papersTODAY 04:00 UTC
Study examines resources needed to learn bosonic Gaussian states
A revised arXiv preprint in machine learning looks at what resources are required to optimally learn bosonic Gaussian states. Such continuous-variable quantum states arise in applications including gravitational-wave and dark-matter detection. The abstract frames this as a fundamental question for continuous-variable quantum technologies spanning computation, communication, and sensing.