Publications

2025

• Refined Analysis of Federated Averaging's Bias and Federated Richardson-Romberg Extrapolation
  
  • Mangold Paul
  • Durmus Alain
  • Dieuleveut Aymeric
  • Samsonov Sergey
  • Moulines Eric
  , 2025. In this paper, we present a novel analysis of FedAvg with constant step size, relying on the Markov property of the underlying process. We demonstrate that the global iterates of the algorithm converge to a stationary distribution and analyze its resulting bias and variance relative to the problem's solution. We provide a first-order bias expansion in both homogeneous and heterogeneous settings. Interestingly, this bias decomposes into two distinct components: one that depends solely on stochastic gradient noise and another on client heterogeneity. Finally, we introduce a new algorithm based on the Richardson-Romberg extrapolation technique to mitigate this bias.
• Heath-Jarrow-Morton meet lifted Heston in energy markets for joint historical and implied calibration
  
  • Abi Jaber Eduardo
  • Bruneau Soukaïna
  • de Carvalho Nathan
  • Sotnikov Dimitri
  • Tur Laurent
  , 2025. In energy markets, joint historical and implied calibration is of paramount importance for practitioners yet notoriously challenging due to the need to align historical correlations of futures contracts with implied volatility smiles from the option market. We address this crucial problem with a parsimonious multiplicative multi-factor Heath-Jarrow-Morton (HJM) model for forward curves, combined with a stochastic volatility factor coming from the Lifted Heston model. We develop a sequential fast calibration procedure leveraging the Kemna-Vorst approximation of futures contracts: (i) historical correlations and the Variance Swap (VS) volatility term structure are captured through Level, Slope, and Curvature factors, (ii) the VS volatility term structure can then be corrected for a perfect match via a fixed-point algorithm, (iii) implied volatility smiles are calibrated using Fourier-based techniques. Our model displays remarkable joint historical and implied calibration fits -to both German power and TTF gas marketsand enables realistic interpolation within the implied volatility hypercube.
• Wavelet-Based Multiscale Flow For Realistic Image Deformation in the Large Diffeomorphic Deformation Model Framework
  
  • Gaudfernau Fleur
  • Blondiaux Eléonore
  • Allassonnière Stéphanie
  • Le Pennec Erwan
  Journal of Mathematical Imaging and Vision, Springer Verlag, 2025, 67 (2), pp.10. Estimating accurate high-dimensional transformations remains very challenging, especially in a clinical setting. In this paper, we introduce a multiscale parameterization of deformations to enhance registration and atlas estimation in the Large Deformation Diffeomorphic Metric Mapping framework. Using the Haar wavelet transform, a multiscale representation of the initial velocity fields is computed to optimize transformations in a coarse-to-fine fashion. This additional layer of spatial regularization does not modify the underlying model of deformations. As such, it preserves the original kernel Hilbert space structure of the velocity fields, enabling the algorithm to perform efficient gradient descent. Numerical experiments on several datasets, including abnormal fetal brain images, show that compared to the original algorithm, the coarse-to-fine strategy reaches higher performance and yields template images that preserve important details while avoiding unrealistic features. This highly versatile strategy can easily be applied to other mathematical frameworks for almost no additional computational cost. (10.1007/s10851-024-01219-5)
  DOI : 10.1007/s10851-024-01219-5
• Surface Waves in Randomly Perturbed Discrete Models
  
  • Garnier Josselin
  • Sharma Basant Lal
  Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Society for Industrial and Applied Mathematics, 2025, 23 (1), pp.158-186. (10.1137/24M165510X)
  DOI : 10.1137/24M165510X
• An exterior optimal transport problem
  
  • Candau-Tilh Jules
  • Goldman Michael
  • Merlet Benoît
  Calculus of Variations and Partial Differential Equations, Springer Verlag, 2025, 64 (2), pp.45. This paper deals with a variant of the optimal transportation problem. Given f ∈ L 1 (R d , [0, 1]) and a cost function c ∈ C(R d × R d) of the form c(x, y) = k(y − x), we minimise ∫ c dγ among transport plans γ whose first marginal is f and whose second marginal is not prescribed but constrained to be smaller than 1 − f. Denoting by Υ(f) the infimum of this problem, we then consider the maximisation problem sup{Υ(f) : ∫ f = m} where m > 0 is given. We prove that maximisers exist under general assumptions on k, and that for k radial, increasing and coercive these maximisers are the characteristic functions of the balls of volume m. (10.1007/s00526-024-02900-8)
  DOI : 10.1007/s00526-024-02900-8
• Polynomial approximations in a generalized Nyman–Beurling criterion
  
