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dc.contributor.advisorKlappenecker, Andreas
dc.creatorChinthamani, Neelima
dc.date.accessioned2004-09-30T02:02:43Z
dc.date.available2004-09-30T02:02:43Z
dc.date.created2005-05
dc.date.issued2004-09-30
dc.identifier.urihttps://hdl.handle.net/1969.1/466
dc.description.abstractQuantum error correction codes were introduced as a means to protect quantum information from decoherance and operational errors. Based on their approach to error control, error correcting codes can be divided into two different classes: block codes and convolutional codes. There has been significant development towards finding quantum block codes, since they were first discovered in 1995. In contrast, quantum convolutional codes remained mainly uninvestigated. In this thesis, we develop the stabilizer formalism for quantum convolutional codes. We define distance properties of these codes and give a general method for constructing encoding circuits, given a set of generators of the stabilizer of a quantum convolutional stabilizer code, is shown. The resulting encoding circuit enables online encoding of the qubits, i.e., the encoder does not have to wait for the input transmission to end before starting the encoding process. We develop the quantum analogue of the Viterbi algorithm. The quantum Viterbi algorithm (QVA) is a maximum likehood error estimation algorithm, the complexity of which grows linearly with the number of encoded qubits. A variation of the quantum Viterbi algorithm, the Windowed QVA, is also discussed. Using Windowed QVA, we can estimate the most likely error without waiting for the entire received sequence.en
dc.format.extent285136 bytesen
dc.format.extent79286 bytesen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjectQuantum error correction codesen
dc.subjectQuantum convolutional codesen
dc.titleQuantum convolutional stabilizer codesen
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentComputer Scienceen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberBettati, Riccardo
dc.contributor.committeeMemberTaylor, Valerie
dc.type.genreElectronic Thesisen
dc.type.materialtexten
dc.format.digitalOriginborn digitalen


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