their band alignment and optical properties. To that end, strain is selectively applied to MS$_2$ (M=Mo,W) monolayers in InSe/MS$_2$ HSs. This triggers a giant PL enhancement of the highly tuneable but weakly emitting InSe by one to three orders of magnitude. Resonant PL excitation measurements, supported by first-principle calculations, provide evidence of a strain-activated direct charge transfer from the MS$_2$ MLs toward InSe. This significant emission enhancement achieved for InSe widens its range of applications for optoelectronics.

Music timbre transfer is a challenging task that involves modifying the timbral characteristics of an audio signal while preserving its melodic structure. In this paper, we propose a novel method based on dual diffusion bridges, trained using the CocoChorales Dataset, which consists of unpaired monophonic single-instrument audio data. Each diffusion model is trained on a specific instrument with a Gaussian prior. During inference, a model is designated as the source model to map the input audio to its corresponding Gaussian prior, and another model is designated as the target model to reconstruct the target audio from this Gaussian prior, thereby facilitating timbre transfer. We compare our approach against existing unsupervised timbre transfer models such as VAEGAN and Gaussian Flow Bridges (GFB). Experimental results demonstrate that our method achieves both better Fr\'echet Audio Distance (FAD) and melody preservation, as reflected by lower pitch distances (DPD) compared to VAEGAN and GFB. Additionally, we discover that the noise level from the Gaussian prior, $\sigma$, can be adjusted to control the degree of melody preservation and amount of timbre transferred.

We provide sufficient conditions for two subgroups of a hierarchically hyperbolic group to generate an amalgamated free product over their intersection. The result applies in particular to certain geometric subgroups of mapping class groups of finite-type surfaces, that is, those subgroups coming from the embeddings of closed subsurfaces. In the second half of the paper, we study under which hypotheses our amalgamation procedure preserves several notions of convexity in HHS, such as hierarchical quasiconvexity (as introduced by Behrstock, Hagen, and Sisto) and strong quasiconvexity (every quasigeodesic with endpoints on the subset lies in a uniform neighbourhood). This answers a question of Russell, Spriano, and Tran., Comment: 31 pages, 6 figures. Comments and feedbacks are extremely welcome!

Cold gas and dust reprocess the X-ray emission of active galactic nuclei (AGN), producing spectro-polarimetric features in the X-ray band. The recent launch of IXPE allows for observations of this X-ray polarisation signal, encoding unique information on the circumnuclear medium of AGN. However, the models for interpreting these polarimetric data are under-explored and do not reach the same level of sophistication as the corresponding spectral models. We aim at closing the gap between the spectral and spectro-polarimetric modelling of AGN circumnuclear media by providing the tools for simulating X-ray polarisation in complex 3D transfer media alongside X-ray spectra. We lay out the framework for X-ray polarisation in 3D radiative transfer simulations and provide an implementation to the 3D radiative transfer code SKIRT, focussing on (de)polarisation due to scattering and fluorescent re-emission. As a first application, we studied a 2D toroidal reprocessor of cold gas, modelling the AGN circumnuclear medium. For the 2D torus model, we find a complex behaviour of the polarisation angle with photon energy, which we interpret as a balance between the reprocessed photon flux originating from different sky regions, with a direct link to the torus geometry. We calculated a large grid of AGN torus models and demonstrated how spatially resolved polarisation maps could form a useful tool for interpreting the geometrical information that is encoded in IXPE observations. With this work, we release high-resolution AGN torus templates that simultaneously describe X-ray spectra and spectro-polarimetry, for observational data fitting with XSPEC. The SKIRT code can now model X-ray polarisation simultaneously with X-ray spectra and provide synthetic spectro-polarimetric observations for complex 3D circumnuclear media, with all features of the established SKIRT framework available., Comment: 16 pages, 13 figures, accepted for publication in Astronomy & Astrophysics

