Publications

2017

• Moral hazard in dynamic risk management
  
  • Cvitanić Jakša
  • Possamaï Dylan
  • Touzi Nizar
  Management Science, INFORMS, 2017, 63 (10), pp.3328-3346. We consider a contracting problem in which a principal hires an agent to manage a risky project. When the agent chooses volatility components of the output process and the principal observes the output continuously, the principal can compute the quadratic variation of the output, but not the individual components. This leads to moral hazard with respect to the risk choices of the agent. We identify a family of admissible contracts for which the optimal agent's action is explicitly characterized, and, using the recent theory of singular changes of measures for Itô processes, we study how restrictive this family is. In particular, in the special case of the standard Homlstrom-Milgrom model with fixed volatility, the family includes all possible contracts. We solve the principal-agent problem in the case of CARA preferences, and show that the optimal contract is linear in these factors: the contractible sources of risk, including the output, the quadratic variation of the output and the cross-variations between the output and the contractible risk sources. Thus, like sample Sharpe ratios used in practice, path-dependent contracts naturally arise when there is moral hazard with respect to risk management. In a numerical example, we show that the loss of efficiency can be significant if the principal does not use the quadratic variation component of the optimal contract. (10.1287/mnsc.2016.2493)
  DOI : 10.1287/mnsc.2016.2493
• Correction to Black--Scholes Formula Due to Fractional Stochastic Volatility
  
  • Garnier Josselin
  • Sølna Knut
  SIAM Journal on Financial Mathematics, Society for Industrial and Applied Mathematics, 2017, 8 (1), pp.560 - 588. (10.1137/15M1036749)
  DOI : 10.1137/15M1036749
• Consistent functional cross field design for mesh quadrangulation
  
  • Azencot Omri
  • Corman Etienne
  • Ben-Chen Mirela
  • Ovsjanikov Maks
  ACM Transactions on Graphics, Association for Computing Machinery, 2017, 36 (4), pp.92. We propose a novel technique for computing consistent cross fields on a pair of triangle meshes given an input correspondence, which we use as guiding fields for approximately consistent quadrangulations. Unlike the majority of existing methods our approach does not assume that the meshes share the same connectivity or even have the same number of vertices, and furthermore does not place any restrictions on the topology (genus) of the shapes. Importantly, our method is robust with respect to small perturbations of the given correspondence, as it only relies on the transportation of real-valued functions and thus avoids the costly and error-prone estimation of the map differential. Key to this robustness is a novel formulation, which relies on the previously-proposed notion of power vectors, and we show how consistency can be enforced without pre-alignment of local basis frames, in which these power vectors are computed. We demonstrate that using the same formulation we can both compute a quadrangulation that would respect a given symmetry on the same shape or a map across a pair of shapes. We provide quantitative and qualitative comparison of our method with several baselines and show that it both provides more accurate results and allows to handle more general cases than existing techniques. (10.1145/3072959.3073696)
  DOI : 10.1145/3072959.3073696
• Cell Averaging Two-Scale Convergence: Applications to Periodic Homogenization
  
  • Alouges François
  • Di Fratta Giovanni
  Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Society for Industrial and Applied Mathematics, 2017, 15 (4), pp.1651-1671. (10.1137/16M1085309)
  DOI : 10.1137/16M1085309
• An approximation of the M 2 closure: application to radiotherapy dose simulation
  
  • Pichard T
  • Alldredge G W
  • Brull Stéphane
  • Dubroca B
  • Frank M
  Journal of Scientific Computing, Springer Verlag, 2017. Particle transport in radiation therapy can be modelled by a kinetic equation which must be solved numerically. Unfortunately, the numerical solution of such equations is generally too expensive for applications in medical centers. Moment methods provide a hierarchy of models used to reduce the numerical cost of these simulations while preserving basic properties of the solutions. Moment models require a closure because they have more unknowns than equations. The entropy-based closure is based on the physical description of the particle interactions and provides desirable properties. However, computing this closure is expensive. We propose an approximation of the closure for the first two models in the hierarchy, the M 1 and M 2 models valid in one, two or three dimensions of space. Compared to other approximate closures, our method works in multiple dimensions. We obtain the approximation by a careful study of the domain of realizability and by invariance properties of the entropy minimizer. The M 2 model is shown to provide significantly better accuracy than the M 1 model for the numerical simulation of a dose computation in radiotherapy. We propose a numerical solver using those approximated closures. Numerical experiments in dose computation test cases show that the new method is more efficient compared to numerical solution of the minimum entropy problem using standard software tools.
• Optimal control of slender microswimmers
  
