{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/114001"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/114001","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Programmable nanophotonics for quantum information processing and artificial intelligence","abstract":"Over the past decade, progress in digital electronic computing systems has slowed as traditional, transistor-based silicon technologies approach their scaling limits. Quantum computing and non-Von Neumann computing architectures have emerged as promising alternatives for continued computational advancement-garnering significant investment and public interest. As a hardware platform, silicon photonics may play an important role in enabling quantum and classical information processing architectures. Here, I will discuss my thesis work on developing a programmable nanophotonic processor in silicon, as well as applications of this processor within the fields of quantum simulation, quantum computing, and deep learning. I will also cover results on environment-assisted quantum transport, deep learning with coherent nanophotonics, heralded single-photon sources, and highly integrable superconducting nanowire single-photon detectors.","abstract_html":"Over the past decade, progress in digital electronic computing systems has slowed as traditional, transistor-based silicon technologies approach their scaling limits. Quantum computing and non-Von Neumann computing architectures have emerged as promising alternatives for continued computational advancement-garnering significant investment and public interest. As a hardware platform, silicon photonics may play an important role in enabling quantum and classical information processing architectures. Here, I will discuss my thesis work on developing a programmable nanophotonic processor in silicon, as well as applications of this processor within the fields of quantum simulation, quantum computing, and deep learning. I will also cover results on environment-assisted quantum transport, deep learning with coherent nanophotonics, heralded single-photon sources, and highly integrable superconducting nanowire single-photon detectors.","abstract_has_math":false,"creators":["Harris, Nicholas Christopher"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Dirk R. Englund."],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-22T22:21:37Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/114001","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Dirk R. Englund."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/114001"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.","Cataloged from PDF version of thesis.","Includes bibliographical references."]},{"key":"dc:description.abstract","label":"Abstract","values":["Over the past decade, progress in digital electronic computing systems has slowed as traditional, transistor-based silicon technologies approach their scaling limits. Quantum computing and non-Von Neumann computing architectures have emerged as promising alternatives for continued computational advancement-garnering significant investment and public interest. As a hardware platform, silicon photonics may play an important role in enabling quantum and classical information processing architectures. Here, I will discuss my thesis work on developing a programmable nanophotonic processor in silicon, as well as applications of this processor within the fields of quantum simulation, quantum computing, and deep learning. I will also cover results on environment-assisted quantum transport, deep learning with coherent nanophotonics, heralded single-photon sources, and highly integrable superconducting nanowire single-photon detectors."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. D."]},{"key":"dc:title","label":"Title","values":["Programmable nanophotonics for quantum information processing and artificial intelligence"]}]}],"canonical_facts":{"dc:contributor.advisor":["Dirk R. Englund."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:creator":["Harris, Nicholas Christopher"],"dc:date.accessioned":["2018-03-02T22:22:28Z"],"dc:date.available":["2018-03-02T22:22:28Z"],"dc:date.issued":["2017"],"dc:description":["Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.","Cataloged from PDF version of thesis.","Includes bibliographical references."],"dc:description.abstract":["Over the past decade, progress in digital electronic computing systems has slowed as traditional, transistor-based silicon technologies approach their scaling limits. Quantum computing and non-Von Neumann computing architectures have emerged as promising alternatives for continued computational advancement-garnering significant investment and public interest. As a hardware platform, silicon photonics may play an important role in enabling quantum and classical information processing architectures. Here, I will discuss my thesis work on developing a programmable nanophotonic processor in silicon, as well as applications of this processor within the fields of quantum simulation, quantum computing, and deep learning. I will also cover results on environment-assisted quantum transport, deep learning with coherent nanophotonics, heralded single-photon sources, and highly integrable superconducting nanowire single-photon detectors."],"dc:description.degree":["Ph. D."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/114001"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Electrical Engineering and Computer Science."],"dc:title":["Programmable nanophotonics for quantum information processing and artificial intelligence"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:37Z"}