Learning control of quantum systems
Nettet10. okt. 2013 · The balance between exploration and exploitation is a key problem for reinforcement learning methods, especially for Q-learning. In this paper, a fidelity-based probabilistic Q-learning (FPQL) approach is presented to naturally solve this problem and applied for learning control of quantum systems. In this approach, fidelity is adopted … Nettet26. jul. 2015 · Robust control design for quantum systems has been recognized as a key task in the development of practical quantum technology. In this paper, we present a systematic numerical methodology of sampling-based learning control (SLC) for control design of quantum systems with uncertainties. The SLC method includes two steps of …
Learning control of quantum systems
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NettetAbstract: We investigate two classes of quantum control problems by using frequency-domain optimization algorithms in the context of ultrafast laser control of quantum systems. In the first class of problems, the system model is known and a frequency-domain gradient-based optimization algorithm is applied for searching an optimal … Nettet21. des. 2024 · With the development of experimental quantum technology, quantum control has attracted increasing attention due to the realization of controllable artificial quantum systems. However, because quantum-mechanical systems are often too difficult to analytically deal with, heuristic strategies and numerical algorithms which …
Nettet14. okt. 2024 · This paper summarizes several recent achievements in the area of learning control of quantum systems and draw several new directions for future research. Three learning algorithms including gradient method, differential evolution and reinforcement learning are introduced for quantum control. Quantum state control in closed and … Nettetfor 1 dag siden · Gradient Ascent Pulse Engineering (GRAPE) is a popular technique in quantum optimal control, and can be combined with automatic differentiation (AD) to facilitate on-the-fly evaluation of cost-function gradients. We illustrate that the convenience of AD comes at a significant memory cost due to the cumulative storage of a large …
Nettet8. jun. 2024 · A probabilistic Q-learning (PQL) algorithm is first presented to demonstrate the basic idea of probabilistic action selection. Then the FPQL algorithm is presented for learning control of quantum systems. Two examples (a spin- 1/2 system and a lamda-type atomic system) are demonstrated to test the performance of the FPQL algorithm. Nettet18. mar. 2024 · The coherent robust control problem for a class of linear quantum passive systems with model uncertainties is considered in this study, where both the plant and the controller are described by quantum stochastic differential equations (QSDEs). In the framework of language, the model uncertainties are translated into the …
Nettet13. des. 2024 · Quantum control is valuable for various quantum technologies such as high-fidelity gates for universal quantum computing, adaptive quantum-enhanced metrology, and ultra-cold atom manipulation.Although supervised machine learning and reinforcement learning are widely used for optimizing control parameters in classical …
NettetA probabilistic Q-learning (PQL) algorithm is first presented to demonstrate the basic idea of probabilistic action selection. Then the FPQL algorithm is presented for learning control of quantum systems. Two examples (a spin-1/2 system and a Λ-type atomic system) are demonstrated to test the performance of the FPQL algorithm. The results … clifton road forest msNettetHis main research interests are in robust control theory, quantum control theory and stochastic control theory. Ian Petersen was elected IFAC Council Member for the 2014-2024 and 2024-2024 Trienniums. He was also elected to be a member of the IEEE Control Systems Society Board of Governors for the periods 2011-2013 and 2015-2024. boat rentals little torch keyNettet1. jul. 2024 · Request PDF On Jul 1, 2024, Peng Wei and others published Open quantum system control based on reinforcement learning Find, read and cite all the research you need on ResearchGate clifton road gallery littlehamptonNettet10. okt. 2013 · The balance between exploration and exploitation is a key problem for reinforcement learning methods, especially for Q-learning. In this paper, a fidelity-based probabilistic Q-learning (FPQL) approach is presented to naturally solve this problem and applied for learning control of quantum systems. In this approach, fidelity is adopted … boat rentals lewiston idahoNettet2. jun. 2024 · Traditional quantum system control methods often face different constraints, and are easy to cause both leakage and stochastic control errors under the condition of limited resources. Reinforcement learning has been proved as an efficient way to complete the quantum system control task. To learn a satisfactory control … boat rentals lake washingtonclifton road gamesNettet11. apr. 2024 · Solving the ground state and the ground-state properties of quantum many-body systems is generically a hard task for classical algorithms. For a family of ... Download a PDF of the paper titled Exponentially Improved Efficient Machine Learning for Quantum Many-body States with Provable Guarantees, by Yanming Che and Clemens ... clifton road gp