| PROJECT: | Neuromorphic quantum-inspired computing | |||||
| ACRONYM: | NeuroQIC | |||||
| MAIN OBJECTIVE: | This research proposal aims at addressing fundamental aspects of computation, by connecting quantum computation, machine learning, and neuromorphic computing. In essence, we will take inspiration from both quantum mechanics and neuroscience to develop new algorithms for tasks such as pattern recognition. The algorithms will require a new form of hardware implementation, which will be designed in the span of this research project.
The objectives include formulating a quantum-inspired neural network, based on the problem of quantum state discrimination, for but not limited to pattern recognition. Several variants of such algorithms will be considered, and their benefits for different types of data will be assessed. The algorithms will be designed in view of all-optical or optoelectronic implementations. Concrete proposals for hardware implementation will be provided as output of this project. This work will pave the way for a new type of analog optical processor designed to solve machine learning tasks. |
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| Reference: | 2024.14769.CMU | |||||
| Funding: | Fundação para a Ciência e a Tecnologia | |||||
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| Team: | Emmanuel Zambrini Cruzeiro, Preeti Yadav, Elias Towe | |||||
| Groups: | Physics of Information and Quantum Technologies - Lx | |||||
| Partners: | CMU | |||||
| Local Coordinator: | Emmanuel Zambrini Cruzeiro |
This project falls under the following United Nations Strategic Development Goals (SDGs):
No publications associated with this project.