Essays on Numerical Integration in Hamiltonian Monte Carlo

This thesis considers a variety of topics broadly unified under the theme of geometric integration for Riemannian manifold Hamiltonian Monte Carlo. In chapter 2, we review fundamental topics in numerical computing (section 2.1), classical mechanics (section 2.2), integration on manifolds (section 2.3), Riemannian geometry (section 2.5), stochastic differential equations (section 2.4), information geometry (section 2.6), and Markov chain Monte Carlo (section 2.7). The purpose of these sections is to present the topics discussed in the thesis within a broader context. The subsequent chapters are self-contained to an extent, but contain references back to this foundational material where appropriate. Chapter 3 gives a formal means of conceptualizing the Markov chains corresponding to Riemannian manifold Hamiltonian Monte Carlo and related methods; this formalism is useful for understanding the significance of reversibility and volume-preservation for maintaining detailed balance in Markov chain Monte Carlo. Throughout the remainder of the thesis, we investigate alternative methods of geometric numerical integration for use in Riemannian manifold Hamiltonian Monte Carlo, discuss numerical issues involving violations of reversibility and detailed balance, and propose new algorithms with superior theoretical foundations. In chapter 4, we evaluate the implicit midpoint integrator for Riemannian manifold Hamiltonian Monte Carlo, presenting the first time that this integrator has been deployed and assessed within this context. We discuss attributes of the implicit midpoint integrator that make it preferable, and inferior, to alternative methods of geometric integration such as the generalized leapfrog procedure. In chapter 5, we treat an empirical question as to what extent convergence thresholds play a role in geometric numerical integration in Riemannian manifold Hamiltonian Monte Carlo. If the convergence threshold is too large, then the Markov chain transition kernel will fail to maintain detailed balance, whereas a convergence threshold that is very small will incur computational penalties. We investigate these phenomena and suggest two mechanisms, based on stochastic approximation and higher-order solvers for non-linear equations, which can aid in identifying convergence thresholds or suppress its significance. In chapter 6, we consider a numerical integrator for Markov chain Monte Carlo based on the Lagrangian, rather than Hamiltonian, formalism in classical mechanics. Our contributions include clarifying the order of accuracy of this numerical integrator, which has been misunderstood in the literature, and evaluating a simple change that can accelerate the implementation of the method, but which comes at the cost of producing more serially auto-correlated samples. We also discuss robustness properties of the Lagrangian numerical method that do not materialize in the Hamiltonian setting. Chapter 7 examines theories of geometric ergodicity for Riemannian manifold Hamiltonian Monte Carlo and Lagrangian Monte Carlo, and proposes a simple modification to these Markov chain methods that enables geometric ergodicity to be inherited from the manifold Metropolis-adjusted Langevin algorithm. In chapter 8, we show how to revise an explicit integration using a theory of Lagrange multipliers so that the resulting numerical method satisfies the properties of reversibility and volume-preservation. Supplementary content in chapter E investigates topics in the theory of shadow Hamiltonians of the implicit midpoint method in the case of non-canonical Hamiltonian mechanics and chapter F, which treats the continual adaptation of a parameterized proposal distribution in the independent Metropolis-Hastings sampler

Manifold Markov chain Monte Carlo methods for Bayesian inference in a wide class of diffusion models

Bayesian inference for nonlinear diffusions, observed at discrete times, is a challenging task that has prompted the development of a number of algorithms, mainly within the computational statistics community. We propose a new direction, and accompanying methodology, borrowing ideas from statistical physics and computational chemistry, for inferring the posterior distribution of latent diffusion paths and model parameters, given observations of the process. Joint configurations of the underlying process noise and of parameters, mapping onto diffusion paths consistent with observations, form an implicitly defined manifold. Then, by making use of a constrained Hamiltonian Monte Carlo algorithm on the embedded manifold, we are able to perform computationally efficient inference for an extensive class of discretely observed diffusion models. Critically, in contrast with other approaches proposed in the literature, our methodology is highly automated, requiring minimal user intervention and applying alike in a range of settings, including: elliptic or hypo-elliptic systems; observations with or without noise; linear or non-linear observation operators. Exploiting Markovianity, we propose a variant of the method with complexity that scales linearly in the resolution of path discretisation and the number of observation times.Comment: Updated with additional numerical experiments and improvements to methodology. 50 pages, 6 figure

