Keywords
Computer Science and Digital Science
 A6. Modeling, simulation and control
 A6.1. Methods in mathematical modeling
 A6.1.1. Continuous Modeling (PDE, ODE)
 A6.4. Automatic control
 A6.4.1. Deterministic control
 A6.4.3. Observability and Controlability
 A6.4.4. Stability and Stabilization
 A6.4.5. Control of distributed parameter systems
 A6.4.6. Optimal control
Other Research Topics and Application Domains
 B2. Health
 B2.6. Biological and medical imaging
 B4.2.2. Fusion
 B5.2.4. Aerospace
 B5.11. Quantum systems
1 Team members, visitors, external collaborators
Research Scientists
 Mario Sigalotti [Team leader, Inria, Senior Researcher, HDR]
 Andrey Agrachev [Inria, Advanced Research Position, from Oct 2021]
 Barbara Gris [CNRS, Researcher]
 Kevin Le Balc'h [Inria, from Sep 2021, Starting Faculty Position]
Faculty Members
 Ugo Boscain [CNRS, Professor, HDR]
 Jean Michel Coron [Université de Paris, Professor]
 Emmanuel Trélat [Université d'Orléans, Associate Professor, HDR]
PostDoctoral Fellows
 Benoit Bonnet [Inria, from Feb 2021 until Oct 2021]
 Jeffrey Heninger [Inria, until Mar 2021]
PhD Students
 Veljko Askovic [MBDA]
 Daniele Cannarsa [CNRS, until Sep 2021]
 Liangying Chen [Sorbonne Université and Chengdu University, From Nov 2021]
 Justine Dorsz [Sorbonne Université, until Feb 2021]
 Gontran Lance [École Nationale Supérieure de Techniques Avancées, until May 2021]
 Cyril Letrouit [École Normale Supérieure de Paris, until Jun 2021]
 Emilio Molina [Universidad de Chile]
 Aymeric Nayet [ArianeGroup]
 Eugenio Pozzoli [Inria, until Oct 2021]
 Remi Robin [Sorbonne Université]
 Robin Roussel [Sorbonne Université, From Nov 2021]
Interns and Apprentices
 Robin Roussel [Inria, from Apr 2021 until Oct 2021]
 Charlotte Vulliez [Inria, from Apr 2021 until Jul 2021]
Administrative Assistants
 Christelle Guiziou [Inria]
 Mathieu Mourey [Inria, until Oct 2021]
 Scheherazade Rouag [Inria, from Oct 2021]
External Collaborators
 Amaury Hayat [Ecole des Ponts, Since Oct 2021]
 Ludovic Sacchelli [ANR, until Sep 2021, HDR]
2 Overall objectives
CAGE's activities take place in the field of mathematical control theory, with applications in three main directions: geometric models for vision, control of quantum mechanical systems, and control of systems with uncertain dynamics.
The relations between control theory and geometry of vision rely on the notion of subRiemannian structure, a geometric framework which is used to measure distances in nonholonomic contexts and which has a natural and powerful control theoretical interpretation. We recall that nonholonomicity refers to the property of a velocity constraint that cannot be recast as a state constraint. In the language of differential geometry, a subRiemannian structure is a (possibly rankvarying) Lie bracket generating distribution endowed with a smoothly varying norm.
SubRiemannian geometry, and in particular the theory of associated (hypoelliptic) diffusive processes, plays a crucial role in the neurogeometrical model of the primary visual cortex due to Petitot, Citti and Sarti, based on the functional architecture first described by Hubel and Wiesel. Such a model can be used as a powerful paradigm for bioinspired image processing, as already illustrated in the recent literature (including by members of our team). Our contributions to this field are based not only on this approach, but also on another geometric and subRiemannian framework for vision, based on pattern matching in the group of diffeomorphisms. In this case admissible diffeomorphisms correspond to deformations which are generated by vector fields satisfying a set of nonholonomic constraints. A subRiemannian metric on the infinitedimensional group of diffeomorphisms is induced by a length on the tangent distribution of admissible velocities. Nonholonomic constraints can be especially useful to describe distortions of sets of interconnected objects (e.g., motions of organs in medical imaging).
Control theory is one of the components of the forthcoming quantum revolution 1, since manipulation of quantum mechanical systems is ubiquitous in applications such as quantum computation, quantum cryptography, and quantum sensing (in particular, imaging by nuclear magnetic resonance). The efficiency of the control action has a dramatic impact on the quality of the coherence and the robustness of the required manipulation. Minimal time constraints and interaction of time scales are important factors for characterizing the efficiency of a quantum control strategy. Time scales analysis is important for evaluation approaches based on adiabatic approximation theory, which is wellknown to improve the robustness of the control strategy. CAGE works for the improvement of evaluation and design tools for efficient quantum control paradigms, especially for what concerns quantum systems evolving in infinitedimensional Hilbert spaces.
Simultaneous control of a continuum of systems with slightly different dynamics is a typical problem in quantum mechanics and also a special case of the third applicative axis to which CAGE is contributing: control of systems with uncertain dynamics. The slightly different dynamics can indeed be seen as uncertainties in the system to be controlled, and simultaneous control rephrased in terms of a robustness task. Robustification, i.e., offsetting uncertainties by suitably designing the control strategy, is a widespread task in automatic control theory, showing up in many applicative domains such as electric circuits or aerospace motion planning. If dynamics are not only subject to static uncertainty, but may also change as time goes, the problem of controlling the system can be recast within the theory of switched and hybrid systems, both in a deterministic and in a probabilistic setting. Our contributions to this research field concern both stabilization (either asymptotic or in finite time) and optimal control, where redundancies and probabilistic tools can be introduced to offset uncertainties.
3 Research program
3.1 Research domain
The activities of CAGE are part of the research in the wide area of control theory. This nowadays mature discipline is still the subject of intensive research because of its crucial role in a vast array of applications.
More specifically, our contributions are in the area of mathematical control theory, which is to say that we are interested in the analytical and geometrical aspects of control applications. In this approach, a control system is modeled by a system of equations (of many possible types: ordinary differential equations, partial differential equations, stochastic differential equations, difference equations,...), possibly not explicitly known in all its components, which are studied in order to establish qualitative and quantitative properties concerning the actuation of the system through the control.
Motion planning is, in this respect, a cornerstone property: it denotes the design and validation of algorithms for identifying a control law steering the system from a given initial state to (or close to) a target one. Initial and target positions can be replaced by sets of admissible initial and final states as, for instance, in the motion planning task towards a desired periodic solution. Many specifications can be added to the pure motion planning task, such as robustness to external or endogenous disturbances, obstacle avoidance or penalization criteria. A more abstract notion is that of controllability, which denotes the property of a system for which any two states can be connected by a trajectory corresponding to an admissible control law. In mathematical terms, this translates into the surjectivity of the socalled endpoint map, which associates with a control and an initial state the final point of the corresponding trajectory. The analytical and topological properties of endpoint maps are therefore crucial in analyzing the properties of control systems.
One of the most important additional objective which can be associated with a motion planning task is optimal control, which corresponds to the minimization of a cost (or, equivalently, the maximization of a gain) 164. Optimal control theory is clearly deeply interconnected with calculus of variations, even if the noninterchangeable nature of the timevariable results in some important specific features, such as the occurrence of abnormal extremals125. Research in optimal control encompasses different aspects, from numerical methods to dynamic programming and nonsmooth analysis, from regularity of minimizers to high order optimality conditions and curvaturelike invariants.
Another domain of control theory with countless applications is stabilization. The goal in this case is to make the system converge towards an equilibrium or some more general safety region. The main difference with respect to motion planning is that here the control law is constructed in feedback form. One of the most important properties in this context is that of robustness, i.e., the performance of the stabilization protocol in presence of disturbances or modeling uncertainties. A powerful framework which has been developed to take into account uncertainties and exogenous nonautonomous disturbances is that of hybrid and switched systems 146, 127, 155. The central tool in the stability analysis of control systems is that of control Lyapunov function. Other relevant techniques are based on algebraic criteria or dynamical systems. One of the most important stability property which is studied in the context of control system is inputtostate stability151, which measures how sensitive the system is to an external excitation.
One of the areas where control applications have nowadays the most impressive developments is in the field of biomedicine and neurosciences. Improvements both in modeling and in the capability of finely actuating biological systems have concurred in increasing the popularity of these subjects. Notable advances concern, in particular, identification and control for biochemical networks 144 and models for neural activity 113. Therapy analysis from the point of view of optimal control has also attracted a great attention 148.
Biological models are not the only one in which stochastic processes play an important role. Stockmarkets and energy grids are two major examples where optimal control techniques are applied in the nondeterministic setting. Sophisticated mathematical tools have been developed since several decades to allow for such extensions. Many theoretical advances have also been required for dealing with complex systems whose description is based on distributed parameters representation and partial differential equations. Functional analysis, in particular, is a crucial tool to tackle the control of such systems 161.
Let us conclude this section by mentioning another challenging application domain for control theory: the decision by the European Union to fund a flagship devoted to the development of quantum technologies is a symptom of the role that quantum applications are going to play in tomorrow's society. Quantum control is one of the bricks of quantum engineering, and presents many peculiarities with respect to standard control theory, as a consequence of the specific properties of the systems described by the laws of quantum physics. Particularly important for technological applications is the capability of inducing and reproducing coherent state superpositions and entanglement in a fast, reliable, and efficient way 114.
3.2 Scientific foundations
At the core of the scientific activity of the team is the geometric control approach, that is, a distinctive viewpoint issued in particular from (elementary) differential geometry, to tackle questions of controllability, observability, optimal control... 74, 118. The emphasis of such a geometric approach to control theory is put on intrinsic properties of the systems and it is particularly well adapted to study nonlinear and nonholonomic phenomena.
One of the features of the geometric control approach is its capability of exploiting symmetries and intrinsic structures of control systems. Symmetries and intrinsic structures can be used to characterize minimizing trajectories, prove regularity properties and describe invariants. An egregious example is given by mechanical systems, which inherently exhibit Lagrangian/Hamiltonian structures which are naturally expressed using the language of symplectic geometry 100. The geometric theory of quantum control, in particular, exploits the rich geometric structure encoded in the Schrödinger equation to engineer adapted control schemes and to characterize their qualitative properties. The Lie–Galerkin technique that we proposed starting from 2009 103 builds on this premises in order to provide powerful tests for the controllability of quantum systems defined on infinitedimensional Hilbert spaces.
Although the focus of geometric control theory is on qualitative properties, its impact can also be disruptive when it is used in combination with quantitative analytical tools, in which case it can dramatically improve the computational efficiency. This is the case in particular in optimal control. Classical optimal control techniques (in particular, Pontryagin Maximum Principle, conjugate point theory, associated numerical methods) can be significantly improved by combining them with powerful modern techniques of geometric optimal control, of the theory of numerical continuation, or of dynamical system theory 159, 147. Geometric optimal control allows the development of general techniques, applying to wide classes of nonlinear optimal control problems, that can be used to characterize the behavior of optimal trajectories and in particular to establish regularity properties for them and for the cost function. Hence, geometric optimal control can be used to obtain powerful optimal syntheses results and to provide deep geometric insights into many applied problems. Numerical optimal control methods with geometric insight are in particular important to handle subtle situations such as rigid optimal paths and, more generally, optimal syntheses exhibiting abnormal minimizers.
Optimal control is not the only area where the geometric approach has a great impact. Let us mention, for instance, motion planning, where different geometric approaches have been developed: those based on the Lie algebra associated with the control system 139, 129, those based on the differentiation of nonlinear flows such as the return method107, 108, and those exploiting the differential flatness of the system 112.
Geometric control theory is not only a powerful framework to investigate control systems, but also a useful tool to model and study phenomena that are not a priori controlrelated. Two occurrences of this property play an important role in the activities of CAGE:
 geometric control theory as a tool to investigate properties of mathematical structures;
 geometric control theory as a modeling tool for neurophysical phenomena and for synthesizing biomimetic algorithms based on such models.
