Dr Mustafa Bakr

Quantum Technology Research Fellow at the Department of Physics, and a lecturer in Physics at St Johns and LMH Colleges. My research focuses on addressing scalability challenges in superconducting quantum computing. I lead a team of PhD students and PDRAs, including Mohammed Alghadeer (DPhil student) and Dr. Shuxiang Cao. Alumni from my group include Dr. Sajjad Taravati and Maria Dinca.

N/A

Research interests

quantum computing

Selected publications

Encoding optimization for quantum machine learning demonstrated on a superconducting transmon qutrit

Quantum Science and Technology IOP Publishing 9:4 (2024) 045037

Shuxiang Cao, Weixi Zhang, Jules Tilly, Abhishek Agarwal, Mustafa Bakr, Giulio Campanaro, Simone Diego Fasciati, James Wills, Boris Shteynas, Vivek Chidambaram, Peter J Leek, Ivan Rungger

High coherence and low cross-talk in a tileable 3D integrated superconducting circuit architecture.

Science advances 8:16 (2022) eabl6698

Peter A Spring, Shuxiang Cao, Takahiro Tsunoda, Giulio Campanaro, Simone Fasciati, James Wills, Mustafa Bakr, Vivek Chidambaram, Boris Shteynas, Lewis Carpenter, Paul Gow, James Gates, Brian Vlastakis, Peter J Leek

Superconducting qubit readout enhanced by path signature

(2024)

Shuxiang Cao, Zhen Shao, Jian-Qing Zheng, Mohammed Alghadeer, Simone D Fasciati, Michele Piscitelli, Peter A Spring, Shiyu Wang, Shuhei Tamate, Neel Vora, Yilun Xu, Gang Huang, Kasra Nowrouzi, Yasunobu Nakamura, Irfan Siddiqi, Peter Leek, Terry Lyons, Mustafa Bakr

Investigation of Stored Energy Distribution in Filters Using K-Means Clustering Algorithm

Institute of Electrical and Electronics Engineers (IEEE) 00 (2019) 396-399

Rucha A Paradkar, Ian C Hunter, Nutapong Somjit, Evaristo Musonda, Richard Parry, Mustafa S Bakr

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Dr Mustafa Bakr

Research theme

Sub department

Research interests

Selected publications

Encoding optimization for quantum machine learning demonstrated on a superconducting transmon qutrit

High coherence and low cross-talk in a tileable 3D integrated superconducting circuit architecture.

Superconducting qubit readout enhanced by path signature

Investigation of Stored Energy Distribution in Filters Using K-Means Clustering Algorithm

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Dr Mustafa Bakr

Research theme

Sub department

Research groups

Research interests

Selected publications

Encoding optimization for quantum machine learning demonstrated on a superconducting transmon qutrit

High coherence and low cross-talk in a tileable 3D integrated superconducting circuit architecture.

Superconducting qubit readout enhanced by path signature

Investigation of Stored Energy Distribution in Filters Using K-Means Clustering Algorithm