  • Zoppello Marta
  • Desimone Antonio
  • Alouges François
  • Giraldi Laetitia
  • Martinon Pierre
  , 2017, pp.21. We discuss a reduced model to compute the motion of slender swimmers which propel themselves by changing the curvature of their body. Our approach is based on the use of Resistive Force Theory for the evaluation of the viscous forces and torques exerted by the surrounding fluid, and on discretizing the kinematics of the swimmer by representing its body through an articulated chain of N rigid links capable of planar deformations. The resulting system of ODEs governing the motion of the swimmer is easy to assemble and to solve, making our reduced model a valuable tool in the design and optimization of bio-inspired artificial microdevices. We prove that the swimmer is controllable in the whole plane for N is greater of equal to 3 and for almost every set of stick lengths. As a direct result, there exists an optimal swimming strategy to reach a desired configuration in minimum time. Numerical experiments for N = 3 (Purcell swimmer) suggest that the optimal strategy is periodic, namely a sequence of identical strokes. Our results indicate that this candidate for an optimal stroke indeed gives a better displacement speed than the classical Purcell stroke. (10.1007/978-3-319-73371-5_8)
  DOI : 10.1007/978-3-319-73371-5_8
• HOMOGENIZATION OF STOKES SYSTEM USING BLOCH WAVES
  
  • Allaire Grégoire
  • Ghosh Tuhin
  • Vanninathan Muthusamy
  Networks and Heterogeneous Media, American Institute of Mathematical Sciences, 2017, 12 (4), pp.525-550. In this work, we study the Bloch wave homogenization for the Stokes system with periodic viscosity coefficient. In particular, we obtain the spectral interpretation of the homogenized tensor. The presence of the incompressibility constraint in the model raises new issues linking the homogenized tensor and the Bloch spectral data. The main difficulty is a lack of smoothness for the bottom of the Bloch spectrum, a phenomenon which is not present in the case of the elasticity system. This issue is solved in the present work, completing the homogenization process of the Stokes system via the Bloch wave method.
• A numerical approach to determine mutant invasion fitness and evolutionary singular strategies
  
  • Fritsch Coralie
  • Campillo Fabien
  • Ovaskainen Otso
  Theoretical Population Biology, Elsevier, 2017, 115, pp.89-99. We propose a numerical approach to study the invasion fitness of a mutant and to determine evolutionary singular strategies in evolutionary structured models in which the competitive exclusion principle holds. Our approach is based on a dual representation, which consists of the modelling of the small size mutant population by a stochastic model and the computation of its corresponding deterministic model. The use of the deterministic model greatly facilitates the numerical determination of the feasibility of invasion as well as the convergence-stability of the evolutionary singular strategy. Our approach combines standard adaptive dynamics with the link between the mutant survival criterion in the stochastic model and the sign of the eigenvalue in the corresponding deterministic model. We present our method in the context of a mass-structured individual-based chemostat model. We exploit a previously derived mathematical relationship between stochastic and deterministic representations of the mutant population in the chemostat model to derive a general numerical method for analyzing the invasion fitness in the stochastic models. Our method can be applied to the broad class of evolutionary models for which a link between the stochastic and deterministic invasion fitnesses can be established. (10.1016/j.tpb.2017.05.001)
  DOI : 10.1016/j.tpb.2017.05.001
• Sampling method for sign changing contrast
  
  • Audibert Lorenzo
  Inverse Problems and Imaging, AIMS American Institute of Mathematical Sciences, 2017. We extend the applicability of the Generalized Linear Sampling Method (GLSM) [2] and the Factorization Method (FM)[14] to the case of inhomogeneities where the contrast change sign strictly inside the obstacle. Both methods give an exact characterization of the target shapes in term of the fareld operator (at a xed frequency). One of the key ingredient to prove this exact characterization is based on a factorization of the fareld operator. This factorization involves three operators which should exhibit specic properties. This paper is concerned with the extension of the coercivity property required on one of them to the case of sign changing contrast both for isotropic and anisotropic scatters with possibly dierent supports for the isotropic and anisotropic parts. We fnally validate the method through some numerical tests in two dimensions.
• Understanding the Time-Dependent Effective Diffusion Coefficient Measured by Diffusion MRI: the Intra-Cellular Case
  