Examples of the first type, concern, for instance, hypoelliptic heat kernels 72 or shape optimization 83. Examples of the second type are inactivation principles in human motricity 86 or neurogeometrical models for image representation of the primary visual cortex in mammals 96.
A particularly relevant class of control systems, both from the point of view of theory and applications, is characterized by the linearity of the controlled vector field with respect to the control parameters. When the controls are unconstrained in norm, this means that the admissible velocities form a distribution in the tangent bundle to the state manifold. If the distribution is equipped with a pointdependent quadratic form (encoding the cost of the control), the resulting geometrical structure is said to be subRiemannian. SubRiemannian geometry appears as the underlying geometry of nonlinear control systems: in a similar way as the linearization of a control system provides local informations which are readable using the Euclidean metric scale, subRiemannian geometry provides an adapted nonisotropic class of lenses which are often much more informative. As such, its study is fundamental for control design. The importance of subRiemannian geometry goes beyond control theory and it is an active field of research both in differential geometry 137, geometric measure theory 77 and hypoelliptic operator theory 89.
The geometric control approach has historically been related to the development of finitedimensional control theory. However, its impact in the analysis of distributed parameter control systems and in particular systems of controlled partial differential equations has been growing in the last decades, complementing analytical and numerical approaches, providing dynamical, qualitative and intrinsic insight 106. CAGE's ambition is to be at the core of this development in the years to come.
4 Application domains
4.1 First axis: Geometry of vision
A suggestive application of subRiemannian geometry and in particular of hypoelliptic diffusion comes from a model of geometry of vision describing the functional architecture of the primary visual cortex V1. In 1958, Hubel and Wiesel (Nobel in 1981) observed that the visual cortex V1 is endowed with the socalled pinwheel structure, characterized by neurons grouped into orientation columns, that are sensible both to positions and directions 117. The mathematical rephrasing of this discovery is that the visual cortex lifts an image from ${\mathbf{R}}^{2}$ into the bundle of directions of the plane 104, 143, 145, 116.
A simplified version of the model can be described as follows: neurons of V1 are grouped into orientation columns, each of them being sensitive to visual stimuli at a given point of the retina and for a given direction on it. The retina is modeled by the real plane, i.e., each point is represented by a pair $(x,y)\in {\mathbb{R}}^{2}$, while the directions at a given point are modeled by the projective line, i.e. an element $\theta $ of the projective line ${P}^{1}$. Hence, the primary visual cortex V1 is modeled by the so called projective tangent bundle ${\mathrm{PTR}}^{2}={\mathbf{R}}^{2}\times {\mathbf{P}}^{1}$. From a neurological point of view, orientation columns are in turn grouped into hypercolumns, each of them being sensitive to stimuli at a given point $(x,y)$ with any direction.
Orientation columns are connected between them in two different ways. The first kind of connections are the vertical (inhibitory) ones, which connect orientation columns belonging to the same hypercolumn and sensible to similar directions. The second kind of connections are the horizontal (excitatory) connections, which connect neurons belonging to different (but not too far) hypercolumns and sensible to the same directions. The resulting metric structure is subRiemannian and the model obtained in this way provides a convincing explanation in terms of subRiemannian geodesics of gestalt phenomena such as Kanizsa illusory contours.
The subRiemannian model for image representation of V1 has a great potential of yielding powerful bioinspired image processing algorithms 111, 96. Image inpainting, for instance, can be implemented by reconstructing an incomplete image by activating orientation columns in the missing regions in accordance with subRiemannian nonisotropic constraints. The process intrinsically defines an hypoelliptic heat equation on ${\mathrm{PTR}}^{2}$ which can be integrated numerically using noncommutative Fourier analysis on a suitable semidiscretization of the group of rototranslations of the plane 94.
We have been working on the model and its software implementation since 2012. This work has been supported by several project, as the ERC starting grant GeCoMethods and the ERC Proof of Concept ARTIV1 of U. Boscain, and the ANR GCM.
A parallel approach that we will pursue and combine with this first one is based on pattern matching in the group of diffeomorphisms. We want to extend this approach, already explored in the Riemannian setting 160, 134, to the general subRiemannian framework. The paradigm of the approach is the following: consider a distortable object, more or less rigid, discretized into a certain number of points. One may track its distortion by considering the paths drawn by these points. One would however like to know how the object itself (and not its discretized version) has been distorted. The study in 160, 134 shed light on the importance of Riemannian geometry in this kind of problem. In particular, they study the Riemannian submersion obtained by making the group of diffeomorphisms act transitively on the manifold formed by the points of the discretization, minimizing a certain energy so as to take into account the whole object. Settled as such, the problem is Riemannian, but if one considers objects involving connections, or submitted to nonholonomic constraints, like in medical imaging where one tracks the motions of organs, then one comes up with a subRiemannian problem. The transitive group is then far bigger, and the aim is to lift curves submitted to these nonholonomic constraints into curves in the set of diffeomorphisms satisfying the corresponding constraints, in a unique way and minimizing an energy (giving rise to a subRiemannian structure).
4.2 Second axis: Quantum control
The goal of quantum control is to design efficient protocols for tuning the occupation probabilities of the energy levels of a system. This task is crucial in atomic and molecular physics, with applications ranging from photochemistry to nuclear magnetic resonance and quantum computing. A quantum system may be controlled by exciting it with one or several external fields, such as magnetic or electric fields. The goal of quantum control theory is to adapt the tools originally developed by control theory and to develop new specific strategies that tackle and exploit the features of quantum dynamics (probabilistic nature of wavefunctions and density operators, measure and wavefunction collapse, decoherence, ...). A rich variety of relevant models for controlled quantum dynamics exist, encompassing lowdimensional models (e.g., singlespin systems) and PDEs alike, with deterministic and stochastic components, making it a rich and exciting area of research in control theory.
The controllability of quantum system is a wellestablished topic when the state space is finitedimensional 109, thanks to general controllability methods for leftinvariant control systems on compact Lie groups 99, 119. When the state space is infinitedimensional, it is known that in general the bilinear Schrödinger equation is not exactly controllable 162. Nevertheless, weaker controllability properties, such as approximate controllability or controllability between eigenstates of the internal Hamiltonian (which are the most relevant physical states), may hold. In certain cases, when the state space is a function space on a 1D manifold, some rather precise description of the set of reachable states has been provided 84. A similar description for higherdimensional manifolds seems intractable and at the moment only approximate controllability results are available 135, 141, 120. The most widely applicable tests for controllability of quantum systems in infinitedimensional Hilbert spaces are based on the Lie–Galerkin technique103, 91, 92. They allow, in particular, to show that the controllability property is generic among this class of systems 132.
A family of algorithms which are specific to quantum systems are those based on adiabatic evolution 166, 165, 123. The basic principle of adiabatic control is that the flow of a slowly varying Hamiltonian can be approximated (up to a phase factor) by a quasistatic evolution, with a precision proportional to the velocity of variation of the Hamiltonian. The advantage of the adiabatic approach is that it is constructive and produces control laws which are both smooth and robust to parameter uncertainty. The paradigm is based on the adiabatic perturbation theory developed in mathematical physics 90, 140, 158, where it plays an important role for understanding molecular dynamics. Approximation theory by adiabatic perturbation can be used to describe the evolution of the occupation probabilities of the energy levels of a slowly varying Hamiltonian. Results from the last 15 years, including those by members of our team 69, 95, have highlighted the effectiveness of control techniques based on adiabatic path following.
4.3 Third axis: Stability and uncertain dynamics
Switched and hybrid systems constitute a broad framework for the description of the heterogeneous aspects of systems in which continuous dynamics (typically pertaining to physical quantities) interact with discrete/logical components. The development of the switched and hybrid paradigm has been motivated by a broad range of applications, including automotive and transportation industry 150, energy management 142 and congestion control 133.
Even if both controllability 154 and observability 121 of switched and hybrid systems have attracted much research efforts, the central role in their study is played by the problem of stability and stabilizability. The goal is to determine whether a dynamical or a control system whose evolution is influenced by a timedependent signal is uniformly stable or can be uniformly stabilized 127, 155. Uniformity is considered with respect to all signals in a given class. Stability of switched systems lead to several interesting phenomena. For example, even when all the subsystems corresponding to a constant switching law are exponentially stable, the switched systems may have divergent trajectories for certain switching signals 126. This fact illustrates the fact that stability of switched systems depends not only on the dynamics of each subsystem but also on the properties of the class of switching signals which is considered.
The most common class of switching signals which has been considered in the literature is made of all piecewise constant signals.
In this case uniform stability of the system is equivalent to the existence of a common quadratic Lyapunov function 136. Moreover, provided that the system has finitely many modes, the Lyapunov function can be taken polyhedral or polynomial 88, 87, 110. A special role in the switched control literature has been played by common quadratic Lyapunov functions, since their existence can be tested rather efficiently (see the surveys 128, 149 and the references therein). It is known, however, that the existence of a common quadratic Lyapunov function is not necessary for the global uniform exponential stability of a linear switched system with finitely many modes. Moreover, there exists no uniform upper bound on the minimal degree of a common polynomial Lyapunov function 131. More refined tools rely on multiple and nonmonotone Lyapunov functions 98. Let us also mention linear switched systems technics based on the analysis of the Lie algebra generated by the matrices corresponding to the modes of the system 71.
For systems evolving in the plane, more geometrical tests apply, and yield a complete characterization of the stability 97, 78. Such a geometric approach also yields sufficient conditions for uniform stability in the linear planar case 93.
In many situations, it is interesting for modeling purposes to specify the features of the switched system by introducing constrained switching rules. A typical constraint is that each mode is activated for at least a fixed minimal amount of time, called the dwelltime. Switching rules can also be imposed, for instance, by a timed automata. When constraints apply, the common Lyapunov function approach becomes conservative and new tools have to be developed to give more detailed characterizations of stable and unstable systems.
Our approach to constrained switching is based on the idea of relating the analytical properties of the classes of constrained switching laws (shiftinvariance, compactness, closure under concatenation, ...) to the stability behavior of the corresponding switched systems. One can introduce probabilistic uncertainties by endowing the classes of admissible signals with suitable probability measures. One then looks at the corresponding Lyapunov exponents, whose existence is established by the multiplicative ergodic theorem. The interest of this approach is that probabilistic stability analysis filters out highly `exceptional' worstcase trajectories. Although less explicitly characterized from a dynamical viewpoint than its deterministic counterpart, the probabilistic notion of uniform exponential stability can be studied using several reformulations of Lyapunov exponents proposed in the literature 85, 105, 163.
4.4 Joint theoretical core
The theoretical questions raised by the different applicative area will be pooled in a research axis on the transversal aspects of geometric control theory and subRiemannian structures.
We recall that subRiemannian geometry is a generalization of Riemannian geometry, whose birth dates back to Carathéodory's seminal paper on the foundations of Carnot thermodynamics 101, followed by E. Cartan's address at the International Congress of Mathematicians in Bologna 102. In the last twenty years, subRiemannian geometry has emerged as an independent research domain, with a variety of motivations and ramifications in several parts of pure and applied mathematics. Let us mention geometric analysis, geometric measure theory, stochastic calculus and evolution equations together with applications in mechanics and optimal control (motion planning, robotics, nonholonomic mechanics, quantum control) 79, 80.
One of the main open problems in subRiemannian geometry concerns the regularity of lengthminimizers 75, 138. Lengthminimizers are solutions to a variational problem with constraints and satisfy a firstorder necessary condition resulting from the Pontryagin Maximum Principle (PMP). Solutions of the PMP are either normal or abnormal. Normal lengthminimizer are wellknown to be smooth, i.e., ${C}^{\infty}$, as it follows by the Hamiltonian nature of the PMP. The question of regularity is then reduced to abnormal lengthminimizers. If the subRiemannian structure has step 2, then abnormal lengthminimizers can be excluded and thus every lengthminimizer is smooth. For step 3 structures, the situation is already more complicated and smoothness of lengthminimizers is known only for Carnot groups 122, 157. The question of regularity of lengthminimizers is not restricted to the smoothness in the ${C}^{\infty}$ sense. A recent result prove that lengthminimizers, for subRiemannian structures of any step, cannot have cornerlike singularities 115. When the subRiemannian structure is analytic, more is known on the size of the set of points where a lengthminimizer can lose analyticity 156, regardless of the rank and of the step of the distribution.
