PICTS: A Novel Deep Reinforcement Learning Approach for Dynamic P-I Control in Scanning Probe Microscopy

TL;DR

This paper introduces PICTS, a deep reinforcement learning-based system that dynamically optimizes control strategies in real-time for scanning probe microscopy, enhancing precision and efficiency.

Contribution

The paper presents a novel deep reinforcement learning approach specifically designed for real-time control in scanning probe microscopy, which was not previously available.

Findings

Improved control accuracy in scanning probe microscopy.

Real-time adaptation enhances imaging quality.

Demonstrated effectiveness through experimental validation.

Abstract

We have developed a Parallel Integrated Control and Training System, leveraging the deep reinforcement learning to dynamically adjust the control strategies in real time for scanning probe microscopy techniques.