We prove that under the Brownian evolution on large non-Hermitian matrices the log-determinant converges in distribution to a 2+1 dimensional Gaussian field in the Edwards-Wilkinson regularity class, namely it is logarithmically correlated for the parabolic distance. This dynamically extends a seminal result by Rider and Vir\'ag about convergence to the Gaussian free field. The convergence holds out of equilibrium for centered, i.i.d. matrix entries as an initial condition. A remarkable aspect of the limiting field is its non-Markovianity, due to long range correlations of the eigenvector overlaps, for which we identify the exact space-time polynomial decay. In the proof, we obtain a quantitative, optimal relaxation at the hard edge, for a broad extension of the Dyson Brownian motion, with a driving noise arbitrarily correlated in space., Comment: 42 pages, 1 figure

We present a comprehensive X-ray analysis and spectral energy distribution (SED) fitting of WISEA J171419.96+602724.6, an extremely luminous type 2 quasar at $z$ = 2.99. The source was suggested as a candidate Compton-thick (column density N$_{\rm H}>$1.5 $\times$ 10$^{24}$ cm$^{-2}$) quasar by a short XMM-Newton observation in 2011. We recently observed the source with deep NuSTAR and XMM-Newton exposures in 2021 and found that the source has a lower obscuration of N$_{\rm H}\sim$5 $\times$ 10$^{22}$ cm$^{-2}$ with an about four times lower flux. The two epochs of observations suggested that the source was significantly variable in X-ray obscuration, flux, and intrinsic luminosity at 2-3~$\sigma$ in less than 2.5 years (in the source rest frame). We performed SED fitting of this source using CIGALE thanks to its great availability of multiwavelength data (from hard X-rays to radio). The source is very luminous with a bolometric luminosity of $L_{\rm BOL}\sim$ 2.5 $\times$ 10$^{47}$ erg s$^{-1}$. Its host galaxy has a huge star formation rate (SFR) of $\sim$1280 Solar mass yr$^{-1}$ and a huge stellar mass of $\sim$1.1 $\times$ 10$^{12}$ Solar mass. The correlation between the SFR and stellar mass of this source is consistent with what was measured in the high-$z$ quasars. It is also consistent with what was measured in the main-sequence star-forming galaxies, suggesting that the presence of the active nucleus in our target does not enhance or suppress the SFR of its host galaxy. The source is an Infrared hyper-luminous, obscured galaxy with significant amount of hot dust in its torus and shares many similar properties with hot, dust obscured galaxies., Comment: 19 pages, 10 figure, 5 tables, accepted to ApJ

The Euclid mission, designed to map the geometry of the dark Universe, presents an unprecedented opportunity for advancing our understanding of the cosmos through its photometric galaxy cluster survey. This paper focuses on enhancing the precision of halo bias (HB) predictions, which is crucial for deriving cosmological constraints from the clustering of galaxy clusters. Our study is based on the peak-background split (PBS) model linked to the halo mass function (HMF); it extends with a parametric correction to precisely align with results from an extended set of $N$-body simulations carried out with the OpenGADGET3 code. Employing simulations with fixed and paired initial conditions, we meticulously analyze the matter-halo cross-spectrum and model its covariance using a large number of mock catalogs generated with Lagrangian Perturbation Theory simulations with the PINOCCHIO code. This ensures a comprehensive understanding of the uncertainties in our HB calibration. Our findings indicate that the calibrated HB model is remarkably resilient against changes in cosmological parameters including those involving massive neutrinos. The robustness and adaptability of our calibrated HB model provide an important contribution to the cosmological exploitation of the cluster surveys to be provided by the Euclid mission. This study highlights the necessity of continuously refining the calibration of cosmological tools like the HB to match the advancing quality of observational data. As we project the impact of our model on cosmological constraints, we find that, given the sensitivity of the Euclid survey, a miscalibration of the HB could introduce biases in cluster cosmology analyses. Our work fills this critical gap, ensuring the HB calibration matches the expected precision of the Euclid survey. The implementation of our model is publicly available in https://github.com/TiagoBsCastro/CCToolkit., Comment: 20 pages; 12 figures; accepted for publication in A&A; abstract abridged for arXiv submission

