Dissertationen zum Thema „Dynamical large deviations“

Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.
Title from electronic title page (viewed Sep. 16, 2008). " ... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Statistics and Operations Research Statistics." Discipline: Statistics and Operations Research; Department/School: Statistics and Operations Research.

Quantum Markov processes are widely used models of the dynamics open quantum systems, a fundamental topic in theoretical and mathematical physics with important applications in experimental realisations of quantum systems such as ultracold atomic gases and new quantum information technologies such as quantum metrology and quantum control. In this thesis we present a mathematical framework which effectively characterises dynamical phase transitions in quantum Markov processes, using the theory of large deviations, by combining insights developed in non-equilibrium dynamics with techniques from quantum information and probability. We provide a natural decomposition for quantum Markov chains into phases, paving the way for the rigorous treatment of critical features of such systems such as phase transitions and phase purification. A full characterisation of dynamical phase transitions beyond properties of the steady state is described in terms of a dynamical perspective through critical behaviour of the quantum jump trajectories. We extend a fundamental result from large deviations for classical Markov chains, the Sanov theorem, to a quantum setting; we prove this Sanov theorem for the output of quantum Markov chains, a result which could be extended to a quantum Donsker-Varadhan theory. We perform an in-depth analysis of the atom maser, an infinite-dimensional quantum Markov process exhibiting various types of critical behaviour: for certain parameters it exhibits strong intermittency in the atom detection counts, and has a bistable stationary state. We show that the atom detection counts satisfy a large deviations principle, and therefore we deal with a phase cross-over rather than a genuine phase transition, although the latter occurs in the limit of infinite pumping rate. As a corollary, we obtain the Central Limit Theorem for the counting process.

Die vorliegende Dissertation beschäftigt sich mit der Anwendung der Theorie der großen Abweichungen auf verschiedene Fragestellungen der stochastischen Analysis und stochastischen Dynamik von Sprungprozessen. Die erste Fragestellung behandelt die erste Austrittszeit aus einem beschränkten Gebiet für eine bestimmte Klasse von Sprungdiffusionen mit exponentiell leichten Sprüngen. In Abhängigkeit von der Leichtheit des Sprungmaßes wird das asymptotische Verhalten der Verteilung und insbesondere der Erwartung der ersten Austrittszeit bestimmt wenn das Rauschen verschwindet. Dabei folgt die Verteilung der ersten Austrittszeit einem Prinzip der großen Abweichungen im Falle eines superexponentiellen Sprungmaßes. Wohingegen im subexponentiellen Fall die Verteilung einem Prinzip moderater Abweichungen genügt. In beiden Fällen wird die Asymptotik bestimmt durch eine deterministische Größe, die den minimalen Energieaufwand beschreibt, um die Sprungdiffusion einen optimalen Kontrollpfad, der zum Austritt führt, folgen zu lassen. Die zweite Fragestellung widmet sich dem Grenzverhalten gekoppelter Vorwärts-Rückwärtssysteme stochastischer Differentialgleichungen bei kleinem Rauschen. Dazu assoziiert ist eine spezielle Klasse nicht-lokaler partieller Differentialgleichungen, die auch in nicht-lokalen Modellen der Fluiddynamik eine Rolle spielen. Mithilfe eines probabilistischen Ansatzes und der Markovschen Struktur dieser Systeme wird die Konvergenz auf Ebene von Viskositätslösungen untersucht. Dabei wird ein Prinzip der großen Abweichungen für die involvierten Stochastischen Prozesse hergeleitet.
This thesis deals with applications of Large Deviations Theory to different problems of Stochastic Dynamics and Stochastic Analysis concerning Jump Processes. The first problem we address is the first exit time from a fixed bounded domain for a certain class of exponentially light jump diffusions. According to the lightness of the jump measure of the driving process, we derive, when the source of the noise vanishes, the asymptotic behavior of the law and of the expected value of first exit time. In the super-exponential regime the law of the first exit time follows a large deviations scale and in the sub-exponential regime it follows a moderate deviations one. In both regimes the first exit time is comprehended, in the small noise limit, in terms of a deterministic quantity that encodes the minimal energy the jump diffusion needs to spend in order to follow an optimal controlled path that leads to the exit. The second problem that we analyze is the small noise limit of a certain class of coupled forward-backward systems of Stochastic Differential Equations. Associated to these stochastic objects are some nonlinear nonlocal Partial Differential Equations that arise as nonlocal toy-models of Fluid Dynamics. Using a probabilistic approach and the Markov nature of these systems we study the convergence at the level of viscosity solutions and we derive a large deviations principles for the laws of the stochastic processes that are involved.

