Outmaneuvering correlated noise in quantum computers. The project aims to characterise and control quantum machines available today. These machines overwhelmingly suffer from noise with complex structures. Thus, a key target of the project is to develop a theory to describe and manipulate complex quantum processes. The project then intends to apply this theory to commercial-grade quantum computers. This approach is anticipated to lead to a new understanding of time-correlated complex quantum pro ....Outmaneuvering correlated noise in quantum computers. The project aims to characterise and control quantum machines available today. These machines overwhelmingly suffer from noise with complex structures. Thus, a key target of the project is to develop a theory to describe and manipulate complex quantum processes. The project then intends to apply this theory to commercial-grade quantum computers. This approach is anticipated to lead to a new understanding of time-correlated complex quantum processes and develop methods to enhance the performance of today's quantum computers. Noise characterisation and mitigation should have commercial value and benefit research groups working to develop quantum technologies, both in Australia and internationally.Read moreRead less
Quantum measurement as a resource. Advanced quantum computers will use modular measurements significantly enhancing their capabilities. However, due to the noisy environment, the measurements may have nontrivial effects on the computation. Making best use of realistic (hence imperfect) measurements is a challenging problem that hinders the development of these technologies. This project, using modern tools of resource theory, aims to design optimal realistic measurement procedures for near-term ....Quantum measurement as a resource. Advanced quantum computers will use modular measurements significantly enhancing their capabilities. However, due to the noisy environment, the measurements may have nontrivial effects on the computation. Making best use of realistic (hence imperfect) measurements is a challenging problem that hinders the development of these technologies. This project, using modern tools of resource theory, aims to design optimal realistic measurement procedures for near-term noisy quantum devices. The expected outcomes of the project are refined methods to optimise quantum measurements in today's rudimentary quantum machines. This will provide a significant benefit to the Australian community, advancing the development of disruptive quantum technologies.Read moreRead less
Gravity and quantum-limited measurements with a fundamental minimum length. This project aims to investigate the effects of a fundamental minimum length on the nature of gravity and on how accurately we can make measurements in our world. The key challenge is to combine our best theories of fundamental physics to model what happens at ultra-short distances. This project will generate new knowledge at this interface by using a novel approach inspired by information theory. The expected outcomes a ....Gravity and quantum-limited measurements with a fundamental minimum length. This project aims to investigate the effects of a fundamental minimum length on the nature of gravity and on how accurately we can make measurements in our world. The key challenge is to combine our best theories of fundamental physics to model what happens at ultra-short distances. This project will generate new knowledge at this interface by using a novel approach inspired by information theory. The expected outcomes are new connections between fundamental limitations on measurements, the nature of gravitation, and ultra-small-scale quantum physics. The benefit of this work is breaking the logjam in answering the most important open question in all of physics: how to unite quantum theory and gravitation.Read moreRead less
Superconducting silicon nanodevices. This project will investigate superconductivity in silicon nanowire devices exhibiting both p-type and n-type conductivity. It builds on the recent demonstration at the University of Melbourne of superconductivity in nanowire devices at length-scales suitable for realisation of a broad range of superconducting device structures and utilises standard semiconductor-industry processes. This project will create a new platform for superconducting device developmen ....Superconducting silicon nanodevices. This project will investigate superconductivity in silicon nanowire devices exhibiting both p-type and n-type conductivity. It builds on the recent demonstration at the University of Melbourne of superconductivity in nanowire devices at length-scales suitable for realisation of a broad range of superconducting device structures and utilises standard semiconductor-industry processes. This project will create a new platform for superconducting device development in silicon with potential for building devices with new functionality and improved performance for applications in quantum information technologies, enhancing Australia’s global reputation in quantum information science and assisting emerging industries in this high-valued added area.Read moreRead less