An interesting set of recent results in subRiemannian geometry concerns the extension to such a setting of the Riemannian notion of sectional curvature. The curvature operator can be introduced in terms of the symplectic invariants of the Jacobi curve 73, 124, 70, a curve in the Lagrange Grassmannian related to the linearization of the Hamiltonian flow. Alternative approaches to curvatures in metric spaces are based either on the associated heat equation and the generalization of the curvaturedimension inequality 81, 82 or on optimal transport and the generalization of Ricci curvature 153, 152, 130, 76.
5 Highlights of the year
5.1 Awards
Barbara Gris was awarded the GSI Women in Machine Learning & Data Science Prize at the conference GSI2021
Rémi Robin was part of the winning team of the challenge mathématiques et enterprises de l'AMIES “Modélisation du profil longitudinal de la voie à partir d'enregistrement inclinométriques" 
6 New software and platforms
6.1 New software
6.1.1 Stellacode

Keywords:
Plasma physics, Stellarator, Inverse problem, Magnetic fusion, Electromagnetics, Shape optimization

Functional Description:
The goal of Stellacode is to optimize the Coil Winding Surface of a stellarator. What does this means and what for? A stellarator is a nuclear fusion reactor which produces energy from the fusion of nuclei in a very hot plasma. The confinement of this plasma is a very complicated task and a stellarator is able to achieve it thanks to a complex set of nonplanar supraconductor coils lying on the socalled "Coil Winding Surface". Stellacode is able to perform efficiently the shape optimization of this surface, taking into account both plasma confinement figures of merit and engineering costs.
 Publication:

Contact:
Rémi Robin
7 New results
7.1 Geometry of vision and subRiemannian geometry: new results
Let us list here our new results in the geometry of vision axis and, more generally, on hypoelliptic diffusion and subRiemannian geometry.
 A natural way to model the evolution of an object (growth of a leaf for instance) is to estimate a plausible deforming path between two observations. This interpolation process can generate deceiving results when the set of considered deformations is not relevant to the observed data. To overcome this issue, the framework of deformation modules allows to incorporate in the model structured deformation patterns coming from prior knowledge on the data. The goal of 45 is twofold. First defining new deformation modules incorporating structures coming from the elastic properties of the objects. Second, presenting the IMODAL library allowing to perform registration through structured deformations. This library is modular: adapted priors can be easily defined by the user, several priors can be combined into a global one and various types of data can be considered such as curves, meshes or images.
 Based on a SubRiemannian framework, deformation modules provide a way of building large diffeomorphic deformations satisfying a given geometrical structure. This allows to incorporate prior knowledge about object deformations into the model as a means of regularisation. However, diffeomorphic deformations can lead to deceiving results if the deformed object is composed of several shapes which are close to each other but require drastically different deformations. For the related Large Deformation Diffemorphic Metric Mapping, which yields unstructured deformations, this issue was addressed in previous works, introducing object boundary constraints. We develop in 44 a new registration problem, marrying the two frameworks to allow for different constrained deformations in different coupled shapes.
 The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of 43 is to refine the auditory cortex model introduced previously, and inspired by the geometrical modelling of vision. The algorithm transforms the degraded sound in an 'image' in the timefrequency domain via a shorttime Fourier transform. Such an image is then lifted in the Heisenberg group and it is reconstructed via a WilsonCowan differointegral equation. Numerical experiments on a library of speech recordings are provided, showing the good reconstruction properties of the algorithm.
 Loss of cellular homeostasis has been implicated in the etiology of several neurodegenerative diseases (NDs). However, the molecular mechanisms that underlie this loss remain poorly understood on a systems level in each case. In 41, using a novel computational approach to integrate dimensional RNAseq and in vivo neuron survival data, we map the temporal dynamics of homeostatic and pathogenic responses in four striatal cell types of Huntington's disease (HD) model mice. This map shows that most pathogenic responses are mitigated and most homeostatic responses are decreased over time, suggesting that neuronal death in HD is primarily driven by the loss of homeostatic responses. Moreover, different cell types may lose similar homeostatic processes, for example, endosome biogenesis and mitochondrial quality control in Drd1expressing neurons and astrocytes. HD relevance is validated by human stem cell, genomewide association study, and postmortem brain data. These findings provide a new paradigm and framework for therapeutic discovery in HD and other NDs.
 The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of 19 is to propose a mathematical model of sound reconstruction based on the functional architecture of the auditory cortex (A1). The model is inspired by the geometrical modelling of vision, which has undergone a great development in the last ten years. The algorithm transforms the degraded sound in an image in the timefrequency domain via a shorttime Fourier transform. Such an image is then lifted in the Heisenberg group (i.e., the celebrated Brockett integrator) and it is reconstructed via a WilsonCowan differointegral equation. Numerical experiments are provided.
 Hörmander's propagation of singularities theorem does not fully describe the propagation of singularities in subelliptic wave equations, due to the existence of doubly characteristic points. In 63, building upon a visionary 1986 conference paper by R. Melrose, we prove that singularities of subelliptic wave equations only propagate along nullbicharacteristics and abnormal extremal lifts of singular curves, which are wellknown curves in optimal control theory. We first revisit in depth the ideas sketched by R. Melrose, notably providing a full proof of its main statement. Making more explicit computations, we then explain how subRiemannian geometry and abnormal extremals come into play. This result shows that abnormal extremals have an important role in the classicalquantum correspondence between subRiemannian geometry and subelliptic operators. See also 47.
 In the note 57 we consider a closed threedimensional contact subRiemannian manifold. The objective is to provide a precise description of the subRiemannian geodesics with large initial momenta: we prove that they “spiral around the Reeb orbits”, not only in the phase space but also in the configuration space. Our analysis is based on a normal form along any Reeb orbit due to Melrose.
 In 26 we prove that for the Martinet wave equation with “flat” metric, which a subelliptic wave equation, singularities can propagate at any speed between 0 and 1 along any singular geodesic. This is in strong contrast with the usual propagation of singularities at speed 1 for wave equations with elliptic Laplacian.
 In 27 we establish smalltime asymptotic expansions for heat kernels of hypoelliptic Hörmander operators in a neighborhood of the diagonal, generalizing former results obtained in particular by Métivier and by Ben Arous. The coefficients of our expansions are identified in terms of the nilpotentization of the underlying subRiemannian structure. Our approach is purely analytic and relies in particular on local and global subelliptic estimates as well as on the local nature of smalltime asymptotics of heat kernels. The fact that our expansions are valid not only along the diagonal but in an asymptotic neighborhood of the diagonal is the main novelty, useful in view of deriving Weyl laws for subelliptic Laplacians. In turn, we establish a number of other results on hypoelliptic heat kernels that are interesting in themselves, such as Kac's principle of not feeling the boundary, asymptotic results for singular perturbations of hypoelliptic operators, global smoothing properties for selfadjoint heat semigroups.
 In the survey paper 62 we report on recent works concerning exact observability (and, by duality, exact controllability) properties of subelliptic wave and Schrödingertype equations. These results illustrate the slowdown of propagation in directions transverse to the horizontal distribution. The proofs combine subRiemannian geometry, semiclassical analysis, spectral theory and noncommutative harmonic analysis.
 It is wellknown that observability (and, by duality, controllability) of the elliptic wave equation, i.e., with a Riemannian Laplacian, in time ${T}_{0}$ is almost equivalent to the Geometric Control Condition (GCC), which stipulates that any geodesic ray meets the control set within time ${T}_{0}$. We show in 35 that in the subelliptic setting, GCC is never verified, and that subelliptic wave equations are never observable in finite time. More precisely, given any subelliptic Laplacian $\Delta ={\sum}_{i=1}^{m}{X}_{i}^{*}{X}_{i}$ on a manifold $M$ such that $\mathrm{Lie}({X}_{1},...,{X}_{m})=TM$ but $\mathrm{Span}({X}_{1},...,{X}_{m})\ne TM$, we show that for any ${T}_{0}>0$ and any measurable subset $\omega \subset M$ such that $M\setminus \omega $ has nonempty interior, the wave equation with subelliptic Laplacian $\Delta $ is not observable on $\omega $ in time ${T}_{0}$. The proof is based on the construction of sequences of solutions of the wave equation concentrating on spiraling geodesics (for the associated subRiemannian distance) spending a long time in $M\setminus \omega $. As a counterpart, we prove a positive result of observability for the wave equation in the Heisenberg group, where the observation set is a wellchosen part of the phase space.
 In 36, we study the observability (or, equivalently, the controllability) of some subelliptic evolution equations depending on their step. This sheds light on the speed of propagation of these equations, notably in the “degenerated directions” of the subelliptic structure. First, for any $\gamma \ge 1$, we establish a resolvent estimate for the BaouendiGrushintype operator ${\Delta}_{\gamma}={\partial}_{x}^{2}+{\leftx\right}^{2\gamma}{\partial}_{y}^{2}$, which has step $\gamma +1$. We then derive consequences for the observability of the Schrödinger type equation $i{\partial}_{t}u{({\Delta}_{\gamma})}^{s}u=0$ where $s\in N$. We identify three different cases: depending on the value of the ratio $(\gamma +1)/s$, observability may hold in arbitrarily small time, or only for sufficiently large times, or even fail for any time. As a corollary of our resolvent estimate, we also obtain observability for heattype equations ${\partial}_{t}u+{({\Delta}_{\gamma})}^{s}u=0$ and establish a decay rate for the damped wave equation associated with ${\Delta}_{\gamma}$.
 In 32 we give necessary and sufficient conditions for the controllability of a Schrödinger equation involving a subelliptic operator on a compact manifold. This subelliptic operator is the subLaplacian of the manifold that is obtained by taking the quotient of a group of Heisenberg type by one of its discrete subgroups. This class of nilpotent Lie groups is a major example of stratified Lie groups of step 2. The subLaplacian involved in these Schrödinger equations is subelliptic, and, contrarily to what happens for the usual elliptic Schrödinger equation for example on flat tori or on negatively curved manifolds, there exists a minimal time of controllability. The main tools used in the proofs are (operatorvalued) semiclassical measures constructed by use of representation theory and a notion of semiclassical wave packets that we introduce here in the context of groups of Heisenberg type.
 In 13 we are concerned with stochastic processes on surfaces in threedimensional contact subRiemannian manifolds. Employing the Riemannian approximations to the subRiemannian manifold which make use of the Reeb vector field, we obtain a second order partial differential operator on the surface arising as the limit of LaplaceBeltrami operators. The stochastic process associated with the limiting operator moves along the characteristic foliation induced on the surface by the contact distribution. We show that for this stochastic process elliptic characteristic points are inaccessible, while hyperbolic characteristic points are accessible from the separatrices. We illustrate the results with examples and we identify canonical surfaces in the Heisenberg group, and in $\mathrm{SU}\left(2\right)$ and $\mathrm{SL}(2,\mathbb{R})$ equipped with the standard subRiemannian contact structures as model cases for this setting. Our techniques further allow us to derive an expression for an intrinsic Gaussian curvature of a surface in a general threedimensional contact subRiemannian manifold.
