Enhancing variational quantum state diagonalization using reinforcement learning techniques

Enhancing variational quantum state diagonalization using reinforcement learning techniques

The variational quantum algorithms are crucial for the application of NISQ computers. Such algorithms require short quantum circuits, which are more amenable to implementation on near-term hardware, and many such methods have been developed. One of particular interest is the so-called variational qu...

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Bibliographic Details
Main Authors: Akash Kundu, Przemysław Bedełek, Mateusz Ostaszewski, Onur Danaci, Yash J Patel, Vedran Dunjko, Jarosław A Miszczak
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:New Journal of Physics
Subjects:
quantum state diagonalization
reinforcement learning
quantum architecture search
RL-VQSD
random search
entanglement spectroscopy
Online Access:https://doi.org/10.1088/1367-2630/ad1b7f

Internet

https://doi.org/10.1088/1367-2630/ad1b7f

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