Quantum learning machines
Abstract: Physical learning machines, be they classical or quantum, are necessarily dissipative systems. The rate of energy dissipation decreases as the learning error rate decreases linking thermodynamic efficiency and learning efficiency. In the classical case the energy is dissipated as heat. We give an example based on a quantum optical perceptron where the energy is dissipated as spontaneous emission. At optical frequencies the temperature is effectively zero so this perceptron is as efficient as it is possible to get. The example illustrates a general point: In a classical learning machine, measurement is taken to reveal objective facts about the world. In quantum learning machines what is learned is defined by the nature of the measurement itself.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.