Stability of propagation features under time-asymptotic approximations for a class of dispersive equations

We consider solutions in frequency bands of dispersive equations on the line defined by Fourier multipliers, these solutions being considered as wave packets. In this paper, a refinement of an existing method permitting to expand time-asymptotically the solution formulas is proposed, leading to a first term inheriting the mean position of the true solution together with a constant variance error. In particular, this first term is supported in a space-time cone whose origin position depends explicitly on the initial state, implying especially a shifted time-decay rate. This method, which takes into account both spatial and frequency information of the initial state, makes then stable some propagation features and permits a better description of the motion and the dispersion of the solutions of interest. The results are achieved firstly by making apparent the cone origin in the solution formula, secondly by applying precisely an adapted version of the stationary phase method with a new error bound, and finally by minimizing the error bound with respect to the cone origin.Comment: 32 pages, no figure

From industry-wide parameters to aircraft-centric on-flight inference: improving aeronautics performance prediction with machine learning

Aircraft performance models play a key role in airline operations, especially in planning a fuel-efficient flight. In practice, manufacturers provide guidelines which are slightly modified throughout the aircraft life cycle via the tuning of a single factor, enabling better fuel predictions. However this has limitations, in particular they do not reflect the evolution of each feature impacting the aircraft performance. Our goal here is to overcome this limitation. The key contribution of the present article is to foster the use of machine learning to leverage the massive amounts of data continuously recorded during flights performed by an aircraft and provide models reflecting its actual and individual performance. We illustrate our approach by focusing on the estimation of the drag and lift coefficients from recorded flight data. As these coefficients are not directly recorded, we resort to aerodynamics approximations. As a safety check, we provide bounds to assess the accuracy of both the aerodynamics approximation and the statistical performance of our approach. We provide numerical results on a collection of machine learning algorithms. We report excellent accuracy on real-life data and exhibit empirical evidence to support our modelling, in coherence with aerodynamics principles.Comment: Published in Data-Centric Engineerin

An end-to-end data-driven optimization framework for constrained trajectories

Abstract Many real-world problems require to optimize trajectories under constraints. Classical approaches are often based on optimal control methods but require an exact knowledge of the underlying dynamics and constraints, which could be challenging or even out of reach. In view of this, we leverage data-driven approaches to design a new end-to-end framework which is dynamics-free for optimized and realistic trajectories. Trajectories are here decomposed on function basis, trading the initial infinite dimension problem on a multivariate functional space for a parameter optimization problem. Then a maximum a posteriori approach which incorporates information from data is used to obtain a new penalized optimization problem. The penalized term narrows the search on a region centered on data and includes estimated features of the problem. We apply our data-driven approach to two settings in aeronautics and sailing routes optimization. The developed approach is implemented in the Python library PyRotor

An end-to-end data-driven optimisation framework for constrained trajectories

28 pagesMany real-world problems require to optimise trajectories under constraints. Classical approaches are based on optimal control methods but require an exact knowledge of the underlying dynamics, which could be challenging or even out of reach. In this paper, we leverage data-driven approaches to design a new end-to-end framework which is dynamics-free for optimised and realistic trajectories. We first decompose the trajectories on function basis, trading the initial infinite dimension problem on a multivariate functional space for a parameter optimisation problem. A maximum \emph{a posteriori} approach which incorporates information from data is used to obtain a new optimisation problem which is regularised. The penalised term focuses the search on a region centered on data and includes estimated linear constraints in the problem. We apply our data-driven approach to two settings in aeronautics and sailing routes optimisation, yielding commanding results. The developed approach has been implemented in the Python library PyRotor

Lossless estimates for asymptotic methods with applications to propagation features for dispersive equations

