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In the era of Extremely Large Telescopes, the current generation of 8-10m facilities are likely to remain competitive at ground-UV wavelengths for the foreseeable future. The Cassegrain U-Band Efficient Spectrograph (CUBES) has been designed to provide high instrumental efficiency ( $>$ 37\%) observations in the near UV (305-400 nm requirement, 300-420 nm goal) at a spectral resolving power of R $>$ 20, 000 (with a lower-resolution, sky-limited mode of R $\sim$ 7, 000). With the design focusing on maximizing the instrument throughput (ensuring a Signal to Noise Ratio -SNR- $\sim$ 20 per spectral resolution element at 313 nm for U $\sim$ 17.5 mag objects in 1h of observations), it will offer new possibilities in many fields of astrophysics: i) access to key lines of stellar spectra (e.g. lighter elements, in particular Beryllium), extragalactic studies (e.g. circumgalactic medium of distant galaxies, cosmic UV background) and follow-up of explosive transients. We present the CUBES instrument design, currently in Phase-C and approaching the final design review, summarizing the hardware architecture and interfaces between the different subsystems as well as the relevant technical requirements. We describe the optical, mechanical, electrical design of the different subsystems (from the telescope adapter and support structure, through the main opto-mechanical path, including calibration unit, detector devices and cryostat control, main control electronics), detailing peculiar instrument functions like the Active Flexure Compensation (AFC). Furthermore, we outline the AITV concept and the main instrument operations giving an overview of its software ecosystem. Installation at the VLT is planned for 2028-2029 and first science operations in late 2029.

Low-energy (<300 keV) protons entering the field of view of XMM-Newton are observed in the form of a sudden increase in the background level, the so-called soft proton flares, affecting up to 40% of the mission observing time. In-flight XMM-Newton's observations of soft protons represent a unique laboratory to validate and improve our understanding of their interaction with the mirror, optical filters, and X-ray instruments. At the same time, such models would link the observed background flares to the primary proton population encountered by the telescope, converting XMM-Newton into a monitor for soft protons. We built a Geant4 simulation of XMM-Newton, including a verified mass model of the X-ray mirror, the focal plane assembly, and the EPIC MOS and pn-CCDs. We encoded the energy redistribution and proton transmission efficiency into a redistribution matrix file (RMF) and an auxiliary response file (ARF). For the validation, three averaged soft proton spectra, one for each filter configuration, were extracted from a collection of 13 years of MOS observations of the focused non X-ray background and analysed with Xspec. The best-fit model is in agreement with the power-law distribution predicted from independent measurements for the XMM-Newton orbit, spent mostly in the magnetosheath and nearby regions. For the first time we are able to link detected soft proton flares with the proton radiation environment in the Earth's magnetosphere, while proving the validity of the simulation chain in predicting the background of future missions. Benefiting from this work and contributions from the Athena instrument consortia, we also present the response files for the Athena mission and updated estimates for its focused charged background.

Reconfigurable photonic integrated circuits (PICs) can implement arbitrary operations and signal processing functionalities directly in the optical domain. Run-time configuration of these circuits requires an electronic control layer to adjust the working point of their building elements and make them compensate for thermal drifts or degradations of the input signal. As the advancement of photonic foundries enables the fabrication of chips of increasing complexity, developing scalable electronic controllers becomes crucial for the operation of complex PICs. In this paper, we present an electronic application-specific integrated circuit (ASIC) designed for reconfiguration of PICs featuring numerous tuneable elements. Each channel of the ASIC controller independently addresses one optical component of the PIC, as multiple parallel local feedback loops are operated to achieve full control. The proposed design is validated through real-time reconfiguration of a 16-channel silicon photonics adaptive beam coupler. Results demonstrate automatic coupling of an arbitrary input beam to a single-mode waveguide, dynamic compensation of beam wavefront distortions and successful transmission of a 50 Gbit/s signal through an optical free-space link. The low power consumption and compactness of the electronic chip provide a scalable paradigm that can be seamlessly extended to larger photonic architectures., Comment: Manuscript contains both main text and supplementary information

The Chern-Simons gravitational term during inflation is usually coupled to the inflaton field. The resulting theory suffers from ghost-field formation in the tensor sector, which limits the observational effects of P-violation on cosmological correlators. In this work, we consider the Chern-Simons term coupled to an isocurvature component in a multi-field model of inflation. Since the resulting theory does not affect the quadratic action of tensor perturbations, ghost fields do not appear. This operator provides (P-violating) interactions between the isocurvature perturbation and the curvature and tensor perturbations. We show that combining these couplings with interactions between the curvature and isocurvature components coming from a turning trajectory, the resulting $\langle sst \rangle_{PV}$ non-Gaussianities can reach $f^{sst, PV}_{\rm NL}=B_{PV}^{\zeta\zeta h}(k,k,k)/P^2_{\zeta}(k)\sim \mathcal O(1)$ within the parameter space of the theory. Our result motivates the systematic study of the Chern-Simons gravitational term coupled to isocurvature fields in multi-field models of inflation with couplings between the curvature and isocurvature fields or other mechanisms that transfer effects on the isocurvature field into the curvature field., Comment: 28 pages, 3 figures

Late-decaying particles naturally arise in many extensions of the Standard Model, directly impacting key cosmological processes in the early universe, such as Big Bang Nucleosynthesis (BBN). BBN studies often consider electromagnetic energy injection episodes only, but in practice long-lived particles are also amenable to hadronic decays. The latter can greatly alter the predicted abundances of light elements such as $\mathrm{D}/\mathrm{H}$, $Y_p$, ${}^3\mathrm{He}/\mathrm{D}$, and ${}^7\mathrm{Li}/\mathrm{H}$. Incorporating up-to-date measurements, we place constraints on the primordial abundance of long-lived particles as a function of their lifetime. Lastly, we apply our results to the gravitino problem and set bounds on the reheating temperature, which controls the gravitino primordial abundance., Comment: 8 pages, 5 figures

