Pauli Network Circuit Synthesis with Reinforcement Learning Paper Published
Pauli Network Circuit Synthesis with Reinforcement LearningReally happy to see the paper on arxiv. The described AI-powered transpiler pass for Pauli Networks has been available in the Qiskit Transpiler Service since last November 2024, as presented in the Quantum Developer Conference 2024 Check out the paper https://arxiv.org/abs/2503.14448 and the related documentation on how to use it https://docs.quantum.ibm.com/guides/ai-transpiler-passes#ai-circuit-synthesis-passes
Context: In response to Ayushi Dubal’s post about the Reinforcement Learning-based synthesis pass for Pauli Networks (Clifford + arbitrary angle Pauli rotation circuits). The research paper Pauli Network Circuit Synthesis with Reinforcement Learning was presented at the American Physical Society March Meeting in Anaheim.
Originally shared on LinkedIn on March 19, 2025 - 16 reactions, 2 comments as of 11/12/2025
I research and develop AI-based systems to tackle complex problems in quantum computing and other relevant areas.
My work sits at the intersection of quantum computing, machine learning, and open source. I hold IBM Master Inventor status and have contributed to tools used by millions of developers worldwide.
I have a PhD in Computer Engineering from the University of Salamanca (2018), have authored 80+ publications, and received the 2019 SCIE-BBVA Award for best young researcher in Computer Science in Spain.