Framework for learning and control in the classical and quantum domains
DOI10.1016/J.AOP.2023.169471arXiv2307.04256MaRDI QIDQ6065699
Unnamed Author, Barry C. Sanders, Seyed Shakib Vedaie, Eduardo J. Páez
Publication date: 15 November 2023
Published in: Annals of Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2307.04256
Artificial neural networks and deep learning (68T07) Learning and adaptive systems in artificial intelligence (68T05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Graphs, diagram schemes, precategories (18A10) Hamilton-Jacobi equations (35F21) Quantum control (81Q93)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Adaptive optimal control for continuous-time linear systems based on policy iteration
- Conservative logic
- Online learning versus offline learning
- The variational quantum eigensolver: a review of methods and best practices
- Quantum feedback: theory, experiments, and applications
- From model-based control to data-driven control: survey, classification and perspective
- Quantum Computation and Quantum Information
- A theory of the learnable
- Lectures on Quantum Mechanics
- Principles of Optics
- QUANTIZATION METHODS: A GUIDE FOR PHYSICISTS AND ANALYSTS
- Modeling and Control of Quantum Systems: An Introduction
- Quantum Information Theory
- Quantum Mechanics
- Geometric quantum mechanics
- Learning and Robust Control in Quantum Technology
This page was built for publication: Framework for learning and control in the classical and quantum domains