AI Methods for Approximate Compiling of Unitaries Paper Published
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.
Qiskit HumanEval: Evaluation Benchmark for Quantum Code Generation Published
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.
Starting New Role: First Ever AI for Quantum Product Owner at IBM Quantum
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.
IBM Develops The AI-Quantum Link: Featured in Forbes
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.
Optimize Quantum Circuits with AI-Powered Transpiler Passes
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.
Qiskit Code Assistant: Training LLMs for Quantum Code Generation Paper Published
Published research paper on training specialized LLMs for quantum computing code generation using Qiskit. Addresses unique challenges in quantum programming, including scarcity of quantum code examples and rapid field evolution. Our model outperforms existing state-of-the-art quantum computing models.
Reinforcement Learning for Quantum Transpiling: Research Paper Published
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.
Comparing Natural Language Processing and Quantum NLP: Research Published
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.
Qiskit SDK v1.0 Released: Including Qiskit Transpiler and Code Assistant
Extremely proud of the massive Qiskit SDK v1.0 release including two projects from my team: the Qiskit Transpiler with AI transpiling passes and the Qiskit Code Assistant. This full-stack software for quantum computing brings together cutting-edge AI and quantum technologies.
Systematic Literature Review: Quantum Machine Learning and Its Applications Published
Published systematic literature review on quantum machine learning and its applications in Computer Science Review journal. Analyzed 94 studies from 2017-2023, identifying two primary algorithm categories and highlighting image classification as a key application area, while noting that quantum hardware improvements are necessary for QML full potential.