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

Recent work has highlighted the remarkable properties of quantum turbulence in superfluid helium II, consisting of a disordered tangle of quantised vortex lines which interact with each other and reconnect when they collide. According to Landau's two-fluid theory, these vortex lines move in a surrounding of thermal excitations called the normal fluid. Until now, the normal fluid has often been considered a passive background which simply provides the vortex lines with a mechanism for dissipating their kinetic energy into heat. Using a model which fully takes into account the two-way interaction between the vortex lines and the normal fluid, here we show that each vortex line creates a macroscopic wake in the normal fluid that can be larger than the average distance between vortex lines; this is surprising, given the microscopic size of the superfluid vortex cores which induce these wakes. We show that in heat transfer experiments, the flow of the normal fluid can therefore be described as the superposition of an imposed uniform flow and wakes generated by the vortex lines, leading to non-classical statistics of the normal fluid velocity. We also argue that this first evidence of independent fluid structures in the thermal excitations postulated by Landau may be at the root of recent, unaccounted for, experimental findings., Comment: 10 pages, 9 figures

The interplay between substrate interactions and electron-phonon coupling in two-dimensional (2D) materials presents a significant challenge in understanding and controlling their electronic properties. Here, we present a comparative study of the structural characteristics, phonon dynamics, and electron-phonon interactions in bulk and monolayer NbSe$_2$ on epitaxial bilayer graphene (BLG) using helium atom scattering (HAS). High-resolution helium diffraction reveals a (9x9)0$^{\circ}$ superstructure within the NbSe$_2$ monolayer, commensurate with the BLG lattice, while out-of-plane HAS diffraction spectra indicate a low-corrugated (3$\sqrt{3}$x3$\sqrt{3}$)30$^{\circ}$ substructure. By monitoring the thermal attenuation of the specular peak across a temperature range of 100 K to 300 K, we determined the electron-phonon coupling constant $\lambda_{HAS}$ as 0.76 for bulk 2H-NbSe$_2$. In contrast, the NbSe$_2$ monolayer on graphene exhibits a reduced $\lambda_{HAS}$ of 0.55, corresponding to a superconducting critical temperature (T$_C$) of 1.56 K according to the MacMillan formula, consistent with transport measurement findings. Inelastic HAS data provide, besides a set of dispersion curves of acoustic and lower optical phonons, a soft, dispersionless branch of phonons at 1.7 meV, attributed to the interface localized defects distributed with the superstructure period, and thus termed moir\'e phonons. Our data show that moir\'e phonons contribute significantly to the electron-phonon coupling in monolayer NbSe$_2$. These results highlight the crucial role of the BLG on the electron-phonon coupling in monolayer NbSe$_2$, attributed to enhanced charge transfer effects, providing valuable insights into substrate-dependent electronic interactions in 2D superconductors.

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

Spectral densities encode essential information about system-environment interactions in open-quantum systems, playing a pivotal role in shaping the system's dynamics. In this work, we leverage machine learning techniques to reconstruct key environmental features, going beyond the weak-coupling regime by simulating the system's dynamics using the reaction coordinate mapping. For a dissipative spin-boson model with a structured spectral density expressed as a sum of Lorentzian peaks, we demonstrate that the time evolution of a system observable can be used by a neural network to classify the spectral density as comprising one, two, or three Lorentzian peaks and accurately predict their central frequency., Comment: 15+6 pages, 11 figures. Comments welcome!

In recent years, AI red teaming has emerged as a practice for probing the safety and security of generative AI systems. Due to the nascency of the field, there are many open questions about how red teaming operations should be conducted. Based on our experience red teaming over 100 generative AI products at Microsoft, we present our internal threat model ontology and eight main lessons we have learned: 1. Understand what the system can do and where it is applied 2. You don't have to compute gradients to break an AI system 3. AI red teaming is not safety benchmarking 4. Automation can help cover more of the risk landscape 5. The human element of AI red teaming is crucial 6. Responsible AI harms are pervasive but difficult to measure 7. LLMs amplify existing security risks and introduce new ones 8. The work of securing AI systems will never be complete By sharing these insights alongside case studies from our operations, we offer practical recommendations aimed at aligning red teaming efforts with real world risks. We also highlight aspects of AI red teaming that we believe are often misunderstood and discuss open questions for the field to consider.

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

This paper presents a novel optimization approach for allocating grid operation costs in Peer-to-Peer (P2P) electricity markets using Quantum Computing (QC). We develop a Quadratic Unconstrained Binary Optimization (QUBO) model that matches logical power flows between producer-consumer pairs with the physical power flow to distribute grid usage costs fairly. The model is evaluated on IEEE test cases with up to 57 nodes, comparing Quantum Annealing (QA), hybrid quantum-classical algorithms, and classical optimization approaches. Our results show that while the model effectively allocates grid operation costs, QA performs poorly in comparison despite extensive hyperparameter optimization. The classical branch-and-cut method outperforms all solvers, including classical heuristics, and shows the most advantageous scaling behavior. The findings may suggest that binary least-squares optimization problems may not be suitable candidates for near-term quantum utility.

