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 …
Published research paper on AI methods for approximate compiling of unitaries, accepted at QCE24. The work uses deep learning and autoencoder-like models to enhance quantum circuit transpiling, demonstrating improvements over exhaustive search and random initialization on 2 and 3-qubit unitaries.
Published research paper introducing Qiskit HumanEval dataset for evaluating Large Language Models capability to generate quantum computing code. The dataset comprises more than 100 quantum computing tasks with prompts, solutions, test cases, and difficulty ratings, establishing benchmarks for generative AI tools in quantum code development.
Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and effort required to build applications. This paper focuses on training …
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.
Excited about Forbes article highlighting IBM Quantum work at the intersection of AI and quantum computing. The integration of AI and Quantum Computing has the potential to transform industries and advance quantum computing capabilities significantly.
Announcing multiple major releases at the convergence of AI and quantum computing: beta version of Qiskit transpiler service (unveiled at THINK24), research paper on AI-powered transpiler passes, and Qiskit Code Assistant with LLMs and the Qiskit HumanEval benchmark. Both projects recognized through IBM Quantum Challenge.
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.
Published peer-reviewed research comparing classical and quantum approaches to natural language processing in Expert Systems with Applications. Demonstrated that quantum NLP models can obtain the same or better results for simpler text classification tasks, with experiments utilizing up to 7 qubits across multiple classification scenarios.
Quantum physics has changed the way we understand our environment, and one of its branches, quantum mechanics, has demonstrated accurate and consistent theoretical results. Quantum computing is the process of performing calculations using quantum …