Design and fabrication of a robust hard X-ray multilayer using multi-objective genetic algorithms
Optics Express
|July 2, 2026
Summary
This study introduces a novel multi-objective genetic algorithm (MOGA) for designing X-ray supermirrors. The approach enhances mirror flatness and robustness, optimizing performance for advanced applications.
Area of Science:
- Optics and Materials Science
- Computational Physics
- Nanotechnology
Background:
- X-ray supermirrors are crucial for focusing and manipulating X-rays.
- Designing aperiodic multilayers presents challenges in optimizing reflectivity and flatness.
- Existing design methods may not fully explore the potential performance of these complex structures.
Purpose of the Study:
- To propose a novel design approach for aperiodic multilayer X-ray supermirrors.
- To optimize the trade-off between average reflectivity and flatness.
- To enhance the robustness and overall performance of X-ray supermirror designs.
Main Methods:
- Utilizing multi-objective genetic algorithms (MOGAs) for aperiodic multilayer design.
- Identifying critical turning points between reflectivity and flatness using nondominated solutions.
- Employing an angle-based preference selection mechanism (MOGA-ANGLE) for refined solution exploration.
Main Results:
- Nondominated solutions revealed key trade-offs between reflectivity and flatness.
- The MOGA-ANGLE method successfully identified optimized design solutions.
- Experimental validation confirmed superior flatness and robustness compared to traditional genetic algorithm methods.
Conclusions:
- The proposed MOGA-based approach effectively designs high-performance aperiodic multilayer X-ray supermirrors.
- The method achieves enhanced flatness and robustness, fully exploring design potential.
- This approach offers a significant advancement in X-ray optics design and fabrication.