We consider a simple one-dimensional random dynamical system with two driving vector fields and random switchings between them. We show that this system satisfies a one force - one solution principle and compute its unique invariant density explicitly. We study the limiting behavior of the invariant density as the switching rate approaches zero and infinity and derive analogues of classical probabilistic results such as the central limit theorem and large deviations principle.

Cette thèse porte sur l'obtention rigoureuse de limites de champ moyen pour la dynamique continue de grands réseaux de neurones hétérogènes. Nous considérons des neurones à taux de décharge, et sujets à un bruit Brownien additif. Le réseau est entièrement connecté, avec des poids de connections dont la variance décroît comme l'inverse du nombre de neurones conservant un effet non trivial dans la limite thermodynamique. Un second type d'hétérogénéité, interprété comme une position spatiale, est considéré au niveau de chaque cellule. Pour la pertinence biologique, nos modèles incluent ou bien des délais, ainsi que des moyennes et variances de connections, dépendants de la distance entre les cellules, ou bien des synapses dépendantes de l'état des deux neurones post- et présynaptique. Ce dernier cas s'applique au modèle de Kuramoto pour les oscillateurs couplés. Quand les poids synaptiques sont Gaussiens et indépendants, nous prouvons un principe de grandes déviations pour la mesure empirique de l'état des neurones. La bonne fonction de taux associée atteint son minimum en une unique mesure de probabilité, impliquant convergence et propagation du chaos sous la loi "averaged". Dans certains cas, des résultats "quenched" sont obtenus. La limite est solution d'une équation implicite, non Markovienne, dans laquelle le terme d'interactions est remplacé par un processus Gaussien qui dépend de la loi de la solution du réseau entier. Une universalité de cette limite est prouvée, dans le cas de poids synaptiques non-Gaussiens avec queues sous-Gaussiennes. Enfin, quelques résultats numérique sur les réseau aléatoires sont présentés, et des perspectives discutées
This thesis addresses the rigorous derivation of mean-field results for the continuous time dynamics of heterogeneous large neural networks. In our models, we consider firing-rate neurons subject to additive noise. The network is fully connected, with highly random connectivity weights. Their variance scales as the inverse of the network size, and thus conserves a non-trivial role in the thermodynamic limit. Moreover, another heterogeneity is considered at the level of each neuron. It is interpreted as a spatial location. For biological relevance, a model considered includes delays, mean and variance of connections depending on the distance between cells. A second model considers interactions depending on the states of both neurons at play. This last case notably applies to Kuramoto's model of coupled oscillators. When the weights are independent Gaussian random variables, we show that the empirical measure of the neurons' states satisfies a large deviations principle, with a good rate function achieving its minimum at a unique probability measure, implying averaged convergence of the empirical measure and propagation of chaos. In certain cases, we also obtained quenched results. The limit is characterized through a complex non Markovian implicit equation in which the network interaction term is replaced by a non-local Gaussian process whose statistics depend on the solution over the whole neural field. We further demonstrate the universality of this limit, in the sense that neuronal networks with non-Gaussian interconnections but sub-Gaussian tails converge towards it. Moreover, we present a few numerical applications, and discuss possible perspectives

