In the thesis work we investigate four problems connected with dynamical processes in condensed medium, using different techniques of equilibrium and non-equilibrium statistical mechanics. Biology is rich in dynamical events ranging from processes involving single molecule [1] to collective phenomena [2]. In cell biology, translocation and transport processes of biological molecules constitute an important class of dynamical phenomena occurring in condensed phase. Examples include protein transport through membrane channels, gene transfer between bacteria, injection of DNA from virus head to the host cell, protein transport thorough the nuclear pores etc. We present a theoretical description of the problem of protein transport across the nuclear pore complex [3]. These nuclear pore complexes (NPCs) [4] are very selective filters that monitor the transport between the cytoplasm and the nucleoplasm. Two models have been suggested for the plug of the NPC. The first suggests that the plug is a reversible hydrogel while the other suggests that it is a polymer brush. In the thesis, we propose a model for the transport of a protein through the plug, which is treated as elastic continuum, which is general enough to cover both the models. The protein stretches the plug and creates a local deformation, which together with the protein is referred to as the bubble. The relevant coordinate describing the transport is the center of the bubble. We write down an expression for the energy of the system, which is used to analyze the motion. It shows that the bubble executes a random walk, within the gel. We find that for faster relaxation of the gel, the diffusion of the bubble is greater. Further, on adopting the same kind of free energy for the brush too, one finds that though the energy cost for the entry of the particle is small but the diffusion coefficient is much lower and hence, explanation of the rapid diffusion of the particle across the nuclear pore complex is easier within the gel model. In chemical physics, processes occurring in condensed phases like liquid or solid often involve barrier crossing. Simplest possible description of rate for such barrier crossing phenomena is given by the transition state theory [5]. One can go one step further by introducing the effect of the environment by incorporating phenomenological friction as is done in Kramer’s theory [6]. The “method of reactive flux” [7, 8] in chemical physics allows one to calculate the time dependent rate constant for a process involving large barrier by expressing the rate as an ensemble average of an infinite number of trajectories starting at the barrier top and ending on the product side at a specified later time. We compute the time dependent transmission coefficient using this method for a structureless particle surmounting a one dimensional inverted parabolic barrier. The work shows an elegant way of combining the traditional system plus reservoir model [9] and the method of reactive flux [7] and the normal mode analysis approach by Pollak [10] to calculate the time dependent transmission coefficient [11]. As expected our formula for the time dependent rate constant becomes equal to the transition state rate constant when one takes the zero time limit. Similarly Kramers rate constant is obtained by taking infinite time limit. Finally we conclude by noting that the method of analyzing the coupled Hamiltonian, introduced by Pollak is very powerful and it enables us to obtain analytical expressions for the time dependent reaction rate in case of Ohmic dissipation, even in underdamped case. The theory of first passage time [12] is one of the most important topics of research in chemical physics. As a model problem we consider a particle executing Brownian motion in full phase space with an absorbing boundary condition at a point in the position space we derive a very general expression of the survival probability and the first passage time distribution, irrespective of the statistical nature of the dynamics. Also using the prescription adopted elsewhere [13] we define a bound to the actual survival probability and an approximate first passage time distribution which are expressed in terms of the position-position, velocity-velocity and position-velocity variances. Knowledge of these variances enables one to compute the survival probability and consequently the first passage distribution function. We compute both the quantities for gaussian Markovian process and also for non-Markovian dynamics. Our analysis shows that the survival probability decays exponentially at the long time, irrespective of the nature of the dynamics with an exponent equal to the transition state rate constant [14]. Although the field of equilibrium thermodynamics and equilibrium statistical mechanics are well explored, there existed almost no theory for systems arbitrarily far from equilibrium until the advent of fluctuation theorems (FTs)[15] in mid 90�s. In general, these fluctuation theorems have provided a general prescription on energy exchanges that take place between a system and its surroundings under general nonequilibrium conditions and explain how macroscopic irreversibility appears naturally in systems that obey time reversible microscopic dynamics. Based on a Hamiltonian description we present a rigorous derivation [16] of the transient state work fluctuation theorem and the Jarzynski equality [17] for a classical harmonic oscillator linearly coupled to a harmonic heat bath, which is dragged by an external agent. Coupling with the bath makes the dynamics dissipative. Since we do not assume anything about the spectral nature of the harmonic bath the derivation is valid for a general non-Ohmic bath.

