We are a research group at the Centre for Quantum Technologies and the Department of Electrical and Computer Engineering at the National University of Singapore.
Our research
Our research interests lie in the intersection of information theory, computer science and quantum physics. The main focus is on the mathematical foundations of the theory of quantum information, for example the study of entropy and other information measures and their applications. A particular application area of our research are theoretical questions that arise in quantum communication and cryptography when the available resources are limited.
Information processing with finite resources
A challenge when engineering quantum processors is that complex quantum systems are notoriously hard to prepare and control. Thus, there will be limitations on the size and noise resilience of quantum computers for the foreseeable future. We investigate quantum information processing with noisy and limited resources.
For example, we analyse the fundamental limits that restrict information transmission between two parties that possess a small quantum device.
Cryptography in a quantum world
Securing information against potential adversaries is a ubiquitous challenge in our modern world, appearing in diverse guises such as sending private email and online commerce, among myriad others. Quantum cryptography studies secure information processing using quantum devices.
For example, we devise security proofs for cryptographic schemes — formal mathematical arguments that certify that the behavior of a given protocol is indeed secure.
Mathematical foundations of quantum information
New results on mathematical properties of information and correlation measures often have various applications beyond the specific ones that originally inspired the research. As such, progress in information theory often goes hand in hand with a more thorough understanding of the mathematical framework underlying it.
For example, we explore measures of entropy, information and correlation based on Rényi divergences.
Learning theory for quantum systems
Learning theory asks how much data, and how many measurements, are needed to learn the properties of an unknown system. We study these questions for quantum systems and also for classical data, aiming for procedures that are provably optimal and for matching limits on what any procedure can achieve.
For example, we design strategies for learning an unknown quantum state that make the fewest possible mistakes while learning, an idea borrowed from multi-armed bandits in classical machine learning.