Protein Qubits Machine Learning Project

A researcher is developing a machine learning project to optimize protein-based qubits by modeling artificial selection in fluorescent proteins, aiming to extend their coherence times for quantum computing applications. The project draws inspiration from a 2025 Nature study on protein qubits, which remain non-competitive due to short coherence times compared to traditional qubit technologies. The goal is to use ML-driven evolution to identify protein variants with improved quantum properties, potentially bridging the gap between biotech and scalable quantum hardware. Feedback is being sought from the quantum computing community to refine the approach, with a focus on experimental validation and computational efficiency. A weekly blog will document progress, offering transparency into the challenges and breakthroughs of merging biology with quantum information science.