The quantum world is innately parallel. Quantum objects may exist in many places at the same time and in general have a superposition of attributes that would be mutually exclusive for an object on the everyday classical scale. In 1982 Richard Feynman suggested that one might attempt to use this parallelism to speed up computation and in 1982 Peter Shor discovered an algorithm that could, theoretically, make use of it in a calculation. Since these early theoretical works, there has been a dramatic effort in the theory of quantum computation while at the same time trying to find a physical system where these ideas could be realized. Taking the queue from the success of digital, gate-based, classical computation, much of this effort has focused on gate based digital quantum computation. There is an alternative, however, which harnesses our understanding of physical process rather more directly. Nature is rather good at solving problems such as finding the most efficient way to arrange a collection of atoms into a crystal. Nature achieves this by gradually reducing the temperature of a system so that it can eventually settle to its lowest energy state - a process known as thermal annealing. This is used in a range of classical optimization algorithms. A quantum version of this, originally known as quantum annealing - now known as adiabatic quantum computation - may ultimately prove to be more effective for quantum computation than the gate based model. Indeed, a Canadian company, D-wave Systems, has attempted to make just such a computer with some promising initial results. Interpreting such attempts is difficult, however, since the failure mode of an adiabatic quantum computation is a classical thermal anneal. This project aims to develop a systematic way to test whether an adiabatic quantum computation has taken place using a pragmatic, physics based approach. In doing so, new insights into how to optimize the performance of such a system will result.