P. F. Tupper

Benoit Charbonneau, Yuriy Svyrydov, P. F. Tupper

We consider the weak convergence of numerical methods for stochastic differential equations (SDEs). Weak convergence is usually expressed in terms of the convergence of expected values of test functions of the trajectories. Here we present an alternative formulation of weak convergence in terms of the well-known Prokhorov metric on spaces of random variables. For a general class of methods, we establish bounds on the rates of convergence in terms of the Prokhorov metric. In doing so, we revisit the original proofs of weak convergence and show explicitly how the bounds on the error depend on the smoothness of the test functions. As an application of our result, we use the Strassen - Dudley theorem to show that the numerical approximation and the true solution to the system of SDEs can be re-embedded in a probability space in such a way that the method converges there in a strong sense. One corollary of this last result is that the method converges in the Wasserstein distance, another metric on spaces of random variables. Another corollary establishes rates of convergence for expected values of test functions assuming only local Lipschitz continuity. We conclude with a review of the existing results for pathwise convergence of weakly converging methods and the corresponding strong results available under re-embedding.

P. F. Tupper

Molecular dynamics refers to the computer simulation of a material at the atomic level. An open problem in numerical analysis is to explain the apparent reliability of molecular dynamics simulations. The difficulty is that individual trajectories computed in molecular dynamics are accurate for only short time intervals, whereas apparently reliable information can be extracted from very long-time simulations. It has been conjectured that long molecular dynamics trajectories have low-dimensional statistical features that accurately approximate those of the original system. Another conjecture is that numerical trajectories satisfy the shadowing property: that they are close over long time intervals to exact trajectories but with different initial conditions. We prove that these two views are actually equivalent to each other, after we suitably modify the concept of shadowing. A key ingredient of our result is a general theorem that allows us to take random elements of a metric space that are close in distribution and embed them in the same probability space so that they are close in a strong sense. This result is similar to the Strassen-Dudley Theorem except that a mapping is provided between the two random elements. Our results on shadowing are motivated by molecular dynamics but apply to the approximation of any dynamical system when initial conditions are selected according to a probability measure.

B. Goodman, P. F. Tupper

Exemplar models are a popular class of models used to describe language change. Here we study how limiting the memory capacity of an individual in these models affects the system's behaviour. In particular we demonstrate the effect this change has on the extinction of categories. Previous work in exemplar dynamics has not addressed this question. In order to investigate this, we will inspect a simplified exemplar model. We will prove for the simplified model that all the sound categories but one will always become extinct, whether memory storage is limited or not. However, computer simulations show that changing the number of stored memories alters how fast categories become extinct.

P. F. Tupper

We develop a model of phonological contrast in natural language. Specifically, the model describes the maintenance of contrast between different words in a language, and the elimination of such contrast when sounds in the words merge. An example of such a contrast is that provided by the two vowel sounds 'i' and 'e', which distinguish pairs of words such as 'pin' and 'pen' in most dialects of English. We model language users' knowledge of the pronunciation of a word as consisting of collections of labeled exemplars stored in memory. Each exemplar is a detailed memory of a particular utterance of the word in question. In our model an exemplar is represented by one or two phonetic variables along with a weight indicating how strong the memory of the utterance is. Starting from an exemplar-level model we derive integro-differential equations for the evolution of exemplar density fields in phonetic space. Using these latter equations we investigate under what conditions two sounds merge, thus eliminating the contrast. Our main conclusion is that for the preservation of phonological contrast, it is necessary that anomalous utterances of a given word are discarded, and not merely stored in memory as an exemplar of another word.

P. F. Tupper

We develop a model for the stability and maintenance of phonological categories. Examples of phonological categories are vowel sounds such as "i" and "e". We model such categories as consisting of collections of labeled exemplars that language users store in their memory. Each exemplar is a detailed memory of an instance of the linguistic entity in question. Starting from an exemplar-level model we derive integro-differential equations for the long-term evolution of the density of exemplars in different portions of phonetic space. Using these latter equations we investigate under what conditions two phonological categories merge or not. Our main conclusion is that for the preservation of distinct phonological categories, it is necessary that anomalous speech tokens of a given category are discarded, and not merely stored in memory as an exemplar of another category.

P. F. Tupper

An open problem in numerical analysis is to explain why molecular dynamics works. The difficulty is that numerical trajectories are only accurate for very short times, whereas the simulations are performed over long time intervals. It is believed that statistical information from these simulations is accurate, but no one has offered a rigourous proof of this. In order to give mathematicians a clear goal in understanding this problem, we state a precise mathematical conjecture about molecular dynamics simulation of a particular system. We believe that if the conjecture is proved, we will then understand why molecular dynamics works.

P. F. Tupper

We consider the numerical simulation of Hamiltonian systems of ordinary differential equations. Two features of Hamiltonian systems are that energy is conserved along trajectories and phase space volume is preserved by the flow. We want to determine if there are integration schemes that preserve these two properties for all Hamiltonian systems, or at least for all systems in a wide class. This paper provides provides a negative result in the case of two dimensional (one degree of freedom) Hamiltonian systems, for which phase space volume is identical to area. Our main theorem shows that there are no computationally reasonable numerical integrators for which all Hamiltonian systems of one degree of freedom can be integrated while conserving both area and energy. Before proving this result we define what we mean by a computationally reasonable integrator. We then consider what obstructions this result places on the existence of volume- and energy-conserving integrators for Hamiltonian systems with an arbitrary number of degrees of freedom.