Discovery Early Career Researcher Award - Grant ID: DE240101033
Funder
Australian Research Council
Funding Amount
$449,744.00
Summary
Superconducting Circuits for Error-Resilient Quantum Computers . This project aims to build a new class of intrinsically error-resilient quantum bits, harnessing the power of superconducting and hybrid superconducting circuits. The core goal of this research is to improve the performance of modern quantum processors, in order to reap the benefits of their vast computational power in real world applications like cryptography, chemistry, machine learning and finance. The outcomes of this project a ....Superconducting Circuits for Error-Resilient Quantum Computers . This project aims to build a new class of intrinsically error-resilient quantum bits, harnessing the power of superconducting and hybrid superconducting circuits. The core goal of this research is to improve the performance of modern quantum processors, in order to reap the benefits of their vast computational power in real world applications like cryptography, chemistry, machine learning and finance. The outcomes of this project are expected to accelerate quantum computing efforts globally and generate critical insights into quantum circuit technology, thus expanding Australia’s capabilities in nanotechnology, superconducting quantum systems and quantum processing. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101329
Funder
Australian Research Council
Funding Amount
$432,355.00
Summary
Trading Privacy, Bandwidth and Accuracy in Algorithmic Machine Learning. This project aims to investigate the trade-offs between privacy, communication costs and accuracy of results when learning from users' sensitive data. The project intends to design faster and more accurate algorithms for a wide range of machine learning tasks by developing a novel and widely-applicable algorithmic framework. Expected outcomes of this project include new theoretical tools to guide the design of data-driven d ....Trading Privacy, Bandwidth and Accuracy in Algorithmic Machine Learning. This project aims to investigate the trade-offs between privacy, communication costs and accuracy of results when learning from users' sensitive data. The project intends to design faster and more accurate algorithms for a wide range of machine learning tasks by developing a novel and widely-applicable algorithmic framework. Expected outcomes of this project include new theoretical tools to guide the design of data-driven decision systems and rigorously analyse their performance and privacy guarantees. Privacy of individuals' information in data analytics pipelines is a key societal concern. This project should lead to significant benefits by strengthening privacy in these pipelines while also improving accuracy and cost-efficiency.Read moreRead less
Reconciliation strategies for continuous variable quantum key distribution. This project aims to advance a novel key distribution method, called quantum key distribution, which distributes secure keys using the quantum state of optical channels. Key distribution is a foundational part of data security, allowing digital keys to be securely exchanged between two or more parties, before they are used to protect and share information. The expected outcome is new rateless error correction codes desi ....Reconciliation strategies for continuous variable quantum key distribution. This project aims to advance a novel key distribution method, called quantum key distribution, which distributes secure keys using the quantum state of optical channels. Key distribution is a foundational part of data security, allowing digital keys to be securely exchanged between two or more parties, before they are used to protect and share information. The expected outcome is new rateless error correction codes designed specifically to implement quantum key distribution over long distances. Quantum key distribution is beneficial for ultra-secure communications as it avoids the vulnerability to weak random numbers and quantum-computing brute force attacks that currently threated the security of data protected by existing methods. Read moreRead less
Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric ....Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric graphs, which both advances the knowledge in this field of computer science and make our existing networks more reliable. This should provide significant benefits in the maintenance and utilisation of the communication and transport networks we use every day.Read moreRead less