Optimized electric heater configuration design with magnetic-field self-suppression using genetic algorithm

Atomic vapor cells are core components in various atomic sensors, and usually heated by an electric heater which would generate an additional magnetic field. To sufficiently suppress this magnetic-field interference, an optimized electric heater configuration method with magnetic-field self-suppression using a genetic algorithm is proposed. The resistance tracks in the electric heater configuration are decomposed into several heating coils; the size and current direction of each coil are optimized by the genetic algorithm to minimize the magnetic field in the heated space. The effectiveness of the proposed method is verified through the finite element simulation and an experimental test. The results show that for the optimal electric heater configuration, the average magnetic flux density introduced is approximately 2–4 times less than and dozens of times less than, respectively, the average magnetic flux density introduced in previously proposed 2 ^N multipole and common spiral configurations. This study is significative for electric heating with lower magnetic field and contributes to further improving the performance of atomic sensors.