A new measure of instability and topological entropy of area-preserving twist diffeomorphisms

We introduce a new measure of instability of area-preserving twist diffeomorphisms, which generalizes the notions of angle of splitting of separatrices, and flux through a gap of a Cantori. As an example of application, we establish a sharp >0 lower bound on the topological entropy in a neighbourhood of a hyperbolic, unique action-minimizing fixed point, assuming only no topological obstruction to diffusion, i.e. no homotopically non-trivial invariant circle consisting of orbits with the rotation number 0. The proof is based on a new method of precise construction of positive entropy invariant measures, applicable to more general Lagrangian systems, also in higher degrees of freedom

Heisenberg Picture Approach to the Stability of Quantum Markov Systems

Quantum Markovian systems, modeled as unitary dilations in the quantum stochastic calculus of Hudson and Parthasarathy, have become standard in current quantum technological applications. This paper investigates the stability theory of such systems. Lyapunov-type conditions in the Heisenberg picture are derived in order to stabilize the evolution of system operators as well as the underlying dynamics of the quantum states. In particular, using the quantum Markov semigroup associated with this quantum stochastic differential equation, we derive sufficient conditions for the existence and stability of a unique and faithful invariant quantum state. Furthermore, this paper proves the quantum invariance principle, which extends the LaSalle invariance principle to quantum systems in the Heisenberg picture. These results are formulated in terms of algebraic constraints suitable for engineering quantum systems that are used in coherent feedback networks

Heisenberg Picture Approach to the Stability of Quantum Markov Systems

Quantum Markovian systems, modeled as unitary dilations in the quantum stochastic calculus of Hudson and Parthasarathy, have become standard in current quantum technological applications. This paper investigates the stability theory of such systems. Lyapunov-type conditions in the Heisenberg picture are derived in order to stabilize the evolution of system operators as well as the underlying dynamics of the quantum states. In particular, using the quantum Markov semigroup associated with this quantum stochastic differential equation, we derive sufficient conditions for the existence and stability of a unique and faithful invariant quantum state. Furthermore, this paper proves the quantum invariance principle, which extends the LaSalle invariance principle to quantum systems in the Heisenberg picture. These results are formulated in terms of algebraic constraints suitable for engineering quantum systems that are used in coherent feedback networks

Invariance-like theorems and “lim inf” convergence properties

International audienceSeveral theorems, inspired by the Krasovskii-LaSalle invariance principle, to establish “lim inf” convergence results are presented in a unified framework. These properties are useful to “describe” the oscillatory behavior of the solutions of dynamical systems. The theorems resemble “lim inf” Matrosov and Small-gain theorems and are based on a “lim inf” Barbalat's Lemma. Additional technical assumptions to have “lim” convergence are given: the “lim inf”/“lim” relation is discussed in-depth and the role of some of the assumptions is illustrated by means of examples

Robust stability theory for stochastic dynamical systems

In this work, we focus on developing analysis tools related to stability theory forcertain classes of stochastic dynamical systems that permit non-unique solutions. Thenon-unique nature of solutions arise primarily due to the system dynamics that aremodeled by set-valued mappings. There are two main motivations for studying suchclasses of systems. Firstly, understanding such systems is crucial to developing a robuststability theory. Secondly, such system models allow flexibility in control design problems.We begin by developing analysis tools for a simple class of discrete-time stochasticsystem modeled by set-valued maps and then extend the results to a larger class ofstochastic hybrid systems. Stochastic hybrid systems are a class of dynamical systemsthat combine continuous-time dynamics, discrete-time dynamics and randomness. Theanalysis tools are established for properties like global asymptotic stability in probabilityand global recurrence. We focus on establishing results related to sufficient conditions for stability, weak sufficient conditions for stability, robust stability conditions and converse Lyapunov theorems. In this work a primary assumption is that the stochastic system satisfies some mild regularity properties with respect to the state variable and random input. The regularity properties are needed to establish the existence of random solutions and results on sequential compactness for the solution set of the stochastic system.We now explain briefly the four main types of analysis tools studied in this work.Sufficient conditions for stability establish conditions involving Lyapunov-like functionssatisfying strict decrease properties along solutions that are needed to verify stability properties. Weak sufficient conditions relax the strict decrease nature of the Lyapunov like function along solutions and rely on either knowledge about the behavior of thesolutions on certain level sets of the Lyapunov-like function or use multiple nested non-strict Lyapunov-like functions to conclude stability properties. The invariance principleand Matrosov function theory fall in to this category. Robust stability conditions determinewhen stability properties are robust to sufficiently small perturbations of thenominal system data. Robustness of stability is an important concept in the presenceof measurement errors, disturbances and parametric uncertainty for the nominal system.We study two approaches to verify robustness. The first approach to establish robustnessrelies on the regularity properties of the system data and the second approach isthrough the use of Lyapunov functions. Robustness analysis is an area where the notionof set-valued dynamical systems arise naturally and it emphasizes the reason for ourstudy of such systems. Finally, we focus on developing converse Lyapunov theorems forstochastic systems. Converse Lyapunov theorems are used to illustrate the equivalencebetween asymptotic properties of a system and the existence of a function that satisfiesa decrease condition along the solutions. Strong forms of the converse theorem implythe existence of smooth Lyapunov functions. A fundamental way in which our resultsdiffer from the results in the literature on converse theorems for stochastic systems isthat we exploit robustness of the stability property to establish the existence of a smoothLyapunov function

Robust open-loop stabilization of Fock states by time-varying quantum interactions

A quantum harmonic oscillator (spring subsystem) is stabilized towards a target Fock state by reservoir engineering. This passive and open-loop stabilization works by consecutive and identical Hamiltonian interactions with auxiliary systems, here three-level atoms (the auxiliary ladder subsystem), followed by a partial trace over these auxiliary atoms. A scalar control input governs the interaction, defining which atomic transition in the ladder subsystem is in resonance with the spring subsystem. We use it to build a time-varying interaction with individual atoms, that combines three non-commuting steps. We show that the resulting reservoir robustly stabilizes any initial spring state distributed between 0 and 4n+3 quanta of vibrations towards a pure target Fock state of vibration number n. The convergence proof relies on the construction of a strict Lyapunov function for the Kraus map induced by this reservoir setting on the spring subsystem. Simulations with realistic parameters corresponding to the quantum electrodynamics setup at Ecole Normale Superieure further illustrate the robustness of the method