We Got AI Agents to Train RL Models for Quantum Transpilation
A new MCP server that enables AI agents to autonomously train reinforcement learning models for quantum circuit synthesis - including permutation, linear function, and Clifford …
A new MCP server that enables AI agents to autonomously train reinforcement learning models for quantum circuit synthesis - including permutation, linear function, and Clifford …
This paper investigates artificial intelligence (AI) methodologies for the synthesis and transpilation of permutation circuits across generic topologies. Our approach uses …
Qiskit is an open-source quantum computing framework that allows users to design, simulate, and run quantum circuits on real quantum hardware. We explore post-training techniques …
Systems and techniques that facilitate quantum circuit transpiling are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a …
Celebrating the arxiv publication of the Pauli Network Circuit Synthesis with Reinforcement Learning paper. The AI-powered transpiler pass has been available in the Qiskit …
We introduce a Reinforcement Learning (RL)-based method for re-synthesis of quantum circuits containing arbitrary Pauli rotations alongside Clifford operations. By collapsing each …
AI-powered quantum circuit optimization library — Ranking 3rd in Unitary Foundation 2025 Survey, 981K+ downloads
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 …
Reinforcement learning environments for quantum circuit synthesis — powers the AI transpiler passes
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 …