Noise memory kernel reconstruction via the post-Markovian master equation

Presenting Author: Haimeng Zhang, University of Southern California
Contributing Author(s): Daniel A. Lidar

Understanding and combating decoherence is one of the central topics in realizing quantum computation. Correlated, non-Markovian noise presents a particularly relevant challenge in superconducting qubit systems. This talk will present results on the construction of a bath memory kernel function from the experimentally measured state dynamics of a superconducting qubit. This phenomenological memory kernel arises in the post-Markovian master equation (PMME) [A. Shabani and D. A. Lidar, PRA 71, 020101 (2005)]. The memory kernel as constructed is of practical interest for quantum computation tasks as it provides insight into the noise origin and the characteristic timescales associated with bath memory effect. It also illuminates how the non-Markovian property of the noise can potentially be utilized to extend coherence timescales relative to the Markovian limit.

(Session 5 : Saturday from 5:00pm - 7:00pm)


SQuInT Chief Organizer
Akimasa Miyake, Associate Professor

SQuInT Co-Organizer
Brian Smith, Associate Professor UO

SQuInT Program Committee
Postdoctoral Fellows:
Markus Allgaier (UO OMQ)
Sayonee Ray (UNM CQuIC)
Pablo Poggi (UNM CQuIC)
Valerian Thiel (UO OMQ)

SQuInT Event Co-Organizers (Oregon)
Jorjie Arden
Holly Lynn

SQuInT Event Administrator (Oregon)
Brandy Todd

SQuInT Administrator (CQuIC)
Gloria Cordova
505 277-1850

SQuInT Founder
Ivan Deutsch, Regents' Professor, CQuIC Director

Tweet About SQuInT 2020!