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Probabilistic Heat Transfer Coupled For Improved Urban Climate Predictions
No full textOur cities are getting hotter, particularly during heatwaves, which impacts our comfort and energy bills. It is crucial to predict how heat moves through complex urban areas, from buildings to streets, in order to design cooler, more sustainable cities. However, current methods struggle to cope with the complexity of urban landscapes. This paper introduces a revolutionary computer model that addresses this challenge. Using the Monte Carlo technique, our model can accurately simulate combined heat transfer in complex city geometry, accounting for precise thermal and solar radiative heat transfers. Unlike previous models, ours can handle intricate city designs with ease, enabling us to understand the combined effects of conduction, convection and radiation. We have demonstrated the high accuracy of our model, even in detailed 3D city environments. For example, we used it to simulate a heatwave, demonstrating that planting trees can significantly cool streets during the day, although they might slightly reduce night-time radiative cooling. This new tool will empower researchers to improve the coupling of building energy models with urban climate models, and ultimately create cities that are more comfortable and energy-efficient for all.</div
A Menagerie of Wormholes and Cosmologies in the Gravitational Path Integral
No full textInternational audienceWe analyse a variety of Euclidean saddles in the gravitational path integral, with asymptotic AdS boundary conditions, in a class of Einstein-Scalar-Maxwell models. These include single boundary solutions, usual and wineglass wormholes, as well as more exotic (quasi)-oscillatory saddles. Our construction shows how an unbound number of oscillations gets tamed, when flat directions of the potential get lifted. We find several interesting phase transitions between these solutions. The Euclidean wormhole backgrounds can be analytically continued to Lorentzian FLRW universes. Some of them contain an early period of inflation. We delineate the conditions under which they can be the dominant saddles in the gravitational path integral and use them to estimate ratios of probabilities for different cosmological outcomes
On the Impact of the Utility in Semivalue-based Data Valuation
No full text44 pages, 19 figures.International audienceSemivalue–based data valuation uses cooperative‐game theory intuitions to assign each data point a value reflecting its contribution to a downstream task. Still, those values depend on the practitioner’s choice of utility, raising the question: How robust is semivalue-based data valuation to changes in the utility? This issue is critical when the utility is set as a trade‐off between several criteria and when practitioners must select among multiple equally valid utilities. We address this by introducing the notion of a dataset’s spatial signature: given a semivalue, we embed each data point into a lower-dimensional space in which any utility becomes a linear functional, making the data valuation framework amenable to a simpler geometric picture. Building on this, we propose a practical methodology centered on an explicit robustness metric that informs practitioners whether and by how much their data valuation results will shift as the utility changes. We validate this approach across diverse datasets and semivalues, demonstrating strong agreement with rank‐correlation analyses and offering analytical insight into how choosing a semivalue can amplify or diminish robustness
Code de Conduite du GDR-IFM
No full textThis code of conduct was written by the PÉDI committee. On 21 November 2025, the GDR executive committee unanimously approved (with one abstention) a motion that this code has to be accepted by any person participating in any event organised or funded by the GDR.Ce code de bonne conduite a été rédigé par le comité PÉDI. Le comité exécutif du GDR du 21 novembre 2025 a voté à l’unanimité moins un vote blanc le principe selon lequel ce code devait être approuvé par toute personne participant à un événement organisé ou financé par le GDR
Hall thruster modeling with multiple simulation techniques: Model benchmarking, fluid–kinetic consistency, and experimental validation
No full textInternational audienceNumerical plasma models are critical tools for aiding the design and understanding of electric propulsion systems, such as Hall thrusters, particularly when considering challenges associated with diagnostic access and reliable internal measurements. For complex plasma systems, such as Hall thrusters, theoretical verification solutions are often missing, and therefore, benchmarking represents an important element in assessing the correctness and consistency of the underlying mathematical model, and the computational performance of the numerical implementation. In this work, we benchmark three different numerical codes by simulating an SPT-100 Hall thruster under identical operating conditions. The codes include one-dimensional stationary and non-stationary fluid models describing the axial thruster direction, as well as a two-dimensional axial–azimuthal Particle-In-Cell/Monte Carlo Collision (PIC/MCC) model. A partial validation is performed with available experimental measurements of the discharge current, thrust, and anode specific impulse, showing good agreement. Overall, the fluid and PIC/MCC models compare favorably with each other, and several fluid approximations are found to be acceptable. For example, axial electron energy transport is relatively minor such that the electron temperature is reasonably determined by a local energy balance. Other approximations, however, require a more careful examination: particularly the assumption of Maxwellian electrons and the neglect of electron–wall collisions in the electron momentum balance equations