Cette thèse s'intéresse à un processus d'exclusion en contact faible avec des réservoirs. Plus précisément, on reprend le modèle étudié dans l'article "Hydrostatics and dynamical large deviations of boundary driven gradient symmetric exclusion processes" de J. Farfan, C. Landim, M. Mourragui mais dans le cas d'un contact faible (et non plus fort) avec les réservoirs. Par ce contact faible, des résultats sont modifiés comme le théorème de la limite hydrodynamique et le théorème des grandes déviations dynamiques. Ce sont les modifications de ses deux résultats qui sont étudiés dans cette thèse dans le cas de la dimension 1.La première partie de la thèse consistera à montrer le théorème de la limite hydrodynamique pour notre modèle, i.e. montrer la convergence de la mesure empirique. En se basant sur les étapes de la Section 5 du livre "Scaling limits of interacting particle systems" de C. Kipnis, C. Landim, il s'agira de montrer que cette suite est relativement compacte avant d'étudier les propriétés de ses points limites. Pour chacune des sous-suites convergentes, on montrera que celles-ci convergent vers des points limites qui se concentrent sur des trajectoires absolument continues et dont les densités sont solutions faibles d'une équation qu'on nommera l'équation hydrodynamique. En finissant par montrer qu’il y a unicité des solutions faibles de l’équation hydrodynamique, on aura alors un unique point limite et la convergence de la suite sera établie.Dans la deuxième partie de la thèse, on montrera le théorème des grandes déviations dynamiques, i.e. qu'il existe une fonction taux I_{[0,T]}( . |\gamma) vérifiant le principe des grandes déviations pour la suite étudiée dans la première partie. Après avoir définit la fonction taux, on montrera donc que celle-ci est semicontinue inférieurement, qu'elle a ses ensembles de niveaux compacts et qu'elle vérifie une propriété de borne inférieure et de borne supérieure. Une des principales difficulté sera de montrer qu’on a une propriété de densité pour un ensemble F pour notre fonction taux. Ceci représentera donc une part importante de cette section. De plus, pour montrer cette densité, on aura besoin de décomposer la fonction I_{[0,T]}( .|\gamma) qui admet des termes de bords et n’a pas de propriété de convexité comme l’ont les fonctions taux de plusieurs modèles déjà existants. En raison de ses deux contraintes, de nouvelles propriétés de régularités ainsi qu'un nouveau type de décomposition seront démontrés
This thesis focuses on a process of exclusion in weak contact with reservoirs. More precisely, we revisit the model studied in the article "Hydrostatics and dynamical large deviations of boundary driven gradient symmetric exclusion processes" by J. Farfan, C. Landim, M. Mourragui but in the case of weak (rather than strong) contact with the reservoirs. Through this weak contact, results are modified such as the hydrodynamic limit theorem and the theorem of large dynamical deviations. The modifications of these two results are studied in this thesis in the case of dimension 1. The first part of the thesis will consist of proving the hydrodynamic limit theorem for our model, i.e. showing the convergence of the empirical measure. Based on the steps in Section 5 of the book "Scaling limits of interacting particle systems" by C. Kipnis, C. Landim, we will show that this sequence is relatively compact before studying the properties of its limit points. For each convergent subsequence, we will show that they converge to limit points that concentrate on absolutely continuous trajectories and whose densities are weak solutions of an equation that we will call the hydrodynamic equation. By demonstrating the uniqueness of weak solutions of the hydrodynamic equation, we will then have a unique limit point and the convergence of the sequence will be established. In the second part of the thesis, we will demonstrate the theorem of large dynamical deviations, i.e. that there exists a rate function I_{[0,T]}(.|\gamma) satisfying the large deviations principle for the sequence studied in the first part. After defining the rate function, we will show that it is lower semicontinuous, has compact level sets, and satisfies a lower bound and an upper bound property. One of the main challenges will be to show a density property for a set F. This will represent a significant part of this section. Moreover, to prove this density property, we will need to decompose the function I_{[0,T]}(.|\gamma) which contains boundary terms and does not have a convexity property like the rate functions of several existing models. Due to these two constraints, new regularity properties as well as a new type of decomposition will be demonstrated

