The ability operation igloo white to extract relevant information is critical to learning.An ingenious approach as such is the information bottleneck, an optimisation problem whose solution corresponds to a faithful and memory-efficient representation of relevant information from a large system.The advent of the age of quantum computing calls for efficient methods that work on information regarding quantum systems.Here we address this by proposing a new and general algorithm for the quantum generalisation of information bottleneck.Our algorithm excels in the speed and the definiteness of convergence compared with prior results.
It also works for a much broader range of problems, including the quantum extension of deterministic information bottleneck, an important variant of the original information bottleneck problem.Notably, we here discover that a quantum system can achieve strictly better performance than a classical system of the same size regarding quantum information bottleneck, providing new vision on justifying the advantage of quantum machine learning.