 Twodimension almostRiemannian structures of step 2 are natural generalizations of the Grushin plane. They are generalized Riemannian structures for which the vectors of a local orthonormal frame can become parallel. Under the 2step assumption the singular set $Z$, where the structure is not Riemannian, is a 1D embedded submanifold. While approaching the singular set, all Riemannian quantities diverge. A remarkable property of these structure is that the geodesics can cross the singular set without singularities, but the heat and the solution of the Schrödinger equation (with the LaplaceBeltrami operator $\Delta $) cannot. This is due to the fact that (under a natural compactness hypothesis), the LaplaceBeltrami operator is essentially selfadjoint on a connected component of the manifold without the singular set. In the literature such phenomenon is called quantum confinement. In 16 we study the selfadjointness of the curvature Laplacian, namely $\frac{1}{2}\Delta +cK$, for $c>0$ (here $K$ is the Gaussian curvature), which originates in coordinate free quantization procedures (as for instance in pathintegral or covariant Weyl quantization). We prove that there is no quantum confinement for this type of operators.
7.2 Quantum control: new results
Let us list here our new results in quantum control theory.
 In 64 we present an analytical approach to construct the Lie algebra of finitedimensional subsystems of the driven asymmetric top rotor. Each rotational level is degenerate due to the isotropy of space, and the degeneracy increases with rotational excitation. For a given rotational excitation, we determine the nested commutators between drift and drive Hamiltonians using a graph representation. We then generate the Lie algebra for subsystems with arbitrary rotational excitation using an inductive argument. See also 48.
 In 17 we discuss which controllability properties of classical Hamiltonian systems are preserved after quantization. We discuss some necessary and some sufficient conditions for smalltime controllability of classical systems and quantum systems using the WKB method. In particular, we investigate the conjecture that if the classical system is not smalltime controllable, then the corresponding quantum system is not smalltime controllable either.
 In 59, we study, in the semiclassical sense, the global approximate controllability in small time of the quantum density and quantum momentum of the 1D semiclassical cubic Schrödinger equation with two controls between two states with positive quantum densities. We first control the asymptotic expansions of the zeroth and first order of the physical observables via AgrachevSarychev's method. Then we conclude the proof through techniques of semiclassical approximation of the nonlinear Schrödinger equation.
 In 12 we study up to which extent we can apply adiabatic control strategies to a quantum control model obtained by rotating wave approximation. In particular, we show that, under suitable assumptions on the asymptotic regime between the parameters characterizing the rotating wave and the adiabatic approximations, the induced flow converges to the one obtained by considering the two approximations separately and by combining them formally in cascade. As a consequence, we propose explicit control laws which can be used to induce desired populations transfers, robustly with respect to parameter dispersions in the controlled Hamiltonian.
 In the physics literature it is common to see the rotating wave approximation and the adiabatic approximation used “in cascade” to justify the use of chirped pulses for twolevel quantum systems driven by one external field, in particular when the resonance frequency of the system is not known precisely. Both approximations need relatively long time and are essentially based on averaging theory of dynamical systems. Unfortunately, the two approximations cannot be done independently since, in a sense, the two time scales interact. The purpose of 66 is to study how the cascade of the two approximations can be justified and how large becomes the final time as the fidelity goes to one, while preserving the robustness of the adiabatic strategy. Our main result gives a precise quantification of the uncertainty interval of the resonance frequency for which the strategy works.
 Optimal Control Theory has become a widely used method to improve process performance in quantum technologies by means of highly efficient control of quantum dynamics. Our review 20 aims at providing an introduction to key concepts of optimal control theory, accessible to physicists and engineers working in quantum control or in related fields. The different mathematical results are introduced intuitively, before being rigorously stated. The review describes modern aspects of optimal control theory, with a particular focus on the Pontryagin Maximum Principle, which is the main tool for determining openloop control laws without experimental feedback. The different steps to solve an optimal control problem are discussed, before moving on to more advanced topics such as the existence of optimal solutions or the definition of the different types of extremals, namely normal, abnormal, and singular. The review covers various quantum control issues and describes their mathematical formulation suitable for optimal control. The optimal solution of different lowdimensional quantum systems is presented in detail, illustrating how the mathematical tools are applied in a practical way.
7.3 Stability and uncertain dynamics: new results
Let us list here our new results about stability and stabilization of control systems, on the properties of systems with uncertain dynamics.
 The paper 30 is devoted to the controllability of a general linear hyperbolic system in one space dimension using boundary controls on one side. Under precise and generic assumptions on the boundary conditions on the other side, we previously established the optimal time for the null and the exact controllability for this system for a generic source term. In this work, we prove the nullcontrollability for any time greater than the optimal time and for any source term. Similar results for the exact controllability are also discussed.
 Consider a nonautonomous continuoustime linear system in which the timedependent matrix determining the dynamics is piecewise constant and takes finitely many values ${A}_{1},\cdots ,{A}_{N}$. The paper 56 studies the equality cases between the maximal Lyapunov exponent associated with the set of matrices $\{{A}_{1},\cdots ,{A}_{N}\}$, on the one hand, and the corresponding ones for piecewise deterministic Markov processes with modes ${A}_{1},\cdots ,{A}_{N}$, on the other hand. A fundamental step in this study consists in establishing a result of independent interest, namely, that any sequence of Markov processes associated with the matrices ${A}_{1},\cdots ,{A}_{N}$ converges, up to extracting a subsequence, to a Markov process associated with a suitable convex combination of those matrices. The analogous problem in continuous time has been studied in 56.
 In 55 we recall some general properties of extremal and Barabanov norms and we give a necessary and sufficient condition for a finitedimensional continuoustime linear switched system to admit a Barabanov norm.
 Adaptive control using the modification provides an easily implementable way to stabilize systems with uncertain or fluctuating parameters. Motivated by a specific application from neuroscience, we extend in 42 this methodology to nonlinear timedelay systems ruled by globally Lipschitz dynamics. In order to make the result more handy in practice, we provide an explicit construction of a Lyapunov–Krasovskii functional (LKF) with linear bounds and strict dissipation rate based on the knowledge of an LKF with quadratic bounds and pointwise dissipation rate. When applied to a model of neuronal populations involved in Parkinson’s disease, the benefits with respect to a pure proportional stabilization scheme are discussed through numerical simulations.
 The paper 38 is concerned with the Proportional Integral (PI) regulation control of the left Neumann trace of a onedimensional semilinear wave equation. The control input is selected as the right Neumann trace. The control design goes as follows. First, a preliminary (classical) velocity feedback is applied in order to shift all but a finite number of the eivenvalues of the underlying unbounded operator into the open left halfplane. We then leverage on the projection of the system trajectories into an adequate Riesz basis to obtain a truncated model of the system capturing the remaining unstable modes. Local stability of the resulting closedloop infinitedimensional system composed of the semilinear wave equation, the preliminary velocity feedback, and the PI controller, is obtained through the study of an adequate Lyapunov function. Finally, an estimate assessing the set point tracking performance of the left Neumann trace is derived.
 In 31 we construct explicit timevarying feedback laws leading to the global (null) stabilization in small time of the viscous Burgers equation with three scalar controls. Our feedback laws use first the quadratic transport term to achieve the smalltime global approximate stabilization and then the linear viscous term to get the smalltime local stabilization.
 In 15 we give sufficient conditions for InputtoState Stability in ${C}^{1}$ norm of general quasilinear hyperbolic systems with boundary input disturbances. In particular the derivation of explicit InputtoState Stability conditions is discussed for the special case of $2\times 2$ systems.
 Because they represent physical systems with propagation delays, hyperbolic systems are well suited for feedforward control. This is especially true when the delay between a disturbance and the output is larger than the control delay. In 14, we address the design of feedforward controllers for a general class of $2\times 2$ hyperbolic systems with a single disturbance input located at one boundary and a single control actuation at the other boundary. The goal is to design a feedforward control that makes the system output insensitive to the measured disturbance input. We show that, for this class of systems, there exists an efficient ideal feedforward controller which is causal and stable. The problem is first stated and studied in the frequency domain for a simple linear system. Then, our main contribution is to show how the theory can be extended, in the time domain, to general nonlinear hyperbolic systems. The method is illustrated with an application to the control of an open channel represented by Saint Venant equations where the objective is to make the output water level insensitive to the variations of the input flow rate. Finally, we address a more complex application to a cascade of pools where a blind application of perfect feedforward control can lead to detrimental oscillations. A pragmatic way of modifying the control law to solve this problem is proposed and validated with a simulation experiment.
 Selforganization and control around flocks and mills is studied in 54 for secondorder swarming systems involving selfpropulsion and potential terms. It is shown that through the action of constrained control, is it possible to control any initial configuration to a flock or a mill. The proof builds on an appropriate combination of several arguments: LaSalle invariance principle and Lyapunovlike decreasing functionals, control linearization techniques, and quasistatic deformations. A stability analysis of the secondorder system guides the design of feedback laws for the stabilization to flock and mills, which are also assessed computationally.
 In 18, we study sufficient conditions for the emergence of asymptotic consensus and flocking in a certain class of nonlinear generalised CuckerSmale systems subject to multiplicative communication failures. Our approach is based on the combination of strict Lyapunov design together with the formulation of a suitable persistence condition for multiagent systems. The latter can be interpreted as a lower bound on the algebraic connectivity of the timeaverage of the interaction graph generated by the communication weights, and provides quantitative decay estimates for the variance functional along the solutions of the system.
 In 51, we investigate the asymptotic formation of consensus for several classes of timedependent cooperative graphon dynamics. After motivating the use of this type of macroscopic model to describe multiagent systems, we adapt the classical notion of scrambling coefficient to this setting, and leverage it to establish sufficient conditions ensuring the exponential convergence to consensus with respect to the ${L}^{\infty}$norm topology. We then shift our attention to consensus formation expressed in terms of the ${L}^{2}$norm, and prove three different consensus result for symmetric, balanced and strongly connected topologies, which involve a suitable generalisation of the notion of algebraic connectivity to this infinitedimensional framework. We then show that, just as in the finitedimensional setting, the notion of algebraic connectivity that we propose encodes information about the connectivity properties of the underlying interaction topology. We finally use the corresponding results to shed some light on the relation between ${L}^{2}$and ${L}^{\infty}$consensus formation, and illustrate our contributions by a series of numerical simulations.
 In 58 we study the socalled water tank system. In this system, the behavior of water contained in a 1D tank is modelled by SaintVenant equations, with a scalar distributed control. It is wellknown that the linearized systems around uniform steadystates are not controllable, the uncontrollable part being of infinite dimension. Here we will focus on the linearized systems around nonuniform steady states, corresponding to a constant acceleration of the tank. We prove that these systems are controllable in Sobolev spaces, using the moments method and perturbative spectral estimates. Then, for steady states corresponding to small enough accelerations, we design an explicit Proportional Integral feedback law (obtained thanks to a wellchosen dynamic extension of the system) that stabilizes these systems exponentially with arbitrarily large decay rate. Our design relies on feedback equivalence/backstepping.
 In 53 we consider finite and infinitedimensional firstorder consensus systems with timeconstant interaction coefficients. For symmetric coefficients, convergence to consensus is classically established by proving, for instance, that the usual variance is an exponentially decreasing Lyapunov function. We investigate here the convergence to consensus in the nonsymmetric case: we identify a positive weight which allows to define a weighted mean corresponding to the consensus, and obtain exponential convergence towards consensus. Moreover, we compute the sharp exponential decay rate.
 In 24 we study asymptotic stability of continuoustime systems with modedependent guaranteed dwell time. These systems are reformulated as special cases of a general class of mixed (discretecontinuous) linear switching systems on graphs, in which some modes correspond to discrete actions and some others correspond to continuoustime evolutions. Each discrete action has its own positive weight which accounts for its timeduration. We develop a theory of stability for the mixed systems; in particular, we prove the existence of an invariant Lyapunov norm for mixed systems on graphs and study its structure in various cases, including discretetime systems for which discrete actions have inhomogeneous time durations. This allows us to adapt recent methods for the joint spectral radius computation (Gripenberg's algorithm and the Invariant Polytope Algorithm) to compute the Lyapunov exponent of mixed systems on graphs.