  • Alouges François
  • Darses Sébastien
  • Hillion Erwan
  , 2023, pp.767 - 785. The Nyman-Beurling criterion, equivalent to the Riemann hypothesis, is an approximation problem in the space of square integrable functions on $(0,\infty)$, involving dilations of the fractional part function by factors $\theta_k\in(0,1)$, $k\ge1$. Randomizing the $\theta_k$ generates new structures and criteria. One of them is a sufficient condition that splits into (i) showing that the indicator function can be approximated by convolution with the fractional part, (ii) a control on the coefficients of the approximation. This self-contained paper aims at identifying functions for which (i) holds unconditionally, by means of polynomial approximations. This yields in passing a short probabilistic proof of a known consequence of Wiener's Tauberian theorem. In order to tackle (ii) in the future, we give some expressions of the scalar products. New and remarkable structures arise for the Gram matrix, in particular moment matrices for a suitable weight that may be the squared $\Xi$-function for instance. (10.5802/jtnb.1227)
  DOI : 10.5802/jtnb.1227
• Understanding the worst-kept secret of high-frequency trading
  
  • Pulido Sergio
  • Rosenbaum Mathieu
  • Sfendourakis Emmanouil
  Finance and Stochastics, Springer Verlag (Germany), 2025. Volume imbalance in a limit order book is often considered as a reliable indicator for predicting future price moves. In this work, we seek to analyse the nuances of the relationship between prices and volume imbalance. To this end, we study a market-making problem which allows us to view the imbalance as an optimal response to price moves. In our model, there is an underlying efficient price driving the mid-price, which follows the model with uncertainty zones. A single market maker knows the underlying efficient price and consequently the probability of a mid-price jump in the future. She controls the volumes she quotes at the best bid and ask prices. Solving her optimization problem allows us to understand endogenously the price-imbalance connection and to confirm in particular that it is optimal to quote a predictive imbalance. Our model can also be used by a platform to select a suitable tick size, which is known to be a crucial topic in financial regulation. The value function of the market maker's control problem can be viewed as a family of functions, indexed by the level of the market maker's inventory, solving a coupled system of PDEs. We show existence and uniqueness of classical solutions to this coupled system of equations. In the case of a continuous inventory, we also prove uniqueness of the market maker's optimal control policy.
• Inexact subgradient methods for semialgebraic functions
  
  • Bolte Jérôme
  • Le Tam
  • Moulines Éric
  • Pauwels Edouard
  Mathematical Programming, Series A, Springer, 2025. Motivated by the extensive application of approximate gradients in machine learning and optimization, we investigate inexact subgradient methods subject to persistent additive errors. Within a nonconvex semialgebraic framework, assuming boundedness or coercivity, we establish that the method yields iterates that eventually fluctuate near the critical set at a proximity characterized by an $O(\epsilon^\rho)$ distance, where $\epsilon$ denotes the magnitude of subgradient evaluation errors, and $\rho$ encapsulates geometric characteristics of the underlying problem. Our analysis comprehensively addresses both vanishing and constant step-size regimes. Notably, the latter regime inherently enlarges the fluctuation region, yet this enlargement remains on the order of $\epsilon^\rho$. In the convex scenario, employing a universal error bound applicable to coercive semialgebraic functions, we derive novel complexity results concerning averaged iterates. Additionally, our study produces auxiliary results of independent interest, including descent-type lemmas for nonsmooth nonconvex functions and an invariance principle governing the behavior of algorithmic sequences under small-step limits. (10.1007/s10107-025-02245-w)
  DOI : 10.1007/s10107-025-02245-w
• Universal complexity bounds based on value iteration for stochastic mean payoff games and entropy games
  