Unsupervised data-driven detection of exceptional atmospheric trajectories
No full textExtreme weather events in Europe are closely linked to the large-scale atmospheric circulation and often develop over several consecutive days. Most existing circulation-based approaches focus on identify extreme weather patterns as instantaneous atmospheric states and therefore do not explicitly account for the temporal evolution of the flow. In this study, we apply a data-driven and unsupervised methodology to identify rare atmospheric trajectories from reanalysis data. The method quantifies how isolated short segments of atmospheric evolution are within the space of all observed trajectories, using daily sea-level pressure fields over Europe. We apply the approach to several decades of reanalysis data and identify the most isolated trajectories for different trajectory lengths. The detected trajectories are characterised by large-scale circulation anomalies and strong pressure gradients. A comparison with independent databases of European extreme events shows a statistically significant overlap, particularly for windstorms. Increasing the trajectory length enhances the detection of multi-day events, indicating that the method captures persistent atmospheric evolutions rather than isolated states. In addition to windstorms, the detected trajectories correspond to cold spells and blocking-like circulation patterns, as well as events that are not systematically documented in existing pan-European databases. These results indicate that analysing rare atmospheric trajectories provides complementary information to state-based approaches and offers a general framework for the detection of extreme atmospheric evolutions in reanalysis datasets
Observation of the decay
No full textInternational audienceThe first observation of the decay is reported using proton-proton collision data recorded with the LHCb detector corresponding to an integrated luminosity of . The decay mode is observed for the first time, with a significance of . Its branching fraction is measured relative to the decay mode \begin{align*} \frac{\cal{BF}(χ_{c1}(3872)\rightarrow J\mskip -3mu/\mskip -2muψμ^+μ^-)}{\cal{BF}(χ_{c1}(3872)\rightarrow J\mskip -3mu/\mskip -2muψπ^+π^-)} = \left(1.64\pm 0.32\pm 0.05\right)\times10^{-3}, \end{align*} where the first uncertainty includes both statistical contributions and systematic contributions which are uncorrelated between data-taking periods, and the second represents the systematic contributions that are correlated between data-taking periods
Full event interpretation with machine-learning-based particle-flow reconstruction in the CMS detector
No full textInternational audienceThe particle-flow (PF) algorithm constructs a global description of each particle collision by producing a comprehensive list of final-state particles, and is central to event reconstruction in the CMS experiment at the CERN LHC. The existing PF implementation relies on physics-motivated heuristics and assumptions that can be replaced by machine-learning (ML) models trained directly on simulated data and naturally suited to modern graphics processing units (GPUs). A state-of-the-art ML-based PF (MLPF) reconstruction algorithm, implemented within the CMS software framework, is presented. The MLPF algorithm performs a learnable full-event reconstruction on GPUs, generalizes across detector conditions and collision energies, and replaces multiple modular reconstruction steps with a single unified model. Physics performance comparable to standard PF reconstruction is achieved in both simulation and data, with improved jet energy resolution and inference time. In simulated top quark-antiquark events under LHC Run-3 (20232024) conditions, the jet energy resolution improves by 1020% for jets with transverse momentum between 30100 GeV. Inference time is evaluated using simulated multijet events, with a median of 20 ms per event on an Nvidia L4 GPU, compared to approximately 110 ms for the standard CMS PF reconstruction
A 3D-shell model of left atrial electromechanics
No full textThe thin-walled nature of the atrial myocardium can lead to artificial stiffening when full 3D electromechanical models are discretized using standard finite elements. In this work, we propose an electromechanical model of the left atrium based on a 3D-shell formulation that overcomes these limitations. The model incorporates both passive and active components of atrial tissue mechanics, while atrioventricular interaction is described by the coupling with a 0D electromechanical model of the left ventricle. The proposed approach is assessed under physiological and pathological conditions and systematically compared with the standard full 3D formulation. The results demonstrate the superior robustness and computational efficiency of the proposed 3D-shell electromechanical model
Entropic Mirror Monte Carlo
No full textImportance sampling is a Monte Carlo method which designs estimators of expectations under a target distribution using weighted samples from a proposal distribution. When the target distribution is complex, such as multimodal distributions in highdimensional spaces, the efficiency of importance sampling critically depends on the choice of the proposal distribution. In this paper, we propose a novel adaptive scheme for the construction of efficient proposal distributions. Our algorithm promotes efficient exploration of the target distribution by combining global sampling mechanisms with a delayed weighting procedure. The proposed weighting mechanism plays a key role by enabling rapid resampling in regions where the proposal distribution is poorly adapted to the target. Our sampling algorithm is shown to be geometrically convergent under mild assumptions and is illustrated through various numerical experiments