Photonic approaches to multi-party entanglement in solids and learning in the brain

dc.contributor.advisorSimon, Christoph
dc.contributor.authorZarkeshian, Parisa
dc.contributor.committeememberBarzanjeh, Shabir
dc.contributor.committeememberOblak, Daniel
dc.contributor.committeememberCraddock, Travis
dc.contributor.committeememberJackel, Brian
dc.date2021-11
dc.date.accessioned2021-08-13T18:53:14Z
dc.date.available2021-08-13T18:53:14Z
dc.date.issued2021-08-06
dc.description.abstractUnderstanding the fundamental quantum and classical properties of photons is crucial in a wide range of applications. Photons exhibit quantum entanglement, the strongest form of correlation that has been observed between subsystems. Entanglement is perhaps the most valuable resource for many quantum information and quantum computation tasks, empowering them to be superior to their classical counterparts. Undoubtedly, understanding how entanglement can be generated, manipulated, and measured are among the most pre-eminent research questions in quantum information processing. However, the realm of influence of photons is not just limited to information technologies. Photons are, surprisingly, being produced constantly in biological systems as well. Modeling and characterizing the involvement of photons in various biological processes are active areas of research. In the first part of my Ph.D. program, I focused on the problem of quantifying multi-partite entanglement in a solid, an atomic frequency comb (AFC) crystal, using a single photon. We proposed a novel entanglement witness and showed that our witness is well suited for demonstrating and quantifying multi-partite entanglement in AFC systems. Our results are the first demonstration of multi-partite entanglement in a solid between over two hundred ensembles each containing a billion atoms. The second project of my Ph.D. was motivated by the question of why brain cells are producing biophotons. Photons are known as perfect carriers for information. The brain is the computation centre where all the learning and decision makings are happening. Learning, in theory, is an informational task, and its biological realization in the brain is not completely understood. We asked if photons could play a role in the process of learning in the brain. A common form of learning involves multiple cycles of training, evaluating, and receiving feedback. Both forward and backward parts of these cycles require an information flow. Existing theories mainly focus on neural electrochemical signals. We proposed that biophotons can propagate the feedback teaching signals required for learning in the brain. By multiple numerical experiments simulated on an artificial neural network, we demonstrated that stochastic emissions of biophotons carrying partial backward information enable learning in the network.en_US
dc.identifier.citationZarkeshian, P. (2021). Photonic approaches to multi-party entanglement in solids and learning in the brain (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/39094
dc.identifier.urihttp://hdl.handle.net/1880/113732
dc.language.isoengen_US
dc.publisher.facultyScienceen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectQuantumen_US
dc.subjectMultipartite Entanglementen_US
dc.subjectBackpropagationen_US
dc.subjectLearning in the Brainen_US
dc.subjectBiophotonen_US
dc.subject.classificationPhysicsen_US
dc.subject.classificationOpticsen_US
dc.titlePhotonic approaches to multi-party entanglement in solids and learning in the brainen_US
dc.typedoctoral thesisen_US
thesis.degree.disciplinePhysics & Astronomyen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameDoctor of Philosophy (PhD)en_US
ucalgary.item.requestcopyfalseen_US
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