  • Allamigeon Xavier
  • Gaubert Stéphane
  • Katz Ricardo
  • Skomra Mateusz
  Information and Computation, Elsevier, 2025, 302, pp.105236. We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to a given precision. We show that the number of calls to the oracle needed to determine exact optimal (positional) strategies is, up to a factor polynomial in the dimension, of order R/sep, where the “separation” sep is defined as the minimal difference between distinct values arising from strategies, and R is a metric estimate, involving the norm of approximate sub and super-eigenvectors of the dynamic programming operator. We illustrate this method by two applications. The first one is a new proof, leading to improved complexity estimates, of a theorem of Boros, Elbassioni, Gurvich and Makino, showing that turn-based mean-payoff games with a fixed number of random positions can be solved in pseudo-polynomial time. The second one concerns entropy games, a model introduced by Asarin, Cervelle, Degorre, Dima, Horn and Kozyakin. The rank of an entropy game is defined as the maximal rank among all the ambiguity matrices determined by strategies of the two players. We show that entropy games with a fixed rank, in their original formulation, can be solved in polynomial time, and that an extension of entropy games incorporating weights can be solved in pseudo-polynomial time under the same fixed rank condition. (10.1016/j.ic.2024.105236)
  DOI : 10.1016/j.ic.2024.105236
• Ergodic control of a heterogeneous population and application to electricity pricing
  
  • Jacquet Quentin
  • van Ackooij Wim
  • Alasseur Clémence
  • Gaubert Stéphane
  IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2025, 70 (7). We consider a control problem for a heterogeneous population composed of agents able to switch at any time between different options. The controller aims to maximize an average gain per time unit, supposing that the population is of infinite size. This leads to an ergodic control problem for a “mean-field” Markov Decision Process in which the state space is a product of simplices, and the population evolves according to controlled linear dynamics. By exploiting contraction properties of the dynamics in Hilbert’s projective metric, we prove that the infinite-dimensional ergodic eigenproblem admits a solution and show that the latter is in general non unique. This allows us to obtain optimal strategies, and to quantify the gap between steady-state strategies and optimal ones. In particular, we prove in the one-dimensional case that there exist cyclic policies – alternating between discount and profit taking stages – which secure a greater gain than constant-price policies. On numerical aspects, we develop a policy iteration algorithm with “on-the-fly” generated transitions, specifically adapted to decomposable models, leading to substantial memory savings. We finally apply our results on realistic instances coming from an electricity pricing problem encountered in the retail markets, and numerically observe the emergence of cyclic promotions for sufficient inertia in the customer behavior.
• Optimal Liquidation with Signals: the General Propagator Case
  
  • Abi Jaber Eduardo
  • Neuman Eyal
  Mathematical Finance, Wiley, 2025, 35 (4), pp.841–866. We consider a class of optimal liquidation problems where the agent's transactions create transient price impact driven by a Volterra-type propagator along with temporary price impact. We formulate these problems as minimization of a revenue-risk functionals, where the agent also exploits available information on a progressively measurable price predicting signal. By using an infinite dimensional stochastic control approach, we characterize the value function in terms of a solution to a free-boundary $L^2$-valued backward stochastic differential equation and an operator-valued Riccati equation. We then derive analytic solutions to these equations which yields an explicit expression for the optimal trading strategy. We show that our formulas can be implemented in a straightforward and efficient way for a large class of price impact kernels with possible singularities such as the power-law kernel.
• A new approach for the unitary Dyson Brownian motion through the theory of viscosity solutions
  
  • Bertucci Charles
  • Pesce Valentin
  , 2025. In this paper, we study the unitary Dyson Brownian motion through a partial differential equation approach recently introduced for the real Dyson case. The main difference with the real Dyson case is that the spectrum is now on the circle and not on the real line, which leads to particular attention to comparison principles. First we recall why the system of particles which are the eigenvalues of unitary Dyson Brownian motion is well posed thanks to a containment function. Then we proved that the primitive of the limit spectral measure of the unitary Dyson Brownian motion is the unique solution to a viscosity equation obtained by primitive the Dyson equation on the circle. Finally, we study some properties of solutions of Dyson's equation on the circle. We prove a L ∞ regularization. We also look at the long time behaviour in law of a solution through a study of the so-called free entropy of the system. We conclude by discussing the uniform convergence towards the uniform measure on the circle of a solution of the Dyson equation.
• Maxwell's equations with hypersingularities at a negative index material conical tip
  
