Quantum computing has the potential to bring a new class of previously intractable problems within the reach of computer science. Harnessing the quantum mechanical phenomena of superposition and entanglement, a quantum computer can manipulate vast amounts of information in a single computational step and perform certain operations exponentially faster than classical (i.e. non-quantum) computers.
However, devising algorithms to harness the power of a quantum computer has proved extraordinarily difficult. Over twenty years after the publication of the first quantum algorithm in 1985, despite the efforts of a sizeable community of top-class researchers, only a handful of distinct algorithms have been discovered.
This thesis makes the case that evolutionary search techniques can be used to discover quantum circuits, quantum programs and ultimately new quantum algorithms. It presents a number of original results, including an algorithm discovered by evolutionary search techniques which implements the Quantum Fourier Transform on n qubits, and an algorithm discovered by evolutionary search techniques which returns the maximum value for arbitrary permutation functions.
Full thesis : PDF 1.36MB