Optimizing microwave pulses without pre-defined parameters previously relied heavily on chance encounters. Now, an autonomous artificial intelligence has learned to discover high-performance pulse sequences exceeding those found by random search alone. This fully adaptable approach promises faster, lower-error quantum state preparation across diverse superconducting devices, beginning with successful simulations of hydrogen molecules.
Southern Methodist Team Optimises Pulses Via AI Learning
Optimizing microwave pulses without pre-defined parameters previously relied heavily on chance encounters. Now, an autonomous artificial intelligence has learned to discover high-performance pulse sequences exceeding those found by random search alone. This fully adaptable approach promises faster, lower-error quantum state preparation across diverse superconducting devices, beginning with successful simulations of hydrogen molecules.