Presenter: Junan Lin (PhD Candidate, Physics and Astronomy – Quantum Information)
In experimental physics, one often encounters the problem of measuring a system prepared by some experimental procedures. However, when both of these processes are imperfect, it is sometimes tricky to separately identify the source of error. In this talk, I will address this problem from a quantum information perspective. I will first illustrate how this problem can be formally expressed as a "gauge freedom", and then describe two different principles that can be applied to get around it. The first one can be understood as an effective propagation of state preparation noise from the target system to an ancillary qubit, whereas the second one utilizes measurements and post-selection to reduce the state preparation noise and can be interpreted as a form of algorithmic cooling. For the first method, I will present experimental and simulation data obtained from real quantum processors. For the second method, I will analyze its overhead through an upper bound on the expected number of runs to achieve a given error-reduction ratio.