We study the fluctuation effects in the seminal cyclic predator-prey model in population dynamics due to Robert May and Warren Leonard both in the zero-dimensional and two-dimensional spatial version. We compute the mean time to extinction of a stable set of coexisting populations driven by large fluctuations. We see that the contribution of large fluctuations to extinction can be captured by a quasi-stationary approximation and the Wentzel–Kramers–Brillouin (WKB) eikonal ansatz. We see that near the Hopf bifurcation, extinctions are fast owing to the flat non-Gaussian distribution whereas away from the bifurcation, extinctions are dominated by large fluctuations of the fat tails of the distribution. We compare our results to Gillespie simulations and a single-species theoretical calculation. In addition, we study the spatio-temporal pattern formation of the stochastic May--Leonard model through the Doi-Peliti coherent state path integral formalism to obtain a coarse-grained Langevin description, i.e. the Complex Ginzburg Landau equation with stochastic noise in one complex field. We see that when one restricts the internal reaction noise to small amplitudes, one can obtain a simple form for the stochastic noise correlations that modify the Complex Ginzburg Landau equation. Finally, we study the effect of coupling a spatially extended May--Leonard model in two dimensions with symmetric predation rates to one with asymmetric rates that is prone to reach extinction. We show that the symmetric region induces otherwise unstable coexistence spiral patterns in the asymmetric May--Leonard lattice. We obtain the stability criterion for this pattern induction as we vary the strength of the extinction inducing asymmetry. This research was sponsored by the Army Research Office and was accomplished under Grant Number W911NF-17-1-0156.
Doctor of Philosophy
In the field of ecology, the cyclic predator-prey patterns in a food web are relevant yet independent to the hierarchical archetype. We study the paradigmatic cyclic May--Leonard model of three species, both analytically and numerically. First, we employ well--established techniques in large-deviation theory to study the extinction of populations induced by large but rare fluctuations. In the zero--dimensional version of the model, we compare the mean time to extinction computed from the theory to numerical simulations. Secondly, we study the stochastic spatial version of the May--Leonard model and show that for values close to the Hopf bifurcation, in the limit of small fluctuations, we can map the coarse-grained description of the model to the Complex Ginsburg Landau Equation, with stochastic noise corrections. Finally, we explore the induction of ecodiversity through spatio-temporal spirals in the asymmetric version of the May--Leonard model, which is otherwise inclined to reach an extinction state. This is accomplished by coupling to a symmetric May-Leonard counterpart on a two-dimensional lattice. The coupled system creates conditions for spiral formation in the asymmetric subsystem, thus precluding extinction.

In the present Thesis we study the behavior of multi-time correlation functions and of thermodynamical quantities such as heat in open quantum systems undergoing an evolution generally affected by the presence of memory effects, i.e. non-Markovian. In the last decade, a large part of the scientific community in this field has dedicated its efforts to the understanding, precise definition and quantification of non-Markovianity in the quantum realm and now we have at our disposal several benchmark results and a plethora of different estimators that allow to determine the degree of non-Markovianity of a given dynamics. It comes therefore natural to investigate how other different dynamical quantities relate to such estimators also in order to understand the physical implications of memory effects on the statistics of observable quantities. In the first part of this work, a quantitative test of the violation of the so-called quantum regression theorem in presence of a non-Markovian dynamical regime is investigated. The quantum regression theorem represents a procedure that, whenever valid, allows to reconstruct two-time correlation functions of system's operators from the sole knowledge of the dynamics of mean values. It is worth stressing that two-time correlation functions are necessary in order to fully characterize the statistical properties of a quantum system, since they are able to catch aspects of the dynamics, such as fluorescence spectrum, in general not accessible looking at mean values. Despite their relevance however, obtaining two-time correlation functions often represents a formidable task, since the knowledge of the full "system+environment" dynamics is required, a generally too demanding request in the context of open quantum systems theory. The quantum regression theorem represents in this regard the easiest route to determine two-time correlation functions, this highlighting its importance. In this work we show that, in a pure-dephasing spin-boson model, the quantum regression theorem represents a stronger condition than non-Markovianity, in the sense that any presence of memory effects in the reduced dynamics inevitably results in violations to the former. These results have been published in [G.Guarnieri, A. Smirne, B. Vacchini, Phys. Rev. A 90, 022110 (2014)]. The second part of the Thesis is devoted to the characterization of heat ow at the microscopic level in open quantum systems, both finite and infinite dimensional. In particular we begin by studying the time behavior of its mean value in a non-Markovian dynamical regime, showing that, at variance with what happens in the Born-Markov semigroup limiting case, heat can backflow from the environment to the system. After providing a condition for the occurrence of such phenomenon and a measure for its amount for a given dynamics, the relationship with suitable non-Markovianity estimators is sought in two paradigmatic models, namely the spin-boson and the quantum brownian motion. The results, collected in [ G. Guarnieri, C. Uchiyama, B. Vacchini, Phys. Rev. A 93, 012118 (2016); G. Guarnieri, J. Nokkala, R. Schmidt, S. Maniscalco, B. Vacchini, Phys. Rev. A 94, 062101 (2016)], on the one hand allow for the identification of parameter-regions where the heat backflow is absent or maximum. On the other hand they show that the occurrence of heat backflow represents a stricter condition than non-Markovianity, in the sense that non-Markovianity allows for the observation of heat flowing back from the environment to the system and, vice versa, a Markovian dynamics prevents its occurrence. This Thesis concludes with the formulation of a new family of lower bounds to the mean dissipated heat in an environmental-assisted erasure-protocol scenario where Landauer's principle applies. As originally conceived for classical systems, this principle states that every irreversible erasure of information stored in a system inevitably carries along an amount of heat dissipated into the environment which is expended to perform the action. Within the framework recently put forward in [D. Reeb, M. M. Wolf, New J. Phys. 16, 103011 (2014)], which guarantees the validity of Landauer's principle in an open quantum systems scenario, we provide an asymptotically tight family of lower bounds to the dissipated heat which are also valid in the non-equilibrium setting. This construction is applied to an open system consisting of a three-level V-system, in which one transition is externally pumped by a laser field while the other is coupled through an XX-interaction to an environment consisting of a spin chain. Beside calculating all these quantities, an exact solution for the dynamics of such system is also provided. These results are collected in [G. Guarnieri, S. Campbell, J. Goold, S. Pigeon, M. Paternostro, B. Vacchini, in preparation].