  • Bonnet-Ben Dhia Anne-Sophie
  • Chesnel Lucas
  • Rihani Mahran
  Pure and Applied Analysis, Mathematical Sciences Publishers, 2025, 7 (1), pp.127–169. We study a transmission problem for the time harmonic Maxwell's equations between a classical positive material and a so-called negative index material in which both the permittivity ε and the permeability µ take negative values. Additionally, we assume that the interface between the two domains is smooth everywhere except at a point where it coincides locally with a conical tip. In this context, it is known that for certain critical values of the contrasts in ε and in µ, the corresponding scalar operators are not of Fredholm type in the usual H^1 spaces. In this work, we show that in these situations, the Maxwell's equations are not well-posed in the classical L^2 framework due to existence of hypersingular fields which are of infinite energy at the tip. By combining the T-coercivity approach and the Kondratiev theory, we explain how to construct new functional frameworks to recover well-posedness of the Maxwell's problem. We also explain how to select the setting which is consistent with the limiting absorption principle. From a technical point of view, the fields as well as their curls decompose as the sum of an explicit singular part, related to the black hole singularities of the scalar operators, and a smooth part belonging to some weighted spaces. The analysis we propose rely in particular on the proof of new key results of scalar and vector potential representations of singular fields.
• Proximal Point Nash Learning from Human Feedback
  
  • Tiapkin Daniil
  • Calandriello Daniele
  • Belomestny Denis
  • Moulines Eric
  • Naumov Alexey
  • Rasul Kashif
  • Valko Michal
  • Menard Pierre
  , 2025. Traditional Reinforcement Learning from Human Feedback (RLHF) often relies on reward models, frequently assuming preference structures like the Bradley--Terry model, which may not accurately capture the complexities of real human preferences (e.g., intransitivity). Nash Learning from Human Feedback (NLHF) offers a more direct alternative by framing the problem as finding a Nash equilibrium of a game defined by these preferences. While many works study the Nash learning problem directly in the policy space, we instead consider it under a more realistic policy parametrization setting. We first analyze a simple self-play policy gradient method, which is equivalent to Online IPO. We establish high-probability last-iterate convergence guarantees for this method, but our analysis also reveals a possible stability limitation of the underlying dynamics. Motivated by this, we embed the self-play updates into a proximal point framework, yielding a stabilized algorithm. For this combined method, we prove high-probability last-iterate convergence and discuss its more practical version, which we call Nash Prox. Finally, we apply this method to post-training of large language models and validate its empirical performance. (10.48550/arXiv.2505.19731v2)
  DOI : 10.48550/arXiv.2505.19731v2
• Ergodic behavior of products of random positive operators
  
  • Ligonnière Maxime
  ALEA : Latin American Journal of Probability and Mathematical Statistics, Instituto Nacional de Matemática Pura e Aplicada (Rio de Janeiro, Brasil) [2006-....], 2025, XXII, pp.93-129. This article is devoted to the study of products of random operators of the form $M_{0,n}=M_0\cdots M_{n-1}$, where $(M_{n})_{n\geq 0}$ is an ergodic sequence of positive operators acting on the space of signed measures on some set $\XX$. Under suitable conditions, in particular, a Doeblin-type minoration suited for non conservative operators, we obtain asymptotic results of the form \[ \mu M_{0,n} \simeq \mu({h}) r_n \pi_n,\] for any positive measure $\mu$, where $\tilde{h}$ is a random bounded function, $(r_n)_{n\geq 0}$ is a random non negative sequence and $(\pi_n)$ is a random sequence of probability measures on $\XX$. Moreover, $\tilde{h}$, $(r_n)$ and $(\pi_n)$ do not depend on the choice of the measure $\mu$. We prove additionally that $n^{-1} \log (r_n)$ converges almost surely to the Lyapunov exponent $\lambda$ of the process $(M_{0,n})_{n\geq 0}$ and that the sequence of random probability measures $(\pi_n)$ converges weakly towards a random probability measure. These results are analogous to previous estimates from Hennion in the case of $d\times d$ matrices, that were obtained with different techniques, based on a projective contraction in Hilbert distance. In the case where the sequence $(M_n)$ is i.i.d, we additionally exhibit an expression of the Lyapunov exponent $\lambda$ as an integral with respect to the weak limit of the sequence of random probability measures $(\pi_n)$ and exhibit an oscillation behavior of $r_n$ and $\Vert \mu M_{0,n} \Vert$ when $\lambda=0$. We provide a detailed comparison of our assumptions with the ones of Hennion and present an example of application of our results to the modelling of an age structured population. (10.30757/ALEA.v22-03)
  DOI : 10.30757/ALEA.v22-03
• Bridging multifluid and drift-diffusion models for bounded plasmas
  