Vision-language models (VLMs) have demonstrated remarkable potential in integrating visual and linguistic information, but their performance is often constrained by the need for extensive, high-quality image-text training data. Curation of these image-text pairs is both time-consuming and computationally expensive. To address this challenge, we introduce SVP (Supervision-free Visual Projection), a novel framework that enhances vision-language alignment without relying on curated data or preference annotation. SVP leverages self-captioning and a pre-trained grounding model as a feedback mechanism to elicit latent information in VLMs. We evaluate our approach across six key areas: captioning, referring, visual question answering, multitasking, hallucination control, and object recall. Results demonstrate significant improvements, including a 14% average improvement in captioning tasks, up to 12% increase in object recall, and substantial reduction in hallucination rates. Notably, a small VLM using SVP achieves hallucination reductions comparable to a model five times larger, while a VLM with initially poor referring capabilities more than doubles its performance, approaching parity with a model twice its size., Comment: Preprint

The joint optimization of sensor poses and 3D structure is fundamental for state estimation in robotics and related fields. Current LiDAR systems often prioritize pose optimization, with structure refinement either omitted or treated separately using representations like signed distance functions or neural networks. This paper introduces a framework for simultaneous optimization of sensor poses and 3D map, represented as surfels. A generalized LiDAR uncertainty model is proposed to address degraded or less reliable measurements in varying scenarios. Experimental results on public datasets demonstrate improved performance over most comparable state-of-the-art methods. The system is provided as open-source software to support further research., Comment: 8 pages, 6 figures, this work has been submitted to IEEE RA-L

Control of individual spins at the atomic level holds great promise for miniaturized spintronics, quantum sensing, and quantum information processing. Both single atomic and molecular spin centers are prime candidates for these applications and are often individually addressed and manipulated using scanning tunneling microscopy (STM). In this work, we present a hybrid approach and demonstrate a robust method for self-assembly of magnetic organometallic complexes consisting of individual iron (Fe) atoms and molecules on a silver substrate using STM. We employ two types of molecules, bis(dibenzoylmethane) copper(II) [Cu(dbm)2] and iron phthalocyanine (FePc). We show that in both cases the Fe atoms preferentially attach underneath the benzene ring ligand of the molecules, effectively forming an organometallic half-sandwich arene complex, Fe(C6H6), that is akin to the properties of metallocenes. In both situations, a molecule can be combined with up to two Fe atoms. In addition, we observe a change in the magnetic properties of the attached Fe atoms in scanning tunneling spectroscopy, revealing a distinct Kondo signature at the Fe sites. We explain the latter using density functional theory calculations, and find that the bond formation between the Fe 3d-orbitals and the benzene {\pi}-molecular orbitals creates a favorable situation for Kondo screening of the d_xz- and d_yz-like orbitals. Thus, this work establishes a reliable design principle for forming hybrid organometallic complexes and simultaneous tuning of their atomic spin states., Comment: 16 pages, 5 figures

We develop an Integral Transformation Method (ITM) for the study of suitable optimal control and differential game models. This allows for a solution to such dynamic problems to be found through solving a family of optimization problems parametrized by time. The method is quite flexible, and it can be used in several economic applications where the state equation and the objective functional are linear in a state variable. We illustrate the ITM in the context of a two-country integrated assessment climate model. We characterize emissions, consumption, transfers, and welfare by computing the Nash equilibria of the associated dynamic game. We then compare them to efficiency benchmarks. Further, we apply the ITM in a robust control setup, where we investigate how (deep) uncertainty affects climate outcomes.

Conventional general relativity supplies the notion of a vacuum tension and thus a maximum force $F_{max}=c^4/4G\approx\ 3\times 10^{43}$ Newtons, that is realized for a black hole. In conjunction with the Wilson area rule, we are thus led to the surface confinement of the mass of a black hole analogous to the surface confinement of quarks. The central result of our paper is that PeV scale protons exist on the surface of a Kerr black hole residing at our galactic center that is in concert with the HAWC Collaboration result of a PeVatron at the galactic center., Comment: 5 pages, no figures

In this paper we present a novel telescope composed exclusively of thin, flat optical elements, each being a hot-pressed multi-layered structure combining the properties of a lens, its anti-reflection coating and frequency selection or filtering. We discuss the design process, from fundamental physical metamaterial properties of the single periodic cell structure to the lens concept, which constitutes the building block of the telescope design, and the iterative process that is part of the lens optimization. We provide the results of a laboratory test campaign for different telescope designs based on three-lens arrangements. Beam cuts and focus measurements both on- and off-axis are compared with models showing good agreement. We conclude that a broad-band mm-wave complete telescope system consisting entirely of metamaterial flat lenses has been built and tested, showing comparable performance with conventional state-of-the-art refractive telescopes in the same wavelength region. This new broadband design, highly efficient at frequencies between 90 and 190 GHz, offers multiple advantages. These include a $> 80\%$ weight reduction, reduced issues tied to coating-survivability at cryogenic temperatures caused by differential contraction exacerbated by non-flat surfaces, as well as a reduction in the overall number of components and mechanical mounts., Comment: Submitted to Nature Astronomy

The detection by the LHAASO Collaboration of the gamma-ray burst GRB 221009A at redshift $z = 0.151$ with energies up to $(13-18) \, \rm TeV$ challenges conventional physics. Photons emitted with energies above $10 \, \rm TeV$ at this redshift can hardly be observed on Earth due to their interaction with the extragalactic background light (EBL). We show that indeed the LHAASO Collaboration should not have observed photons with energies above $10 \, \rm TeV$ if the state-of-the-art EBL model by Saldana-Lopez et al. is taken into account. A problem therefore arises: the Universe should be more transparent than currently believed. We also show that the issue is solved if we introduce the interaction of photons with axion-like particles (ALPs). ALPs are predicted by String Theory, are among the best candidates for dark matter and can produce spectral and polarization effects on astrophysical sources in the presence of external magnetic fields. In particular, for GRB 221009A, photon-ALP oscillations occur within the crossed magnetized media, i.e. the host galaxy, the extragalactic space, the Milky Way, partially reducing the EBL absorption to a level that explains the LHAASO detection of GRB 221009A and its observed spectrum without the need of contrived choices of parameter values, which are instead compulsory within proposed emission models within conventional physics. This fact regarding GRB 221009A represents a strong hint at the ALP existence, which adds to two other indications coming from blazars, a class of active galactic nuclei., Comment: 4 pages, 1 figure, contribution to the 2024 Very High Energy Phenomena in the Universe session of the 58th Rencontres de Moriond

We investigate gas transfer processes occurring at the air-water interface of progressive water waves using high-fidelity numerical simulations. Waves with varying initial steepness, including regular wave patterns, mild spilling and intense plunging breakers are examined. A multiphase solver is employed to model gas flux and diffusion processes enabling precise estimation of the air-water interface area and gas transfer velocity, achieving an accuracy unattainable in experiments. We reveal that the volume of gas transferred across the air-water interface increases significantly with the amount of air entrained due to wave breaking, peak values in the gas transfer velocity being concurrent with peaks in energy dissipation rate and air entrainment. Furthermore, the gas transfer velocity is observed to scale approximately as the one-fourth power of the energy dissipation rate, consistent with previous theoretical predictions. We anticipate that the present findings can help reduce the substantial uncertainty associated with parameterizing fundamental natural processes, such as CO2 absorption by the oceans.