 In 49 we study the numerical approximation of the stabilization of the semidiscrete linearized Boussinesq system around an unstable stationary state. The stabilization is achieved by internal feedback controls applied on the velocity and the temperature equations, localized in an arbitrary open subset. The goal is to study the approximation by penalization of the free divergence condition in the semidiscrete case. More precisely, considering infinite time horizon LQR optimal control problem, we establish convergence results for the optimal controls, optimal solutions and Riccati operators when the penalization parameter goes to zero. We then propose a numerical validation of these results in a twodimensional setting.
 In 61 we study the exponential stability in the ${H}^{2}$ norm of the nonlinear SaintVenant (or shallow water) equations with arbitrary friction and slope using a single ProportionalIntegral (PI) control at one end of the channel. Using a good but simple Lyapunov function we find a simple and explicit condition on the gain the PI control to ensure the exponential stability of any steadystates. This condition is independent of the slope, the friction coefficient, the length of the river, the inflow disturbance and, more surprisingly, can be made independent of the steady state considered. When the inflow disturbance is timedependent and no steadystate exist, we still have the InputtoState stability of the system, and we show that changing slightly the PI control enables to recover the exponential stability of slowly varying trajectories.
 In 29 we are interested in the boundary stabilization in finite time of onedimensional linear hyperbolic balance laws with coefficients depending on time and space. We extend the so called “backstepping method” by introducing appropriate timedependent integral transformations in order to map our initial system to a new one which has desired stability properties. The kernels of the integral transformations involved are solutions to nonstandard multidimensional hyperbolic PDEs, where the time dependence introduces several new difficulties in the treatment of their wellposedness. This work generalizes previous results of the literature, where only timeindependent systems were considered.
 Given a discretetime linear switched system associated with a finite set of matrices, we consider the measures of its asymptotic behavior given by, on the one hand, its deterministic joint spectral radius and, on the other hand, its probabilistic joint spectral radius for Markov random switching signals with given transition matrix and corresponding invariant probability. In 25, we investigate the cases of equality between the two measures.
 The general context of 37 is the feedback control of an infinitedimensional system so that the closedloop system satisfies a fadingmemory property and achieves the setpoint tracking of a given reference signal. More specifically , this paper is concerned with the Proportional Integral (PI) regulation control of the left Neumann trace of a onedimensional reactiondiffusion equation with a delayed right Dirichlet boundary control. In this setting, the studied reactiondiffusion equation might be either openloop stable or unstable. The proposed control strategy goes as follows. First, a finitedimensional truncated model that captures the unstable dynamics of the original infinitedimensional system is obtained via spectral decomposition. The truncated model is then augmented by an integral component on the tracking error of the left Neumann trace. After resorting to the Artstein transformation to handle the control input delay, the PI controller is designed by pole shifting. Stability of the resulting closedloop infinitedimensional system, consisting of the original reactiondiffusion equation with the PI controller, is then established thanks to an adequate Lyapunov function. In the case of a timevarying reference input and a timevarying distributed disturbance, our stability result takes the form of an exponential InputtoState Stability (ISS) estimate with fading memory. Finally, another exponential ISS estimate with fading memory is established for the tracking performance of the reference signal by the system output. In particular, these results assess the setpoint regulation of the left Neumann trace in the presence of distributed perturbations that converge to a steadystate value and with a timederivative that converges to zero. Numerical simulations are carried out to illustrate the efficiency of our control strategy.
 In 33 we deal with infinitedimensional nonlinear forward complete dynamical systems which are subject to external disturbances. We first extend the wellknown Datko lemma to the framework of the considered class of systems. Thanks to this generalization, we provide characterizations of the uniform (with respect to disturbances) local, semiglobal, and global exponential stability, through the existence of coercive and noncoercive Lyapunov functionals. The importance of the obtained results is underlined through some applications concerning 1) exponential stability of nonlinear retarded systems with piecewise constant delays, 2) exponential stability preservation under sampling for semilinear control switching systems, and 3) the link between inputtostate stability and exponential stability of semilinear switching systems.
7.4 Controllability: new results
Let us list here our new results on controllability beyond the quantum control framework.
 The work 60 studies the reachable space of infinite dimensional control systems which are null controllable in any positive time, the typical example being the heat equation controlled from the boundary or from an arbitrary open set. The focus is on the robustness of the reachable space with respect to linear or nonlinear perturbations of the generator. More precisely, our first main results asserts that this space is invariant under perturbations which are small (in an appropriate sense). A second main result asserts the invariance of the reachable space with respect to perturbations which are compact (again in an appropriate sense), provided that a Hautus type condition is satisfied. Moreover, our methods give precise information on the behavior of the reachable space when the generator is perturbed by a class of nonlinear operators. When applied to the classical heat equation, our results provide detailed information on the reachable space when the generator is perturbed by a small potential or by a class of non local operators, and in particular in one space dimension, we deduce from our analysis that the reachable space for perturbations of the 1d heat equation is a space of holomorphic functions. We also show how our approach leads to reachability results for a class of semilinear parabolic equations.
 In 23 we show that a bilinear control system is approximately controllable if and only if it is controllable in ${\mathbb{R}}^{n}\setminus \left\{0\right\}$. We approach this problem by looking at the foliation made by the orbits of the system, and by showing that there does not exist a codimensionone foliation in ${\mathbb{R}}^{n}\setminus \left\{0\right\}$ with dense leaves that are everywhere transversal to the radial direction. The proposed geometric approach allows to extend the results to homogeneous systems that are angularly controllable.
 Under a regularity assumption we prove in 21 that reachability in fixed time for nonlinear control systems is robust under control sampling.
 Our goal in 34 is to relate the observation (or control) of the wave equation on observation domains which evolve in time with some dynamical properties of the geodesic flow. In comparison to the case of static domains of observation, we show that the observability of the wave equation in any dimension of space can be improved by allowing the domain of observation to move.
 In 39 we consider the controllability problem for finitedimensional linear autonomous control systems with nonnegative controls. Despite the Kalman condition, the unilateral nonnegativity control constraint may cause a positive minimal controllability time. When this happens, we prove that, if the matrix of the system has a real eigenvalue, then there is a minimal time control in the space of Radon measures, which consists of a finite sum of Dirac impulses. When all eigenvalues are real, this control is unique and the number of impulses is less than half the dimension of the space. We also focus on the control system corresponding to a finitedifference spatial discretization of the onedimensional heat equation with Dirichlet boundary controls, and we provide numerical simulations.
7.5 Optimal control and optimization: new results
Let us list here our new results in optimal control theory beyond quantum control and the subRiemannian framework.
 We are interested in the design of stellarators, devices for the production of controlled nuclear fusion reactions alternative to tokamaks. The confinement of the plasma is entirely achieved by a helical magnetic field created by the complex arrangement of coils fed by high currents around a toroidal domain. Such coils describe a surface called “coil winding surface” (CWS). In 65, we model the design of the CWS as a shape optimization problem, so that the cost functional reflects both optimal plasma confinement properties, through a least square discrepancy, and also manufacturability, thanks to geometrical terms involving the lateral surface or the curvature of the CWS. We completely analyze the resulting problem: on the one hand, we establish the existence of an optimal shape, prove the shape differentiability of the criterion, and provide the expression of the differential in a workable form. On the other hand, we propose a numerical method and perform simulations of optimal stellarator shapes. We discuss the efficiency of our approach with respect to the literature in this area.
 The outbreak of COVID19 resulted in high death tolls all over the world. The aim of 40 is to show how a simple SEIR model was used to make quick predictions for New Jersey in early March 2020 and call for action based on data from China and Italy. A more refined model, which accounts for social distancing, testing, contact tracing and quarantining, is then proposed to identify containment measures to minimize the economic cost of the pandemic. The latter is obtained taking into account all the involved costs including reduced economic activities due to lockdown and quarantining as well as the cost for hospitalization and deaths. The proposed model allows one to find optimal strategies as combinations of implementing various nonpharmaceutical interventions and study different scenarios and likely initial conditions.
 In 52 we study a family of optimal control problems in which one aims at minimizing a cost that mixes a quadratic control penalization and the variance of the system, both for finitely many agents and for the meanfield dynamics as their number goes to infinity. While solutions of the discrete problem always exist in a unique and explicit form, the behavior of their macroscopic counterparts is very sensitive to the magnitude of the time horizon and penalization parameter. When one minimizes the final variance, there always exists a Lipschitzinspace optimal controls for the infinite dimensional problem, which can be obtained as a suitable extension of the optimal controls for the finitedimensional problems. The same holds true for variance maximizations whenever the time horizon is sufficiently small. On the contrary, for large final times (or equivalently for small penalizations of the control cost), it can be proven that there does not exist Lipschitzregular optimal controls for the macroscopic problem.
 Magnetic confinement devices for nuclear fusion can be large and expensive. Compact stellarators are promising candidates for construction, but introduce new difficulties: confinement in smaller volumes requires higher magnetic field, which calls for higher coilcurrents and ultimately causes higher Laplace forces on the coilsif everything else remains the same. This motivates the inclusion of force reduction in stellarator coil optimization. In 67 we consider a coil winding surface, we prove that there is a natural and rigorous way to define the Laplace force (despite the magnetic field discontinuity across the currentsheet), we provide examples of cost associated (peak force, surfaceintegral of the force squared) and discuss easy generalizations to parallel and normal forcecomponents, as these will be subject to different engineering constraints. Such costs can then be easily added to the figure of merit in any multiobjective stellarator coil optimization code. We demonstrate this for a generalization of the REGCOIL code, which we rewrote in python, and provide numerical examples for the NCSX (now QUASAR) design. We present results for various definitions of the cost function, including peak force reductions by up to 40%, and outline future work for further reduction.
 In 50 we consider a measuretheoretical formulation of the training of NeurODEs in the form of a meanfield optimal control with ${L}^{2}$regularization of the control. We derive first order optimality conditions for the NeurODE training problem in the form of a meanfield maximum principle, and show that it admits a unique control solution, which is Lipschitz continuous in time. As a consequence of this uniqueness property, the meanfield maximum principle also provides a strong quantitative generalization error for finite sample approximations. Our derivation of the meanfield maximum principle is much simpler than the ones currently available in the literature for meanfield optimal control problems, and is based on a generalized Lagrange multiplier theorem on convex sets of spaces of measures. The latter is also new, and can be considered as a result of independent interest.
 Our aim in 11 is to present a new model which encompasses pace optimization and motor control effort for a runner on a fixed distance. We see that for long races, the long term behaviour is well approximated by a turnpike problem. We provide numerical simulations quite consistent with this approximation which leads to a simplified problem. We are also able to estimate the effect of slopes and ramps.
 In 22 we revisit and extend the Riccati theory, unifying continuoustime linearquadratic optimal permanent and sampleddata control problems, in finite and infinite time horizons. In a nutshell, we prove that: – when the time horizon T tends to $+\infty $, one passes from the SampledData Difference Riccati Equation (SDDRE) to the SampledData Algebraic Riccati Equation (SDARE), and from the Permanent Differential Riccati Equation (PDRE) to the Permanent Algebraic Riccati Equation (PARE); – when the maximal step of the time partition $\Delta $ tends to 0, one passes from (SDDRE) to (PDRE), and from (SDARE) to (PARE). Our notations and analysis provide a unified framework in order to settle all corresponding results.
 The turnpike phenomenon stipulates that the solution of an optimal control problem in large time, remains essentially close to a steadystate of the dynamics, itself being the optimal solution of an associated static optimal control problem. Under general assumptions, it is known that not only the optimal state and the optimal control, but also the adjoint state coming from the application of the Pontryagin maximum principle, are exponentially close to a steadystate, except at the beginning and at the end of the time frame. In such results, the turnpike set is a singleton, which is a steadystate. In 68 we establish a turnpike result for finitedimensional optimal control problems in which some of the coordinates evolve in a monotone way, and some others are partial steadystates of the dynamics. We prove that the discrepancy between the optimal trajectory and the turnpike set is then linear, but not exponential: we thus speak of a linear turnpike theorem. See also 46 for shape turnpike results.
Let us also mention the publication 28, in honor of Enrique Zuazua, at the occasion of his sixtieth birthday.