Quand le mouvement de particules sous l'action d'un forçage extérieur est restreint par des mécanismes d'exclusion ou de blocage, des corrélations spatio-temporelles non triviales peuvent être observées, dans une dynamique caractérisé par des hétérogénéités spatiales et grandes fluctuations dans le temps.Dans cette thèse, nous étudions deux exemples d'un tel type de mouvement, en prenant en considération deux processus d'exclusion sur des réseaux discrètes en 2d et en 1d.Le premier modèle est inspiré par les mécanismes de relaxation lents observés dans le cisaillement ou le forçage de systèmes colloïdaux ou granulaires: pour des densités élevées, en augmentant le forçage la viscosité peut croitre énormément. Nous expliquons le mécanisme de blocage à grandes densités comme conséquence de l'existence simultanée de régions bloquées et mobiles dans le système, et nous déterminons la signature d'une telle dynamique par le moyen de la thermodynamique des histoires. Nous mesurons aussi l'extension spatiale des structures hétérogènes et fournissons un modèle phénoménologique reliant les propriétés microscopiques de la dynamique au comportement macroscopique de l'écoulement.Le deuxième modèle consiste en un processus d'exclusion en une dimension, incluant les effets dus à la présence structurelle d'un défaut dynamique localisé. Inspirés par la complexité et la richesse du processus de translation du ARN messager, nous proposons un nouveau modèle pour la dynamique de particules dont le mouvement est affecté par des modification stochastiques et structurelles de leur conditions de transport. Nous fournissons une description complète du modèle, avec la caractérisation de tous les régimes dynamiques possibles et une explication quantitative des profils macroscopiques du courant
When the motion of particles driven by external forces is restricted by exclusion mechanisms or bottlenecks, non-trivial space-time correlations in their motion may be observed, giving rise to a dynamics which involves spatial heterogeneities and large fluctuations in time.Here we study two examples of such kind of motion, considering two exclusion processes on discrete lattices in 2d and 1d.The first model is inspired by the slow relaxation occurring when stirring or shearing colloidal or granular materials: at high densities (or packing fractions) increasing the external forcing may lead to a strong increase in the viscosity. We explain the blockage dynamics at high density as the coexistence of blocked and mobile regions and we determine the signature of such dynamics with the use of the thermodynamics of histories. We also quantify the spatial extension of such structures and provide a phenomenological model relating the microscopic properties of the dynamics to the macroscopic flow behavior.The second model consists in a one-dimensional exclusion process incorporating a structural, localized, dynamical defect. Inspired by the complexity and richness of mRNA translation, we propose a new model for the dynamics arising when the particles flow is regulated by structural or conformational changes in the transport medium. We provide a complete description of the model, characterizing all the possible dynamical regimes and addressing a quantitative explanation of the macroscopic current profiles