The recent detection by LHAASO up to 18 TeV of the gamma ray burst GRB 221009A at redshift $z = 0.151$ challenges standard physics because of the strong absorption due to the extragalactic background light (EBL) for photons with energies above 10 TeV. Emission models partially avoiding EBL absorption proposed to explain such an event are unsatisfactory since they require peculiar and contrived assumptions. By introducing in magnetized media the interaction of photons with axion-like particles (ALPs) - which are a generic prediction of most theories extending the standard model of particle physics towards a more satisfying theory - the detection of GRB 221009A can be naturally explained, thereby providing a strong hint at ALP existence., Comment: 6 pages, 3 figures. Proceeding of the "ASTRI and LHAASO Workshop", Milan, Italy, 7 - 8 March 2023 (to appear in the Proceedings)

We revisit and extend the construction of six-dimensional orientifolds built upon the $T^4/\mathbb{Z}_N$ orbifolds with a non-vanishing Kalb-Ramond background, both in the presence of $\mathcal{N}=(1,0)$ supersymmetry and Brane Supersymmetry Breaking, thus amending some statements present in the literature. In the $N=2$ case, we show how the gauge groups on unoriented D9 and D5 (anti-)branes do not need to be correlated, but can be independently chosen complex or real. For $N>2$ we find that the Diophantine tadpole conditions severely constrain the vacua. Indeed, only the $N=4$ orbifold with a rank-two Kalb-Ramond background may admit integer solutions for the Chan-Paton multiplicities, if the $\mathbb{Z}_4$ fixed points support $\text{O}5_-$ planes, both with and without supersymmetry. All other cases would involve a fractional number of branes, which is clearly unacceptable. We check the consistency of the new $\mathbb{Z}_2$ and $\mathbb{Z}_4$ vacua by verifying the unitarity constraints for string defects coupled to Ramond-Ramond two-forms entering the Green-Schwarz-Sagnotti mechanism., Comment: 34 pages

Perovskites have recently brought significant advances to active nanophotonics, offering a unique combination of gain and phase-change properties for tunable light-emitting devices. However, current wavelength-tunable devices often rely on tuning mechanisms or device architectures that lead to slow modulation or bulky setups. In this study, we overcome limitations on speed and size by demonstrating a compact tunable microlaser embedding electrical microheaters beneath a perovskite metasurface. This architecture allows to efficiently deliver heat and rapidly modulate the phase transition. Our device leverages the optical gain and crystallographic phase tuning of the perovskite, and a high-quality factor cavity design based on bound states in the continuum. With it, we demonstrate reversible laser wavelength switching between 763 nm and 783 nm within 13 ms at 2.3 V. This work unlocks the potential of perovskite metasurfaces for electrically tunable light sources and introduces a flexible platform which can be easily extended to the dynamic control of polarization or directionality for optical communication, sensing and spectroscopy., Comment: 20 pages, 11 figures

The collection of updated data on social contact patterns following the COVID-19 pandemic disruptions is crucial for future epidemiological assessments and evaluating non-pharmaceutical interventions (NPIs) based on physical distancing. We conducted two waves of an online survey in March 2022 and March 2023 in Italy, gathering data from a representative population sample on direct (verbal/physical interactions) and indirect (prolonged co-location in indoor spaces) contacts. Using a generalized linear mixed model, we examined determinants of individuals' total social contacts and evaluated the potential impact of work-from-home and distance learning on the transmissibility of respiratory pathogens. In-person attendance at work or school emerged as a primary driver of social contacts. Adults attending in person reported a mean of 1.69 (95% CI: 1.56-1.84) times the contacts of those staying home; among children and adolescents, this ratio increased to 2.38 (95% CI: 1.98-2.87). We estimated that suspending all non-essential work alone would marginally reduce transmissibility. However, combining distance learning for all education levels with work-from-home policies could decrease transmissibility by up to 23.7% (95% CI: 18.2%-29.0%). Extending these measures to early childcare services would yield only minimal additional benefits. These results provide useful data for modelling the transmission of respiratory pathogens in Italy after the end of the COVID-19 emergency. They also provide insights into the potential epidemiological effectiveness of social distancing interventions targeting work and school attendance, supporting considerations on the balance between the expected benefits and their heavy societal costs., Comment: 10 pages, 2 tables, 3 figures

Spatial metapopulation models are fundamental to theoretical ecology, enabling to study how landscape structure influences global species dynamics. Traditional models, including recent generalizations, often rely on the deterministic limit of stochastic processes, assuming large population sizes. However, stochasticity - arising from dispersal events and population fluctuations - profoundly shapes ecological dynamics. In this work, we extend the classical metapopulation framework to account for finite populations, examining the impact of stochasticity on species persistence and dynamics. Specifically, we analyze how the limited capacity of local habitats influences survival, deriving analytical expressions for the finite-size scaling of the survival probability near the critical transition between survival and extinction. Crucially, we demonstrate that the deterministic metapopulation capacity plays a fundamental role in the statistics of survival probability and extinction time moments. These results provide a robust foundation for integrating demographic stochasticity into classical metapopulation models and their extensions.

