Quantum LDPC code discovery requires searching large algebraic design spaces while reliably certifying the parameters and equivalence classes of any candidates found. We present a workflow that uses large language models to mutate Python programs …
We adapted Microsoft's QuantumKatas from Q# to Qiskit and turned them into a 350-task benchmark for evaluating how well LLMs write quantum code. We ran 16 models across 7 prompting setups — 39,200 runs — and the results say a lot about where these models are strong and where they still fall short.
A computer-implemented system with machine learning capabilities designed to address quantum computing challenges. The system's recommendation component employs a machine learning model to generate, based on an input, a recommendation comprising a …
This paper investigates artificial intelligence (AI) methodologies for the synthesis and transpilation of permutation circuits across generic topologies. Our approach uses Reinforcement Learning (RL) techniques to achieve near-optimal synthesis of …
Thrilled to have been a keynote speaker at Metafuturo 2025, sharing insights on the convergence of Quantum Computing and AI. From LLMs and agentic AI applications for quantum computing to AI-optimized quantum circuits at IBM Quantum.
This paper explores the application of machine learning (ML) techniques in predicting the QPU processing time of quantum jobs. By leveraging ML algorithms, this study introduces predictive models that are designed to enhance operational efficiency in …
An approach for assisting in the generation of quantum source code. The approach may include receiving a quantum source code input with a specification of constraints of a quantum unit on which the quantum source code input is to be run, wherein the …
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 …
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 rotations typical in superconducting hardware. Our approach involves three …
Excited to announce starting a new position at IBM Quantum as the first ever AI for Quantum Product Owner, leading initiatives at the convergence of artificial intelligence and quantum computing.