Bulletin of the American Physical Society
APS March Meeting 2023
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session D72: Techniques for Learning Noise in Quantum Systems
3:00 PM–6:00 PM,
Monday, March 6, 2023
Room: Room 406
Sponsoring
Unit:
DQI
Chair: Daniel Hothem, Sandia National Laboratories
Abstract: D72.00007 : Full characterisation of quantum non-Markovian processes: from tomography to noise detection.*
4:12 PM–4:24 PM
Presenter:
Christina Giarmatzi
(University of Technology Sydney)
Author:
Christina Giarmatzi
(University of Technology Sydney)
Collaboration:
n/a
We present a method of full quantum process tomography that captures non-Markovian noise and a method to detect quantum memory in a non-Markovian process [1]. We call a process Markovian when the environment does not provide a memory that retains correlations across different system-environment interactions. We define two types of non-Markovian processes, depending on the required memory being classical or quantum. We formalise this distinction using the process matrix formalism, through which a process is represented as a multipartite state. Within this formalism, a test for entanglement in the state can be mapped to a test for quantum memory in the process.
We demonstrate the method in a simple toy model, but our methods have been applied experimentally, too, in photonics [2] and superconducting qubits [3].
[1] C. Giarmatzi and F. Costa Quantum 5, 440 (2021)
[2] K. Goswami, C. Giarmatzi, et al. Phys. Rev. A 104, 022432 (2021)
[3] Upcoming paper
*This work was supported by the Australian Research Council (ARC) Centre of Excellence for Quantum Engineered Systems grant (CE 110001013). C.G. is the recipient of a Sydney Quantum Academy Postdoctoral Fellowship.
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