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An introduction to quantum filtering

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dc.contributor.authorBouten, Luc
dc.contributor.authorVan Handel, Ramon
dc.contributor.authorJames, Matthew
dc.date.accessioned2015-12-10T21:55:45Z
dc.date.issued2007
dc.date.updated2015-12-09T07:31:40Z
dc.description.abstractThis paper provides an introduction to quantum filtering theory. An introduction to quantum probability theory is given, focusing on the spectral theorem and the conditional expectation as a least squares estimate, and culminating in the construction of Wiener and Poisson processes on the Fock space. We describe the quantum Itô calculus and its use in the modeling of physical systems. We use both reference probability and innovations methods to obtain quantum filtering equations for system-probe models from quantum optics.
dc.identifier.issn0363-0129
dc.identifier.urihttp://hdl.handle.net/1885/39127
dc.publisherSIAM Publications
dc.sourceSiam Journal on Control and Optimization
dc.subjectKeywords: Conditional expectations; Filtering theories; Fock spaces; Least squares estimates; Physical systems; Poisson processes; Probe models; Quantum filtering; Quantum probabilities; Quantum probability; Quantum stochastic processes; Reference probabilities; Sp Quantum filtering; Quantum probability; Quantum stochastic processes
dc.titleAn introduction to quantum filtering
dc.typeJournal article
local.bibliographicCitation.issue6
local.bibliographicCitation.lastpage41
local.bibliographicCitation.startpage2199
local.contributor.affiliationBouten, Luc, California Institute of Technology
local.contributor.affiliationVan Handel, Ramon, California Institute of Technology
local.contributor.affiliationJames, Matthew, College of Engineering and Computer Science, ANU
local.contributor.authoruidJames, Matthew, u9109947
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor010203 - Calculus of Variations, Systems Theory and Control Theory
local.identifier.ariespublicationU1408929xPUB172
local.identifier.citationvolume46
local.identifier.doi10.1137/060651239
local.identifier.scopusID2-s2.0-40849121360
local.type.statusPublished Version

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