Data for "Emulating two qubits with a four-level transmon qudit for variational quantum algorithms"

University of Oxford (2024)

Abstract:

Data for "Emulating two qubits with a four-level transmon qudit for variational quantum algorithms"

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

University of Oxford (2024)

Abstract:

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

The Singlet: Direct Synthesis of Pseudo-Elliptic Inline Filters With Frequency Variant Couplings

IEEE Transactions on Microwave Theory and Techniques Institute of Electrical and Electronics Engineers (IEEE) 71:11 (2023) 4969-4981

Authors:

Evaristo Musonda, Mustafa S Bakr

Multi-agent blind quantum computation without universal cluster states

New Journal of Physics IOP Publishing 25:10 (2023) 103028

Abstract:

Blind quantum computation (BQC) protocols enable quantum algorithms to be executed on third-party quantum agents while keeping the data and algorithm confidential. The previous proposals for measurement-based BQC require preparing a highly entangled cluster state. In this paper, we show that such a requirement is not necessary. Our protocol only requires pre-shared Bell pairs between delegated quantum agents, and there is no requirement for any classical or quantum information exchange between agents during the execution. Our proposal requires fewer quantum resources than previous proposals by eliminating the need for a universal cluster state.

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

(2023)

Authors:

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