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Mr. Tyler Jones

Tyler moved to Brisbane in 2015 to study a Bachelor of Advanced Science majoring in physics at UQ. He became interested in conducting his honours research in the field of superconducting qubits and decided to pursue an opportunity with the SQD lab. He completed a project investigating the effects of inducing rapid qubit dynamics during measurement in 2018. He joined the lab as as PhD student in 2020 to continue his research in superconducting quantum circuits. 


Jones Tyler et al, 2021
Physical Review Applied, 16, 054039

Classical simulations of time-dependent quantum systems are widely used in quantum control research. In particular, these simulations are commonly used to host iterative optimal control algorithms.

Navarathna Rohit et al, 2021
Applied Physics Letters

Neural networks have proven to be efficient for a number of practical applications ranging from image recognition to identifying phase transitions in quantum physics models.


Szombati D. et al, 2020
Phys. Rev. Lett, 124, pp. 70401

Quantum mechanics postulates that measuring the qubit's wave function results in its collapse, with the recorded discrete outcome designating the particular eigenstate the qubit collapsed into. We show this picture breaks down when the qubit is strongly driven during measurement. More specifically, for a fast evolving qubit the measurement returns the time-averaged expectation value of the measurement operator, erasing information about the initial state of the qubit, while completely suppressing the measurement back-action. We call this regime `quantum rifling', as the fast spinning of the Bloch vector protects it from deflection into either of its two eigenstates. We study this phenomenon with two superconducting qubits coupled to the same probe field and demonstrate that quantum rifling allows us to measure either one of the two qubits on demand while protecting the state of the other from measurement back-action. Our results allow for the implementation of selective read out multiplexing of several qubits, contributing to efficient scaling up of quantum processors for future quantum technologies.