  • Haddar Houssem
  • Li Jing-Rebecca
  • Schiavi Simona
  SIAM Journal on Applied Mathematics, Society for Industrial and Applied Mathematics, 2017. Diffusion Magnetic Resonance Imaging (dMRI) can be used to measure a time-dependent effective diffusion coefficient that can in turn reveal information about the tissue geometry. Recently a mathematical model for the time-dependent effective diffusion coefficient was obtained using homogenization techniques after imposing a certain scaling relationship for the time, the biological cell membrane permeability, the diffusion-encoding magnetic field gradient strength, and a periodicity length of the cellular geometry. With this choice of the scaling of the physical parameters, the effective diffusion coefficient of the medium can be computed after solving a diffusion equation subject to a time-dependent Neumann boundary condition, independently in the biological cells and in the extra-cellular space. In this paper, we analyze this new model, which we call the H-ADC model, in the case of finite domains, which is relevant to diffusion inside biological cells. We use both the eigenfunction expansion and the single layer potential representation for the solution of the above mentioned diffusion equation to obtain analytical expressions for the effective diffusion coefficient in different diffusion time regimes. These expressions are validated using numerical simulations in two dimensions.
• Parameter Estimation in Nonlinear Mixed Effect Models Using saemix, an R Implementation of the SAEM Algorithm
  
  • Comets Emmanuelle
  • Lavenu Audrey Paris
  • Lavielle Marc
  Journal of Statistical Software, University of California, Los Angeles, 2017, 80 (3), pp.i03. The saemix package for R provides maximum likelihood estimates of parameters in nonlinear mixed effect models, using a modern and efficient estimation algorithm, the stochastic approximation expectation-maximisation (SAEM) algorithm. In the present paper we describe the main features of the package, and apply it to several examples to illustrate its use. Making use of S4 classes and methods to provide user-friendly interaction, this package provides a new estimation tool to the R community. (10.18637/jss.v080.i03)
  DOI : 10.18637/jss.v080.i03
• On perturbed proximal gradient algorithms
  
  • Atchadé Yves
  • Fort Gersende
  • Moulines Éric
  Journal of Machine Learning Research, Microtome Publishing, 2017, 18 (10), pp.1-33.
• The infinitesimal model: definition, derivation, and implications
  
  • Barton Nick
  • Etheridge Alison M
  • Véber Amandine
  Theoretical Population Biology, Elsevier, 2017. Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation , population structure, ... We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1/\sqrt{M}. Simulations suggest that in some cases the convergence may be as fast as 1/\sqrt{M} .
• Adaptive multipreconditioned FETI: scalability results and robustness assessment
  
  • Bovet Christophe
  • Parret-Fréaud Augustin
  • Spillane Nicole
  • Gosselet Pierre
  Computers & Structures, Elsevier, 2017, 193, pp.1-20. The purpose of this article is to assess the adaptive multipreconditioned FETI solvers (AMPFETI) on realistic industrial problems and hardware. The multi-preconditioned FETI algorithm (first introduced as Simultaneous FETI [1]) is a non-overlapping domain decomposition method which exhibits good robust-ness properties without requiring the explicit knowledge of the original partial differential equation, or any a priori analysis of the algebraic system through eigenvalues problems. Multipreconditioned FETI solves critical problems in significantly fewer iterations than classical FETI but each iteration involves a larger computational effort. An adaptive strategy (known as the adaptive mul-tipreconditioned conjugate gradient algorithm [2]) has been proposed to achieve balance between robustness and efficiency and we will observe that it provides an efficient solver for the problems considered here. (10.1016/j.compstruc.2017.07.010)
  DOI : 10.1016/j.compstruc.2017.07.010
• A characterization of switched linear control systems with finite L 2 -gain
  
  • Chitour Yacine
  • Mason Paolo
  • Sigalotti Mario
  IEEE Transactions on Automatic Control, Institute of Electrical and Electronics Engineers, 2017, 62, pp.1825-1837. Motivated by an open problem posed by J.P. Hespanha, we extend the notion of Barabanov norm and extremal trajectory to classes of switching signals that are not closed under concatenation. We use these tools to prove that the finiteness of the L2-gain is equivalent, for a large set of switched linear control systems, to the condition that the generalized spectral radius associated with any minimal realization of the original switched system is smaller than one. (10.1109/tac.2016.2593678)
  DOI : 10.1109/tac.2016.2593678
• Dependence of tropical eigenspaces
  