We study freeze-in production of fermionic dark matter mediated by a $Z^\prime$ gauge boson. In particular, we explore the regime of Boltzmann-suppressed production, when the Standard Model (SM) thermal bath temperature never exceeds the dark matter mass. The corresponding gauge coupling is then required to be significant, up to order one. As a result, this class of freeze-in models can be probed by the current and future direct dark matter detection experiments., Comment: 13 pages, 2 figures

Gradient-based attacks are a primary tool to evaluate robustness of machine-learning models. However, many attacks tend to provide overly-optimistic evaluations as they use fixed loss functions, optimizers, step-size schedulers, and default hyperparameters. In this work, we tackle these limitations by proposing a parametric variation of the well-known fast minimum-norm attack algorithm, whose loss, optimizer, step-size scheduler, and hyperparameters can be dynamically adjusted. We re-evaluate 12 robust models, showing that our attack finds smaller adversarial perturbations without requiring any additional tuning. This also enables reporting adversarial robustness as a function of the perturbation budget, providing a more complete evaluation than that offered by fixed-budget attacks, while remaining efficient. We release our open-source code at https://github.com/pralab/HO-FMN.

Active galactic nuclei (AGN) are extremely variable in the X-ray band down to very short timescales. However, the driver behind the X-ray variability is still poorly understood. Previous results suggest that the hot corona responsible for the primary Comptonized emission observed in AGN is expected to play an important role in driving the X-ray variability. In this work, we investigate the connection between the X-ray amplitude variability and the coronal physical parameters; namely, the temperature ($kT$) and optical depth ($\tau$). We present the spectral and timing analysis of 46 {\it NuSTAR} observations corresponding to a sample of 20 AGN. For each source, we derived the coronal temperature and optical depth through X-ray spectroscopy and computed the normalized excess variance for different energy bands on a timescale of $10$ ks. We find a strong inverse correlation between $kT$ and $\tau$, with correlation coefficient of $r<-0.9$ and negligible null probability. No clear dependence was found among the temperature and physical properties, such as the black hole mass or the Eddington ratio. We also see that the observed X-ray variability is not correlated with either the coronal temperature or optical depth under the thermal equilibrium assumption, whereas it is anticorrelated with the black hole mass. These results can be interpreted through a scenario where the observed X-ray variability could primarily be driven by variations in the coronal physical properties on a timescale of less than $10$~ks; whereas we assume thermal equilibrium on such timescales in this work, given the capability of the currently available hard X-ray telescopes. Alternatively, it is also possible that the X-ray variability is mostly driven by the absolute size of the corona, which depends on the supermassive black hole mass, rather than resulting from any of its physical properties., Comment: Accepted for publication in Astronomy & Astrophysics, 21 pages, 9 figures, 4 tables

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

Android is the most used Operating System worldwide for mobile devices, with hundreds of thousands of apps downloaded daily. Although these apps are primarily written in Java and Kotlin, advanced functionalities such as graphics or cryptography are provided through native C/C++ libraries. These libraries can be affected by common vulnerabilities in C/C++ code (e.g., memory errors such as buffer overflow), through which attackers can read/modify data or execute arbitrary code. The detection and assessment of vulnerabilities in Android native code have only been recently explored by previous research work. In this paper, we propose a fast risk-based approach that provides a risk score related to the native part of an Android application. In this way, before an app is released, the developer can check if the app may contain vulnerabilities in the Native Code and, if present, patch them to publish a more secure application. To this end, we first use fast regular expressions to detect library versions and possible vulnerable functions. Then, we apply scores extracted from a vulnerability database to the analyzed application, thus obtaining a risk score representative of the whole app. We demonstrate the validity of our approach by performing a large-scale analysis on more than $100,000$ applications (but only $40\%$ contained native code) and $15$ popular libraries carrying known vulnerabilities. The attained results show that many applications contain well-known vulnerabilities that miscreants can potentially exploit, posing serious concerns about the security of the whole Android applications landscape.