{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/150215"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/150215","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Large-scale programmable silicon photonics for quantum and classical machine learning","abstract":"Photonic technologies provide many unique physical advantages including ultra-high bandwidths, energy-efficient operations, and low coupling to environmental noise. Furthermore, recent advances in foundry-based manufacturing platforms have enabled the emerging field of integrated systems photonics. In contrast to their bulk optics counterparts, these systems can co-integrate dense ensembles of active photonic and electronic components on a single wafer with high phase stability and small device footprints. Initial demonstrations of each element in the integrated photonics stack—sources, processors, and detectors—motivate the development of wafer-scale photonic integrated circuit implementations, which are poised to form a key building block for fundamental advancements in computing, communications, and sensing. The first part of this thesis will discuss the development and early system-level demonstrations of linear programmable nanophotonic processors in the silicon-on-insulator platform for applications in quantum and classical machine learning and information processing. Using our developed processor architecture, we then present a nanophotonic Ising sampler for noise-assisted combinatorial optimization. Subsequently, we present a novel, foundry-compatible platform for integrating telecommunication-wavelength artificial atom quantum emitters directly in silicon photonic circuits. Finally, we report a capacity analysis of a structured interferometric receiver implemented with a silicon photonic processor for detection of optical signals in photon-sparse communication links.","abstract_html":"Photonic technologies provide many unique physical advantages including ultra-high bandwidths, energy-efficient operations, and low coupling to environmental noise. Furthermore, recent advances in foundry-based manufacturing platforms have enabled the emerging field of integrated systems photonics. In contrast to their bulk optics counterparts, these systems can co-integrate dense ensembles of active photonic and electronic components on a single wafer with high phase stability and small device footprints. Initial demonstrations of each element in the integrated photonics stack—sources, processors, and detectors—motivate the development of wafer-scale photonic integrated circuit implementations, which are poised to form a key building block for fundamental advancements in computing, communications, and sensing. The first part of this thesis will discuss the development and early system-level demonstrations of linear programmable nanophotonic processors in the silicon-on-insulator platform for applications in quantum and classical machine learning and information processing. Using our developed processor architecture, we then present a nanophotonic Ising sampler for noise-assisted combinatorial optimization. Subsequently, we present a novel, foundry-compatible platform for integrating telecommunication-wavelength artificial atom quantum emitters directly in silicon photonic circuits. Finally, we report a capacity analysis of a structured interferometric receiver implemented with a silicon photonic processor for detection of optical signals in photon-sparse communication links.","abstract_has_math":false,"creators":["Prabhu, Mihika"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Englund, Dirk R."],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-02","date_published":"2023-02","updated_at":"2026-07-22T22:21:50Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"rights_urls":["http://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/150215","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Englund, Dirk R."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Prabhu, Mihika"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-03-31T14:40:09Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-03-31T14:40:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2023-02"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctoral","Doctor of Philosophy"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright - Educational Use Permitted","Copyright MIT"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/page/InC-EDU/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/150215"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Photonic technologies provide many unique physical advantages including ultra-high bandwidths, energy-efficient operations, and low coupling to environmental noise. Furthermore, recent advances in foundry-based manufacturing platforms have enabled the emerging field of integrated systems photonics. In contrast to their bulk optics counterparts, these systems can co-integrate dense ensembles of active photonic and electronic components on a single wafer with high phase stability and small device footprints. Initial demonstrations of each element in the integrated photonics stack—sources, processors, and detectors—motivate the development of wafer-scale photonic integrated circuit implementations, which are poised to form a key building block for fundamental advancements in computing, communications, and sensing. The first part of this thesis will discuss the development and early system-level demonstrations of linear programmable nanophotonic processors in the silicon-on-insulator platform for applications in quantum and classical machine learning and information processing. Using our developed processor architecture, we then present a nanophotonic Ising sampler for noise-assisted combinatorial optimization. Subsequently, we present a novel, foundry-compatible platform for integrating telecommunication-wavelength artificial atom quantum emitters directly in silicon photonic circuits. Finally, we report a capacity analysis of a structured interferometric receiver implemented with a silicon photonic processor for detection of optical signals in photon-sparse communication links."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Large-scale programmable silicon photonics for quantum and classical machine learning"]}]}],"canonical_facts":{"dc:contributor.advisor":["Englund, Dirk R."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"],"dc:creator":["Prabhu, Mihika"],"dc:date.accessioned":["2023-03-31T14:40:09Z"],"dc:date.available":["2023-03-31T14:40:09Z"],"dc:date.issued":["2023-02"],"dc:description.abstract":["Photonic technologies provide many unique physical advantages including ultra-high bandwidths, energy-efficient operations, and low coupling to environmental noise. Furthermore, recent advances in foundry-based manufacturing platforms have enabled the emerging field of integrated systems photonics. In contrast to their bulk optics counterparts, these systems can co-integrate dense ensembles of active photonic and electronic components on a single wafer with high phase stability and small device footprints. Initial demonstrations of each element in the integrated photonics stack—sources, processors, and detectors—motivate the development of wafer-scale photonic integrated circuit implementations, which are poised to form a key building block for fundamental advancements in computing, communications, and sensing. The first part of this thesis will discuss the development and early system-level demonstrations of linear programmable nanophotonic processors in the silicon-on-insulator platform for applications in quantum and classical machine learning and information processing. Using our developed processor architecture, we then present a nanophotonic Ising sampler for noise-assisted combinatorial optimization. Subsequently, we present a novel, foundry-compatible platform for integrating telecommunication-wavelength artificial atom quantum emitters directly in silicon photonic circuits. Finally, we report a capacity analysis of a structured interferometric receiver implemented with a silicon photonic processor for detection of optical signals in photon-sparse communication links."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/150215"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"dc:rights.uri":["http://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Large-scale programmable silicon photonics for quantum and classical machine learning"],"dc:type":["Thesis"],"thesis:degree_name":["Doctoral","Doctor of Philosophy"]},"updated_at":"2026-07-22T22:21:50Z"}