Fig. 1. Flowchart of the rapid design method of metamaterials based on particle swarm optimization

Fig. 2. Particle swarm optimization process

Fig. 3. Fitness curves of classical particle swarm optimization (PSO) and particle swarm optimization algorithm with linearly decreasing weight (PSO-W)

Fig. 4. Structure diagram of automatically designed metamaterial absorber

Fig. 5. Simulation curve of absorption characteristics of terahertz metamaterial absorber with continuous dielectric layer

Fig. 6. Simulation curve of absorption characteristics of terahertz metamaterial absorber when the refractive index of the analyte to be measured changes from 　n＝1.0 to n＝2.0

Fig. 7. Variation and fitting curve of resonant frequency of metamaterial absorber covered by analytes with different refractive indices. The depth of the covering analyte to be tested is 40 μm

Fig. 8. Surface current and electric field distributions at the resonance point of the metamaterial. (a) Surface current distribution; (b) surface electric field distribution

Fig. 9. Electromagnetic field distributions at the resonance point of the metamaterial. (a) Electric field distribution at the y＝0 section; (b) magnetic field distribution at the x＝0 section

Fig. 10. Schematic diagram of metamaterial structure with microcavity structure

Fig. 11. Simulation curve of absorption characteristics of metamaterials with microcavity structure without 　filling any analyte to be measured

Fig. 12. Simulation curve of absorption characteristics of metamaterial absorber with microcavity structure when the refractive index of the analyte to be measured changes from n＝1.0 to n＝2.0

Fig. 13. Variation and fitting curve of resonant frequency of metamaterial absorber with microcavity structure covered by analytes to be measured with different refractive indices