Reinforcement Learning

Pauli Network Circuit Synthesis with Reinforcement Learning

We introduce a Reinforcement Learning (RL)-based method for re-synthesis of quantum circuits containing arbitrary Pauli rotations alongside Clifford operations. By collapsing each sub-block to a compact representation and then synthesizing it …

Reinforced Learning for Quantum Design

A computer-implemented process for generating a policy for design of quantum devices using a quantum hardware design kit including instructions and parameters associated with the instructions includes the following operations. An environment for a …

Reinforcement Learning based Clifford Circuit Synthesis

Systems and techniques that facilitate Clifford circuit synthesis are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can …

Practical and efficient quantum circuit synthesis and transpiling with Reinforcement Learning

This paper demonstrates the integration of Reinforcement Learning (RL) into quantum transpiling workflows, significantly enhancing the synthesis and routing of quantum circuits. By employing RL, we achieve near-optimal synthesis of Linear Function, …