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Le rôle des socialisations multiples dans le développement de l’inclusion occupationnelle des individus en formation-emploi
No full textInternational audienc
Existence and uniqueness of the solution to a class of Fredholm Integral Equations related to Difference Equations
No full textInternational audienceThis paper addresses the existence and uniqueness of the solution to a class of Fredholm integral equations associated with scalar Linear Integral Delay Equations (LIDEs). Based on an operator-theoretic framework involving transport partial differential equations, we provide general conditions that guarantee well-posedness of these equations. Leveraging this result, we introduce a constructive approach for the numerical computation of the Lyapunov matrix corresponding to scalar LIDEs with commensurate delays. Specifically, the Lyapunov matrix equations are reformulated as the Fredholm integral equation under consideration, for which the proposed conditions are satisfied under exponential stability of the LIDE. The resulting integral equation can then be discretized, and the linear system efficiently solved to compute the Delay Lyapunov matrix. Numerical examples illustrate the effectiveness and applicability of this methodology
Black Hole Spectroscopy and Tests of General Relativity with GW250114
No full textInternational audienceThe binary black hole signal GW250114, the loudest gravitational wave detected to date, offers a unique opportunity to test Einstein’s general relativity (GR) in the high-velocity, strong-gravity regime and probe whether the remnant conforms to the Kerr metric. Upon perturbation, black holes emit a spectrum of damped sinusoids with specific, complex frequencies. Our analysis of the postmerger signal shows that at least two quasinormal modes are required to explain the data, with the most damped remaining statistically significant for about one cycle. We probe the remnant’s Kerr nature by constraining the spectroscopic pattern of the dominant quadrupolar (ℓ=m=2) mode and its first overtone to match the Kerr prediction to tens of percent at multiple postpeak times. The measured mode amplitudes and phases agree with a numerical-relativity simulation having parameters close to GW250114. By fitting a parametrized waveform that incorporates the full inspiral-merger-ringdown sequence, we constrain the fundamental (ℓ=m=4) mode to tens of percent and bound the quadrupolar frequency to within a few percent of the GR prediction. We perform a suite of tests—spanning inspiral, merger, and ringdown—finding constraints that are comparable to, and in some cases 2–3 times more stringent than those obtained by combining dozens of events in the fourth Gravitational-Wave Transient Catalog. These results constitute the most stringent single-event verification of GR and the Kerr nature of black holes to date, and outline the power of black-hole spectroscopy for future gravitational-wave observations
Directional Search for Persistent Gravitational Waves: Results from the First Part of LIGO-Virgo-KAGRA's Fourth Observing Run
No full textInternational audienceThe angular distribution of gravitational-wave power from persistent sources may exhibit anisotropies arising from the large-scale structure of the Universe. This motivates directional searches for astrophysical and cosmological gravitational-wave backgrounds, as well as continuous-wave emitters. We present results of such a search using data from the first observing run through the first portion of the fourth observing run of the LIGO-Virgo-KAGRA Collaborations. We apply gravitational-wave radiometer techniques to generate skymaps and search for both narrowband and broadband persistent gravitational-wave sources. Additionally, we use spherical harmonic decomposition to probe spatially extended sources. No evidence of persistent gravitational-wave signals is found, and we set the most stringent constraints to date on such emissions. For narrowband point sources, our sensitivity estimate to effective strain amplitude lies in the range across all sky and frequency range Hz. For targeted sources -- Scorpius X-1, SN 1987A, the Galactic Center, Terzan 5, and NGC 6397 -- we constrain the strain amplitude with best limits ranging from to . For persistent broadband sources, we constrain the gravitational-wave flux F_{α, \hat{n}}^{95\%, \mathrm{UL}}(25\, \mathrm{Hz}) < (0.008 - 5.5) \times 10^{-8}\, \mathrm{erg\, cm^{-2}\, s^{-1}\, Hz^{-1}}, depending on the sky direction and spectral index . Finally, for extended sources, we place upper limits on the strain angular power spectrum C_\ell^{1/2} < (0.63 - 17) \times 10^{-10} \,\mathrm{sr}^{-1}
On Forgetting and Stability of Score-based Generative Models
No full textUnderstanding the stability and long-time behavior of generative models is a fundamental problem in modern machine learning.This paper provides quantitative bounds on the sampling error of score-based generative models by leveraging stability and forgetting properties of the Markov chain associated with the reverse-time dynamics.Under weak assumptions, we provide the two structural properties to ensure the propagation of initialization and discretization errors of the backward process: a Lyapunov drift condition and a Doeblin-type minorization condition.A practical consequence is quantitative stability of the sampling procedure, as the reverse diffusion dynamics induces a contraction mechanism along the sampling trajectory.Our results clarify the role of stochastic dynamics in score-based models and provide a principled framework for analyzing propagation of errors in such approaches
Recent advances in metal hybrid additive manufacturing: a comprehensive review
