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Spatially-Controlled Planar Guided Crystallization of Low-Loss Phase Change Materials for Programmable Photonics
No full textInternational audiencePhotonic integrated devices are progressively evolving beyond passive components into fully programmable systems, notably driven by the progress in chalcogenide phase-change materials (PCMs) for non-volatile reconfigurable nanophotonics. However, the stochastic nature of their crystal grain formation results in strong spatial and temporal crystalline inhomogeneities. Here, we propose the concept of spatially-controlled planar Czochralski growth, a novel method for programming the quasi-monocrystalline growth of low-loss Sb2S3 PCM, leveraging the seeded directional and progressive crystallization within confined channels. This guided crystallization method is experimentally shown to circumvent the current limitations of conventional PCM-based nanophotonic devices, including a multilevel non-volatile optical phase-shifter exploiting a silicon nitride-based Mach-Zehnder interferometer, and a programmable metasurface with spectrally reconfigurable bound state in the continuum. Precisely controlling the growth of PCMs to ensure uniform crystalline properties across large areas is the cornerstone for the industrial development of non-volatile reconfigurable photonic integrated circuits
Eco-friendly Insulating Materials for Transformers in MVDC and HVDC Power Networks
No full textInternational audienceThis work investigates the viability of natural and synthetic ester liquids as potential alternatives to mineral oil in MVDC and HVDC transformer insulation systems. Finite Element Method simulations (FEM) were performed using the measured dielectric properties of the oils and their impregnated pressboards as input parameters to evaluate their influence on steady state electric field distribution. A comparison on the field distribution under AC and DC condition is performed for the different materials, identifying regions of maximum stress around the corona head and high voltage electrode. The temperature dependence of electrical conductivity values of the materials and their effect on the steady state DC electric field distribution is explored. The higher conductivity of ester liquids when compared to mineral oil provides a more uniform field redistribution between the oil and pressboard, also facilitating the shift of maximum electrical stress from the oil to pressboard. The results support the technical merits of using ester-based insulation material for field stress equalization in HVDC networks
Experimental study on gravity currents flowing on heated walls
No full textWe present an experimental study on steady gravity currents advancing along a heated wall. The current is generated by a mixture of air and carbon dioxide continuously supplied at the channel inlet. To have a complete point-wise characterization of the flow, simultaneous high-frequency measurements of two velocity components, CO_2 concentration, and temperature are performed. An experimental protocol is presented to reconstruct the local fluid density and to estimate turbulent vertical and horizontal fluxes of CO_2, temperature, and buoyancy. The reliability of both the flow measurements and of the estimate of convective heat flux exchanged at the wall is assessed through integral balances of \textnormal{CO} mass, enthalpy, and buoyancy, performed at different distances from the source. Three wall-heating conditions are considered: an adiabatic case, a moderately heated case, and a strongly heated case. In the heated experiments, a convectively unstable boundary layer forms near the wall, capped by a stably stratified region. The influence of this condition on the first- and second-order flow statistics profiles is examined. Although wall heating influences the vertical shear, the Brunt-Vaisala frequency, and both shear and buoyancy production of turbulent kinetic energy within the stably-stratified region characterized by an almost constant vertical gradient of streamwise velocity, neither the gradient Richardson number nor the flux Richardson number exhibits a clear trend in this region with the imposed wall heat flux
Joint reconstruction and pansharpening for high-resolution hyperspectral single-pixel imaging
No full textInternational audienceWe address the problem of single-pixel hyperspectral imaging, which requires balancing acquisition speed and spatial resolution. To improve spatial resolution when acquiring a small number of measurements in low-light conditions, we leverage side information from a high-resolution grayscale camera. Our joint reconstruction and fusion approach combines hyperspectral measurements and the grayscale image by minimizing a hand-crafted cost function that incorporates smooth spatial regularization and a low-rank approximation. Experiments on synthetic data show that our method improves spatial fidelity and per-pixel accuracy in photon-limited settings while preserving spectral alignment
Warm-Starting Collision-Free Model Predictive Control With Object-Centric Diffusion
No full textInternational audienceActing in cluttered environments requires predicting and avoiding collisions while still achieving precise control. Conventional optimization-based controllers can enforce physical constraints, but they struggle to produce feasible solutions quickly when many obstacles are present. Diffusion models can generate diverse trajectories around obstacles, yet prior approaches lacked a general and efficient way to condition them on scene structure. In this paper, we show that combining diffusion-based warmstarting conditioned with a latent object-centric representation of the scene and with a collision-aware model predictive controller (MPC) yields reliable and efficient motion generation under strict time limits. Our approach conditions a diffusion transformer on the system state, task, and surroundings, using an objectcentric slot attention mechanism to provide a compact obstacle representation suitable for control. The sampled trajectories are refined by an optimal control problem that enforces rigidbody dynamics and signed-distance collision constraints, producing feasible motions in real time. On benchmark tasks, this hybrid method achieved markedly higher success rates and lower latency than sampling-based planners or either component alone. Real-robot experiments with a torque-controlled Panda confirm reliable and safe execution with MPC. An open-source implementation is provided here