Perfect simulation  and the EM algorithm are the main topics in this thesis. In paper I, we present coupling from the past (CFTP) algorithms that generate perfectly distributed samples from the multi-type Widom--Rowlin-son (W--R) model and some generalizations of it. The classical W--R model is a point process in the plane or the  space consisting of points of several different types. Points of different types are not allowed to be closer than some specified distance, whereas points of the same type can be arbitrary close. A stick-model and soft-core generalizations are also considered. Further, we  generate samples without edge effects, and give a bound on sufficiently small intensities (of the points) for the algorithm to terminate. In paper II, we consider the  forestry problem on how to estimate  seedling dispersal distributions and effective plant fecundities from spatially data of adult trees  and seedlings, when the origin of the seedlings are unknown.   Traditional models for fecundities build on allometric assumptions, where the fecundity is related to some  characteristic of the adult tree (e.g.\ diameter). However, the allometric assumptions are generally too restrictive and lead to nonrealistic estimates. Therefore we present a new model, the unrestricted fecundity (UF) model, which uses no allometric assumptions. We propose an EM algorithm to estimate the unknown parameters.   Evaluations on real and simulated data indicates better performance for the UF model. In paper III, we propose  EM algorithms to  estimate the passage time distribution on a graph.Data is obtained by observing a flow only at the nodes -- what happens on the edges is unknown. Therefore the sample of passage times, i.e. the times it takes for the flow to stream between two neighbors, consists of right censored and uncensored observations where it sometimes is unknown which is which.       For discrete passage time distributions, we show that the maximum likelihood (ML) estimate is strongly consistent under certain  weak conditions. We also show that our propsed EM algorithm  converges to the ML estimate if the sample size is sufficiently large and the starting value is sufficiently close to the true parameter. In a special case we show that it always converges.  In the continuous case, we propose an EM algorithm for fitting  phase-type distributions to data.