Macdonald processes

Macdonald processes are probability measures on sequences of partitions defined in terms of nonnegative specializations of the Macdonald symmetric functions and two Macdonald parameters q,t in [0,1). We prove several results about these processes, which include the following. (1) We explicitly evaluate expectations of a rich family of observables for these processes. (2) In the case t=0, we find a Fredholm determinant formula for a q-Laplace transform of the distribution of the last part of the Macdonald-random partition. (3) We introduce Markov dynamics that preserve the class of Macdonald processes and lead to new "integrable" 2d and 1d interacting particle systems. (4) In a large time limit transition, and as q goes to 1, the particles of these systems crystallize on a lattice, and fluctuations around the lattice converge to O'Connell's Whittaker process that describe semi-discrete Brownian directed polymers. (5) This yields a Fredholm determinant for the Laplace transform of the polymer partition function, and taking its asymptotics we prove KPZ universality for the polymer (free energy fluctuation exponent 1/3 and Tracy-Widom GUE limit law). (6) Under intermediate disorder scaling, we recover the Laplace transform of the solution of the KPZ equation with narrow wedge initial data. (7) We provide contour integral formulas for a wide array of polymer moments. (8) This results in a new ansatz for solving quantum many body systems such as the delta Bose gas.Comment: 175 pages (6 chapters, 24 page introduction, index, glossary), 6 figures; updated references and minor mistakes correcte

Iterative and doubling algorithms for Riccati-type matrix equations: a comparative introduction

We review a family of algorithms for Lyapunov- and Riccati-type equations which are all related to each other by the idea of \emph{doubling}: they construct the iterate $Q_k = X_{2^k}$ of another naturally-arising fixed-point iteration $(X_h)$ via a sort of repeated squaring. The equations we consider are Stein equations $X - A^*XA=Q$, Lyapunov equations $A^*X+XA+Q=0$, discrete-time algebraic Riccati equations $X=Q+A^*X(I+GX)^{-1}A$, continuous-time algebraic Riccati equations $Q+A^*X+XA-XGX=0$, palindromic quadratic matrix equations $A+QY+A^*Y^2=0$, and nonlinear matrix equations $X+A^*X^{-1}A=Q$. We draw comparisons among these algorithms, highlight the connections between them and to other algorithms such as subspace iteration, and discuss open issues in their theory.Comment: Review article for GAMM Mitteilunge