No full textInternational audienceAbstract Metal additive manufacturing (AM) holds significant potential for rapid prototyping of complex parts in aerospace, defense and military industry, biomedicine and other fields. Despite its advantages over conventional manufacturing methods, AM faces technical bottlenecks (e.g., poor densification, high residual stress, and significant anisotropy of mechanical properties), which hinder its large-scale industrial application. The newly emerging metal hybrid additive manufacturing (MHAM) serves as a viable approach to address the inherent issues associated with AM. This method integrates different auxiliary technologies (e.g., subtractive manufacturing, formative manufacturing, magnetic field, ultrasonic field, thermal field, etc.), leveraging the strengths of these technologies to enhance the precision and performance of metal components produced via AM. Metal hybrid additive manufacturing facilitates advantageous outcomes like controlling the flow of the melt pool, refining microstructure, optimizing grain size orientation, reducing residual stress, enhancing surface quality, and improving mechanical properties and fatigue resistance. This work offers a thorough and current analysis of the state of MHAM development, including additive and subtractive hybrid manufacturing, additive and formative hybrid manufacturing, and energy field assisted additive manufacturing. It delineates the MHAM technology framework and clarifies the interaction mechanisms among various auxiliary technologies used in AM. Additionally, it discusses the impacts of MHAM on melt pool dynamics, solidification processes, densification, microstructure evolution, surface quality improvements, as well as mechanical and fatigue properties. In summary, the distinct characteristics of various MHAM techniques are outlined, and future trends in MHAM development are anticipated
Leveraging Cutting-Edge High Performance Computing for Large-Scale Applications
No full textInternational audienceHigh Performance Computing (HPC) recently entered into the exascale era, marking an important milestone of its history. High-end supercomputers and clusters with remarkable levels of performance are now commonly available for general and specific computational needs, thereby increasing the focus on HPC and related topics. Leveraging the potential of high-speed processing units is an HPC skillful task that requires in-depth knowledge in both hardware and software domains. In fact, the architectural structure of cutting-edge HPC processors is complex and involves several specialized features provided through specific units/mechanisms, the processing constraint/overhead of which can turn out to be an efficiency bottleneck. Large-scale supercomputers present greater challenges due to the significant overhead associated with interprocessor communication and synchronization. The evolution of HPC appears closely tied to the growing demand for speed from large-scale applications like complex combinatorial problems, big data applications, the training of large-scale AI models and high-precision simulations, to name a few. As a result, the implementation of cutting-edge techniques should remain scalable on large-scale machines for the benefit of end-users
Structure and crystallization kinetics of PVDF/organoclay nanocomposites processed by twin-screw extrusion and electrical contact poling
No full textInternational audienc
A strong-weak duality for the 1d long-range Ising model
No full textInternational audienceWe investigate the one-dimensional Ising model with long-range interactions decaying as . In the critical regime, for , this system realizes a family of nontrivial one-dimensional conformal field theories (CFTs), whose data vary continuously with . For s>1 the model has instead no phase transition at finite temperature, as in the short-range case. In the standard field-theoretic description, involving a generalized free field with quartic interactions, the critical model is weakly coupled near but strongly coupled in the vicinity of the short-range crossover at . We introduce a dual formulation that becomes weakly coupled as . Precisely at , the dual description becomes an exactly solvable conformal boundary condition of the two-dimensional free scalar. We present a detailed study of the dual model and demonstrate its effectiveness by computing perturbatively the CFT data near , up to next-to-next-to-leading order in , by two independent approaches: (i) standard renormalization of our dual field-theoretic description and (ii) the analytic conformal bootstrap. The two methods yield complete agreement
Flexiblity-Aware Residential Consumption Forecasting: a Hybrid Machine Learning and Foundation Model Approach for Nudge-based Demand Response
No full textInternational audienceDistribution system operators (DSOs) increasingly rely on demand-side flexibility to manage grid constraints and integrate renewable energy. The flexibility signals may take different forms, such as price-based incentives, but behavioral nudging mechanisms, such as SMS alerts to encourage the consumer to shift their consumption during high solar production or curtailment calls to reduce load during peak demand, seem a good alternative to those intrusive signals and have been tested in Grenoble, France, in the context of the EXPESIGNO project. However, accurate short-term demand forecasting under flexibility activations remains challenging,[1] especially at the local and residential scale. Indeed, traditional models definitely do not capture the behavioral heterogeneity and temporal dynamics of the responses of households to nudges. To address it, this work suggests a hybrid two-stage forecasting architecture that combines a lightweight model (Random Forest/XGBoost/LightGBM) for alert prediction with the Chronos (Amazon) Time series foundation model for consumption forecasting. Tested on the EXPESIGNO dataset (175 French households, 28 flexibility events, 2019-2021),[2] our approach achieves moderate alert prediction accuracy and demonstrates that reactive households exhibit +11% consumption increase during green alerts and 18% reduction during orange alerts, with an improved forecasting accuracy for responsive households versus non-responsive ones