Unified analysis of finite-size error for periodic Hartree-Fock and second order M{\o}ller-Plesset perturbation theory

Despite decades of practice, finite-size errors in many widely used electronic structure theories for periodic systems remain poorly understood. For periodic systems using a general Monkhorst-Pack grid, there has been no comprehensive and rigorous analysis of the finite-size error in the Hartree-Fock theory (HF) and the second order M{\o}ller-Plesset perturbation theory (MP2), which are the simplest wavefunction based method, and the simplest post-Hartree-Fock method, respectively. Such calculations can be viewed as a multi-dimensional integral discretized with certain trapezoidal rules. Due to the Coulomb singularity, the integrand has many points of discontinuity in general, and standard error analysis based on the Euler-Maclaurin formula gives overly pessimistic results. The lack of analytic understanding of finite-size errors also impedes the development of effective finite-size correction schemes. We propose a unified analysis to obtain sharp convergence rates of finite-size errors for the periodic HF and MP2 theories. Our main technical advancement is a generalization of the result of [Lyness, 1976] for obtaining sharp convergence rates of the trapezoidal rule for a class of non-smooth integrands. Our result is applicable to three-dimensional bulk systems as well as low dimensional systems (such as nanowires and 2D materials). Our unified analysis also allows us to prove the effectiveness of the Madelung-constant correction to the Fock exchange energy, and the effectiveness of a recently proposed staggered mesh method for periodic MP2 calculations [Xing, Li, Lin, J. Chem. Theory Comput. 2021]. Our analysis connects the effectiveness of the staggered mesh method with integrands with removable singularities, and suggests a new staggered mesh method for reducing finite-size errors of periodic HF calculations

Some quadrature methods for general and singular integrals in one and two dimensions

In this thesis numerical integration in one and two dimensions is considered. In chapter two transformation methods are considered primarily for singular integrals and methods of computing the transformations themselves are derived. The well-known transformation based on the IMT rule and error function are extended to non-standard functions. The implementation of these rules and their performances are demonstrated. These transformations are then extended to two-dimensions and are used to develop accurate rules for integrating singular integrals. In addition to this, a polynomial transformation with the aim of the reduction in the number of function evaluations is also considered and the resultant product rule is applied to two-dimensional non-singular integrals. Finally, the use of monomials in the construction of integration rules for non-singular two-dimensional integrals is considered and some rules developed. In all these situations the rules developed are tested and compared with existing methods. The results show that the new rules compare favourably with existing ones

Time domain boundary element method for room acoustics

This thesis is about improving the suitability of the time domain Boundary Element Method (BEM) for predicting the scattering from surface treatments used to improve the acoustics of rooms. The discretised integral equations are typically solved by marching on in time from initial silence; however, this being iterative has potential for divergence. Such instability and high computational cost have prohibited the time domain BEM from widespread use.The underlying integral equation is known to not possess unique solutions at certain frequencies, physically interpreted as cavity resonances, and these manifest as resonant poles, all excited and potentially divergent due to numerical error. This has been addressed by others using the combined field integral equation; an approach built upon in this thesis.Accuracy and stability may also be compromised by poor discretisation and integration accuracy. The latter is investigated on real-world surfaces, demonstrating that the popular Gaussian integration schemes are not suitable in some circumstances. Instead a contour integration scheme capable of resolving the integrands‟ singular nature is developed.Schroeder diffusers are Room Acoustic treatments which comprise wells separated by thin fins. The algorithm is extended to model such surfaces, applying the combined field integral equation to the body and an open surface model to the fins. It is shown that this improves stability over an all open surface model.A new model for compliant surfaces is developed, comparable to the surface impedance model used in the frequency domain. This is implemented for surfaces with welled and absorbing sections, permitting modelling of a Schroeder diffuser as a box with surface impedances that simulate the delayed reflections caused by the wells. A Binary Amplitude Diffuser - a partially absorbing diffuser - is also modelled.These new models achieve good accuracy but not universal stability and avenues of future research are proposed to address the latter issue

A Fully Parallelized and Budgeted Multi-level Monte Carlo Framework for Partial Differential Equations: From Mathematical Theory to Automated Large-Scale Computations

All collected data on any physical, technical or economical process is subject to uncertainty. By incorporating this uncertainty in the model and propagating it through the system, this data error can be controlled. This makes the predictions of the system more trustworthy and reliable. The multi-level Monte Carlo (MLMC) method has proven to be an effective uncertainty quantification tool, requiring little knowledge about the problem while being highly performant. In this doctoral thesis we analyse, implement, develop and apply the MLMC method to partial differential equations (PDEs) subject to high-dimensional random input data. We set up a unified framework based on the software M++ to approximate solutions to elliptic and hyperbolic PDEs with a large selection of finite element methods. We combine this setup with a new variant of the MLMC method. In particular, we propose a budgeted MLMC (BMLMC) method which is capable to optimally invest reserved computing resources in order to minimize the model error while exhausting a given computational budget. This is achieved by developing a new parallelism based on a single distributed data structure, employing ideas of the continuation MLMC method and utilizing dynamic programming techniques. The final method is theoretically motivated, analyzed, and numerically well-tested in an automated benchmarking workflow for highly challenging problems like the approximation of wave equations in randomized media

Loaded Dice in Monte Carlo: importance sampling in phase space integration and probability distributions for discrepancies

Discrepancies play an important role in the study of uniformity properties of point sets. Their probability distributions are a help in the analysis of the efficiency of the Quasi Monte Carlo method of numerical integration, which uses point sets that are distributed more uniformly than sets of independently uniformly distributed random points. In this thesis, generating functions of probability distributions of quadratic discrepancies are calculated using techniques borrowed from quantum field theory. The second part of this manuscript deals with the application of the Monte Carlo method to phase space integration, and in particular with an explicit example of importance sampling. It concerns the integration of differential cross sections of multi-parton QCD-processes, which contain the so-called kinematical antenna pole structures. The algorithm is presented and compared with RAMBO, showing a substantial reduction in computing time. In behalf of completeness of the thesis, short introductions to probability theory, Feynman diagrams and the Monte Carlo method of numerical integration are included.Comment: PhD thesis, uses times and eule