As part of the BISTRO survey, we present JCMT 850 $\mu$m polarimetric observations towards the Orion Integral-Shaped Filament (ISF) that covers three portions known as OMC-1, OMC-2, and OMC-3. The magnetic field threading the ISF seen in the JCMT POL-2 map appears as a tale of three: pinched for OMC-1, twisted for OMC-2, and nearly uniform for OMC-3. A multi-scale analysis shows that the magnetic field structure in OMC-3 is very consistent at all the scales, whereas the field structure in OMC-2 shows no correlation across different scales. In OMC-1, the field retains its mean orientation from large to small scales, but shows some deviations at small scales. Histograms of relative orientations between the magnetic field and filaments reveal a bimodal distribution for OMC-1, a relatively random distribution for OMC-2, and a distribution with a predominant peak at 90$^\circ$ for OMC-3. Furthermore, the magnetic fields in OMC-1 and OMC-3 both appear to be aligned perpendicular to the fibers, which are denser structures within the filament, but the field in OMC-2 is aligned along with the fibers. All these suggest that gravity, turbulence, and magnetic field are each playing a leading role in OMC-1, 2, and 3, respectively. While OMC-2 and 3 have almost the same gas mass, density, and non-thermal velocity dispersion, there are on average younger and fewer young stellar objects in OMC-3, providing evidence that a stronger magnetic field will induce slower and less efficient star formation in molecular clouds., Comment: published in the ApJ Letters

Time series play a crucial role in many fields, including finance, healthcare, industry, and environmental monitoring. The storage and retrieval of time series can be challenging due to their unstoppable growth. In fact, these applications often sacrifice precious historical data to make room for new data. General-purpose compressors can mitigate this problem with their good compression ratios, but they lack efficient random access on compressed data, thus preventing real-time analyses. Ad-hoc streaming solutions, instead, typically optimise only for compression and decompression speed, while giving up compression effectiveness and random access functionality. Furthermore, all these methods lack awareness of certain special regularities of time series, whose trends over time can often be described by some linear and nonlinear functions. To address these issues, we introduce NeaTS, a randomly-accessible compression scheme that approximates the time series with a sequence of nonlinear functions of different kinds and shapes, carefully selected and placed by a partitioning algorithm to minimise the space. The approximation residuals are bounded, which allows storing them in little space and thus recovering the original data losslessly, or simply discarding them to obtain a lossy time series representation with maximum error guarantees. Our experiments show that NeaTS improves the compression ratio of the state-of-the-art lossy compressors that use linear or nonlinear functions (or both) by up to 14%. Compared to lossless compressors, NeaTS emerges as the only approach to date providing, simultaneously, compression ratios close to or better than the best existing compressors, a much faster decompression speed, and orders of magnitude more efficient random access, thus enabling the storage and real-time analysis of massive and ever-growing amounts of (historical) time series data., Comment: Accepted for publication in Proceedings of the 41st IEEE International Conference on Data Engineering (ICDE 2025)

High-resolution gridded climate data are readily available from multiple sources, yet climate research and decision-making increasingly require country and region-specific climate information weighted by socio-economic factors. Moreover, the current landscape of disparate data sources and inconsistent weighting methodologies exacerbates the reproducibility crisis and undermines scientific integrity. To address these issues, we have developed a globally comprehensive dataset at both country (GADM0) and region (GADM1) levels, encompassing various climate indicators (precipitation, temperature, SPEI, wind gust). Our methodology involves weighting gridded climate data by population density, night-time light intensity, cropland area, and concurrent population count -- all proxies for socio-economic activity -- before aggregation. We process data from multiple sources, offering daily, monthly, and annual climate variables spanning from 1900 to 2023. A unified framework streamlines our preprocessing steps, and rigorous validation against leading climate impact studies ensures data reliability. The resulting Weighted Climate Dataset is publicly accessible through an online dashboard at https://weightedclimatedata.streamlit.app/., Comment: 10 pages, 5 figures

The screened massive expansion of full QCD is used in conjunction with a model for infrared quark masses to compute the Landau-gauge gluon propagator at finite temperature and baryonic density. Analytic expressions up to a one-dimensional momentum integral are provided for the propagator, and its behavior is studied at zero Matsubara frequency with respect to temperature, chemical potential, and the parameters of the expansion. The phase diagram of QCD is explored under the assumption that the deconfinement temperature can be identified as the position of the maximum of the longitudinal gluon propagator at zero Matsubara frequency and fixed spatial momentum.

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/

This paper introduces a new generalized control method designed for multi-degrees-of-freedom devices to help people with limited motion capabilities in their daily activities. The challenge lies in finding the most adapted strategy for the control interface to effectively map user's motions in a low-dimensional space to complex robotic assistive devices, such as prostheses, supernumerary limbs, up to remote robotic avatars. The goal is a system which integrates the human and the robotic parts into a unique system, moving so as to reach the targets decided by the human while autonomously reducing the user's effort and discomfort. We present a framework to control general multi DoFs assistive systems, which translates user-performed compensatory motions into the necessary robot commands for reaching targets while canceling or reducing compensation. The framework extends to prostheses of any number of DoF up to full robotic avatars, regarded here as a sort of whole-body prosthesis of the person who sees the robot as an artificial extension of their own body without a physical link but with a sensory-motor integration. We have validated and applied this control strategy through tests encompassing simulated scenarios and real-world trials involving a virtual twin of the robotic parts (prosthesis and robot) and a physical humanoid avatar., Comment: Submitted to the International Journal of Robotics Research (IJRR), under review since October 2024, 16 pages, 30 figures

Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are prominent approaches for solving combinatorial optimization problems, such as those formulated as Quadratic Unconstrained Binary Optimization (QUBO). These algorithms aim to minimize the objective function $x^T Q x$, where $Q$ is a QUBO matrix. However, the number of two-qubit CNOT gates in QAOA circuits and the complexity of problem embeddings in Quantum Annealing scale linearly with the number of non-zero couplings in $Q$, contributing to significant computational and error-related challenges. To address this, we introduce the concept of \textit{semi-symmetries} in QUBO matrices and propose an algorithm for identifying and factoring these symmetries into ancilla qubits. \textit{Semi-symmetries} frequently arise in optimization problems such as \textit{Maximum Clique}, \textit{Hamilton Cycles}, \textit{Graph Coloring}, and \textit{Graph Isomorphism}. We theoretically demonstrate that the modified QUBO matrix $Q_{\text{mod}}$ retains the same energy spectrum as the original $Q$. Experimental evaluations on the aforementioned problems show that our algorithm reduces the number of couplings and QAOA circuit depth by up to $45\%$. For Quantum Annealing, these reductions also lead to sparser problem embeddings, shorter qubit chains and better performance. This work highlights the utility of exploiting QUBO matrix structure to optimize quantum algorithms, advancing their scalability and practical applicability to real-world combinatorial problems., Comment: arXiv admin note: substantial text overlap with arXiv:2411.08824

InAs on Insulator (InAsOI) has recently been demonstrated as a promising platform to develop hybrid semiconducting-superconducting electronics, which features an InAs epilayer grown onto a cryogenic insulating InAlAs metamorphic buffer. The miniaturization of Si microchips has progressed significantly due to the integration of high permittivity (high-k) gate insulators, compared to the conventional thermally-growth SiO2. Here, we investigate the gate-tunable electrical properties of InAsOI-based Josephson Field Effect Transistors (JoFETs) featuring different high-k gate insulators, namely, HfO2 and Al2O3. With both dielectrics, the JoFETs can entirely suppress the switching current and increase the normal state resistance by 10-20 times using negative gate voltages. The HfO2-JoFETs exhibit improved gate-tunable electrical performance compared to those achieved with Al2O3-JoFETs, which is related to the higher permittivity of the insulator. Gate-dependent electrical properties of InAsOI-based JoFETs were evaluated in the temperature range from 50 mK to 1 K. Moreover, under the influence of an out-of-plane magnetic field, JoFETs exhibited an unconventional Fraunhofer diffraction pattern., Comment: 16 pages, 4 figures, supporting information at the end of the paper

Motivated by empirical evidence from the joint behavior of realized volatility time series, we propose to model the joint dynamics of log-volatilities using a multivariate fractional Ornstein-Uhlenbeck process. This model is a multivariate version of the Rough Fractional Stochastic Volatility model proposed in Gatheral, Jaisson, and Rosenbaum, Quant. Finance, 2018. It allows for different Hurst exponents in the different marginal components and non trivial interdependencies. We discuss the main features of the model and propose an estimator that jointly identifies its parameters. We derive the asymptotic theory of the estimator and perform a simulation study that confirms the asymptotic theory in finite sample. We carry out an extensive empirical investigation on all realized volatility time series covering the entire span of about two decades in the Oxford-Man realized library. Our analysis shows that these time series are strongly correlated and can exhibit asymmetries in their cross-covariance structure, accurately captured by our model. These asymmetries lead to spillover effects that we analyse theoretically within the model and then using our empirical estimates. Moreover, in accordance with the existing literature, we observe behaviors close to non-stationarity and rough trajectories., Comment: 32 pages, 12 figures

From life sciences and ecology to quantum physics and finance, anomalous diffusion appears in countless complex systems as a signature of emergent transport properties beyond Brownian motion. Despite substantial theoretical progress, the experimental study of real-world systems exhibiting anomalous diffusion remains challenging due to an intrinsically elusive ground truth and the limited information contained in typical single trajectories. Here, unlike previous experimental systems, we demonstrate the controlled generation of two-dimensional trajectories with fully tailored statistics spanning the entire spectrum of anomalous diffusion, from subdiffusion to superdiffusion, and over statistically significant temporal and spatial scales (covering at least two decades). We achieve this feat by simultaneously tuning the step-length distribution and, critically, the velocity autocorrelation function of microscopic superparamagnetic colloidal walkers with magnetic fields during extended acquisitions. Supported by theoretical reasoning, fine control of these two quantities combined allows us to generate trajectories compatible with L\'evy walks and fractional Brownian motion with tailored anomalous diffusion exponents. We envisage our approach will offer a robust, controllable experimental framework for validating and advancing theoretical models, analysis techniques, and predictive tools to study anomalous diffusion in real-life phenomena. These include transport in physical and biological systems, animal movement, human ecology, and financial markets.

The search for new gravity-like interactions at the sub-millimeter scale is a compelling area of research, with important implications for the understanding of classical gravity and its connections with quantum physics. We report improved constraints on Yukawa-type interactions in the $10\,\mathrm{\mu m}$ regime using optically levitated dielectric microspheres as test masses. The search is performed, for the first time, sensing multiple spatial components of the force vector, and with sensitivity improved by a factor of $\sim 100$ with respect to previous measurements using the same technique. The resulting upper limit on the strength of a hypothetical new force is $10^7$ at a Yukawa range $\lambda\simeq 5\;\mu$m and close to $10^6$ for $\lambda \gtrsim 10\;\mu$m. This result also advances our efforts to measure gravitational effects using micrometer-size objects, with important implications for embryonic ideas to investigate the quantum nature of gravity.

