Fast Quantum State Reconstruction via Accelerated Non-Convex Programming

Fast Quantum State Reconstruction via Accelerated Non-Convex Programming

We propose a new quantum state reconstruction method that combines ideas from compressed sensing, non-convex optimization, and acceleration methods. The algorithm, called Momentum-Inspired Factored Gradient Descent (MiFGD), extends the applicability of quantum tomography for larger systems. Despite...

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Bibliographic Details
Main Authors: Junhyung Lyle Kim, George Kollias, Amir Kalev, Ken X. Wei, Anastasios Kyrillidis
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Photonics
Subjects:
quantum state tomography
non-convex optimization
matrix factorization
acceleration
Online Access:https://www.mdpi.com/2304-6732/10/2/116

Internet

https://www.mdpi.com/2304-6732/10/2/116

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