  • Niv Adi
  • Rowen Louis
  Communications in Algebra, Taylor & Francis, 2017, 45 (3), pp.924-942. We study the pathology that causes tropical eigenspaces of distinct su-pertropical eigenvalues of a non-singular matrix A, to be dependent. We show that in lower dimensions the eigenvectors of distinct eigenvalues are independent, as desired. The index set that differentiates between subsequent essential monomials of the characteristic polynomial, yields an eigenvalue λ, and corresponds to the columns of adj(A + λI) from which the eigenvectors are taken. We ascertain the cause for failure in higher dimensions, and prove that independence of the eigenvectors is recovered in case the " difference criterion " holds, defined in terms of disjoint differences between index sets of subsequent coefficients. We conclude by considering the eigenvectors of the matrix A ∇ := 1 det(A) adj(A) and the connection of the independence question to generalized eigenvectors. (10.1080/00927872.2016.1172603)
  DOI : 10.1080/00927872.2016.1172603
• Log-majorization of the moduli of the eigenvalues of a matrix polynomial by tropical roots
  
  • Akian Marianne
  • Gaubert Stéphane
  • Sharify Meisam
  Linear Algebra and its Applications, Elsevier, 2017, 528, pp.394--435. We show that the sequence of moduli of the eigenvalues of a matrix polynomial is log-majorized, up to universal constants, by a sequence of "tropical roots" depending only on the norms of the matrix coefficients. These tropical roots are the non-differentiability points of an auxiliary tropical polynomial, or equivalently, the opposites of the slopes of its Newton polygon. This extends to the case of matrix polynomials some bounds obtained by Hadamard, Ostrowski and Pólya for the roots of scalar polynomials. We also obtain new bounds in the scalar case, which are accurate for "fewnomials" or when the tropical roots are well separated. (10.1016/j.laa.2016.11.004)
  DOI : 10.1016/j.laa.2016.11.004
• Matched-Filter and Correlation-Based Imaging for Fast Moving Objects Using a Sparse Network of Receivers
  
  • Garnier Josselin
  • Fournier J.
  • Papanicolaou G.
  • Tsogka C.
  SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2017, 10 (4), pp.2165 - 2216. (10.1137/17M112364X)
  DOI : 10.1137/17M112364X
• Certified Descent Algorithm for shape optimization driven by fully-computable a posteriori error estimators
  
  • Giacomini Matteo
  • Pantz Olivier
  • Trabelsi Karim
  ESAIM: Control, Optimisation and Calculus of Variations, EDP Sciences, 2017, 23 (3), pp.977-1001. In this paper we introduce a novel certified shape optimization strategy-named Certified Descent Algorithm (CDA)-to account for the numerical error introduced by the Finite Element approximation of the shape gradient. We present a goal-oriented procedure to derive a certified upper bound of the error in the shape gradient and we construct a fully-computable, constant-free a posteriori error estimator inspired by the complementary energy principle. The resulting CDA is able to identify a genuine descent direction at each iteration and features a reliable stopping criterion. After validating the error estimator, some numerical simulations of the resulting certified shape optimization strategy are presented for the well-known inverse identification problem of Electrical Impedance Tomography. (10.1051/cocv/2016021)
  DOI : 10.1051/cocv/2016021
• Pulse Reflection in a Random Waveguide with a Turning Point
  
  • Garnier Josselin
  • Borcea Liliana
  Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Society for Industrial and Applied Mathematics, 2017, 15 (4), pp.1472 - 1501. (10.1137/16M1094154)
  DOI : 10.1137/16M1094154
• Introducing a level-set based shape and topology optimization method for the wear of composite materials with geometric constraints
  
  • Feppon Florian
  • Michailidis G
  • Sidebottom M.A.
  • Allaire Grégoire
  • Krick B.A.
  • Vermaak N
  Structural and Multidisciplinary Optimization, Springer Verlag, 2017, 55 (2), pp.547-568. The wear of materials continues to be a limiting factor in the lifetime and performance of mechanical systems with sliding surfaces. As the demand for low wear materials grows so does the need for models and methods to systematically optimize tribological systems. Elastic foundation models offer a simplified framework to study the wear of multimaterial composites subject to abrasive sliding. Previously, the evolving wear profile has been shown to converge to a steady-state that is characterized by a time-independent elliptic equation. In this article, the steady-state formulation is generalized and integrated with shape optimization to improve the wear performance of bi-material composites. Both macroscopic structures and periodic material microstructures are considered. Several common tribological objectives for systems undergoing wear are identified and mathematically formalized with shape derivatives. These include (i) achieving a planar wear surface from multimaterial composites and (ii) minimizing the run-in volume of material lost before steady-state wear is achieved. A level-set based topology optimization algorithm that incorporates a novel constraint on the level-set function is presented. In particular, a new scheme is developed to update material interfaces ; the scheme (i) conveniently enforces volume constraints at each iteration, (ii) controls the complexity of design features using perimeter penalization, and (iii) nucleates holes or inclusions with the topological gradient. The broad applicability of the proposed formulation for problems beyond wear is discussed, especially for problems where convenient control of the complexity of geometric features is desired. (10.1007/s00158-016-1512-4)
  DOI : 10.1007/s00158-016-1512-4
• Application of the Sparse Cardinal Sine Decomposition to 3D Stokes Flows
  
