Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148315
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dc.contributor.authorHuang, Ruochengen_US
dc.date.accessioned2021-04-22T06:34:28Z-
dc.date.available2021-04-22T06:34:28Z-
dc.date.issued2021-
dc.identifier.citationHuang, R. (2021). Predictive modelling of quantum stochastic processes. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148315en_US
dc.identifier.urihttps://hdl.handle.net/10356/148315-
dc.description.abstractIn this paper, predictive modelling involving non-orthogonal emissions upon state transitions of Hidden Markov Model is studied. Mixed-State Presentation (MSP) is used to unifilarise the process in order to keep track of the state of knowledge over underlying machine states after each measurement. It is then incorporated into a work extraction protocol for the formulation of a predictive work extraction protocol. The MSP-enhanced prediction as well as the work extraction protocol are then applied to two energy-degenerate processes, the perturbed coin and golden mean process. When limited to the task of identifying the most likely next observation, it is found that the MSP-enhanced predictive protocol does not significantly improve pattern prediction. The MSP-enhanced predictive work extraction protocol, however, performs significantly better than the non-MSP protocols, owing to its ability to precisely track the evolution of state of knowledge over time.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectScience::Mathematics::Applied mathematics::Information theoryen_US
dc.subjectScience::Physics::Atomic physics::Quantum theoryen_US
dc.titlePredictive modelling of quantum stochastic processesen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorGu Mileen_US
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.description.degreeBachelor of Science in Physicsen_US
dc.contributor.researchQuantum Huben_US
dc.contributor.supervisoremailgumile@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)
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