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.

原子蒸汽电池是各种原子传感器的核心部件，通常由电加热器加热，从而产生额外的磁场。为了充分抑制这种磁场干扰，提出了一种基于遗传算法的具有磁场自抑制的优化电加热器配置方法。电加热器配置中的电阻轨道被分解成几个加热线圈；通过遗传算法优化每个线圈的大小和电流方向，以最小化加热空间中的磁场。通过有限元仿真和实验测试验证了所提方法的有效性。结果表明，对于最佳电加热器配置， ^N多极和常见的螺旋配置。该研究对低磁场电加热具有重要意义，有助于进一步提高原子传感器的性能。