  • Gangemi G M
  • Alvarez Laguna Alejandro
  • Massot M.
  • Hillewaert K.
  • Magin T.
  Physics of Plasmas, American Institute of Physics, 2025, 32 (2), pp.023502. Fluid models represent a valid alternative to kinetic approaches in simulating low-temperature discharges: a well-designed strategy must be able to combine the ability to predict a smooth transition from the quasineutral bulk to the sheath, where a space charge is built at a reasonable computational cost. These approaches belong to two families: multifluid models, where momenta of each species are modeled separately, and drift-diffusion models, where the dynamics of particles is dependent only on the gradient of particle concentration and on the electric force. It is shown that an equivalence between the two models exists and that it corresponds to a threshold Knudsen number, in the order of the square root of the electron-to-ion mass ratio; for an argon isothermal discharge, this value is given by a neutral background pressure Pn≳1000 Pa. This equivalence allows us to derive two analytical formulas for a priori estimation of the sheath width: the first one does not need any additional hypothesis but relies only on the natural transition from the quasineutral bulk to the sheath; the second approach improves the prediction by imposing a threshold value for the charge separation. The new analytical expressions provide better estimations of the floating sheath dimension in collisions-dominated regimes when tested against two models from the literature. (10.1063/5.0240640)
  DOI : 10.1063/5.0240640
• Dynamics of a kinetic model describing protein exchanges in a cell population
  
  • Magal Pierre
  • Raoul Gaël
  Journal of Mathematical Biology, Springer, 2025, 91 (6), pp.76. We consider a cell population structured by a positive real number, describing the number of P-glycoproteins carried by the cell. We are interested in the effect of those proteins on the growth of the population: those proteins are indeed involve in the resistance of cancer cells to chemotherapy drugs. To describe this dynamics, we introduce a kinetic model. We then introduce a rigorous hydrodynamic limit, showing that if the exchanges are frequent, then the dynamics of the model can be described by a system of two coupled differential equations. Finally, we also show that the kinetic model converges to a unique limit in large times. The main idea of this analysis is to use Wasserstein distance estimates to describe the effect of the kinetic operator, combined to more classical estimates on the macroscopic quantities. (10.1007/s00285-025-02295-w)
  DOI : 10.1007/s00285-025-02295-w
• A holographic global uniqueness in passive imaging
  
  • Novikov Roman
  Journal de l'École polytechnique — Mathématiques, École polytechnique, 2025, 12, pp.1069-1081. We consider a radiation solution $\psi$ for the Helmholtz equation in an exterior region in $\mathbb R^3$. We show that the restriction of $\psi$ to any ray $L$ in the exterior region is uniquely determined by its imaginary part Im $\psi$ on an interval of this ray. As a corollary, the restriction of $\psi$ to any plane $X$ in the exterior region is uniquely determined by Im $\psi$ on an open domain in this plane. These results have holographic prototypes in the recent work Novikov (2024, Proc. Steklov Inst. Math. 325, 218-223). In particular, these and known results imply a holographic type global uniqueness in passive imaging and for the Gelfand-Krein-Levitan inverse problem (from boundary values of the spectral measure in the whole space) in the monochromatic case. Some other surfaces for measurements instead of the planes $X$ are also considered. (10.5802/jep.306)
  DOI : 10.5802/jep.306
• From random matrices to systems of particles in interaction
  
  • Pesce Valentin
  , 2025. The goal of these expository notes is to give an introduction to random matrices for non-specialist of this topic focusing on the link between random matrices and systems of particles in interaction. We first recall some general results about the random matrix theory that create a link between random matrices and systems of particles through the knowledge of the law of the eigenvalues of certain random matrices models. We next focus on a continuous in time approach of random matrices called the Dyson Brownian motion. We detail some general methods to study the existence of system of particles in singular interaction and the existence of a mean field limit for these systems of particles. Finally, we present the main result of large deviations when studying the eigenvalues of random matrices. This method is based on the fact that the eigenvalues of certain models of random matrices can be viewed as log gases in dimension 1 or 2.
• Parameters estimation of a Threshold CKLS process from continuous and discrete observations
  