Complete blood fractionation using a low-cost microfluidic system. This project aims to understand particle focusing in inertial microfluidic systems to design efficient devices for cell sorting. The field of microfluidics could ultimately advance medical research but device design is primitive. Microfluidic particle separations are not thoroughly simulated before fabrication to predict performance. This project is expected to accelerate progress in design of efficient microfluidic devices. The ....Complete blood fractionation using a low-cost microfluidic system. This project aims to understand particle focusing in inertial microfluidic systems to design efficient devices for cell sorting. The field of microfluidics could ultimately advance medical research but device design is primitive. Microfluidic particle separations are not thoroughly simulated before fabrication to predict performance. This project is expected to accelerate progress in design of efficient microfluidic devices. The knowledge and models developed in this project should help design and develop a microfluidic device for efficient fractionation of complex fluids into valuable components.Read moreRead less
Crossing quantum-classical boundaries in a single particle. This project is aimed at constructing and observing an individual quantum system that can exhibit chaotic behaviour under controllable conditions. It is a long-sought goal of modern physics that can become reality for the first time in the world, thanks to the unique availability in Australia of the most quantum-coherent single spin ever made and a long history of theoretical advances in the field. Turning a spin into a chaotic system w ....Crossing quantum-classical boundaries in a single particle. This project is aimed at constructing and observing an individual quantum system that can exhibit chaotic behaviour under controllable conditions. It is a long-sought goal of modern physics that can become reality for the first time in the world, thanks to the unique availability in Australia of the most quantum-coherent single spin ever made and a long history of theoretical advances in the field. Turning a spin into a chaotic system will uncover the true nature of the quantum-classical boundary, and verify whether an underlying classical chaotic dynamics ultimately influences the behaviour of quantum systems. It is expected that the discoveries made will illuminate the path towards the technological exploitation of increasingly complex quantum devices.Read moreRead less
Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowled ....Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowledge and an approach to fast-adapt bilevel optimization solutions when required computing resources change. The anticipated outcomes should significantly improve the reliability of ML with benefits for safety learning and computing resource optimisation in ML-based data analytics.Read moreRead less
Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis f ....Non-invasive prediction of adverse neural events using brain wave activity. This project aims to develop intelligent decision-making systems for non-invasive identification of adverse neural events (fatigue/freezing of gait) through real-time monitoring of brain wave activity. Analyses of the effectiveness of the changes in physiological parameters associated with electroencephalography (EEG) signals, advanced biomedical instrumentation, and optimal computational intelligence will form a basis for the development of platform technology capable of monitoring and detection of neural health status. Success is expected to yield a new generation of smart dynamic non-invasive systems that will be critical for developing effective solutions to counter life threating conditions for a large cross section of the Australian population.Read moreRead less
Long-term Cloud Service Composition. This project proposes an economic model-based framework for the selection and composition of cloud services, thus creating an efficient market for cloud consumers and providers. The project will use economic models that incorporate a range of quality of service (QoS) parameters as a key driver for optimising the selection of cloud services and the acceptance of consumer requests. The main outcomes of this project aim to increase efficiencies in the cloud mark ....Long-term Cloud Service Composition. This project proposes an economic model-based framework for the selection and composition of cloud services, thus creating an efficient market for cloud consumers and providers. The project will use economic models that incorporate a range of quality of service (QoS) parameters as a key driver for optimising the selection of cloud services and the acceptance of consumer requests. The main outcomes of this project aim to increase efficiencies in the cloud market, benefiting consumers and providers.Read moreRead less
Accelerated Finite-time Learning and Control in Cyber-Physical Systems. Efficient learning and control in cyber-physical systems such as smart grids and robotic systems are very important for achieving economic and social benefits. This project aims to establish a breakthrough accelerated finite-time dynamics theory and technology to assist in delivering efficient learning and control. Expected outcomes include new distributed accelerated finite-time dynamics based learning and control algorithm ....Accelerated Finite-time Learning and Control in Cyber-Physical Systems. Efficient learning and control in cyber-physical systems such as smart grids and robotic systems are very important for achieving economic and social benefits. This project aims to establish a breakthrough accelerated finite-time dynamics theory and technology to assist in delivering efficient learning and control. Expected outcomes include new distributed accelerated finite-time dynamics based learning and control algorithms and tools for optimal operations in cyber-physical systems. This should provide significant benefits including a practical technology for industry applications in smart grids and robotic systems, and training of the next generation engineers in this technology for Australia.Read moreRead less