Research focus

Noise and its control in quantum computing systems

After more than two decades of working towards building a computer based on quantum mechanical principles, a basic obstacle remains: noise. Noise-suppression techniques have shown encouraging progress over the years, but the noise threshold below which useful, reliable computation can be accomplished is still far from attainable. We seek better understanding of the physical nature of the noise affecting quantum information processing (QIP) tasks beyond the naive quantum-channel description, and examine the efficacy of error correction and fault-tolerant schemes for different types of noise, different practical QIP tasks, and in different physical implementations of quantum computing components. Of particular recent interest is the goal of bringing the ideas of quantum error correction and fault tolerance from abstract theory towards actual realisation in near-term quantum devices, and to examine the practical resource costs of doing error correction for large-scale reliable quantum computation.

Limitations to quantum computing from resource constraints [from Fellous-Asiani et al. PRX Quantum 2, 040335 (2021)].

This direction of research is supported by a CQT Fellowship, a Tier-2 grant (Ministry of Education Singapore), and an NRF-ANR Singapore-France joint grant.

Relevant publications:

Selected past works of relevance:

  • YL Len and  HK Ng, Open-system quantum error correction, Phys Rev A 98, 022307 (2018); arXiv:1804:09486.
  • HK Ng, DA Lidar, and J Preskill, Combining dynamical decoupling with fault-tolerant quantum computation, Phys Rev A 84, 012305 (2011).
  • HK Ng and P Mandayam, Simple approach to approximate quantum error correction based on the transpose channel, Phys Rev A 81, 062342 (2010).
  • HK Ng and J Preskill, Fault-tolerant quantum computation versus Gaussian noise, Phys Rev A 79, 032318 (2009).


Estimating relevant noise parameters

An essential input to effective noise-suppression strategies is the nature of the noise that afflicts the quantum system. Here, we seek to advance methods for the practical characterization of noise in quantum systems, through better use of limited data from resource-expensive standard process tomography, as well as direct measurements of noise parameters relevant for high-fidelity QIP tasks.

Adaptive quantum tomography aided by neural networks [from Quek et al., arXiv:1812.06693]

Selected works: