Grant: Strategic Projects - Group
Institut national de la recherche scientifique
$190,700.00
Frequency domain nonlinear optical conversion for efficient high-dimensional quantum processing_x000d_ _x000d_ _x000d_
FY 2020-21
Summary
Industry and academia are working on creating new 'smart' services to enable applications such as self-driving cars, computer vision and medical diagnosis. These services depend on machine learning concepts for creating devices that can display intelligent behavior similar to humans. Reservoir comput(ing/ers) (RC) is a new approach that works in a fundamentally different way from electronic processors in laptops/smartphones. Making use of system dynamics, RCs can be trained to recognize and give specific outputs in response to different input signals. This allows them to act as analog computers that can perform tasks such as signal classification, time-series prediction and audio/visual recognition. The goal of this project is to develop a novel type of compact and energy-efficient optical RC platform, utilizing the nonlinear dynamics of microresonator frequency combs, and capable of processing data at the speed of light. Our research team will, together with our three industrial partners (TeraXion, 'E' Machine Learning and Novacam Technologies): (i) exploit RC for high-speed data restoration and noiseless amplification. Additionally, we will (ii) apply RC for processing in an inexpensive light detection and ranging (LIDAR) system. Lastly, we will (iii) apply our platform to real-time optical coherence tomography (OCT), which is a computationally-demanding imaging technique used in, e.g., retinal profiling and surgical guidance. The project will contribute to the long-term vision of incorporating machine-learning methods into optical signal processing systems. This in turn will allow ultrafast computation at unprecedented data rates (~1 THz) using photonic chips, directly compatible with smart sensors and the emerging Internet of Things. The project will also benefit the Canadian workforce, via the training of highly-qualified personnel with multidisciplinary expertise in optics research, multimedia processing and machine learning. The commercialization of our technology will promote the growth of Canadian industries, across numerous high-tech sectors such as telecommunications, health and human-machine interaction.
Program
Strategic Projects - Group
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
521496-2018
Name nom
Morandotti, Roberto
Department département
Énergie Matériaux Télécommunications, Centre - Varennes
Organization id
56
Institution établissement
Institut national de la recherche scientifique
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2018
Award amount
190700
Program id
STPGP
Program name en
Strategic Projects - Group
Program name fr
Projets stratégiques - De groupe
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1588
Committee name en
Strategic Projects - ICT
Committee name fr
Projets stratégiques - ICT
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
3112
Research subject group en
Physics
Research subject group fr
Physique
Research subject en
Photonics
Research subject fr
Photonique
Installment
inst:3 - 3
Partie
1
Nb partie
3
Application title
Frequency domain nonlinear optical conversion for efficient high-dimensional quantum processing_x000d_
_x000d_
_x000d_
Keyword
NSERC
Application summary
Industry and academia are working on creating new 'smart' services to enable applications such as self-driving cars, computer vision and medical diagnosis. These services depend on machine learning concepts for creating devices that can display intelligent behavior similar to humans. Reservoir comput(ing/ers) (RC) is a new approach that works in a fundamentally different way from electronic processors in laptops/smartphones. Making use of system dynamics, RCs can be trained to recognize and give specific outputs in response to different input signals. This allows them to act as analog computers that can perform tasks such as signal classification, time-series prediction and audio/visual recognition. The goal of this project is to develop a novel type of compact and energy-efficient optical RC platform, utilizing the nonlinear dynamics of microresonator frequency combs, and capable of processing data at the speed of light. Our research team will, together with our three industrial partners (TeraXion, 'E' Machine Learning and Novacam Technologies): (i) exploit RC for high-speed data restoration and noiseless amplification. Additionally, we will (ii) apply RC for processing in an inexpensive light detection and ranging (LIDAR) system. Lastly, we will (iii) apply our platform to real-time optical coherence tomography (OCT), which is a computationally-demanding imaging technique used in, e.g., retinal profiling and surgical guidance. The project will contribute to the long-term vision of incorporating machine-learning methods into optical signal processing systems. This in turn will allow ultrafast computation at unprecedented data rates (~1 THz) using photonic chips, directly compatible with smart sensors and the emerging Internet of Things. The project will also benefit the Canadian workforce, via the training of highly-qualified personnel with multidisciplinary expertise in optics research, multimedia processing and machine learning. The commercialization of our technology will promote the growth of Canadian industries, across numerous high-tech sectors such as telecommunications, health and human-machine interaction.