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Publications

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Sont listées ci-dessous, par année, les publications figurant dans l'archive ouverte HAL.

2015

  • Configuration Tracking for Mechanical Systems by Kinematic Reduction and Fast Oscillating Controls
    • Barbero-Liñán M.
    • Sigalotti Mario
    , 2015.
  • A Priori Error Estimate of a Multiscale Finite Element Method for Transport Modeling
    • Ouaki Franck
    • Allaire Grégoire
    • Desroziers Sylvain
    • Enchéry Guillaume
    SeMA Journal: Boletin de la Sociedad Española de Matemática Aplicada, Springer, 2015, 67 (1), pp.1-37. This work proposes an \textit{a priori} error estimate of a multiscale finite element method to solve convection-diffusion problems where both velocity and diffusion coefficient exhibit strong variations at a scale which is much smaller than the domain of resolution. In that case, classical discretization methods, used at the scale of the heterogeneities, turn out to be too costly. Our method, introduced in~\cite{ECCOMAS}, aims at solving this kind of problems on coarser grids with respect to the size of the heterogeneities by means of particular basis functions. These basis functions are defined using cell problems and are designed to reproduce the variations of the solution on an underlying fine grid. Since all cell problems are independent from each other, these problems can be solved in parallel, which makes the method very efficient when used on parallel architectures. This article focuses on the proof of an \textit{a priori} error estimate of this method.
  • Controllability of spin-boson systems
    • Boscain Ugo
    • Mason Paolo
    • Panati Gianluca
    • Sigalotti Mario
    Journal of Mathematical Physics, American Institute of Physics (AIP), 2015, 56. In this paper we study the so-called spin-boson system, namely {a two-level system} in interaction with a distinguished mode of a quantized bosonic field. We give a brief description of the controlled Rabi and Jaynes--Cummings models and we discuss their appearance in the mathematics and physics literature. We then study the controllability of the Rabi model when the control is an external field acting on the bosonic part. Applying geometric control techniques to the Galerkin approximation and using perturbation theory to guarantee non-resonance of the spectrum of the drift operator, we prove approximate controllability of the system, for almost every value of the interaction parameter.
  • Second order mean field games with degenerate diffusion and local coupling
    • Cardaliaguet Pierre
    • Graber J.
    • Porretta Alessio
    • Tonon Daniela
    Nonlinear Differential Equations and Applications, Springer Verlag, 2015, 22 (5), pp.1287-1317. We analyze a (possibly degenerate) second order mean field games system of partial differential equations. The distinguishing features of the model considered are (1) that it is not uniformly parabolic, including the first order case as a possibility, and (2) the coupling is a local operator on the density. As a result we look for weak, not smooth, solutions. Our main result is the existence and uniqueness of suitably defined weak solutions, which are characterized as minimizers of two optimal control problems. We also show that such solutions are stable with respect to the data, so that in particular the degenerate case can be approximated by a uniformly parabolic (viscous) perturbation.
  • Mathematical Methods in Elasticity Imaging
    • Ammari Habib
    • Bretin Elie
    • Garnier Josselin
    • Kang Hyeonbae
    • Lee Hyundae
    • Wahab Abdul
    , 2015, pp.240 p..
  • Dispersal is a major driver of the latitudinal diversity gradient of Carnivora
    • Rolland Jonathan
    • Condamine Fabien L.