Dans cette thèse, nous étudions le comportement d'intégrales oscillantes lorsqu'un paramètre fréquentiel tend vers l'infini. Pour cela, nous considérons la version de la méthode de la phase stationnaire de A. Erdélyi qui couvre le cas d'amplitudes singulières et de phases ayant des points stationnaires d'ordre réel, et qui fournit des estimations explicites de l'erreur. La preuve est entièrement détaillée dans la thèse et la méthode améliorée. De plus nous montrons l'impossibilité de déduire, à partir de cette méthode, des estimations uniformes par rapport à la position du point stationnaire dans le cas d'amplitudes singulières. Afin d'obtenir de telles estimations, nous étendons le lemme de van der Corput au cas d'amplitudes singulières et de points stationnaires d'ordre réel.Ces résultats sont appliqués à des solutions d'équations dispersives sur la droite réelle. La transformée de Fourier de la donnée initiale est à support compact et/ou a un point singulier intégrable. Des développements à un terme et des estimations uniformes dans certains cônes de l'espace-temps sont établis: ceci montre que les paquets d'ondes tendent à être localisés dans certains cônes lorsque le temps tend vers l'infini, décrivant leurs mouvements asymptotiquement en temps.Pour finir, nous considérons des solutions approchées de l'équation de Schrödinger avec potentiel sur la droite réelle, telle que la transformée de Fourier du potentiel est à support compact. En appliquant les méthodes précédentes, nous prouvons que ces solutions approchées tendent à être concentrées dans certains cônes lorsque le temps tend vers l'infini, mettant en évidence des phénomènes de type réflexion et transmission.In this thesis, we study the asymptotic behaviour of oscillatory integrals for one integration variable with respect to a large parameter. We consider the version of the stationary phase method of A. Erdélyi which covers singular amplitudes and phases with stationary points of real order together with explicit error estimates. The proof, which is only sketched in the original paper, is entirely detailed in the present thesis and the method is improved. Moreover we show the impossibility to derive from this method uniform estimates in the case of singular amplitudes with respect to the position of the stationary point. To obtain such estimates, we extend the classical van der Corput lemma to the case of singular amplitudes and stationary points of real order.These results are then applied to solution formulas of certain dispersive equations on the line, covering Schrödinger-type and hyperbolic examples. We suppose that the Fourier transform of the initial condition is compactly supported and/or has a singular point. Expansions to one term and uniform estimates of the solutions in certain space-time cones are established: this shows that the waves packets tend to be time-asymptotically localized in space-time cones, describing their motions when the time tends to infinity.Finally we consider approximate solutions of the Schrödinger equation on the line with potential, where the Fourier transform of the potential is also supposed to have a compact support. Applying the methods mentioned above, we prove that these approximate solutions tend to be time-asymptotically concentrated in certain space-time cones, exhibiting reflection and transmission type phenomena

Stability of propagation features under time-asymptotic approximations for a class of dispersive equations

International audienceWe consider solutions of dispersive equations on the line defined by Fourier multipliers with initial data having compactly supported Fourier transforms. In this paper, a refinement of an existing method permitting to expand time-asymptotically the solution formulas is proposed. Here the first term of the expansion is supported in a space-time cone whose origin depends explicitly on the initial datum. As an important consequence of our refined method, the first term inherits the mean position of the solution together with a constant variance error and a shifted time-decay rate is obtained. Hence this refinement, which takes into account both spatial and frequency information of the initial datum, makes stable some propagation features under time-asymptotic approximations and permits a better description of the time-asymptotic behaviour of the solutions. The results are achieved firstly by making apparent the cone origin in the solution formula, secondly by applying precisely an adapted version of the stationary phase method with a new error bound, and finally by minimising the error bound with respect to the cone origin

The Hill Cipher: A Weakness Studied Through Group Action Theory

(Unpublished)The Hill cipher is considered as one of the most famous symmetric-key encryption algorithm: based on matrix multiplication, it has some interesting structural features which, for instance, can be exploited for teaching both cryptology and linear algebra. On the other hand, these features have rendered it vulnerable to some kinds of attack, such as the known-plaintext attack, and hence inapplicable in cases of real application. Despite this weakness, it does not stop the community proposing different upgrades for application purposes. In the present paper , we show that the Hill cipher preserves an algebraic structure of a given text and we use group action theory to study in a convenient setting some consequences of this fact, which turns out to be a potentially exploitable weakness. Indeed, our study might lead to a ciphertext-only attack requiring only that the alphabet has a prime number of characters. The main feature of this potential attack is the fact that it is not based on a search over all possible keys but rather over an explicit set of texts associated with the considered ciphertext. Group action theory guarantees that there will be, at worst, as much texts to test as keys, implying especially a better complexity

Decrypting the Hill Cipher via a Restricted Search over the Text-Space

International audienceDeveloped by L. S. Hill in 1929, the Hill cipher is a polygraphic substitution cipher based on matrix multiplication. This cipher has been proved vulnerable to many attacks, especially the known-plaintext attack, while only few ciphertext-only attacks have been developed. The aim of our work is to study a new kind of ciphertext-only attack for the Hill cipher which is based on a restricted search over an explicit set of texts, called orbits, and not on a search over the key-space; it is called Orbit-Based Attack (OBA). To explain in a convenient setting this approach, we make use of basic notions from group action theory ; we present then in details an algorithm for this attack and finally results from experiments. We demonstrate experimentally that this new method can be efficient in terms of time-execution and can even be faster on average than the classical Brute-Force Attack in the considered settings