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

Obtaining high certainty in predictive models is crucial for making informed and trustworthy decisions in many scientific and engineering domains. However, extensive experimentation required for model accuracy can be both costly and time-consuming. This paper presents an adaptive sampling approach designed to reduce epistemic uncertainty in predictive models. Our primary contribution is the development of a metric that estimates potential epistemic uncertainty leveraging prediction interval-generation neural networks. This estimation relies on the distance between the predicted upper and lower bounds and the observed data at the tested positions and their neighboring points. Our second contribution is the proposal of a batch sampling strategy based on Gaussian processes (GPs). A GP is used as a surrogate model of the networks trained at each iteration of the adaptive sampling process. Using this GP, we design an acquisition function that selects a combination of sampling locations to maximize the reduction of epistemic uncertainty across the domain. We test our approach on three unidimensional synthetic problems and a multi-dimensional dataset based on an agricultural field for selecting experimental fertilizer rates. The results demonstrate that our method consistently converges faster to minimum epistemic uncertainty levels compared to Normalizing Flows Ensembles, MC-Dropout, and simple GPs., Comment: Accepted to appear in AAAI 2025

Cryogenic phonon detectors are adopted in experiments searching for dark matter interactions or coherent elastic neutrino-nucleus scattering, thanks to the low energy threshold they can achieve. The phonon-mediated sensing of particle interactions in passive silicon absorbers has been demonstrated with Kinetic Inductance Detectors (KIDs). Targets with neutron number larger than silicon, however, feature higher cross section to neutrinos while multi-target absorbers in dark matter experiments would provide a stronger evidence of a possible signal. In this work we present the design, fabrication and operation of KIDs coupled to a germanium absorber, achieving phonon-sensing performance comparable to silicon absorbers. The device introduced in this work is a proof of concept for a scalable neutrino detector and for a multi-target dark matter experiment., Comment: 3 Figures, 2 Tables, 5 pages

Fidelity quantum kernels have shown promise in classification tasks, particularly when a group structure in the data can be identified and exploited through a covariant feature map. In fact, there exist classification problems on which covariant kernels provide a provable advantage, thus establishing a separation between quantum and classical learners. However, their practical application poses two challenges: on one side, the group structure may be unknown and approximate in real-world data, and on the other side, scaling to the `utility' regime (above 100 qubits) is affected by exponential concentration. In this work, we address said challenges by applying fidelity kernels to real-world data with unknown structure, related to the scheduling of a fleet of electric vehicles, and to synthetic data generated from the union of subspaces, which is then close to many relevant real-world datasets. Furthermore, we propose a novel error mitigation strategy specifically tailored for fidelity kernels, called Bit Flip Tolerance (BFT), to alleviate the exponential concentration in our utility-scale experiments. Our multiclass classification reaches accuracies comparable to classical SVCs up to 156 qubits, thus constituting the largest experimental demonstration of quantum machine learning on IBM devices to date. For the real-world data experiments, the effect of the proposed BFT becomes manifest on 40+ qubits, where mitigated accuracies reach 80%, in line with classical, compared to 33% without BFT. Through the union-of-subspace synthetic dataset with 156 qubits, we demonstrate a mitigated accuracy of 80%, compared to 83% of classical models, and 37% of unmitigated quantum, using a test set of limited size.

Different hybrid quantum-classical algorithms have recently been developed as a near-term way to solve linear systems of equations on quantum devices. However, the focus has so far been mostly on the methods, rather than the problems that they need to tackle. In fact, these algorithms have been run on real hardware only for problems in quantum physics, such as Hamiltonians of a few qubits systems. These problems are particularly favorable for quantum hardware, since their matrices are the sum of just a few unitary terms and since only shallow quantum circuits are required to estimate the cost function. However, for many interesting problems in linear algebra, it appears far less trivial to find an efficient decomposition and to trade it off with the depth of the cost quantum circuits. A first simple yet interesting instance to consider are tridiagonal systems of equations. These arise, for instance, in the discretization of one-dimensional finite element analyses. This work presents a method to solve a class of tridiagonal systems of equations with the variational quantum linear solver (VQLS), a recently proposed variational hybrid algorithm for solving linear systems. In particular, we present a new decomposition for this class of matrices based on both Pauli strings and multi--qubit gates, resulting in less terms than those obtained by just using Pauli gates. Based on this decomposition, we discuss the tradeoff between the number of terms and the near-term implementability of the quantum circuits. Furthermore, we present the first simulated and real-hardware results obtained by solving tridiagonal linear systems with VQLS, using the decomposition proposed., Comment: 7 pages, 2 figures, 2 tables

This paper presents a novel control algorithm for robotic manipulators in unstructured environments using proximity sensors partially distributed on the platform. The proposed approach exploits arrays of multi zone Time-of-Flight (ToF) sensors to generate a sparse point cloud representation of the robot surroundings. By employing computational geometry techniques, we fuse the knowledge of robot geometric model with ToFs sensory feedback to generate whole-body motion tasks, allowing to move both sensorized and non-sensorized links in response to unpredictable events such as human motion. In particular, the proposed algorithm computes the pair of closest points between the environment cloud and the robot links, generating a dynamic avoidance motion that is implemented as the highest priority task in a two-level hierarchical architecture. Such a design choice allows the robot to work safely alongside humans even without a complete sensorization over the whole surface. Experimental validation demonstrates the algorithm effectiveness both in static and dynamic scenarios, achieving comparable performances with respect to well established control techniques that aim to move the sensors mounting positions on the robot body. The presented algorithm exploits any arbitrary point on the robot surface to perform avoidance motion, showing improvements in the distance margin up to 100 mm, due to the rendering of virtual avoidance tasks on non-sensorized links., Comment: Submitted for evaluation at the IEEE/ASME Transactions on Mechatronics Journal

We prove that most Artin groups of large and hyperbolic type are Hopfian, meaning that every self-epimorphism is an isomorphism. The class covered by our result is generic, in the sense of Goldsborough-Vaskou. Moreover, assuming the residual finiteness of certain hyperbolic groups with an explicit presentation, we get that all large and hyperbolic type Artin groups are residually finite. We also show that most quotients of the five-holed sphere mapping class group are hierarchically hyperbolic, up to taking powers of the normal generators of the kernels. The main tool we use to prove both results is a Dehn-filling-like procedure for short hierarchically hyperbolic groups (these also include e.g. non-geometric 3-manifolds, and triangle- and square-free RAAGs)., Comment: 55 pages, 9 figures. All comments are gladly welcome!

