Highly efficient quantum spin dynamics simulation algorithms

<p> Spin dynamics simulations are used to gain insight into important magnetic resonance experiments in the fields of chemistry, biochemistry, and physics. Presented in this thesis are investigations into how to accelerate these simulations by making them more efficient. </p> <p>...

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Bibliographic Details
Main Author: Edwards, L
Other Authors: Kuprov, I
Format: Thesis
Language:English
Published: 2014
Subjects:
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author Edwards, L
author2 Kuprov, I
author_facet Kuprov, I
Edwards, L
author_sort Edwards, L
collection OXFORD
description <p> Spin dynamics simulations are used to gain insight into important magnetic resonance experiments in the fields of chemistry, biochemistry, and physics. Presented in this thesis are investigations into how to accelerate these simulations by making them more efficient. </p> <p> Chapter 1 gives a brief introduction to the methods of spin dynamics simulation used in the rest of the thesis. The `exponential scaling problem' that formally limits the size of spin system that can be simulated is described. </p> <p> Chapter 2 provides a summary of methods that have been developed to overcome the exponential scaling problem in liquid state magnetic resonance. </p> <p> The possibility of utilizing the multiple processors prevalent in modern computers to accelerate spin dynamics simulations provides the impetus for the investigation found in Chapter 3. A number of different methods of parallelization leading to acceleration of spin dynamics simulations are derived and discussed. </p> <p> It is often the case that the parameters defining a spin system are time-dependent. This complicates the simulation of the spin dynamics of the system. Chapter 4 presents a method of simplifying such simulations by mapping the spin dynamics into a larger state space. This method is applied to simulations incorporating mechanical spinning of the sample with powder averaging. </p> <p> In Chapter 5, implementations of several magnetic resonance experiments are detailed. In so doing, use of techniques developed in Chapters 2 and 3 are exemplified. Further, specific details of these experiments are utilized to increase the efficiency of their simulation. </p>
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spelling oxford-uuid:3eec480e-5a3a-4197-a786-e6d42988d4a52024-12-07T16:15:20ZHighly efficient quantum spin dynamics simulation algorithmsThesishttp://purl.org/coar/resource_type/c_db06uuid:3eec480e-5a3a-4197-a786-e6d42988d4a5Computational chemistryApplications and algorithmsNMR spectroscopyPhysical & theoretical chemistryEnglishOxford University Research Archive - Valet2014Edwards, LKuprov, ITimmel, C<p> Spin dynamics simulations are used to gain insight into important magnetic resonance experiments in the fields of chemistry, biochemistry, and physics. Presented in this thesis are investigations into how to accelerate these simulations by making them more efficient. </p> <p> Chapter 1 gives a brief introduction to the methods of spin dynamics simulation used in the rest of the thesis. The `exponential scaling problem' that formally limits the size of spin system that can be simulated is described. </p> <p> Chapter 2 provides a summary of methods that have been developed to overcome the exponential scaling problem in liquid state magnetic resonance. </p> <p> The possibility of utilizing the multiple processors prevalent in modern computers to accelerate spin dynamics simulations provides the impetus for the investigation found in Chapter 3. A number of different methods of parallelization leading to acceleration of spin dynamics simulations are derived and discussed. </p> <p> It is often the case that the parameters defining a spin system are time-dependent. This complicates the simulation of the spin dynamics of the system. Chapter 4 presents a method of simplifying such simulations by mapping the spin dynamics into a larger state space. This method is applied to simulations incorporating mechanical spinning of the sample with powder averaging. </p> <p> In Chapter 5, implementations of several magnetic resonance experiments are detailed. In so doing, use of techniques developed in Chapters 2 and 3 are exemplified. Further, specific details of these experiments are utilized to increase the efficiency of their simulation. </p>
spellingShingle Computational chemistry
Applications and algorithms
NMR spectroscopy
Physical & theoretical chemistry
Edwards, L
Highly efficient quantum spin dynamics simulation algorithms
title Highly efficient quantum spin dynamics simulation algorithms
title_full Highly efficient quantum spin dynamics simulation algorithms
title_fullStr Highly efficient quantum spin dynamics simulation algorithms
title_full_unstemmed Highly efficient quantum spin dynamics simulation algorithms
title_short Highly efficient quantum spin dynamics simulation algorithms
title_sort highly efficient quantum spin dynamics simulation algorithms
topic Computational chemistry
Applications and algorithms
NMR spectroscopy
Physical & theoretical chemistry
work_keys_str_mv AT edwardsl highlyefficientquantumspindynamicssimulationalgorithms