Work

ZX-Diagram T-Count Reduction Based on Proximal Policy Optimization

Year: 2026

Type: article

Abstract: In fault-tolerant quantum computing systems, the T gates consume more fault-tolerant resources. In this paper, we propose an automated optimization method based on the Proximal Policy Optimization (PPO) algorithm. We first translate quantum circuits into ZX-diagrams using ZX-calculus, transforming the circuit optimization problem into a graph rewriting task. Subsequently, the PPO agent, powered by graph neural networks (GNNs) to encode the complex graph structures of the ZX-diagrams, learns to predict efficient transformation paths by focusing on local node and edge features. The PPO algorithm ensures stable policy updates through its clipped objective function, which prevents excessively large and potentially detrimental changes during optimization. Experimental results confirm the method’s effectiveness, showing an average reduction in T-count of 3.12% compared to the baseline approach.

Source: Intelligent Computing

DOI: 10.34133/icomputing.0418

Authors: Keyu Xiong, Tao Shang, Chenyi Zhang, Yuchen Liu

Institution: Beihang University

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality

Awards: G7413561138, G7954627783