    • Beeravolu Reddy Champak
    • Jiguet Frédéric
    • Morlon Hélène
    Global Ecology and Biogeography, Wiley, 2015, 24 (9), pp.1059 - 1071. <strong>Aim</strong> Understanding the relative contribution of diversification rates (speciation and extinction) and dispersal in the formation of the latitudinal diversity gradient - the decrease in species richness with increasing latitude - is a main goal of biogeography. The mammalian order Carnivora, which comprises 286 species, displays the traditional latitudinal diversity gradient seen in almost all mammalian orders. Yet the processes driving high species richness in the tropics may be fundamentally different in this group from that in other mammalian groups. Indeed, a recent study suggested that in Carnivora, unlike in all other major mammalian orders, net diversification rates are not higher in the tropics than in temperate regions. Our goal was thus to understand the reasons why there are more species of Carnivora in the tropics. <strong>Location</strong> World-wide. <strong>Methods</strong> We reconstructed the biogeographical history of Carnivora using a time-calibrated phylogeny of the clade comprising all terrestrial species and dispersal-extinction-cladogenesis models. We also analysed a fossil dataset of carnivoran genera to examine how the latitudinal distribution of Carnivora varied through time. <strong>Results</strong> Our biogeographical analyses suggest that Carnivora originated in the East Palaearctic (i.e. Central Asia, China) in the early Palaeogene. Multiple independent lineages dispersed to low latitudes following three main paths: toward Africa, toward India/Southeast Asia and toward South America via the Bering Strait. These dispersal events were probably associated with local extinctions at high latitudes. Fossil data corroborate a high-latitude origin of the group, followed by late dispersal events toward lower latitudes in the Neogene. <strong>Main conclusions</strong> Unlike most other mammalian orders, which originated and diversified at low latitudes and dispersed out of the tropics', Carnivora originated at high latitudes, and subsequently dispersed southward. Our study provides an example of combining phylogenetic and fossil data to understand the generation and maintenance of global-scale geographical variations in species richness. (10.1111/geb.12354)
    DOI : 10.1111/geb.12354
  • Definable Zero-Sum Stochastic Games
    • Bolte Jérôme
    • Gaubert Stéphane
    • Vigeral Guillaume
    Mathematics of Operations Research, INFORMS, 2015, 40 (1), pp.171-191. Definable zero-sum stochastic games involve a finite number of states and action sets, reward and transition functions that are definable in an o-minimal structure. Prominent examples of such games are finite, semi-algebraic or globally subanalytic stochastic games. We prove that the Shapley operator of any definable stochastic game with separable transition and reward functions is definable in the same structure. Definability in the same structure does not hold systematically: we provide a counterexample of a stochastic game with semi-algebraic data yielding a non semi-algebraic but globally subanalytic Shapley operator. %Showing the definability of the Shapley operator in full generality appears thus as a complex and challenging issue. } Our definability results on Shapley operators are used to prove that any separable definable game has a uniform value; in the case of polynomially bounded structures we also provide convergence rates. Using an approximation procedure, we actually establish that general zero-sum games with separable definable transition functions have a uniform value. These results highlight the key role played by the tame structure of transition functions. As particular cases of our main results, we obtain that stochastic games with polynomial transitions, definable games with finite actions on one side, definable games with perfect information or switching controls have a uniform value. Applications to nonlinear maps arising in risk sensitive control and Perron-Frobenius theory are also given. (10.1287/moor.2014.0666)
    DOI : 10.1287/moor.2014.0666
  • Hawkes Processes in Finance
    • Bacry Emmanuel
    • Mastromatteo Iacopo
    • Muzy Jean-François
    Market microstructure and liquidity, World scientific publishing company, 2015, 01 (01), pp.1550005. no abstract (10.1142/S2382626615500057)
    DOI : 10.1142/S2382626615500057
  • Second order BSDEs with jumps: formulation and uniqueness
    • Kazi-Tani Mohamed Nabil
    • Possamaï Dylan
    • Zhou Chao
    The Annals of Applied Probability, Institute of Mathematical Statistics (IMS), 2015, 25 (5), pp.2867-2908. (10.1214/14-AAP1063)
    DOI : 10.1214/14-AAP1063
  • New high order sufficient conditions for configuration tracking
    • Barbero-Liñán M.
    • Sigalotti M.
    Automatica, Elsevier, 2015, 62, pp.222-226. In this paper, we propose new conditions guaranteeing that the trajectories of a mechanical control system can track any curve on the configuration manifold. We focus on systems that can be represented as forced affine connection control systems and we generalize the sufficient conditions for tracking known in the literature. The new results are proved by a combination of averaging procedures by highly oscillating controls with the notion of kinematic reduction. (10.1016/j.automatica.2015.09.032)
    DOI : 10.1016/j.automatica.2015.09.032
  • Control of a Quantum Model for Two Trapped Ions
    • Paduro Esteban
    • Sigalotti Mario
    , 2015.
  • Remarks on the internal exponential stabilization to a nonstationary solution for 1D Burgers equations
    • Kröner Axel
    • Rodrigues Sergio S.