  • Mazzonetto Sara
  • Nieto Benoît
  Scandinavian Journal of Statistics, Wiley, 2025, 52 (4), pp.1670-1707. We consider a continuous time process that is self-exciting and ergodic, called threshold Chan–Karolyi–Longstaff–Sanders (CKLS) process. This process is a generalization of various models in econometrics, such as Vasicek model, Cox-Ingersoll-Ross, and Black-Scholes, allowing for the presence of several thresholds which determine changes in the dynamics. We study the asymptotic behavior of maximum-likelihood and quasi-maximum-likelihood estimators of the drift parameters in the case of continuous time and discrete time observations. We show that for high frequency observations and infinite horizon the estimators satisfy the same asymptotic normality property as in the case of continuous time observations. We also discuss diffusion coefficient estimation. Finally, we apply our estimators to simulated and real data to motivate considering (multiple) thresholds. (10.1111/sjos.70005)
  DOI : 10.1111/sjos.70005
• Tensor rectifiable G-flat chains
  
  • Goldman Michael
  • Merlet Benoît
  Transactions of the American Mathematical Society, American Mathematical Society, 2025. A rigidity result for normal rectifiable $k$-chains in $\mathbb{R}^n$ with coefficients in an Abelian normed group is established. Given some decompositions $k=k_1+k_2$, $n=n_1+n_2$ and some rectifiable $k$-chain $A$ in $\mathbb{R}^n$, we consider the properties: (1) The tangent planes to $\mu_A$ split as $T_x\mu_A=L^1(x)\times L^2(x)$ for some $k_1$-plane $L^1(x)\subset\mathbb{R}^{n_1}$ and some $k_2$-plane $L^2(x)\subset\mathbb{R}^{n_2}$. (2) $A=A_{\vert\Sigma^1\times\Sigma^2}$ for some sets $\Sigma^1\subset\mathbb{R}^{n_1}$, $\Sigma^2\subset\mathbb{R}^{n_2}$ such that $\Sigma^1$ is $k_1$-rectifiable and $\Sigma^2$ is $k_2$-rectifiable (we say that $A$ is $(k_1,k_2)$-rectifiable). The main result is that for normal chains, (1) implies (2), the converse is immediate. In the proof we introduce the new groups of tensor flat chains (or $(k_1,k_2)$-chains) in $\mathbb{R}^{n_1}\times\mathbb{R}^{n_2}$ which generalize Fleming's $G$-flat chains. The other main tool is White's rectifiable slices theorem. We show that on the one hand any normal rectifiable chain satisfying~(1) identifies with a normal rectifiable $(k_1,k_2)$-chain and that on the other hand any normal rectifiable $(k_1,k_2)$-chain is $(k_1,k_2)$-rectifiable. (10.1090/tran/9392)
  DOI : 10.1090/tran/9392
• Integrating Aggregated Electric Vehicle Flexibilities in Unit Commitment Models using Submodular Optimization
  
  • Arvis Hélène
  • Beaude Olivier
  • Gast Nicolas
  • Gaubert Stéphane
  • Gaujal Bruno
  , 2025. <div><p>The Unit Commitment (UC) problem consists in controlling a large fleet of heterogeneous electricity production units in order to minimize the total production cost while satisfying consumer demand. Electric Vehicles (EVs) are used as a source of flexibility and are often aggregated for problem tractability. We develop a new approach to integrate EV flexibilities in the UC problem and exploit the generalized polymatroid structure of aggregated flexibilities of a large population of users to develop an exact optimization algorithm, combining a cutting-plane approach and submodular optimization. We show in particular that the UC can be solved exactly in a time which scales linearly, up to a logarithmic factor, in the number of EV users when each production unit is subject to convex constraints. We illustrate our approach by solving a real instance of a long-term UC problem, combining open-source data of the European grid (European Resource Adequacy Assessment project) and data originating from a survey of user behavior of the French EV fleet.</p></div>
• Development of a rabbit model of uterine rupture after caesarean section, Histological, biomechanical and polarimetric analysis of the uterine tissue
  
