Universal quantum imaging. This project will integrate quantum technology with the rapidly advancing techniques of spatial light modulation utilised in LCD displays and video projectors. We will develop, for the first time, broadly versatile imaging technology based on quantum mechanics, enabling both important applications in future medical diagnostic devices and communication systems; and fundamental advances in the biological and quantum sciences. Quantum technologies offer the promise to rev ....Universal quantum imaging. This project will integrate quantum technology with the rapidly advancing techniques of spatial light modulation utilised in LCD displays and video projectors. We will develop, for the first time, broadly versatile imaging technology based on quantum mechanics, enabling both important applications in future medical diagnostic devices and communication systems; and fundamental advances in the biological and quantum sciences. Quantum technologies offer the promise to revolutionise many aspects of modern life, from computing and communications, to medical imaging and metrology. This project will put Australia at the international forefront of quantum imaging, enhancing Australia's already significant international presence in the area.Read moreRead less
Quantum-Inspired Machine Learning. This project aims to develop new machine learning techniques based around the close correspondence between
neural networks used in deep learning, and tensor networks used in quantum physics. Tensor networks are a form of information compression that is useful in machine learning to construct a compact representation of a large data set in a way that is more amenable to understanding the internal structure than a deep neural network. Expected outcomes of this pr ....Quantum-Inspired Machine Learning. This project aims to develop new machine learning techniques based around the close correspondence between
neural networks used in deep learning, and tensor networks used in quantum physics. Tensor networks are a form of information compression that is useful in machine learning to construct a compact representation of a large data set in a way that is more amenable to understanding the internal structure than a deep neural network. Expected outcomes of this project include more resilient algorithms for machine learning, and new ways to represent quantum states that will impact fundamental physics. The resulting benefits include enhanced capacity for cross-discipline collaboration, and improved methods for future industrial applications.
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