Associate Professor Ng Hui Khoon obtained her Bachelors in Physics and Mathematics at Cornell University in 2002, under the support of a Defence Science and Technology Training Award from Singapore. She was awarded the Paul Hartman Prize from the University for her undergraduate work. She continued at Cornell to do a Masters in Applied Engineering Physics, during which she received the David Delano Clark Prize for Best Masters Thesis (Physics and Applied Physics). She then returned to Singapore to work at DSO National Laboratories for a year, before going for her PhD studies in Physics at the California Institute of Technology, under the generous support of a Betty and Gordon Moore Fellowship. Since her graduation in 2009, she has been holding joint appointments as a Research Fellow at the Centre for Quantum Technologies (CQT), National University of Singapore, and as a Senior Member of Technical Staff at DSO National Laboratories. She joined Yale-NUS in July 2013, and continues to hold a joint appointment at CQT as a CQT Fellow.
Assoc Prof Ng studies quantum systems for the purpose of quantum information processing. Her research interests centre around the question of noise and its effects on quantum information and quantum computation. Given the fragile nature of quantum phenomena, noise is the main stumbling block in any attempt at accessing and controlling quantum systems. She has worked on various aspects of quantum error correction and fault tolerance for noise control. Her recent focus has been on bridging the gap between in-principle theoretical fault-tolerance ideas and the practicalities of implementing those ideas in experiments.
Since joining the Centre for Quantum Technologies (CQT), she has also been working on quantum tomography – the estimation of the state of quantum systems and the characterisation of quantum processes. Quantum tomography is a primitive that underlies nearly all quantum tasks. In particular, Assoc Prof Ng likes to think about techniques that offer significant improvements when only a small amount of data is available, an often-encountered situation in quantum experiments.
JY Sim, J Suzuki, B-G Englert, and HK Ng, User-specified random sampling of quantum channels and its applications, arXiv:1905.00696 [quant-ph] (2019).
Y Gazit, HK Ng, and J Suzuki, Quantum process tomography via optimal design of experiments, arXiv:1904.11849 [quant-ph] (2019).
JY Sim, J Shang, HK Ng, and B-G Englert, Proper error bars for self-calibrating quantum tomography, arXiv:1904.11202 [quant-ph] (2019).
DJ Nott, M Seah, L Al-Labadi, M Evans, HK Ng, and B-G Englert, Using prior expansions for prior-data conflict checking, arXiv:1902.10393 [stat.ME] (2019).
J Qi and HK Ng, Comparing the randomized benchmarking figure with the average infidelity of a quantum gate-set, Int J Quant Inf 4, 1950031 (2019).
Y Quek, S Fort, and HK Ng, Adaptive Quantum State Tomography with Neural Networks, arXiv:1812.06693 [quant-ph] (2018).
B-G Englert, M Evans, GH Jang, HK Ng, DJ Nott, and Y-L Seah, Checking the Model and the Prior for the Constrained Multinomial, arXiv:1804:06906 (2018).
Scientific Inquiry 2
Theory of Quantum Information and Computation