Questa tesi è composta da 3 differenti lavori che ci confermano la prevedibilità degli extra rendimenti rispetto al mercato usando semplici strategie di portafoglio azionario utilizzabili sia dal semplice risparmiatore sia dall'investitore istituzionale. Nel primo capitolo è stata analizzata la profittabilità della contrarian strategy nel mercato azionario Italiano. In letteratura é stato già abbondantemente dimostrato che i rendimenti azionari sono caratterizzati da un’autocorrelazione negativa nel breve periodo e da un effetto di ritorno alla media nel lungo periodo. La contrarian strategy é utilizzata per trarre profitto dalla correlazione seriale negativa dei rendimenti azionari, infatti, vendendo i titoli che si sono rivelati vincenti nel passato (in termini di rendimento) e acquistando quelli "perdenti" si ottengono profitti inaspettati. Nel secondo paper, l'analisi si focalizza sulla strategia di portafoglio definita Dollar Cost Averaging (DCA). La Dollar Cost Averaging si riferisce a una semplice metodologia di portafoglio che prevede di investire una somma fissa di denaro in un'attività rischiosa a uguali intervalli di tempo, per tutto l'orizzonte temporale prefissato. Il lavoro si propone di confrontare i vantaggi, in termini di riduzione sostanziale del rischio, di questa strategia dal punto di vista di un semplice risparmiatore. Nell'ultimo capitolo, ipotizzando di essere un investitore istituzionale che possiede ogni giorno numerose informazioni e previsioni, ho cercato di capire come egli può usare tutte le informazioni in suo possesso per decidere prontamente come allocare al meglio il patrimonio del fondo. L’investitore normalmente cerca di identificare la migliore previsione possibile, ma quasi sempre non riesce ad identificare l’esatto processo dei prezzi sottostanti. Quest’osservazione ha condotto molti ricercatori ad utilizzare numerosi fattori esplicativi per ottenere un buona previsione. Il paper supporta l’esistente letteratura che utilizza un nuovo approccio per trasformare previsioni di rendimenti in scelte di gestione di portafoglio che possano offrire una maggiore performance del portafoglio.Partendo dal modello d’incertezza di Pesaran e Timmerman(1996), considero un cospicuo numero di fattori macroeconomici per identificare un modello predittivo che mi permetta di prevedere i movimenti del mercato tenendo presente i maggiori indicatori economici e finanziari e considerato che il loro rispettivo potere predittivo cambia nel tempo. / This thesis is composed by three different papers that confirm us the predictability of expected returns using different simple portfolio strategy and under different point of view (i.e. a generic saver and institutional investor). In the first chapter, I investigate the profitability of contrarian strategy in the Italian Stock Market. However empirical research has shown that asset returns tend to exhibit some form of negative autocorrelation in the short term and mean-reversion over long horizons. Contrarian strategy is used to take advantage of serial correlation in stock price returns, such that selling winners and buying losers generates abnormal profits. On the second chapter, the analyse is focused in another classic portfolio strategy called Dollar Cost Averaging (DCA). Dollar Cost Averaging refers to an investment methodology in which a set dollar amount is invested in a risky asset at equal intervals over a holding period. The paper compares the advantages and risk of this strategy from the point of view of a saver. Lastly, supposing to be an institutional investor who has a large number of information and forecasts, I tried to understand how using all them he decide with dispatch how to allocate the portfolio fund. When a wide set of forecasts of some future economic events are available, decision makers usually attempt to discover which is the best forecast, but in almost all cases a decision maker cannot identify ex ante the true process. This observation has led researchers to introduce several sources of uncertainty in forecasting exercises. The paper supporting the existent literature employs a novel approaches to transform predicted returns into portfolio asset allocations, and their relative performances. First of all dealing with model uncertainty, as Pesaran and Timmerman (1996), I consider a richer parameterization for the forecasting model to find that the predictive power of various economic and financial factors over excess returns change through time.

No description available.

We propose a simple and general method to obtain the boundary crossing probability for Brownian motion. This method can be easily extended to higher dimensional of Brownian motion. It also covers certain classes of stochastic processes associated with Brownian motion. The basic idea of the method is based on being able to construct a nite Markov chain such that the boundary crossing probability of Brownian motion is obtained as the limiting probability of the nite Markov chain entering a set of absorbing states induced by the boundary. Numerical results are given to illustrate our method.

We propose a simple and general method to obtain the boundary crossing probability for Brownian motion. This method can be easily extended to higher dimensional of Brownian motion. It also covers certain classes of stochastic processes associated with Brownian motion. The basic idea of the method is based on being able to construct a nite Markov chain such that the boundary crossing probability of Brownian motion is obtained as the limiting probability of the nite Markov chain entering a set of absorbing states induced by the boundary. Numerical results are given to illustrate our method.

Single-particle tracking (SPT) is a method used to study the diffusion of various molecules within the cell. SPT involves tagging proteins with optical labels and observing their individual two-dimensional trajectories with a microscope. The analysis of this data provides important information about protein movement and mechanism, and is used to create multistate biological models. One of the challenges in SPT analysis is the variety of complex environments that contribute to heterogeneity within movement paths. In this thesis, we explore the limitations of current methods used to analyze molecular movement, and adapt analytical methods used in animal movement analysis, such as correlated random walks and first-passage time variance, to SPT data of leukocyte function-associated antigen-1 (LFA-1) integral membrane proteins. We discuss the consequences of these methods in understanding different types of heterogeneity in protein movement behaviour, and provide support to results from current experimental work. / Applied Mathematics

