School of Physics - Theses
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ItemMatrix product states in quantum information processing( 2015)We employ the newly developed Matrix Product State (MPS) formalism to simulate two problems in the context of quantum information processing. One is the Boson sampling problem, the other is the ground state energy density of an n-qubit Hamiltonian. We find that the MPS representation of the Boson sampling problem is inefficient due to large entan- glement as the number of photons increases. In the context of adiabatic quantum computing (AQC), MPS is used to find the first four moments of an n-qubit Hamiltonian to approximate the ground state energy density of the Hamiltonian. We show an advantage of using the first-four-moment method over the conventional adiabatic procedure. Future work around AQC using MPS is discussed.
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ItemTopological quantum error correction and quantum algorithm simulations( 2011)Quantum computers are machines that manipulate quantum information stored in the form of qubits, the quantum analogue to the classical bit. Unlike the bit, quantum mechanics allows a qubit to be in a linear superposition of both its basis states. Given the same number of bits and qubits, the latter stores exponentially more information. Quantum algorithms exploit these superposition states, allowing quantum computers to solve problems such as prime number factorisation and searches faster than classical computers. Realising a large-scale quantum computer is difficult because quantum information is highly susceptible to noise. Error correction may be employed to suppress the noise, so that the results of large quantum algorithms are valid. The overhead incurred from introducing error correction is neutralised if all elementary quantum operations are constructed with an error rate below some threshold error rate. Below threshold, arbitrary length quantum computation is possible. We investigate two topological quantum error correcting codes, the planar code and the 2D colour code. We find the threshold for the 2D colour code to be 0.1%, and improve the planar code threshold from 0.75% to 1.1%. Existing protocols for the transmission of quantum states are hindered by maximum communication distances and low communication rates. We adapt the planar code for use in quantum communication, and show that this allows the fault-tolerant transmission of quantum information over arbitrary distances at a rate limited only by local quantum gate speed. Error correction is an expensive investment and thus one seeks to employ as little as possible without compromising the integrity of the results. It is therefore important to study the robustness of algorithms to noise. We show that using the matrix product state representation allows one to simulate far larger instances of the quantum factoring algorithm than under the traditional amplitude formalism representation. We simulate systems with as many as 42 qubits on a single processor with 32GB RAM, comparable to amplitude formalism simulations performed on far larger computers.