Autonomous machine learning boost for quantum sensors

Researchers in the UK have developed an autonomous machine learning algorithm that dramatically simplifies quantum systems. Researchers at the University of Bristol's Quantum Engineering Technology Labs (QETLabs) developed a new protocol to formulate and validate approximate models for quantum systems of interest. The Quantum Model Learning Agent (QMLA) algorithm works autonomously, designing and performing experiments on the targeted quantum system, with the resultant data being fed back into the algorithm. It proposes candidate Hamiltonian models to describe the target system, and distinguishes between them using statistical metrics, namely Bayes factors. The researchers were able to use the algorithm on a real-life quantum experiment involving defect centres in a diamond, a well-studied platform for quantum information processing and quantum sensing.