Gaussian Mixture Model with unknown diagonal covariances via continuous sparse regularization
No full textThis paper addresses the statistical estimation of Gaussian Mixture Models (GMMs) with unknown diagonal covariances from independent and identically distributed samples. We employ the Beurling-LASSO (BLASSO), a convex optimization framework that promotes sparsity in the space of measures, to simultaneously estimate the number of components and their parameters. Our main contribution extends the BLASSO methodology to multivariate GMMs with component-specific unknown diagonal covariance matrices. This setting is significantly more flexible than previous approaches, which required known and identical covariances. We establish non-asymptotic recovery guarantees with nearly parametric convergence rates for component means, diagonal covariances, and weights, as well as for density prediction. A key theoretical contribution is the identification of an explicit separation condition on mixture components that enables the construction of non-degenerate dual certificates—essential tools for establishing statistical guarantees for the BLASSO. Our analysis leverages the Fisher-Rao geometry of the statistical model and introduces a novel semi-distance adapted to our framework, providing new insights into the interplay between component separation, parameter space geometry, and achievable statistical recovery
Weak error estimates of fully-discrete schemes for the stochastic Cahn-Hilliard equation
No full textInternational audienceWe study a class of fully-discrete schemes for the numerical approximation of solutions of stochastic Cahn-Hilliard equations with cubic nonlinearity and driven by additive noise. The spatial (resp. temporal) discretization is performed with a spectral Galerkin method (resp. a tamed exponential Euler method). We consider two situations: space-time white noise in dimension d " 1 and trace-class noise in dimensions d " 1, 2, 3. In both situations, we prove weak error estimates, where the weak order of convergence is twice the strong order of convergence with respect to the spatial and temporal discretization parameters. To prove these results, we show appropriate regularity estimates for solutions of the Kolmogorov equation associated with the stochastic Cahn-Hilliard equation, which have not been established previously and may be of interest in other contexts
Topological Properties of Photonic Bands with Synthetic Momentum
No full textInternational audienceWe investigate topological aspects of photonic crystal bands in a hybrid momentum space consisting of a genuine momentum and a synthetic one. The system is realised by a one-dimensional system of bilayer photonic grating, with the translational displacement between the two layers naturally taking the role of the synthetic momentum. Remarkably, the unconventional behaviour of the synthetic momentum allows for the existence of non-trivial topological phases of the system associated with a non-zero total Berry flux without breaking the time-reversal symmetry. Moreover, the resulting band structure in the hybrid momentum space realises the interesting dynamics of merging and splitting of twin Dirac points, as well as gap opening as the system parameters vary. Introducing a simple topological argument, we explain all the changes of the total Berry flux associated with the topological phase transitions. As a signature of different topological phases, edge states at their interface are calculated and analysed in detail. The optomechanical nature of the system also allows for the investigation of the adiabatic evolution of the edge states. Our results pave the way to the paradigm of rich topological phenomena of photonic systems with hybrid momentum space
EVALUATING SEGMENTATION USING BETTI-1 TOPOLOGICAL METRIC: APPLICATION TO NASAL CAVITIES IN THE CONTEXT OF AIRFLOW SIMULATION
No full textInternational audienceComputational fluid dynamics (CFD) simulations offer an objective means to analyze nasal airflow. However, to be patient-specific, their accuracy relies on precise CT-based volume segmentation of the nasal cavity. Existing segmentation methods typically prioritize volumetric accuracy (e.g., Dice coefficient) while often overlooking topological fidelity, which is critical for generating anatomically consistent CFD meshes. To address this limitation, we propose an automatic nasal cavity segmentation framework based on nnUNet, augmented with a topology-based evaluation metric that quantifies differences in the number of tunnels between predicted and reference segmentations. Evaluation on the NasalSeg public dataset shows a Dice score of 0.947, comparable to state-of-the-art results, while improving the segmentation consistency by removing tunnels
Positional s-of-k games
No full textWe introduce a general framework for positional games in which players score points by claiming a prescribed portion of each winning set, extending the notion of scoring Maker-Breaker games. In the scoring variant, Maker gains a point by fully claiming a winning set, while Breaker aims to minimize Maker's total score. In this paper, we generalize these models for all k-uniform positional games by fixing an integer threshold s in {1,2,..., k} so that a player scores a point whenever she claims at least s elements of a winning set of size k. We refer to this class as s-of-k games. Such formulation allows for a flexible description of scoring objectives that appear in both theoretical models and real-life board games.We further investigate the impact of strategy restrictions on the achievable score. In particular, we analyze s-of-k games both under optimal play, where the score is denoted by SC, and under the additional constraint that Maker is restricted to a pairing strategy. The corresponding score in this setting is denoted by SC_2. While the unrestricted score captures the standard notion of optimal play in scoring positional games, the pairing-restricted score allows us to observe Maker's loss incurred by limiting her to these standard strategies.We comprehensively study s-of-k games played on regular grids, which provide a natural and uniform setting for illustrating the general framework. After developing several general tools for the analysis of both scores, we complement them by a number of ad-hoc strategies tailored for particular cases of these games, to obtain both upper and lower bounds for the two scores on triangular, square, rhombus and hexagonal grids