8 Bilateral contracts and grants with industry
8.1 Bilateral contracts with industry
Contract CIFRE with ArianeGroup (les Mureaux), 2019–2021, funding the thesis of A. Nayet. Participants : M. Cerf (ArianeGroup), E. Trélat (coordinator).
Contract with MBDA (Palaiseau), 2021–2023. Subject: “Controôle optimal pour la planification de trajectoires et l’estimation des ensembles accessibles". Pariticpants: V. Askovic (MBDA & CAGE), E. Trélat (coordinator).
8.2 Bilateral grants with industry
Grant by AFOSR (Air Force Office of Scientific Research), 2020–2023. Participants : Mohab Safey El Din (LIP6), E. Trélat.
9 Partnerships and cooperations
9.1 International research visitors
9.1.1 Visits of international scientists
Inria International Chair
IIC AGRACHEV Andrei

Name of the chair:
SubRiemannan geometry and applications

Institution of origin:
SISSA

Country:
Italy

Dates:
From Sep 01 2020 to Nov 30 2021

Title:
SubRiemannan geometry and applications
9.2 European initiatives
9.2.1 FP7 & H2020 projects
Program: H2020EU.1.3.1.  Fostering new skills by means of excellent initial training of researchers
Call for proposal: MSCAITN2017  Innovative Training Networks
Project acronym: QUSCO
Project title: Quantumenhanced Sensing via Quantum Control
Duration: From November 2017 to October 2021.
Coordinator: Christiane Koch
Coordinator for the participant Inria: Ugo Boscain
Abstract: Quantum technologies aim to exploit quantum coherence and entanglement, the two essential elements of quantum physics. Successful implementation of quantum technologies faces the challenge to preserve the relevant nonclassical features at the level of device operation. It is thus deeply linked to the ability to control open quantum systems. The currently closest to market quantum technologies are quantum communication and quantum sensing. The latter holds the promise of reaching unprecedented sensitivity, with the potential to revolutionize medical imaging or structure determination in biology or the controlled construction of novel quantum materials. Quantum control manipulates dynamical processes at the atomic or molecular scale by means of specially tailored external electromagnetic fields. The purpose of QuSCo is to demonstrate the enabling capability of quantum control for quantum sensing and quantum measurement, advancing this field by systematic use of quantum control methods. QuSCo will establish quantum control as a vital part for progress in quantum technologies. QuSCo will expose its students, at the same time, to fundamental questions of quantum mechanics and practical issues of specific applications. Albeit challenging, this reflects our view of the best possible training that the field of quantum technologies can offer. Training in scientific skills is based on the demonstrated tradition of excellence in research of the consortium. It will be complemented by training in communication and commercialization. The latter builds on strong industry participation whereas the former existing expertise on visualization and gamification and combines it with more traditional means of outreach to realize target audience specific public engagement strategies.
9.3 National initiatives
The Inria Exploratory Action “StellaCage” is supporting since Spring 2020 a collaboration between CAGE, Yannick Privat (Inria team TONUS), and the startup Renaissance Fusion, based in Grenoble (Francesco Volpe, CEO & Chris Smiet, CSO).
StellaCage approaches the problem of designing better stellarators (yielding better confinement, with simpler coils, capable of higher fields) by combining geometrical properties of magnetic field lines from the control perspective with shape optimization techniques.
9.3.1 ANR
 ANR SRGI, for SubRiemannian Geometry and Interactions, coordinated by Emmanuel Trélat, started in 2015 and run until March 2021. Other partners: Toulon University and Grenoble University. SRGI deals with subRiemannian geometry, hypoelliptic diffusion and geometric control.
 ANR TRECOS, for New Trends in Control and Stabilization: Constraints and nonlocal terms, coordinated by Sylvain Ervedoza, University of Bordeaux. The ANR started in 2021 and runs up to 2024. TRECOS' focus is on control theory for partial differential equations, and in particular models from ecology and biology.
 ANR QUACO, for QUAntum COntrol: PDE systems and MRI applications, coordinated by Thomas Chambrion, started in 2017 and will run until mid 2022. Other partners: Burgundy University. QUACO aims at contributing to quantum control theory in two directions: improving the comprehension of the dynamical properties of controlled quantum systems in infinitedimensional state spaces, and improve the efficiency of control algorithms for MRI.
9.4 Regional initiatives
Barbara Gris is the PI of a Bourse Emergence(s) by the Ville de Paris.
10 Dissemination
10.1 Promoting scientific activities
10.1.1 Scientific events: organisation
Barbara Gris was the organizer of the Journée thématique MIA “Registering Medical Images’' at Henri Poincaré Institute(IHP), October 21, 2021.
Ugo Boscain organized (with Dario Prandi and Alessandro Sarti) the session “SubRiemannian geometry and neuromathematics” at GSI2021, Paris, July 2021.
JeanMichel Coron organized (with Tatsien Li and Zhiqiang Wang) two LIASFMA (Laboratoire International Associé SinoFrançais de Mathématiques Appliquées) International Graduate School on Applied Mathematics, online, the first one in April 2021 and the second one in NovemberDecember 2021.
Ugo Boscain, Eugenio Pozzoli, and Mario Sigalotti were the organizers of the workshop “Quantum day: analysis and control” at LJLL, September 13, 2021.
Mario Sigalotti was one of the organizers of the “Padua Paris SubRiemannian seminar”, Padua, Italy, September 67, 2021.
10.1.2 Journal
Member of the editorial boards
 Ugo Boscain is Associate editor of SIAM Journal of Control and Optimization
 Ugo Boscain is Managing editor of Journal of Dynamical and Control Systems
 JeanMichel Coron is Editorinchief of Comptes Rendus Mathématique
 JeanMichel Coron is Associate editor of Journal of Evolution Equations
 JeanMichel Coron is Associate editor of Asymptotic Analysis
 JeanMichel Coron is Associate editor of ESAIM: Control, Optimisation and Calculus of Variations
 JeanMichel Coron is Associate editor of Applied Mathematics Research Express
 JeanMichel Coron is Associate editor of Advances in Differential Equations
 JeanMichel Coron is Associate editor of Mathematics of Control, Signals, and Systems
 JeanMichel Coron is Associate editor of Annales de l'IHP, Analyse non linéaire
 Mario Sigalotti is Associate editor of ESAIM: Control, Optimisation and Calculus of Variations
 Mario Sigalotti is Associate editor of Journal on Dynamical and Control Systems
 Emmanuel Trélat is Editorinchief of ESAIM: Control, Optimisation and Calculus of Variations
 Emmanuel Trélat is Associate editor of SIAM Review
 Emmanuel Trélat is Associate editor of Systems & Control Letters
 Emmanuel Trélat is Associate editor of Journal on Dynamical and Control Systems
 Emmanuel Trélat is Associate editor of Bollettino dell'Unione Matematica Italiana
 Emmanuel Trélat is Associate editor of ESAIM: Mathematical Modelling and Numerical Analysis
 Emmanuel Trélat is Editor of BCAM Springer Briefs
 Emmanuel Trélat is Associate editor of IEEE Transactions on Automatic Control
 Emmanuel Trélat is Associate editor of Journal of Optimization Theory and Applications
 Emmanuel Trélat is Associate editor of Mathematical Control & Related Fields
 Emmanuel Trélat is Associate editor of Mathematics of Control, Signals, and Systems
 Emmanuel Trélat is Associate editor of Optimal Control Applications and Methods
 Emmanuel Trélat is Associate editor of Advances in Continuous and Discrete Models: Theory and Modern Applications
10.1.3 Invited talks
 Ugo Boscain and Daniele Cannarsa were invited speakers at the “Padua Paris SubRiemannian seminar”, Padua, Italy, September 2021.
 Ugo Boscain was invited speaker at the conference ”Stochastic Differential Geometry and Mathematical Physics”, Rennes (online talk), June 2021.
 Ugo Boscain was invited speaker at the Séminaire de Neuromathématiques Ehess, Collège de France (online), April 2021.
 Ugo Boscain was invited speaker at the conference “Microlocal and Global Analysis, Interactions with Geometry”, Potsdam, Germany (online talk), February 2021.
 Ugo Boscain was invited speaker at the International conference on Dynamic Control and Optimization DCO2021, Aveiro, Portugal (online talk), February 2021.
 Ugo Boscain was invited speaker at the 41th Winter school on Geometry and Physics, Brno, Czech republic (online talk), January 2021.
 Kévin Le Balc'h was invited speaker at the Séminaire du LJLL, December 2021.
 Mario Sigalotti and Emmanuel Trélat were invited speakers at the conference “Analysis, Control, and Numerics for PDE Models of Interest to Physical and Life Sciences”, Levico Terme, Italy (online talks), September, 2021
 Mario Sigalotti was invited speaker at the conference “3 days on Evolution PDEs”, Urbino, Italy, September 2021.
 Mario Sigalotti was invited speaker at the conference “Analyse et contrôle des systèmes d'EDP”, Bordeaux, November 2021.
 Emmanuel Trélat was invited speaker at the Colloquium du Laboratoire J.A. Dieudonneé, Univ. Nice, June 2021.
 Emmanuel Trélat was invited speaker at the Workshop on Nonlinear Analysis and Control Theory, in honor of Enrique Zuazua, online, November 2021.
 Emmanuel Trélat was invited speaker at the conference “Kinetic and mean field problems”, Ferrara, Italy (online talk), October 2021.
 Emmanuel Trélat was invited speaker at the SIAM Conference on Control and Its Applications (CT21), online, July 2021.
 Emmanuel Trélat was invited speaker at the INdAM Workshop “Analysis and Numerics of Design, Control and Inverse Problems”, Rome, July 2021.
 Emmanuel Trélat was invited speaker at the conference “Stochastic Differential Geometry and Mathematical Physics”, Rennes, June 2021.
 Emmanuel Trélat was invited speaker at the miniworkshop “Mathematics of Dissipation – Dynamics, Data and Control”, Oberwolfach, Germany, May 2021.
 Emmanuel Trélat was invited speaker at the online seminar in EDP and applied mathematics, Brazil, October 2021.
 Emmanuel Trélat was invited speaker at the Asia Pacific Analysis and PDE Seminar (online), February 2021.
 Emmanuel Trélat was invited speaker at the seminar at Université Clermont Auvergne, October 2021.
 Emmanuel Trélat was invited speaker at the seminar at Université de Brest, September 2021.
 Emmanuel Trélat was invited speaker at the seminar at Chongqing University (online talk), Mars 2021.
10.1.4 Research administration
Emmanuel Trélat is Head of the Laboratoire JacquesLouis Lions (LJLL).
10.2 Teaching  Supervision  Juries
10.2.1 Teaching
 Ugo Boscain and Mario Sigalotti thought “Geometric control theory” to M2 students at Sorbonne Université
 Ugo Boscain thought “Automatic control with applications in robotics and in quantum engineering” at Ecole Polytechnique.
 Ugo Boscain thought “MODAL of applied mathematics. Contrôle de modèles dynamiques” at Ecole Polytechnique
 Ugo Boscain thought “SubRiemannian geometry” to PhD students at SISSA, Trieste, Italy
 Kévin Le Balc'h thought “Analyse numérique” to L3 students at Sorbonne Université.
 Mario Sigalotti thought “Équations d'évolution, stabilité et contrôle” to M1 students at Sorbonne Université
 Emmanuel Trélat thought “Contrôle en dimension finie et infinie” to M2 students at Sorbonne Université
 Emmanuel Trélat thought “Optimisation numérique et sciences des données” to M1 students at Sorbonne Université
10.2.2 Supervision
 PhD: Daniele Cannarsa, “Surfaces in threedimensionnal contact subRiemannian manifolds and controllability of nonlinear ODEs”, October 2021. Supervisors: Davide Barilari (Padova, Italy) and Ugo Boscain.
 PhD: Gontran Lance, “Shape turnpike, numerical control and optimal design for PDES”, started in September November 2021. Supervisors: Emmanuel Trélat and Enrique Zuazua (Erlangen, Germany).
