Conference Presentation (Invited)

FZJ-2023-00090

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Improve the Pauli coefficient measurement with Active Learning

Ai, J. (Corresponding author)FZJ*

2022

Abstract: We provide an improvement in the process of Active Learning as a concept from machine learning that labels a large amount of data with a small amount of learning material. In this approach, the method is implemented to speed up measuring the Pauli coefficient for the two-qubit gate. The aim of the implementation is to prove the speed up of the measuring process by reducing unwanted interactions.

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Contributing Institute(s):

1. Theoretische Nanoelektronik (PGI-2)

Research Program(s):

1. 5224 - Quantum Networking (POF4-522) (POF4-522)

Appears in the scientific report 2022

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