Title: Stochastic dynamics and energetics of biomolecular systems Author: Artem Ryabov Department: Department of Macromolecular Physics Supervisor: prof. RNDr. Petr Chvosta, CSc., Department of Macromolecular Physics Abstract: The thesis comprises exactly solvable models from non-equilibrium statistical physics. First, we focus on a single-file diffusion, the diffusion of particles in narrow channel where particles cannot pass each other. After a brief review, we discuss open single-file systems with absorbing boundaries. Emphasis is put on an interplay of absorption process at the boundaries and inter-particle entropic repulsion and how these two aspects affect the dynam- ics of a given tagged particle. A starting point of the discussions is the exact distribution for the particle displacement derived by order-statistics argu- ments. The second part of the thesis is devoted to stochastic thermodynam- ics. In particular, we present an exactly solvable model, which describes a Brownian particle diffusing in a time-dependent anharmonic potential. The potential has a harmonic component with a time-dependent force constant and a time-independent repulsive logarithmic barrier at the origin. For a particular choice of the driving protocol, the exact work characteristic func- tion is obtained. An asymptotic analysis of...

La thèse décrit les propriétés d’équilibre et hors d’équilibre de modèles mathématiques stochastiques de systèmes physiques. À l’aide de simulations numériques, on étudie les fluctuations des différentes quantités mais on s’interesse aussi aux grands déviations dans certains systèmes. La première partie de la thèse se concentre sur l’étude des interfaces rugueuses observées dans des processus de croissance. Ces interfaces sont simulées avec des nouvelles techniques de programmation en parallèle qui nous permettent d’accéder à des systèmes de très grande taille. D’une part, on discute le cas diffusif, représenté par l’équation d’Edward-Wilkinson dans des interfaces périodiques, pour lequel on obtient une solution exacte de l’équation discrète dans l’espace de Fourier. Avec cette solution on déduit le facteur de structure associé aux amplitudes des modes et l’expression exacte est comparée avec les valeurs numériques. De plus, on fait le lien entre les propriétés de premier passage des interfaces et le mouvement Brownien. On mesure la distribution des longueurs des intervalles et on compare les résultats avec une version modifiée du théorème de Sparre-Andersen. D’autre part, on étudie le cas général qui inclut les cas sous-diffusif et superdiffusif avec des conditions de bord périodiques. On étudie pour ces interfaces fractionnaires des propriétés de premier passage liées aux zéros des interfaces. Dans l’état stationnaire, on étudie également les premiers cumulants et propriétés d’échellement de la longueur des intervalles et de la densité de zéros. De plus, on mesure la largeur typique de l’interface et ses propriétés d’échellement. Finalement, on analyse le comportement de ces observables dans les interfaces hors d’équilibre et on discute leur dépendance en la taille du système. On discute également les conditions de stabilité des solutions del’équation discrète, importantes pour les simulations des interfaces. Dans une deuxième partie, on étude la transition de phase dynamique dans des modèles cinétiquement contraints afin d’étudier la transition vitreuse observée dans des verres structuraux. Pour un modèle en dimension un, on étudie la géométrie spatio-temporelle des bulles d’inactivité qui caractérisent les hétérogénéités dynamiques observées dans les verres. On trouve que les directions spatiales et temporelles des bulles ne sont pas liées par un comportement diffusif. En contraste, on confirme l’échellement de l’aire et d’autres quantités attendues pour un système, a priori diffusif. De plus, grâce à la théorie des grandes déviations et l’algorithme de clonage, on identifie la transition de phase dynamique dans des systèmes en deux dimensions spatiales. D’abord on mesure l’énergie libre dynamique pour différentes valeurs du paramètre λ. Après, on conjecture des valeurs critiques λ c = Σ/K, avec Σ la tension surface d’une ı̂le de sites actifs entourée par des sites inactifs dans un modèle effectif et K l’activité moyenne du système, pour laquelle la transition de phase a lieu dans la limite de taille infinie. En mesurant l’activité du système et le nombre d’occupation, on observe la dépendance de ces observables avec la taille des systèmes étudiés loin de la transition. Finalement, on mesure la propagation du front des sites actifs dans tout les systèmes. Pour l’un des systèmes étudiés, on identifie une vitesse balistique du front qui nous permet d’observer la transition de phase d’un point de vue dynamique. / This thesis investigates both equilibrium and nonequilibrium properties of mathematical stochastic models that as a representation of physical systems. By means of extensive numerical simulations we study mean quantities and their fluctuations. Nonetheless, in some systems we are interested also in large deviations. The first part of the thesis focuses on the study of rough interfaces observed in growth processes. These interfaces are simulated with state-of-the-art simulations based on parallel computing which allow us to study very large systems. On the one hand, we discuss the diffusive case given by the Edward-Wilkinson equation in periodic interfaces. For the discrete version of such an equation, we obtain an analytic solution in Fourier space. Fur-ther, we derive an exact expression of the structure factor related with the modes amplitudes describing the interface and compare it with the numerical values. Moreover, using a mapping between stationary interfaces and the Brownian motion, we relate the distribution of the intervals generated by the zeros of the interface with the first-passage distribution given by a the Sparre-Andersen theorem in the case of the Brownian motion. As a generalization of the results obtained in the diffusive case, we study a linear Langevin equation with a Riesz-Feller fractional Laplacian of order z used to simulate sub- and super-diffusive interfaces. In this general case, we identify three regimes based on the scaling behaviour of the cumulants of the intervallengths, the density of zeros and the width of the interface. Finally, we study the evolution in time of some of the observables introduced before. In the second part of the thesis, we study the dynamical phase transition in kinetically constrained models (KCMs) in order to get some insight on the glass transition observed in structural glasses. In a one-dimensional KCM we study the geometry of the bubbles of inactivity in space-time for systems at different temperatures. We find that the spatial length of the bubbles does not scale diffusively with its temporal duration. In contrast, we confirm a vidiffusive behaviour for other quantities studied. Further, by means of large deviation theory and cloning algorithms, we identify the dynamical phase transition in two-dimensional systems. To start with, we measure numerically the dynamical free energy both by measuring the largest eigenvalue of the evolution operator,for small systems, and via the cloning algorithm, for larger systems. We conjecture a value λ c = Σ/K, with Σ the surface tensionof a bubble of activity surrounded by a sea of inactive sites in an effective interfacial model and K the mean activity of the system, for each of the systems studied. For the activity of the system and the occupation number we discuss their scaling properties far from the phase transition. Starting from an empty system subject to different boundary conditions, we investigate the front propagation of active sites. We argue that the phase transition in this case can be identified by the abrupt slowing-down of the front. This is done by measuring the ballistic speed of the front in the simplest case studied. Finally, we propose an effective model following the Feynman-Kac formula for a moving front.-proprietés de premier passage, interface rugueuse, diffusion fractionnaire , système hors d'équilibre, transition de phase dynamique, modèle cinétiquement contraint, grandes déviations.-first-passage properties, rough interface, fractional diffusion, out-of-equilibrium system, dynamical phase transition, kinetically constrained model, large deviations