Generalized Bose-Einstein Condensation in Driven-dissipative Quantum Gases

Bose-Einstein condensation is a collective quantum phenomenon where a macroscopic number of bosons occupies the lowest quantum state. For fixed temperature, bosons condense above a critical particle density. This phenomenon is a consequence of the Bose-Einstein distribution which dictates that excited states can host only a finite number of particles so that all remaining particles must form a condensate in the ground state. This reasoning applies to thermal equilibrium. We investigate the fate of Bose condensation in nonisolated systems of noninteracting Bose gases driven far away from equilibrium. An example of such a driven-dissipative scenario is a Floquet system coupled to a heat bath. In these time-periodically driven systems, the particles are distributed among the Floquet states, which are the solutions of the Schrödinger equation that are time periodic up to a phase factor. The absence of the definition of a ground state in Floquet systems raises the question, whether Bose condensation survives far from equilibrium. We show that Bose condensation generalizes to an unambiguous selection of multiple states each acquiring a large occupation proportional to the total particle number. In contrast, the occupation numbers of nonselected states are bounded from above. We observe this phenomenon not only in various Floquet systems, i.a. time-periodically-driven quartic oscillators and tight-binding chains, but also in systems coupled to two baths where the population of one bath is inverted. In many cases, the occupation numbers of the selected states are macroscopic such that a fragmented condensation is formed according to the Penrose-Onsager criterion. We propose to control the heat conductivity through a chain by switching between a single and several selected states. Furthermore, the number of selected states is always odd except for fine-tuning. We provide a criterion, whether a single state (e.g., Bose condensation) or several states are selected. In open systems, which exchange also particles with their environment, the nonequilibrium steady state is determined by the interplay between the particle-number-conserving intermode kinetics and particle-number-changing pumping and loss processes. For a large class of model systems, we find the following generic sequence when increasing the pumping: For small pumping, no state is selected. The first threshold, where the stimulated emission from the gain medium exceeds the loss in a state, is equivalent to the classical lasing threshold. Due to the competition between gain, loss and intermode kinetics, further transitions may occur. At each transition, a single state becomes either selected or deselected. Counterintuitively, at sufficiently strong pumping, the set of selected states is independent of the details of the gain and loss. Instead, it is solely determined by the intermode kinetics like in closed systems. This implies equilibrium condensation when the intermode kinetics is caused by a thermal environment. These findings agree well with observations of exciton-polariton gases in microcavities. In a collaboration with experimentalists, we observe and explain the pump-power-driven mode switching in a bimodal quantum-dot micropillar cavity.Die Bose-Einstein-Kondensation ist ein Quantenphänomen, bei dem eine makroskopische Zahl von Bosonen den tiefsten Quantenzustand besetzt. Die Teilchen kondensieren, wenn bei konstanter Temperatur die Teilchendichte einen kritischen Wert übersteigt. Da die Besetzungen von angeregten Zuständen nach der Bose-Einstein-Statistik begrenzt sind, bilden alle verbleibenden Teilchen ein Kondensat im Grundzustand. Diese Argumentation ist im thermischen Gleichgewicht gültig. In dieser Arbeit untersuchen wir, ob die Bose-Einstein-Kondensation in nicht wechselwirkenden Gasen fern des Gleichgewichtes überlebt. Diese Frage stellt sich beispielsweise in Floquet-Systemen, welche Energie mit einer thermischen Umgebung austauschen. In diesen zeitperiodisch getriebenen Systemen verteilen sich die Teilchen auf Floquet-Zustände, die bis auf einen Phasenfaktor zeitperiodischen Lösungen der Schrödinger-Gleichung. Die fehlende Definition eines Grundzustandes wirft die Frage nach der Existenz eines Bose-Kondensates auf. Wir finden eine Generalisierung der Bose-Kondensation in Form einer Selektion mehrerer Zustände. Die Besetzung in jedem selektierten Zustand ist proportional zur Gesamtteilchenzahl, während die Besetzung aller übrigen Zustände begrenzt bleibt. Wir beobachten diesen Effekt nicht nur in Floquet-Systemen, z.B. getriebenen quartischen Fallen, sondern auch in Systemen die an zwei Wärmebäder gekoppelt sind, wobei die Besetzung des einen invertiert ist. In vielen Fällen ist die Teilchenzahl in den selektierten Zuständen makroskopisch, sodass nach dem Penrose-Onsager Kriterium ein fragmentiertes Kondensat vorliegt. Die Wärmeleitfähigkeit des Systems kann durch den Wechsel zwischen einem und mehreren selektierten Zuständen kontrolliert werden. Die Anzahl der selektierten Zustände ist stets ungerade, außer im Falle von Feintuning. Wir beschreiben ein Kriterium, welches bestimmt, ob es nur einen selektierten Zustand (z.B. Bose-Kondensation) oder viele selektierte Zustände gibt. In offenen Systemen, die auch Teilchen mit der Umgebung austauschen, ist der stationäre Nichtgleichgewichtszustand durch ein Wechselspiel zwischen der (Teilchenzahl-erhaltenden) Intermodenkinetik und den (Teilchenzahl-ändernden) Pump- und Verlustprozessen bestimmt. Für eine Vielzahl an Modellsystemen zeigen wir folgendes typisches Verhalten mit steigender Pumpleistung: Zunächst ist kein Zustand selektiert. Die erste Schwelle tritt auf, wenn der Gewinn den Verlust in einer Mode ausgleicht und entspricht der klassischen Laserschwelle. Bei stärkerem Pumpen treten weitere Übergänge auf, an denen je ein einzelner Zustand entweder selektiert oder deselektiert wird. Schließlich ist die Selektion überraschenderweise unabhängig von der Charakteristik des Pumpens und der Verlustprozesse. Die Selektion ist vielmehr ausschließlich durch die Intermodenkinetik bestimmt und entspricht damit den oben beschriebenen geschlossenen Systemen. Ist die Kinetik durch ein thermisches Bad hervorgerufen, tritt wie im Gleichgewicht eine Grundzustands-Kondensation auf. Unsere Theorie ist in Übereinstimmung mit experimentellen Beobachtungen von Exziton-Polariton-Gasen in Mikrokavitäten. In einer Kooperation mit experimentellen Gruppen konnten wir den Modenwechsel in einem bimodalen Quantenpunkt-Mikrolaser erklären