 PhD: Cyril Letrouit, “Équations souselliptiques : contrôle, singularités et théorie spectrale”, October 2021. Supervisors: Emmanuel Trélat and Yves Colin de Verdière (Grenoble).
 PhD: Eugenio Pozzoli, “Some problems of evolution and control in quantum mechanics”, October 2021. Supervisors: Ugo Boscain and Mario Sigalotti.
 PhD: Justine Dorsz, “Contrôlabilité et limite de champs moyen”, resigned in Febrary 2021. Supervisors: Olivier Glass and Emmanuel Trélat.
 PhD in progress: Emilio Molina, “Application of optimal control techniques to natural resources management”, started in September 2018, supervisors: Pierre Martinon, Héctor Ramírez, and Mario Sigalotti.
 PhD in progress: Aymeric Nayet, “Améliorations d'un solveur de contrôle optimal pour de nouvelles missions Ariane”, started in September 2019. Supervisor: Emmanuel Trélat.
 PhD in progress: Rémi Robin, “Orbit spaces of Lie groups and applications to quantum control”, started in September 2019, supervisors: Ugo Boscain and Mario Sigalotti.
 PhD in progress: Veljko Askovic, “Planification de trajectoires par HJB & PMP”, started in 2020. Supervisors: Emmanuel Trélat and Hasnaa Zidani (INSA, Rouen).
 PhD in progress: Liangying Chen, “Sensitivity, Verification and Conjugate Times in Stochastic Optimal Control”, started in 2021. Supervisors: Emmanuel Trélat and Xu Zhang.
 PhD in progress: Robin Roussel, “Magnetic field lines and confinement in stellarators: a Hamiltonian perspective”, started in 2021. Supervisors: Ugo Boscain and Mario Sigalotti.
10.2.3 Juries
 Ugo Boscain was referee and member of the jury of the PhD thesis of Irigo Zibo, INSA Rouen.
 Emmanuel Trélat was referee and member of the jury of the PhD thesis of B. Wembe, Université de Toulouse.
 Emmanuel Trélat was president of the jury of the PhD thesis of E. Pozzoli, Sorbonne Université.
 Emmanuel Trélat was referee and member of the jury of the PhD thesis of T. Rossi, Université de Grenoble.
 Emmanuel Trélat was referee and member of the jury of the PhD thesis of Y. Song, HongKong University.
 Emmanuel Trélat was member of the jury of the PhD thesis of L. Zonca, ENS Ulm.
 Emmanuel Trélat was referee and member of the jury of the PhD thesis of M. Dus, Université de Toulouse.
 Emmanuel Trélat was referee and member of the jury of the PhD thesis of E. Blazquez, ISAE, Toulouse.
 Emmanuel Trélat was member of the jury of the PhD thesis of K. Kassab, Sorbonne Université.
10.3 Popularization
10.3.1 Internal or external Inria responsibilities
Emmanuel Trélat is member of the Comité d'Honneur du Comité International des Jeux Mathématiques
10.3.2 Articles and contents
The work 11 by Amandine Aftalion and Emmaneul Trélat has been popularized in the article Voici la course parfaite by Muriel Valin, Epsiloon, December 2021.
10.3.3 Interventions
Emmanuel Trélat gave a general public lecture at Les forums régionaux du savoir, Rouen, October 2021.
11 Scientific production
11.1 Major publications
 1 articleStochastic processes on surfaces in threedimensional contact subRiemannian manifolds.Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques25 pages, 2 figures2021
 2 articleOn the regularity of abnormal minimizers for rank 2 subRiemannian structures.Journal de Mathématiques Pures et Appliquées1332020, 118138
 3 articleCorticalinspired WilsonCowantype equations for orientationdependent contrast perception modelling.Journal of Mathematical Imaging and VisionJune 2020
 4 articleOptimal Control of EndoAtmospheric Launch Vehicle Systems: Geometric and Computational Issues.IEEE Transactions on Automatic Control6562020, 24182433
 5 articleClassical and quantum controllability of a rotating 3D symmetric molecule.SIAM Journal on Control and Optimization2020
 6 articleSmalltime global exact controllability of the NavierStokes equation with Navier slipwithfriction boundary conditions.Journal of the European Mathematical Society225May 2020, 16251673
 7 articleFinitetime stabilization in optimal time of homogeneous quasilinear hyperbolic systems in one dimensional space.ESAIM: Control, Optimisation and Calculus of Variations262020, 119
 8 articleNonnegative control of finitedimensional linear systems.Annales de l'Institut Henri Poincaré (C) Non Linear Analysis382021, 301346
 9 articleImage reconstruction through metamorphosis.Inverse Problems362020
 10 unpublishedOn the compatibility of the adiabatic and rotating wave approximations for robust population transfer in qubits.March 2020, working paper or preprint
11.2 Publications of the year
International journals
 11 articlePace and motor control optimization for a runner.Journal of Mathematical Biology8312021, Paper No. 9
 12 articleEffective adiabatic control of a decoupled Hamiltonian obtained by rotating wave approximation.Automatica1362022
 13 articleStochastic processes on surfaces in threedimensional contact subRiemannian manifolds.Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques2021

14
articleFeedforward boundary control of
$22$ nonlinear hyperbolic systems with application to SaintVenant equations.European Journal of Control2021, 4153  15 articleInputtoState Stability in sup norms for hyperbolic systems with boundary disturbances.Nonlinear Analysis: Theory, Methods and Applications2082021

16
articleQuantum confinement for the curvature Laplacian
$+cK$ on 2DalmostRiemannian manifolds.Potential AnalysisAugust 2021  17 articleAn obstruction to smalltime controllability of the bilinear Schrödinger equation.Journal of Mathematical Physics622021
 18 articleConsensus and Flocking under Communication Failures for a Class of CuckerSmale Systems.Systems and Control Letters152June 2021, 104930
 19 articleA bioinspired geometric model for sound reconstruction.Journal of Mathematical Neuroscience111January 2021, 2
 20 articleIntroduction to the Pontryagin Maximum Principle for Quantum Optimal Control.PRX Quantum232021, 030203
 21 articleRobustness under control sampling of reachability in fixed time for nonlinear control systems.Mathematics of Control, Signals, and Systems3332021, 515551
 22 articleUnified Riccati theory for optimal permanent and sampleddata control problems in finite and infinite time horizons.SIAM Journal on Control and Optimization5922021, 489508
 23 articleApproximately controllable finitedimensional bilinear systems are controllable.Systems and Control Letters1573November 2021, 105028
 24 articleSwitching systems with dwell time: computing the maximal Lyapunov exponent.Nonlinear Analysis: Hybrid Systems2021
 25 articleOn the gap between deterministic and probabilistic joint spectral radii for discretetime linear systems.Linear Algebra and its Applications613March 2021, 2445
 26 articlePropagation of wellprepared states along Martinet singular geodesics.Journal of Spectral Theory2021
 27 articleSmalltime asymptotics of hypoelliptic heat kernels near the diagonal, nilpotentization and related results.Annales Henri Lebesgue42021, 897971
 28 articleIntroduction: On Enrique.ESAIM: Control, Optimisation and Calculus of Variations272021, E3
 29 articleBoundary stabilization in finite time of onedimensional linear hyperbolic balance laws with coefficients depending on time and space.Journal of Differential Equations2712021, 11091170
 30 articleNullcontrollability of linear hyperbolic systems in one dimensional space.Systems and Control Letters1482021
 31 articleSmalltime global stabilization of the viscous Burgers equation with three scalar controls.Journal de Mathématiques Pures et Appliquées15192021, 212–256
 32 articleObservability and Controllability for the Schrödinger Equation on Quotients of Groups of Heisenberg Type.Journal de l'École polytechnique — Mathématiques2021
 33 articleLyapunov characterization of uniform exponential stability for nonlinear infinitedimensional systems.IEEE Transactions on Automatic Control2021
 34 articleCatching all geodesics of a manifold with moving balls and application to controllability of the wave equation.Annali della Scuola Normale Superiore di Pisa, Classe di Scienze2021
 35 articleSubelliptic wave equations are never observable.Analysis & PDE2021
 36 articleObservability of BaouendiGrushinType Equations Through Resolvent Estimates.Journal de l'Institut de Mathématiques de Jussieu2021
 37 articlePI Regulation of a ReactionDiffusion Equation with Delayed Boundary Control.IEEE Transactions on Automatic Control664April 2021, 1573  1587
 38 articleProportional Integral regulation control of a onedimensional semilinear wave equation.SIAM Journal on Control and Optimization6012022, 121
 39 articleNonnegative control of finitedimensional linear systems.Annales de l'Institut Henri Poincaré (C) Non Linear Analysis382March 2021, 301346
 40 articleControl of COVID19 outbreak using an extended SEIR model.Mathematical Models and Methods in Applied Sciences3112November 2021, 23992424
 41 articleShape deformation analysis reveals the temporal dynamics of celltypespecific homeostatic and pathogenic responses to mutant huntingtin.eLife102021, e64984
 42 articleAdaptive control of Lipschitz timedelay systems by sigma modification with application to neuronal population dynamics.Systems and Control Letters159January 2022, 105082
International peerreviewed conferences
 43 inproceedingsAn auditory cortex model for sound processing.Geometric Science of InformationGSI 2021: Geometric Science of Information12829Lecture Notes in Computer ScienceParis, FranceJuly 2021
 44 inproceedingsMultishape registration with constrained deformations.Geometric Science of InformationGSI 2021  5th International Conference Geometric Science of Information12829Geometric Science of InformationParis, FranceSpringerJuly 2021, 8290
 45 inproceedingsIMODAL: creating learnable userdefined deformation models.Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)CVPR 2021  IEEE/CVF Conference on Computer Vision and Pattern RecognitionProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Virtual event, United StatesJune 2021, 1290512913
Doctoral dissertations and habilitation theses
 46 thesisShape turnpike, numerical control and optimal design for PDEs.Sorbonne UniversitéNovember 2021
 47 thesisSubelliptic equations : control, singularities and spectral theory.Sorbonne UniversitéOctober 2021
 48 thesisSome problems of evolution and control in quantum mechanics.Sorbonne UniversitéOctober 2021
Reports & preprints
 49 miscSemidiscrete approximation of the penalty approach to the stabilization of the Boussinesq system by localized feedback control.November 2021
 50 miscA Measure Theoretical Approach to the Meanfield Maximum Principle for Training NeurODEs.July 2021
 51 miscConsensus Formation in FirstOrder Graphon Models with TimeVarying Topologies.November 2021
 52 miscVariance Optimization and Control Regularity for MeanField Dynamics.July 2021
 53 miscExponential convergence towards consensus for nonsymmetric linear firstorder systems in finite and infinite dimensions.April 2021
 54 miscControlling swarms towards flocks and mills.November 2021
 55 miscCharacterization of linear switched systems admitting a Barabanov norm.December 2021
 56 miscOn the gap between deterministic and probabilistic Lyapunov exponents for continuoustime linear systems.December 2021
 57 miscSpiraling of subRiemannian geodesics around the Reeb flow in the 3D contact case.February 2021
 58 miscStabilization of the linearized water tank system.March 2021
 59 miscOn the global approximate controllability in small time of semiclassical 1D Schrödinger equations between two states with positive quantum densities.October 2021
 60 miscReachability results for perturbed heat equations.October 2021
 61 miscPI controller for the general SaintVenant equations.August 2021
 62 miscExact observability properties of subelliptic wave and Schrödinger equations.October 2021
 63 miscPropagation of singularities for subelliptic wave equations.December 2021
