Overview
Background
I bring industry and academic experience in working on quantum error mitigation, quantum error correction, and quantum control theory to enable quantum computing demonstrations on near-term hardware. I am currently investigating the feasibility of combining error mitigation and error correction techniques with quantum machine learning algorithms at the University of Queensland. With Sally Shrapnel and partnering with the Queensland Digital Health Center (QDHeC), we are analysing the operational robustness of quantum machine learning, with an eye to digital health use-case discovery and testing. Prior to this, I worked on execution of dynamic circuits for error mitigation and quantum error correction applications at IBM Quantum (US) for three years. My work resulted in 3 patents and being recognised as one of IBM Research’s Top Technical Contributors in 2023 globally. I have also designed classical algorithms for noise filtering and prediction for trapped ions at the Quantum Control Laboratory in the University of Sydney, winning ARC EQUS inaugural Director’s Medal in Australia in 2019.
Availability
- Dr Riddhi Gupta is:
- Available for supervision
Fields of research
Qualifications
- Bachelor, University of Auckland New Zealand
- Bachelor (Honours) of Physics, University of Auckland New Zealand
- Doctoral (Research), The University of Sydney
- Journal Peer-Reviewer, American Physical Society, American Physical Society
Research interests
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Noise characterization and error mitigation for QML algorithms
Contemporary quantum computing hardware is subject to challenging noise environments. Well established techniques exist for noise characterization, and using information about the learned noise environment to improve the performance of quantum computing algorithms. We explore the efficacy and scalability of these techniques in regimes which violate underlying assumptions, e.g. about the noise process, or the properties of the quantum algorithm itself. Our goal is to use these insights to help scale-up quantum algorithms to intermediate scales on hardware, with a specific focus on quantum machine learning applications.
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Error correcting overhead for QML algorithms
Until recently, error correction demonstrations had not surpassed the O(10)-qubit scale. We explore the compatibility of error correction techniques with quantum algorithms such as QML applications. We turn to the question of how errors propagate in quantum algorithms, and what these insights suggest about efficient encoding schemes and decoding strategies for partial or fully error-corrected implementations of quantum algorithms, with a specific focus on quantum machine learning applications.
Works
Search Professor Riddhi Gupta’s works on UQ eSpace
2024
Journal Article
Probabilistic error cancellation for dynamic quantum circuits
Gupta, Riddhi S., van den Berg, Ewout, Takita, Maika, Riste, Diego, Temme, Kristan and Kandala, Abhinav (2024). Probabilistic error cancellation for dynamic quantum circuits. Physical Review A, 109 (6) 062617, 1-13. doi: 10.1103/physreva.109.062617
2024
Journal Article
Encoding a magic state with beyond break-even fidelity
Gupta, Riddhi S., Sundaresan, Neereja, Alexander, Thomas, Wood, Christopher J., Merkel, Seth T., Healy, Michael B., Hillenbrand, Marius, Jochym-O'Connor, Tomas, Wootton, James R., Yoder, Theodore J., Cross, Andrew W., Takita, Maika and Brown, Benjamin J. (2024). Encoding a magic state with beyond break-even fidelity. Nature, 625 (7994), 1-24. doi: 10.1038/s41586-023-06846-3
2021
Journal Article
Adaptive filtering of projective quantum measurements using discrete stochastic methods
Gupta, Riddhi Swaroop and Biercuk, Michael J. (2021). Adaptive filtering of projective quantum measurements using discrete stochastic methods. Physical Review A, 104 (1) 012412, 1-12. doi: 10.1103/physreva.104.012412
2020
Journal Article
Integration of spectator qubits into quantum computer architectures for hardware tune-up and calibration
Gupta, Riddhi Swaroop, Govia, Luke C. G. and Biercuk, Michael J. (2020). Integration of spectator qubits into quantum computer architectures for hardware tune-up and calibration. Physical Review A, 102 (4) 042611, 1-13. doi: 10.1103/physreva.102.042611
2020
Journal Article
Adaptive characterization of spatially inhomogeneous fields and errors in qubit registers
Gupta, Riddhi Swaroop, Edmunds, Claire L., Milne, Alistair R., Hempel, Cornelius and Biercuk, Michael J. (2020). Adaptive characterization of spatially inhomogeneous fields and errors in qubit registers. npj Quantum Information, 6 (1) 53, 1-10. doi: 10.1038/s41534-020-0286-0
2018
Journal Article
Machine Learning for Predictive Estimation of Qubit Dynamics Subject to Dephasing
Gupta, Riddhi Swaroop and Biercuk, Michael J. (2018). Machine Learning for Predictive Estimation of Qubit Dynamics Subject to Dephasing. Physical Review Applied, 9 (6) 064042, 1-32. doi: 10.1103/physrevapplied.9.064042
Funding
Current funding
Supervision
Availability
- Dr Riddhi Gupta is:
- Available for supervision
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Supervision history
Current supervision
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Doctor Philosophy
Characterising the impact of noise in quantum machine learning.
Associate Advisor
Other advisors: Associate Professor Sally Shrapnel
Media
Enquiries
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