    SIAM Journal on Control and Optimization, Society for Industrial and Applied Mathematics, 2015, 53 (2), pp.1020–1055. The feedback stabilization of the Burgers system to a nonstationary solution using finite-dimensional internal controls is considered. Estimates for the dimension of the controller are derived. In the particular case of no constraint on the support of the controla better estimate is derived and the possibility of getting an analogous estimate for the general case is discussed; some numerical examplesare presented illustrating the stabilizing effect of the feedback control, and suggesting that the existence of an estimatein the general case analogous to that in the particular one is plausible.
  • Sparse and spurious: dictionary learning with noise and outliers
    • Gribonval Rémi
    • Jenatton Rodolphe
    • Bach Francis
    IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2015, 61 (11), pp.6298-6319. A popular approach within the signal processing and machine learning communities consists in modelling signals as sparse linear combinations of atoms selected from a learned dictionary. While this paradigm has led to numerous empirical successes in various fields ranging from image to audio processing, there have only been a few theoretical arguments supporting these evidences. In particular, sparse coding, or sparse dictionary learning, relies on a non-convex procedure whose local minima have not been fully analyzed yet. In this paper, we consider a probabilistic model of sparse signals, and show that, with high probability, sparse coding admits a local minimum around the reference dictionary generating the signals. Our study takes into account the case of over-complete dictionaries, noisy signals, and possible outliers, thus extending previous work limited to noiseless settings and/or under-complete dictionaries. The analysis we conduct is non-asymptotic and makes it possible to understand how the key quantities of the problem, such as the coherence or the level of noise, can scale with respect to the dimension of the signals, the number of atoms, the sparsity and the number of observations. (10.1109/TIT.2015.2472522)
    DOI : 10.1109/TIT.2015.2472522
  • Approximate Controllability of the Two Trapped Ions System
    • Paduro Esteban
    • Sigalotti Mario
    Quantum Information Processing, Springer Verlag, 2015, 14, pp.2397-2418. We prove the approximate controllability of a bilinear Schr\"odinger equation modelling a two trapped ions system. A new spectral decoupling technique is introduced, which allows to analyze the controllability of the infinite-dimensional system through finite-dimensional considerations.
  • Mathematical justification of macroscopic models for diffusion MRI through the periodic unfolding method
    • Coatléven Julien
    Asymptotic Analysis, IOS Press, 2015, 93 (3), pp.219-258. Diffusion Magnetic Resonance Imaging (dMRI) is a promising tool to obtain useful information on cellular structure when applied to biological tissues. A coupled macroscopic model has been introduced recently through formal homogenization to model dMRI's signal attenuation. This model was based on a particular scaling of the permeability condition modeling cellular membranes. In this article, we explore all the possible scalings and mathematically justify the corresponding limit models, using the periodic unfolding method. We also illustrate through numerical simulations the respective behavior of the limit models when compared to dMRI measurements. (10.3233/ASY-151294)
    DOI : 10.3233/ASY-151294
  • Finite element approximation of level set motion by powers of the mean curvature
    • Kröner Axel
    • Kröner Eva
    • Kröner Heiko
    , 2015. In this paper we study the level set formulations of certain geometric evolution equations from a numerical point of view. Specifically, we consider the flow by powers greater than one of the mean curvature and the inverse mean curvature flow. Since the corresponding equations in level set form are quasilinear, degenerate and especially possibly singular a regularization method is used in the literature to approximate these equations to overcome the singularities of the equations. Motivated by the paper [29] which studies the finite element approximation of inverse mean curvature flow we prove error estimates for the finite element approximation of the regularized equations for the flow by powers of the mean curvature. We validate the rates with numerical examples. Additionally, the regularization error in the rotational symmetric case for both flows is analyzed numerically. All calculations are performed in the 2D case.
  • Origin and diversification of living cycads: a cautionary tale on the impact of the branching process prior in Bayesian molecular dating
    • Condamine Fabien L.
    • Nagalingum Nathalie S.
    • Marshall Charles R
    • Morlon Hélène
    BMC Evolutionary Biology, BioMed Central, 2015, 15 (1). Background: Bayesian relaxed-clock dating has significantly influenced our understanding of the timeline of biotic evolution. This approach requires the use of priors on the branching process, yet little is known about their impact on divergence time estimates. We investigated the effect of branching priors using the iconic cycads. We conducted phylogenetic estimations for 237 cycad species using three genes and two calibration strategies incorporating up to six fossil constraints to (i) test the impact of two different branching process priors on age estimates, (ii) assess which branching prior better fits the data, (iii) investigate branching prior impacts on diversification analyses, and (iv) provide insights into the diversification history of cycads. Results: Using Bayes factors, we compared divergence time estimates and the inferred dynamics of diversification when using Yule versus birth-death priors. Bayes factors were calculated with marginal likelihood estimated with stepping-stone sampling. We found striking differences in age estimates and diversification dynamics depending on prior choice. Dating with the Yule prior suggested that extant cycad genera diversified in the Paleogene and with two diversification rate shifts. In contrast, dating with the birth-death prior yielded Neogene diversifications, and four rate shifts, one for each of the four richest genera. Nonetheless, dating with the two priors provided similar age estimates for the divergence of cycads from Ginkgo (Carboniferous) and their crown age (Permian). Of these, Bayes factors clearly supported the birth-death prior. Conclusions: These results suggest the choice of the branching process prior can have a drastic influence on our understanding of evolutionary radiations. Therefore, all dating analyses must involve a model selection process using Bayes factors to select between a Yule or birth-death prior, in particular on ancient clades with a potential pattern of high extinction. We also provide new insights into the history of cycad diversification because we found (i) periods of extinction along the long branches of the genera consistent with fossil data, and (ii) high diversification rates within the Miocene genus radiations. (10.1186/s12862-015-0347-8)
    DOI : 10.1186/s12862-015-0347-8
  • Phase retrieval for the Cauchy wavelet transform
    • Waldspurger Irène
    • Mallat Stéphane
    Journal of Fourier Analysis and Applications, Springer Verlag, 2015. We consider the phase retrieval problem in which one tries to reconstruct a function from the modulus of its wavelet transform. We study the unicity and stability of the reconstruction. In the case where the wavelets are Cauchy wavelets, we prove that the modulus of the wavelet transform uniquely determines the function up to a global phase. We show that the reconstruction operator is continuous but not uniformly continuous. We describe how to construct pairs of functions which are far away in L 2-norm but whose wavelet transforms are very close, in modulus. The principle is to modulate the wavelet transform of a fixed initial function by a phase which varies slowly in both time and frequency. This construction seems to cover all the instabilities that we observe in practice; we give a partial formal justification to this fact. Finally, we describe an exact reconstruction algorithm and use it to numerically confirm our analysis of the stability question.
  • A highly anisotropic nonlinear elasticity model for vesicles I. Eulerian formulation, rigidity estimates and vanishing energy limit
    • Merlet Benoit
    Archive for Rational Mechanics and Analysis, Springer Verlag, 2015, 217 (2), pp.651--680. We propose a nonlinear elasticity model for vesicle membranes which is an Eulerian version of a model introduced by Pantz and Trabelsi.We describe the limit behavior of sequences of configurations whose energy goes to 0 in a fixed domain. The material is highly anisotropic and the analysis is based on some rigidity estimates adapted to this anisotropy. The main part of the paper is devoted to these estimates and to some of their consequences. The strongest form of these estimates are used in a second article to derive the thin-shell limit bending theory of the model. (10.1007/s00205-014-0839-5)
    DOI : 10.1007/s00205-014-0839-5
  • Dobrushin ergodicity coefficient for Markov operators on cones
    • Gaubert Stéphane
    • Qu Zheng
    Integral Equations and Operator Theory, Springer Verlag, 2015, 1 (81), pp.127-150. Doeblin and Dobrushin characterized the contraction rate of Markov operators with respect the total variation norm. We generalize their results by giving an explicit formula for the contraction rate of a Markov operator over a cone in terms of pairs of extreme points with disjoint support in a set of abstract probability measures. By duality, we derive a characterization of the contraction rate of consensus dynamics over a cone with respect to Hopf’s oscillation seminorm (the infinitesimal seminorm associated with Hilbert’s projective metric). We apply these results to Kraus maps (noncommutative Markov chains, representing quantum channels), and characterize the ultimate contraction of the map in terms of the existence of a rank one matrix in a certain subspace. (10.1007/s00020-014-2193-2)
    DOI : 10.1007/s00020-014-2193-2
  • Analytical approximations of BSDEs with non-smooth driver
    • Gobet Emmanuel
    • Pagliarani Stefano
    SIAM Journal on Financial Mathematics, Society for Industrial and Applied Mathematics, 2015, 6 (1), pp.919-958. We provide and analyse analytical approximations of BSDEs in the limit of small non-linearity {and short time}, in the case of non-smooth drivers. We identify the first and the second order approximations within this asymptotics and consider two topical financial applications: the two interest rates problem and the Funding Value Adjustment. In high dimensional diffusion setting, we show how to compute explicitly the first order formula by taking advantage of recent proxy techniques. Numerical tests up to dimension 10 illustrate the efficiency of the numerical schemes. (10.1137/14100021X)
    DOI : 10.1137/14100021X
  • Sharp asymptotics of metastable transition times for one dimensional SPDEs
    • Barret Florent
    Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques, Institut Henri Poincaré (IHP), 2015, 51 (1), pp.129-166. We consider a class of parabolic semi-linear stochastic partial differential equations driven by space-time white noise on a compact space interval. Our aim is to obtain precise asymptotics of the transition times between metastable states. A version of the so-called Eyring-Kramers Formula is proven in an infinite dimensional setting. The proof is based on a spatial finite difference discretization of the stochastic partial differential equation. The expected transition time is computed for the finite dimensional approximation and controlled uniformly in the dimension.
