Victor Villar

AI Methods for Permutation Circuit Synthesis Across Generic Topologies

This paper investigates artificial intelligence (AI) methodologies for the synthesis and transpilation of permutation circuits across generic topologies. Our approach uses …

victor-villar
•
AI Methods for Quantum Circuit Optimization featured image

AI Methods for Quantum Circuit Optimization

Full-day tutorial at IEEE Quantum Week 2025 (QCE25) on using and training AI-powered transpiler passes in Qiskit for quantum circuit optimization, co-presented with David Kremer …

david-kremer
•

Reinforcement learning based transpilation of quantum circuits

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 …

david-kremer
•

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 …

ayushi-dubal
•

AI methods for approximate compiling of unitaries

This paper explores artificial intelligence (AI) methods for the approximate compiling of unitaries, focusing on the use of fixed two-qubit gates and arbitrary single-qubit …

david-kremer
•

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 …

david-kremer
•