This dissertation presents a theoretical study of arbitrary discretizations of general nonequilibrium and non-steady-state systems. It will be shown that, without requiring the partitions of the phase-space to fulfill certain assumptions, such as culminating in Markovian partitions, a Markov chain can be constructed which has the same macro-change of probability of the occupation of the states as the original process. This is true for any classical and semiclassical system under any discrete or continuous, deterministic or stochastic, Markovian or non-Markovian dynamics. Restricted to classical and semi-classical systems, a formalism is developed which treats the projection of arbitrary (multidimensional) complex systems onto a discrete set of states of an abstract state-space using time and ensemble sampled transitions between the states of the trajectories of the original process. This formalism is then used to develop expressions for the mean first passage time and (in the case of projections resulting in pseudo-one-dimensional motion) for the individual residence times of the states using just the time and ensemble sampled transition rates. The theoretical work is illustrated by several numerical examples of non-linear diffusion processes. Those include the escape over a Kramers potential and a rough energy barrier, the escape from an entropic barrier, the folding process of a toy model of a linear polymer chain and the escape over a fluctuating barrier. The latter is an example of a non- Markovian dynamics of the original process. The results for the mean first passage time and the residence times (using both physically meaningful and non-meaningful partitions of the phase-space) confirms the theory. With an accuracy restricted only by the resolution of the measurement and/or the finite sampling size, the values of the mean first passage time of the projected process agree with those of a direct measurement on the original dynamics and with any available semi-analytical solution.