Reinforcement Learning

Published research demonstrating integration of Reinforcement Learning into quantum transpiling workflows for Qiskit transpiler service. Achieves near-optimal circuit synthesis and routing with significant performance improvements over traditional optimization methods, handling Linear Function, Clifford, and Permutation circuits up to 65 qubits.

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, …