We consider a mean-field interacting particle system embedded in a site-dependent and i.i.d. random environment. We make it evolve as a continuous time Markov chain on its state space. The dynamics are given depending on few parameters and they are completely described by that of the order parameter of the model. We derive the dynamics of this last quantity, in the infinite volume limit, and then their long time behavior is studied. The limiting dynamics of the order parameter are deterministic and, depending on the values of the parameters, exhibit a phase transition. Our main interest is the study of the critical fluctuations, that are the fluctuations of the order parameter around its limiting dynamics when the parameters take the values for which the phase transition occurs. We aim at analyzing the effect of the disorder in the dynamics of them, as compared with the homogeneous case. We deal with spin-flip and interacting diffusion systems, but we do not treat the subject in total generality, we focus on specific models: the random Curie-Weiss model; a non-reversible spin-flip system motivated by Finance and the homogeneous and inhomogeneous Kuramoto models.
Consideriamo un sistema di particelle interagenti a campo-medio immerso in un ambiente aleatorio i.i.d. e sito-dipendente. Il sistema viene fatto evolvere come una catena di Markov a tempo continuo sullo spazio degli stati. La dinamica dipende da pochi parametri e puo` essere completamente descritta attraverso quella del parametro d'ordine del modello. Ricaviamo la dinamica di quest'ultimo nel limite di volume infinito e quindi ne studiamo il comportamento per tempi lunghi. Tale dinamica limite risulta essere deterministica e, al variare dei parametri, presenta una transizione di fase. Il nostro interesse principale e` lo studio delle fluttuazioni critiche, cioe` le fluttuazioni del parametro d'ordine attorno alla dinamica limite quando i parametri assumono i valori tali per cui si verifica la transizione di fase. Lo scopo e` l'analisi degli effetti causati dal disordine su di esse, confrontandole con le analoghe fluttuazioni per il caso omogeneo. Trattiamo sistemi di spin e di diffusioni, ma non in totale generalita`. Ci concentriamo su dei modelli specifici: il modello di Curie-Weiss con aggiunta di campo aleatorio; un sistema di spin non-reversibile motivato dalla Finanza e il modello di Kuramoto omogeneo e non.

Cette thèse porte sur la dynamique des grandes échelles des écoulements géophysiques turbulents, en particulier sur leur organisation en écoulements parallèles orientés dans la direction est-ouest (jets zonaux). Ces structures ont la particularité d'évoluer sur des périodes beaucoup plus longues que la turbulence qui les entoure. D'autre part, on observe dans certains cas, sur ces échelles de temps longues, des transitions brutales entre différentes configurations des jets zonaux (multistabilité). L'approche proposée dans cette thèse consiste à moyenner l'effet des degrés de liberté turbulents rapides de manière à obtenir une description effective des grandes échelles spatiales de l'écoulement, en utilisant les outils de moyennisation stochastique et la théorie des grandes déviations. Ces outils permettent d'étudier à la fois les attracteurs, les fluctuations typiques et les fluctuations extrêmes de la dynamique des jets. Cela permet d'aller au-delà des approches antérieures, qui ne décrivent que le comportement moyen des jets.Le premier résultat est une équation effective pour la dynamique lente des jets, la validité de cette équation est étudiée d'un point de vue théorique, et les conséquences physiques sont discutées. De manière à décrire la statistique des évènements rares tels que les transitions brutales entre différentes configurations des jets, des outils issus de la théorie des grandes déviations sont employés. Des méthodes originales sont développées pour mettre en œuvre cette théorie, ces méthodes peuvent par exemple être appliquées à des situations de multistabilité
This thesis deals with the dynamics of geophysical turbulent flows at large scales, more particularly their organization into east-west parallel flows (zonal jets). These structures have the particularity to evolve much slower than the surrounding turbulence. Besides, over long time scales, abrupt transitions between different configurations of zonal jets are observed in some cases (multistability). Our approach consists in averaging the effect of fast turbulent degrees of freedom in order to obtain an effective description of the large scales of the flow, using stochastic averaging and the theory of large deviations. These tools provide theattractors, the typical fluctuations and the large fluctuations of jet dynamics. This allows to go beyond previous studies, which only describe the average jet dynamics. Our first result is an effective equation for the slow dynamics of jets, the validityof this equation is studied from a theoretical point of view, and the physical consequences are discussed. In order to describe the statistics of rare events such as abrupt transitions between different jet configurations, tools from large deviation theory are employed. Original methods are developped in order to implement this theory, those methods can be applied for instance in situations of multistability