  • Alouges F.
  • Aussal M.
  • Lefebvre-Lepot A.
  • Pigeonneau Franck
  • Sellier Antoine
  International Journal of Computational Methods and Experimental Measurements, WIT Press, 2017, 5 (3), pp.387 - 394. In boundary element method (BEM), one encounters linear system with a dense and non-symmetric square matrix which might be so large that inverting the linear system is too prohibitive in terms of cpu time and/or memory. Each usual powerful treatment (Fast Multipole Method, H-matrices) developed to deal with this issue is optimized to efficiently perform matrix vector products. This work presents a new technique to adequately and quickly handle such products: the Sparse Cardinal Sine Decomposition. This approach, recently pioneered for the Laplace and Helmholtz equations, rests on the decomposition of each encountered kernel as series of radial Cardinal Sine functions. Here, we achieve this decomposition for the Stokes problem and implement it in MyBEM, a new fast solver for multi-physical BEM. The reported computational examples permit us to compare the advocated method against a usual BEM in terms of both accuracy and convergence. (10.2495/CMEM-V5-N3-387-394)
  DOI : 10.2495/CMEM-V5-N3-387-394
• Multipoint scatterers with zero-energy bound states
  
  • Grinevich Piotr
  • Novikov Roman
  Theoretical and Mathematical Physics, Consultants bureau, 2017, 193 (2), pp.1675-1679. We study multipoint scatterers with zero-energy bound states in three dimensions. We present examples of such scatterers with multiple zero eigenvalue or with strong multipole localization of zero-energy bound states.
• Dimensional Reduction of a Multiscale Model Based on Long Time Asymptotics
  
  • Clément Frédérique
  • Coquel Frédéric
  • Postel Marie
  • Tran Kim Long
  Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Society for Industrial and Applied Mathematics, 2017, 15 (3), pp.1198 - 1241. We consider a class of kinetic models for which a moment equation has a natural interpretation. We show that, depending on their velocity field, some models lead to moment equations that enable one to compute monokinetic solutions economically. We detail the example of a multiscale structured cell population model, consisting of a system of 2D transport equations. The reduced model, a system of 1D transport equations, is obtained by computing the moments of the 2D model with respect to one variable. The 1D solution is defined from the solution of the 2D model starting from an initial condition that is a Dirac mass in the direction removed by reduction. Long time properties of the 1D model solution are obtained in connection with properties of the support of the 2D solution for general case initial conditions. Finite volume numerical approximations of the 1D reduced model can be used to compute the moments of the 2D solution with proper accuracy. The numerical robustness is studied in the scalar case, and a full scale vector case is presented. (10.1137/16M1062545)
  DOI : 10.1137/16M1062545
• Optimal scaling of the Random Walk Metropolis algorithm under Lp mean differentiability
  
  • Durmus Alain
  • Le Corff Sylvain
  • Moulines Éric
  • Roberts Gareth O. O.
  Journal of Applied Probability, Cambridge University press, 2017, 54 (4), pp.1233 -1260. This paper considers the optimal scaling problem for high-dimensional random walk Metropolis algorithms for densities which are differentiable in Lp mean but which may be irregular at some points (like the Laplace density for example) and/or are supported on an interval. Our main result is the weak convergence of the Markov chain (appropriately rescaled in time and space) to a Langevin diffusion process as the dimension d goes to infinity. Because the log-density might be non-differentiable, the limiting diffusion could be singular. The scaling limit is established under assumptions which are much weaker than the one used in the original derivation of [6]. This result has important practical implications for the use of random walk Metropolis algorithms in Bayesian frameworks based on sparsity inducing priors. (10.1017/jpr.2017.61)
  DOI : 10.1017/jpr.2017.61