Intuitively, prostheses with user-controllable stiffness could mimic the intrinsic behavior of the human musculoskeletal system, promoting safe and natural interactions and task adaptability in real-world scenarios. However, prosthetic design often disregards compliance because of the additional complexity, weight, and needed control channels. This paper focuses on designing a Variable Stiffness Actuator (VSA) with weight, size, and performance compatible with prosthetic applications, addressing its implementation for the elbow joint. While a direct biomimetic approach suggests adopting an Agonist-Antagonist (AA) layout to replicate the biceps and triceps brachii with elastic actuation, this solution is not optimal to accommodate the varied morphologies of residual limbs. Instead, we employed the AA layout to craft an elbow prosthesis fully contained in the user's forearm, catering to individuals with distal transhumeral amputations. Additionally, we introduce a variant of this design where the two motors are split in the upper arm and forearm to distribute mass and volume more evenly along the bionic limb, enhancing comfort for patients with more proximal amputation levels. We characterize and validate our approach, demonstrating that both architectures meet the target requirements for an elbow prosthesis. The system attains the desired 120{\deg} range of motion, achieves the target stiffness range of [2, 60] Nm/rad, and can actively lift up to 3 kg. Our novel design reduces weight by up to 50% compared to existing VSAs for elbow prostheses while achieving performance comparable to the state of the art. Case studies suggest that passive and variable compliance could enable robust and safe interactions and task adaptability in the real world., Comment: This article has been accepted for publication in IEEE Transactions on Robotics. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/TRO.2024.3492372

In recent years, artificial feet based on soft robotics and under-actuation principles emerged to improve mobility on challenging terrains. This paper presents the application of the MuJoCo physics engine to realize a digital twin of an adaptive soft foot developed for use with legged robots. We release the MuJoCo soft foot digital twin as open source to allow users and researchers to explore new approaches to locomotion. The work includes the system modeling techniques along with the kinematic and dynamic attributes involved. Validation is conducted through a rigorous comparison with bench tests on a physical prototype, replicating these experiments in simulation. Results are evaluated based on sole deformation and contact forces during foot-obstacle interaction. The foot model is subsequently integrated into simulations of the humanoid robot COMAN+, replacing its original flat feet. Results show an improvement in the robot's ability to negotiate small obstacles without altering its control strategy. Ultimately, this study offers a comprehensive modeling approach for adaptive soft feet, supported by qualitative comparisons of bipedal locomotion with state of the art robotic feet.

Nowadays, many tools are used to facilitate forensic tasks about data extraction and data analysis. In particular, some tools leverage Artificial Intelligence (AI) to automatically label examined data into specific categories (\ie, drugs, weapons, nudity). However, this raises a serious concern about the robustness of the employed AI algorithms against adversarial attacks. Indeed, some people may need to hide specific data to AI-based digital forensics tools, thus manipulating the content so that the AI system does not recognize the offensive/prohibited content and marks it at as suspicious to the analyst. This could be seen as an anti-forensics attack scenario. For this reason, we analyzed two of the most important forensics tools employing AI for data classification: Magnet AI, used by Magnet Axiom, and Excire Photo AI, used by X-Ways Forensics. We made preliminary tests using about $200$ images, other $100$ sent in $3$ chats about pornography and teenage nudity, drugs and weapons to understand how the tools label them. Moreover, we loaded some deepfake images (images generated by AI forging real ones) of some actors to understand if they would be classified in the same category as the original images. From our preliminary study, we saw that the AI algorithm is not robust enough, as we expected since these topics are still open research problems. For example, some sexual images were not categorized as nudity, and some deepfakes were categorized as the same real person, while the human eye can see the clear nudity image or catch the difference between the deepfakes. Building on these results and other state-of-the-art works, we provide some suggestions for improving how digital forensics analysis tool leverage AI and their robustness against adversarial attacks or different scenarios than the trained one.

The third r-process peak (Os, Ir, Pt) is poorly understood due to observational challenges, with spectral lines located in the blue or near-ultraviolet region of stellar spectra. These challenges need to be overcome for a better understanding of the r-process in a broader context. To understand how the abundances of the third r-process peak are synthesised and evolve in the Universe, a homogeneous chemical analysis of metal-poor stars using high quality data observed in the blue region of the electromagnetic spectrum (< 400 nm) is necessary. We provide a homogeneous set of abundances for the third r-process peak (Os, Ir, Pt) and Hf, increasing by up to one order of magnitude their availability in the literature. A classical 1D, local thermodynamic equilibrium (LTE) analysis of four elements (Hf, Os, Ir, Pt) is performed, using ATLAS model atmospheres to fit synthetic spectra in high resolution (> 40,000), high signal-to-noise ratio, of 52 red giants observed with UVES/VLT. Due to the heavy line blending involved, a careful determination of upper limits and uncertainties is done. The observational results are compared with state-of-the-art nucleosynthesis models. Our sample displays larger abundances of Ir (Z=77) in comparison to Os (Z=76), which have been measured in a few stars in the past. The results also suggest decoupling between abundances of third r-process peak elements with respect to Eu (rare earth element) in Eu-poor stars. This seems to contradict a co-production scenario of Eu and the third r-process peak elements Os, Ir, and Pt in the progenitors of these objects. Our results are challenging to explain from the nucleosynthetic point of view: the observationally derived abundances indicate the need for an additional early, primary formation channel (or a non-robust r-process)., Comment: 15 pages, 11 figures, Accepted for publication in A&A

We study numerically wave turbulence in a Bose-Einstein condensate in the forced and dissipated inverse cascade settings. We observe that when the forcing rate is increased, the turbulence spectrum gradually transitions from the weak-wave turbulence Kolmogorov-Zakharov cascade to a critical balance state characterised by a range of scales with balanced linear and nonlinear dynamic timescales. Further forcing increase leads to emergence of a coherent condensate component superimposed with Bogolyubov-type acoustic turbulence.