Silicon Photonic Programmable Optical Processors for Machine Learning and Optical Quantum Computing

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Abstract. Programmable optical processors are promising structures for ultrafast and energy efficient computation in classic and quantum photonics. These processors efficiently perform the vector-matrix multiplication extensively used in artificial intelligence and machine learning tasks. Due to the inherent parallelism presents in optics in contrast with sequential operations in electronics, optical processors offer better energy efficiency compared to their electronic counterparts. Today, deep learning is facing growing computational demand limiting its development if we continue using conventional electronic processors. Energy efficient computational accelerators fabricated in silicon photonic are candidates to meet the computational demands of future machine learning and deep learning tasks. 

Programmable optical processors also pave the way for integrated optical quantum computing. Single photons are excellent candidates for quantum computing due to their noise and decoherence-free nature. One can generate optical qubits by encoding single photons in one degree of freedom such as polarization or path. Optical integrated quantum computing requires quantum logic gates to manipulate these qubits. Quantum logic gates are represented by unitary matrices, such that a 2n × 2n unitary matrix multiplication is identical to an n-qubit gate. Therefore, a programmable optical processor capable of performing unitary matrix multiplication on single photons works as an arbitrary optical integrated quantum gate.



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  • Date: 07 Apr 2022
  • Time: 01:00 PM to 02:30 PM
  • All times are (GMT-05:00) Canada/Eastern
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This is an in-person event. All attendees must be registered to the event and must perform the following COVID self-evaluation before coming on campus: https://www.mcgill.ca/coronavirus/self-evaluation-form).

 

  • McGill University
  • 3630 University Street
  • Montreal, Quebec
  • Canada
  • Building: Lorne M. Trottier Engineering Building
  • Room Number: TR0070
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  • Starts 01 April 2022 05:34 AM
  • Ends 07 April 2022 12:00 PM
  • All times are (GMT-05:00) Canada/Eastern
  • No Admission Charge


  Speakers

Dr. Kaveh Mojaver Dr. Kaveh Mojaver of McGill University

Topic:

Silicon Photonic Programmable Optical Processors for Machine Learning and Optical Quantum Computing

Abstract. Programmable optical processors are promising structures for ultrafast and energy efficient computation in classic and quantum photonics. These processors efficiently perform the vector-matrix multiplication extensively used in artificial intelligence and machine learning tasks. Due to the inherent parallelism presents in optics in contrast with sequential operations in electronics, optical  energy efficiency compared to their electronic counterparts. Today, deep learning is facing growing computational demand limiting its development if we continue using conventional electronic processors. Energy efficient computational accelerators fabricated in silicon photonic are candidates to meet the computational demands of future machine learning and deep learning tasks. 

Programmable optical processors also pave the way for integrated optical quantum computing. Single photons are excellent candidates for quantum computing due to their noise and decoherence-free nature. One can generate optical qubits by encoding single photons in one degree of freedom such as polarization or path. Optical integrated quantum computing requires quantum logic gates to manipulate these qubits. Quantum logic gates are represented by unitary matrices, such that a 2n × 2n unitary matrix multiplication is identical to an n-qubit gate. Therefore, a programmable optical processor capable of performing unitary matrix multiplication on single photons works as an arbitrary optical integrated quantum gate.

Biography:

Kaveh Rahbardar Mojaver was born in Iran in 1986. He received the B.S. and M.S. degrees from Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran, in 2009 and 2011, respectively, and the Ph.D. degree from Concordia University in 2018, all in electrical engineering. In May 2018 he joined the Photonic Systems Group of McGill University as a postdoctoral researcher, where he is currently pursuing his career. His research is focused on photonic integration for data communications, programmable optical processors, mode-division-multiplexing in silicon photonics, and wide bandgap semiconductors.

During 2009-2011, he was with the Photonics Research Laboratory of Tehran Polytechnic as a graduate research assistant where he did his master thesis on modeling of Transistor Lasers. From 2011 to 2013, he was the part-time faculty member at Tehran Azad University. From January 2014 to April 2018, he was with the Reliable Electron Device Laboratory of Concordia University as a PhD research assistant where he was conducting his research on micro-fabrication and physics-based modeling of III-nitride heterojunction field-effect transistors.

Dr. Mojaver’s research works have been published in several journal and conference publications. He has received the Fonds de Recherche du Québec - Nature et technologies (FRQNT) postdoctoral scholarship, Concordia Merit scholarship, Concordia Accelerator Award, and STARaCom scholarship.