 64 miscLie algebra for rotational subsystems of a driven asymmetric top.January 2022
 65 miscOptimal shape of stellarators for magnetic confinement fusion.December 2021
 66 miscEnsemble qubit controllability with a single control via adiabatic and rotating wave approximations.May 2021
 67 miscMinimization of magnetic forces on Stellarator coils.March 2021
 68 miscLinear turnpike theorem.August 2021
11.3 Cited publications
 69 inproceedingsControllability of the Schrödinger Equation via Intersection of Eigenvalues.Proceedings of the 44th IEEE Conference on Decision and Control2005, 10801085
 70 articleCurvature: a variational approach.Mem. Amer. Math. Soc.25612252018, v+142
 71 articleOn robust Liealgebraic stability conditions for switched linear systems.Systems Control Lett.6122012, 347353URL: https://doi.org/10.1016/j.sysconle.2011.11.016
 72 articleThe intrinsic hypoelliptic Laplacian and its heat kernel on unimodular Lie groups.J. Funct. Anal.25682009, 26212655URL: https://doi.org/10.1016/j.jfa.2009.01.006
 73 articleGeneralized Ricci curvature bounds for three dimensional contact subriemannian manifolds.Math. Ann.360122014, 209253URL: https://doi.org/10.1007/s0020801410346
 74 bookControl theory from the geometric viewpoint.87Encyclopaedia of Mathematical SciencesControl Theory and Optimization, IISpringerVerlag, Berlin2004, xiv+412URL: https://doi.org/10.1007/9783662064047
 75 incollectionSome open problems.Geometric control theory and subRiemannian geometry5Springer INdAM Ser.Springer, Cham2014, 113
 76 articleMetric measure spaces with Riemannian Ricci curvature bounded from below.Duke Math. J.16372014, 14051490URL: https://doi.org/10.1215/001270942681605
 77 bookTopics on analysis in metric spaces.25Oxford Lecture Series in Mathematics and its ApplicationsOxford University Press, Oxford2004, viii+133
 78 articleA note on stability conditions for planar switched systems.Internat. J. Control82102009, 18821888URL: https://doi.org/10.1080/00207170902802992
 79 bookD.Davide BarilariU.Ugo BoscainM.Mario SigalottiGeometry, analysis and dynamics on subRiemannian manifolds. Vol. 1.EMS Series of Lectures in MathematicsLecture notes from the IHP Trimester held at the Institut Henri Poincaré, Paris and from the CIRM Summer School ``SubRiemannian Manifolds: From Geodesics to Hypoelliptic Diffusion'' held in Luminy, Fall 2014European Mathematical Society (EMS), Zürich2016, vi+324URL: https://doi.org/10.4171/163
 80 bookD.Davide BarilariU.Ugo BoscainM.Mario SigalottiGeometry, analysis and dynamics on subRiemannian manifolds. Vol. II.EMS Series of Lectures in MathematicsLecture notes from the IHP Trimester held at the Institut Henri Poincaré, Paris and from the CIRM Summer School ``SubRiemannian Manifolds: From Geodesics to Hypoelliptic Diffusion'' held in Luminy, Fall 2014European Mathematical Society (EMS), Zürich2016, viii+299URL: https://doi.org/10.4171/163
 81 articleCurvaturedimension inequalities and Ricci lower bounds for subRiemannian manifolds with transverse symmetries.J. Eur. Math. Soc. (JEMS)1912017, 151219URL: https://doi.org/10.4171/JEMS/663
 82 articleCurvature dimension inequalities and subelliptic heat kernel gradient bounds on contact manifolds.Potential Anal.4022014, 163193URL: https://doi.org/10.1007/s111180139345x
 83 articleAnalytical parameterization of rotors and proof of a Goldberg conjecture by optimal control theory.SIAM J. Control Optim.4762008, 30073036
 84 articleControllability of a quantum particle in a moving potential well.J. Funct. Anal.23222006, 328389
 85 articleQualitative properties of certain piecewise deterministic Markov processes.Ann. Inst. Henri Poincaré Probab. Stat.5132015, 10401075URL: https://doi.org/10.1214/14AIHP619
 86 articleThe inactivation principle: mathematical solutions minimizing the absolute work and biological implications for the planning of arm movements.PLoS Comput. Biol.4102008, e1000194, 25URL: https://doi.org/10.1371/journal.pcbi.1000194
 87 articleA new class of universal Lyapunov functions for the control of uncertain linear systems.IEEE Trans. Automat. Control4431999, 641647URL: http://dx.doi.org/10.1109/9.751368
 88 articleNonquadratic Lyapunov functions for robust control.Automatica J. IFAC3131995, 451461URL: http://dx.doi.org/10.1016/00051098(94)001334
 89 bookStratified Lie groups and potential theory for their subLaplacians.Springer Monographs in MathematicsSpringer, Berlin2007, xxvi+800
 90 articleBeweis des adiabatensatzes.Zeitschrift für Physik A Hadrons and Nuclei51341928, 165180
 91 articleA weak spectral condition for the controllability of the bilinear Schrödinger equation with application to the control of a rotating planar molecule.Comm. Math. Phys.31122012, 423455URL: https://doi.org/10.1007/s002200121441z
 92 articleMultiinput Schrödinger equation: controllability, tracking, and application to the quantum angular momentum.J. Differential Equations256112014, 35243551URL: https://doi.org/10.1016/j.jde.2014.02.004
 93 articleStability of planar nonlinear switched systems.Discrete Contin. Dyn. Syst.1522006, 415432URL: https://doi.org/10.3934/dcds.2006.15.415
 94 articleHypoelliptic diffusion and human vision: a semidiscrete new twist.SIAM J. Imaging Sci.722014, 669695
 95 articleAdiabatic control of the Schroedinger equation via conical intersections of the eigenvalues.IEEE Trans. Automat. Control5782012, 19701983
 96 articleAnthropomorphic image reconstruction via hypoelliptic diffusion.SIAM J. Control Optim.5032012, 13091336
 97 articleStability of planar switched systems: the linear single input case.SIAM J. Control Optim.4112002, 89112
 98 articleMultiple Lyapunov functions and other analysis tools for switched and hybrid systems.IEEE Trans. Automat. Control434Hybrid control systems1998, 475482URL: https://doi.org/10.1109/9.664150
 99 articleSystem theory on group manifolds and coset spaces.SIAM J. Control101972, 265284
 100 bookGeometric control of mechanical systems.49Texts in Applied MathematicsModeling, analysis, and design for simple mechanical control systemsSpringerVerlag, New York2005, xxiv+726
 101 articleUntersuchungen über die Grundlagen der Thermodynamik.Math. Ann.6731909, 355386URL: https://doi.org/10.1007/BF01450409
 102 inproceedingsSur la represéntation géométrique des systèmes matériels non holonomes.Proceedings of the International Congress of Mathematicians. Volume 4.1928, 253261
 103 articleControllability of the discretespectrum Schrödinger equation driven by an external field.Ann. Inst. H. Poincaré Anal. Non Linéaire2612009, 329349URL: https://doi.org/10.1016/j.anihpc.2008.05.001
 104 articleA cortical based model of perceptual completion in the rototranslation space.J. Math. Imaging Vision2432006, 307326URL: http://dx.doi.org/10.1007/s1085100536302
 105 articleDecay rates for stabilization of linear continuoustime systems with random switching.Math. Control Relat. Fields2019
 106 bookControl and nonlinearity.136Mathematical Surveys and MonographsAmerican Mathematical Society, Providence, RI2007, xiv+426
 107 articleGlobal asymptotic stabilization for controllable systems without drift.Math. Control Signals Systems531992, 295312URL: https://doi.org/10.1007/BF01211563
 108 inproceedingsOn the controllability of nonlinear partial differential equations.Proceedings of the International Congress of Mathematicians. Volume IHindustan Book Agency, New Delhi2010, 238264
 109 bookIntroduction to quantum control and dynamics.Chapman & Hall/CRC Applied Mathematics and Nonlinear Science SeriesChapman & Hall/CRC, Boca Raton, FL2008, xiv+343
 110 articleA converse Lyapunov theorem for a class of dynamical systems which undergo switching.IEEE Trans. Automat. Control4441999, 751760URL: http://dx.doi.org/10.1109/9.754812
 111 articleLeftinvariant diffusions on the space of positions and orientations and their application to crossingpreserving smoothing of HARDI images.Int. J. Comput. Vis.9232011, 231264URL: https://doi.org/10.1007/s112630100332z
 112 articleFlatness and defect of nonlinear systems: introductory theory and examples.Internat. J. Control6161995, 13271361URL: https://doi.org/10.1080/00207179508921959
 113 articleA threescale model of spatiotemporal bursting.SIAM J. Appl. Dyn. Syst.1542016, 21432175
 114 articleTraining Schrödinger's cat: quantum optimal control. Strategic report on current status, visions and goals for research in Europe.European Physical Journal D692015, 279
 115 articleNonminimality of corners in subriemannian geometry.Invent. Math.2016, 112
 116 articleMinimal surfaces in the rototranslation group with applications to a neurobiological image completion model.J. Math. Imaging Vision3612010, 127URL: https://doi.org/10.1007/s1085100901679
 117 bookBrain and Visual Perception: The Story of a 25Year Collaboration.OxfordOxford University Press2004
 118 bookGeometric control theory.52Cambridge Studies in Advanced MathematicsCambridge University Press, Cambridge1997, xviii+492
 119 articleControl systems on Lie groups.J. Differential Equations121972, 313329URL: https://doi.org/10.1016/00220396(72)900356
 120 articleControlling Several Atoms in a Cavity.New J. Phys.162014, 065010
 121 articleSwitch observability for switched linear systems.Automatica J. IFAC872018, 121127URL: https://doi.org/10.1016/j.automatica.2017.09.024
 122 articleExtremal Curves in Nilpotent Lie Groups.Geom. Funct. Anal.234jul 2013, 13711401URL: http://arxiv.org/abs/1207.3985
 123 articleAdiabatic passage and ensemble control of quantum systems.Journal of Physics B44152011
 124 articleJacobi equations and comparison theorems for corank 1 subRiemannian structures with symmetries.J. Geom. Phys.6142011, 781807URL: https://doi.org/10.1016/j.geomphys.2010.12.009
 125 bookCalculus of variations and optimal control theory.A concise introductionPrinceton University Press, Princeton, NJ2012, xviii+235
 126 articleStability of switched systems: a Liealgebraic condition.Systems Control Lett.3731999, 117122URL: https://doi.org/10.1016/S01676911(99)000122
 127 bookSwitching in systems and control.Systems & Control: Foundations & ApplicationsBirkhäuser Boston, Inc., Boston, MA2003, xiv+233URL: https://doi.org/10.1007/9781461200178
 128 articleStability and stabilizability of switched linear systems: a survey of recent results.IEEE Trans. Automat. Control5422009, 308322URL: http://dx.doi.org/10.1109/TAC.2008.2012009
 129 articleAveraging theorems for highly oscillatory differential equations and iterated Lie brackets.SIAM J. Control Optim.3561997, 19892020
 130 articleRicci curvature for metricmeasure spaces via optimal transport.Ann. of Math. (2)16932009, 903991URL: https://doi.org/10.4007/annals.2009.169.903
 131 articleCommon polynomial Lyapunov functions for linear switched systems.SIAM J. Control Optim.4512006, 226245 (electronic)
 132 articleGeneric controllability properties for the bilinear Schrödinger equation.Comm. Partial Differential Equations3542010, 685706URL: https://doi.org/10.1080/03605300903540919
 133 articleStability of distributed congestion control with heterogeneous feedback delays.IEEE Trans. Automat. Control476Special issue on systems and control methods for communication networks2002, 895902URL: https://doi.org/10.1109/TAC.2002.1008356
 134 articleGeodesic shooting for computational anatomy.J. Math. Imaging Vision2422006, 209228URL: https://doi.org/10.1007/s1085100536240
 135 articleLyapunov control of a quantum particle in a decaying potential.Ann. Inst. H. Poincaré Anal. Non Linéaire2652009, 17431765URL: https://doi.org/10.1016/j.anihpc.2008.09.006
 136 articleLyapunov functions that specify necessary and sufficient conditions for absolute stability of nonlinear nonstationary control systems, I, II, III.Automat. Remote Control471986, 344354, 443451, 620630
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