Beyond bilinear controllability : applications to quantum control

Quantum control is traditionally expressed through bilinear models and their associated Lie algebra controllability criteria. But, the first order approximation are not always sufficient and higher order developpements are used in recent works. Motivated by these applications, we give in this paper a criterion that applies to situations where the evolution operator is expressed as sum of possibly non-linear real functionals of the control that multiplies some time independent (coupling) operators

Local volatility calibration using an adjoint proxy

We document the calibration of the local volatility in a frame- work similar to Coleman, Li and Verma. The quality of a surface is assessed through a functional to be optimized; the specificity of the approach is to separate the optimization (performed with any suitable optimization algorithm) from the computation of the functional where we use an adjoint (as in L. Jiang et. al.) to obtain an approximation; moreover our main calibration variable is the implied volatility (the procedure can also accommodate the Greeks). The procedure per- forms well on benchmarks from the literature and on FOREX data.

Calibration of local volatility using the local and implied instantaneous variance

We document the calibration of the local volatility in terms of local and implied instantaneous variances; we first explore the theoretical properties of the method for a particular class of volatilities. We confirm the theoretical results through a numerical procedure which uses a Gauss-Newton style approximation of the Hessian in the framework of a sequential quadratic programming (SQP) approach. The procedure performs well on benchmarks from the literature and on FOREX data.calibration; local volatility; implied volatility; Dupire formula; adjoint; instantaneous local variance;instantaneous implied variance; implied variance

Heterogeneous social interactions and the COVID-19 lockdown outcome in a multi-group SEIR model

We study variants of the SEIR model for interpreting some qualitative features of the statistics of the Covid-19 epidemic in France. Standard SEIR models distinguish essentially two regimes: either the disease is controlled and the number of infected people rapidly decreases, or the disease spreads and contaminates a significant fraction of the population until herd immunity is achieved. After lockdown, at first sight it seems that social distancing is not enough to control the outbreak. We discuss here a possible explanation, namely that the lockdown is creating social heterogeneity: even if a large majority of the population complies with the lockdown rules, a small fraction of the population still has to maintain a normal or high level of social interactions, such as health workers, providers of essential services, etc. This results in an apparent high level of epidemic propagation as measured through re-estimations of the basic reproduction ratio. However, these measures are limited to averages, while variance inside the population plays an essential role on the peak and the size of the epidemic outbreak and tends to lower these two indicators. We provide theoretical and numerical results to sustain such a view

Cross-currency smile calibration

We document the numerical aspects of the calibration of cross-currency options on the local volatility framework. We consider the partial differential equation satisfied by the price of the cross-currency option and see that the most important specifications to set are the boundary conditions. We explain how these conditions can be approximated and test the validity of the approximation on simple cases.cross-currency options; calibration; local volatility; implied volatility; Dupire formula; adjoint; boundary conditions;

X-Ray Sobolev Variational Auto-Encoders

The quality of the generative models (Generative adversarial networks, Variational Auto-Encoders, ...) depends heavily on the choice of a good probability distance. However some popular metrics lack convenient properties such as (geodesic) convexity, fast evaluation and so on. To address these shortcomings, we introduce a class of distances that have built-in convexity. We investigate the relationship with some known paradigms (sliced distances, reproducing kernel Hilbert spaces, energy distances). The distances are shown to posses fast implementations and are included in an adapted Variational Auto-Encoder termed X-ray Sobolev Variational Auto-Encoder (XS-VAE) which produces good quality results on standard generative datasets

Equivalence entre les procedures de «local tracking» et les algorithmes monotoniques en contrôle quantique

Les simulations numériques en contrôle quantique utilisent plusieurs approches incluant les procédures de type «local tracking» qui obtiennent le champ de contrôle par la condition que une certaine fonction soit décroissante, mais aussi les algorithmes monotoniques qui résolvent l'équation d'Euler-Lagrance pour une fonctionnelle de coût prédéfinie. Même si différentes en leur implémentations, des travaux récents ont montré que ces classes partagent des caractéristiques communes. Le but de ce travail est de proposer une base rigoureuse pour des telles conclusions et de discuter la formulation précise qui permet de construire une telle équivalence

Stochastic learning control of inhomogeneous quantum ensembles

International audienceIn quantum control, the robustness with respect to uncertainties in the system's parameters or driving field characteristics is of paramount importance and has been studied theoretically, numerically and experimentally. We test in this paper stochastic search procedures (Stochastic gradient descent and the Adam algorithm) that sample, at each iteration, from the distribution of the parameter uncertainty, as opposed to previous approaches that use a fixed grid. We show that both algorithms behave well with respect to benchmarks and discuss their relative merits. In addition the methodology allows to address high dimensional parameter uncertainty; we implement numerically, with good results, a 3D and a 6D case