
Ng Hui Khoon
Hui Khoon Ng did her undergraduate studies in Cornell University, and completed her PhD in the group of John Preskill at Caltech. Upon graduation, she returned to Singapore to join the DSO National Laboratories, spending part of her time at CQT in the group of Berge Englert. In 2013, she joined the faculty of the then-new Yale-NUS College (a liberal arts and sciences college set up by Yale and NUS), while maintaining a joint appointment at CQT. Her research focuses on theoretical aspects of quantum computation, particularly on noise control, quantum error correction, and fault tolerance. She currently heads up the Science Division in Yale-NUS, and is the Deputy Director (NUS) for MajuLab, a French CNRS quantum science lab situated in Singapore. She is also Senior Scientific Advisor to Entropica Labs, a quantum startup in Singapore focusing on error correction and fault-tolerant quantum computing.
Preprints & Publications
Magic states are rarely the most important resource to optimize
Fault-tolerant embedding of quantum circuits on hardware architectures via swap gates
Circuit-level fault tolerance of cat codes
High-Fidelity CZ Gates in Double Quantum Dot — Circuit QED Systems Beyond the Rotating-Wave Approximation
Optimizing resource efficiencies for scalable full-stack quantum computers
Efficacy of noisy dynamical decoupling
Achieving fault tolerance against amplitude-damping noise
Checking the Model and the Prior for the Constrained Multinomial
Adaptive Quantum State Tomography with Neural Networks
Using prior expansions for prior-data conflict checking
Randomized benchmarking in the presence of time-correlated dephasing noise
Limitations in quantum computing from resource constraints
Randomized linear gate set tomography
User-specified random sampling of quantum channels and its applications
Finding good codes using the Cartan form
Direct estimation of minimum gate fidelity
Randomized benchmarking does not measure average infidelity of gates
Proper error bars for self-calibrating quantum tomography
Quantum process tomography via optimal design of experiments
Open-System Quantum Error Correction
Superfast maximum likelihood reconstruction for quantum tomography
Past of a quantum particle revisited
Airy-averaged gradient corrections for two-dimensional fermion gases
Digital quantum simulator in the presence of a bath
Implementing a neutral-atom controlled-phase gate with a single Rydberg pulse
Leading gradient correction to the kinetic energy for two-dimensional fermion gases
Initial system-bath state via the maximum-entropy principle
Optimal error intervals for properties of the quantum state
Monte Carlo sampling from the quantum state space. I
Monte Carlo sampling from the quantum state space. II
Least-bias state estimation with incomplete unbiased measurements
Raman transitions: Adiabatic elimination revisited
Raman transitions without adiabatic elimination: A simple and accurate treatment
One-dimensional transport revisited: A simple and exact solution for phase disorder
Optimal error regions for quantum state estimation
Minimax mean estimator for the trine
A simple minimax estimator for quantum states
Towards a Unified Framework for Approximate Quantum Error Correction
Combining dynamical decoupling with fault-tolerant quantum computation
Information preserving structures: A general framework for quantum zero-error information
Simple approach to approximate quantum error correction based on the transpose channel
Fault-tolerant quantum computation versus Gaussian noise
Characterizing the structure of preserved information in quantum processes
Single-Loop Interferometer for Minimal Ellipsometry
Quantum state tomography: Mean squared error matters, bias does not
Random samples of quantum states: Online resources
Uncorrelated problem-specific samples of quantum states from zero-mean Wishart distributions