  • An iterative approach to non-overdetermined inverse scattering at fixed energy
    • Novikov Roman
    Sbornik: Mathematics, Turpion, 2015, 206 (1), pp.120-134. We propose an iterative approximate reconstruction algorithm for non-overdetermined inverse scattering at fixed energy E with incomplete data in dimension d >= 2. In particular, we obtain rapidly converging approximate reconstructions for this inverse scattering for E --> +infinity.
  • Convergent stochastic Expectation Maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation
    • Allassonnière Stéphanie
    • Kuhn Estelle
    Computational Statistics and Data Analysis, Elsevier, 2015, 91, pp.4-19. Estimation in the deformable template model is a big challenge in image analysis. The issue is to estimate an atlas of a population. This atlas contains a template and the corresponding geometrical variability of the observed shapes. The goal is to propose an accurate estimation algorithm with low computational cost and with theoretical guaranties of relevance. This becomes very demanding when dealing with high dimensional data, which is particularly the case of medical images. The use of an optimized Monte Carlo Markov Chain method for a stochastic Expectation Maximization algorithm, is proposed to estimate the model parameters by maximizing the likelihood. A new Anisotropic Metropolis Adjusted Langevin Algorithm is used as transition in the MCMC method. First it is proven that this new sampler leads to a geometrically uniformly ergodic Markov chain. Furthermore, it is proven also that under mild conditions, the estimated parameters converge almost surely and are asymptotically Gaussian distributed. The methodology developed is then tested on handwritten digits and some 2D and 3D medical images for the deformable model estimation. More widely, the proposed algorithm can be used for a large range of models in many fields of applications such as pharmacology or genetic. The technical proofs are detailed in an appendix. (10.1016/j.csda.2015.04.011)
    DOI : 10.1016/j.csda.2015.04.011
  • Sample Complexity of Dictionary Learning and other Matrix Factorizations
    • Gribonval Rémi
    • Jenatton Rodolphe
    • Bach Francis
    • Kleinsteuber Martin
    • Seibert Matthias
    IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2015, 61 (6), pp.3469-3486. Many modern tools in machine learning and signal processing, such as sparse dictionary learning, principal component analysis (PCA), non-negative matrix factorization (NMF), $K$-means clustering, etc., rely on the factorization of a matrix obtained by concatenating high-dimensional vectors from a training collection. While the idealized task would be to optimize the expected quality of the factors over the underlying distribution of training vectors, it is achieved in practice by minimizing an empirical average over the considered collection. The focus of this paper is to provide sample complexity estimates to uniformly control how much the empirical average deviates from the expected cost function. Standard arguments imply that the performance of the empirical predictor also exhibit such guarantees. The level of genericity of the approach encompasses several possible constraints on the factors (tensor product structure, shift-invariance, sparsity \ldots), thus providing a unified perspective on the sample complexity of several widely used matrix factorization schemes. The derived generalization bounds behave proportional to $\sqrt{\log(n)/n}$ w.r.t.\ the number of samples $n$ for the considered matrix factorization techniques. (10.1109/TIT.2015.2424238)
    DOI : 10.1109/TIT.2015.2424238