  • Debras Elodie
  • Maudot Constance
  • Allain Jean-Marc
  • Pierangelo Angelo
  • Courilleau Aymeric
  • Rivière Julie
  • Dahirel Michèle
  • Richard Christophe
  • Gelin Valérie
  • Morin Gwendoline
  • Capmas Perrine
  • Chavatte-Palmer Pascale
  Reproduction & Fertility, Bioscientifica Ltd, 2025, 6 (4), pp.e-250018. Uterine rupture is a major complication of caesarean section (CS) associated with a high foetal and maternal morbidity. The objective is to develop an in-vivo model of uterus healing and rupture after CS in order to analyse histological phenomena controlling scarring tissue development and potential cause of defects. Eighteen pregnant primiparous female rabbits were bred naturally. At caesarean, after 28 days of gestation, foetuses were either extracted through a longitudinal incision in one of the uterine horns (“CS horn”) or via a short incision at the tip of the contralateral horn (“control horn”). The uterine horns were sutured by single layer, all by the same surgeon. They were mated again 14 days later and euthanized at G28. Genital tracts were collected for histological, biomechanical and polarimetric analyses. Macroscopically, 2/18 presented a dehiscence and 1/18 a spontaneous rupture. The mean thickness of the scarred area was significantly lower 0.9 mm [0.7-1.4] that the non-scarring area on CS horns 2.2 [1.6-2.3] or control horns 2 [1.5-2.3] (p&lt;0.0001). The scar zone was statistically more fibrous (p&lt;0.0001), containing fewer vessels (p=0.03) and oestrogen (p&lt;0.001) and progesterone receptors (p&lt;0.0001). After balloon inflation, ruptured occurred in the scar zone in 8 out of 17 cases (47%). Polarimetry revealed that the scar zone was statistically inhomogeneous (73%). Multifactorial analysis allowed to identify groups with poor uterine healing and less resistant to rupture (balloon inflation) mostly in case of thin myometrium in the scar and a group with strong resistant to rupture and correct healing characteristics. Lay summary Caesarean section rates are rising across the world. When a caesarean section is carried out, it can lead to scarring on the uterus that can affect its resistance to pressure. During the next pregnancy, the uterus can tear, increasing risks to the mother and baby. We carried out caesarean sections in a rabbit, allowing us to analyse the scar on the uterus, the healing and tissue resistance. The scarred part of the uterus was statistically thinner, more fibrous and contained fewer vessels and hormone receptors than the area without scarring. Under similar conditions, poor healing was observed in some animals, reducing resistance in following pregnancies. These results suggest that individual and genetic factor have an effect on healing after a caesarean section. This study may enable us to improve our knowledge and management care for patients who have a caesarean section in order to reduce complications. (10.1530/raf-25-0018)
  DOI : 10.1530/raf-25-0018
• From Stochastic Zakharov System to Multiplicative Stochastic Nonlinear Schrödinger Equation
  
  • Barrué Grégoire
  • de Bouard Anne
  • Debussche Arnaud
  Stochastics and Partial Differential Equations: Analysis and Computations, Springer US, 2025, pp.1-40. We study the convergence of a Zakharov system driven by a time white noise, colored in space, to a multiplicative stochastic nonlinear Schrödinger equation, as the ion-sound speed tends to infinity. In the absence of noise, the conservation of energy gives bounds on the solutions, but this evolution becomes singular in the presence of the noise. To overcome this difficulty, we show that the problem may be recasted in the diffusion-approximation framework, and make use of the perturbed test-function method. We also obtain convergence in probability. The result is limited to dimension one, to avoid too much technicalities. As a prerequisite, we prove the existence and uniqueness of regular solutions of the stochastic Zakharov system.
• An analysis of the noise schedule for score-based generative models
  
  • Strasman Stanislas
  • Ocello Antonio
  • Boyer Claire
  • Le Corff Sylvain
  • Lemaire Vincent
  Transactions on Machine Learning Research Journal, [Amherst Massachusetts]: OpenReview.net, 2022, 2025. Score-based generative models (SGMs) aim at estimating a target data distribution by learning score functions using only noise-perturbed samples from the target. Recent literature has focused extensively on assessing the error between the target and estimated distributions, gauging the generative quality through the Kullback-Leibler (KL) divergence and Wasserstein distances. Under mild assumptions on the data distribution, we establish an upper bound for the KL divergence between the target and the estimated distributions, explicitly depending on any time-dependent noise schedule. Under additional regularity assumptions, taking advantage of favorable underlying contraction mechanisms, we provide a tighter error bound in Wasserstein distance compared to state-of-the-art results. In addition to being tractable, this upper bound jointly incorporates properties of the target distribution and SGM hyperparameters that need to be tuned during training. Finally, we illustrate these bounds through numerical experiments using simulated and CIFAR-10 datasets, identifying an optimal range of noise schedules within a parametric family.