A central problem in uncertainty quantification is how to characterize the impact that our incomplete knowledge about models has on the predictions we make from them. This question naturally lends itself to a probabilistic formulation, by making the unknown model parameters random with given statistics. In the following this approach is used in concert with tools from large deviation theory (LDT) and optimal control to estimate the probability that some observables in a dynamical system go above a large threshold after some time, given the prior statistical information about the system’s parameters and/or its initial conditions. It is established under which conditions the extreme events occur in a predictable way, as the minimizer of the LDT action functional, i.e. the instanton. In the first physical application, the appearance of rogue waves in a long-crested deep sea is investigated. First, the leading order equations are derived for the wave statistics in the framework of wave turbulence (WT), showing that the theory cannot go beyond Gaussianity, although it remains the main tool to understand the energetic transfers. It is shown how by applying our LDT method one can use the incomplete information contained in the spectrum (with the Gaussian statistics of WT) as prior and supplement this information with the governing nonlinear dynamics to reliably estimate the probability distribution of the sea surface elevation far in the tail at later times. Our results indicate that rogue waves occur when the system hits unlikely pockets of wave configurations that trigger large disturbances of the surface height. The rogue wave precursors in these pockets are wave patterns of regular height but with a very specific shape that is identified explicitly, thereby potentially allowing for early detection. Finally, the first experimental evidence of hydrodynamic instantons is presented using data collected in a long wave flume, elevating the instanton description to the role of a unifying theory of extreme water waves. Other applications of the method are illustrated: To the nonlinear Schrödinger equation with random initial conditions, relevant to fiber optics and integrable turbulence, and to a rod with random elasticity pulled by a time-dependent force. The latter represents an interesting nonequilibrium statistical mechanics setup with a strongly out-of-equilibrium transient (absence of local thermodynamic equilibrium) and a small number of degrees of freedom (small system), showing how the LDT method can be exploited to solve optimal-protocol problems.

by Ma Yiguang.
"April 2000."
Thesis (Ph.D.)--Chinese University of Hong Kong, 2000.
Includes bibliographical references (p. 117-[124]).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Mode of access: World Wide Web.
Abstracts in English and Chinese.

In this thesis, common features from the theories of open quantum systems, estimation of state dynamics and statistical mechanics have been integrated in a comprehensive framework, with the aim to analyze and quantify the energetic and information contents that can be extracted from a dynamical system subject to the external environment. The latter is usually assumed to be deleterious for the feasibility of specic control tasks, since it can be responsible for uncontrolled time-dependent (and even discontinuous) changes of the system. However, if the effects of the random interaction with a noisy environment are properly modeled by the introduction of a given stochasticity within the dynamics of the system, then even noise contributions might be seen as control knobs. As a matter of fact, even a partial knowledge of the environment can allow to set the system in a dynamical condition in which the response is optimized by the presence of noise sources. In particular, we have investigated what kind of measurement devices can work better in noisy dynamical regimes and studied how to maximize the resultant information via the adoption of estimation algorithms. Moreover, we have shown the optimal interplay between quantum dynamics, environmental noise and complex network topology in maximizing the energy transport efficiency. Then, foundational scientic aspects, such as the occurrence of an ergodic property for the system-environment interaction modes of a randomly perturbed quantum system or the characterization of the stochastic quantum Zeno phenomena, have been analyzed by using the predictions of the large deviation theory. Finally, the energy cost in maintaining the system in the non-equilibrium regime due to the presence of the environment is evaluated by reconstructing the corresponding thermodynamics entropy production. In conclusion, the present thesis can constitute the basis for an effective resource theory of noise, which is given by properly engineering the interaction between a dynamical (quantum or classical) system and its external environment.