Highly efficient method for cutting position selection of an x-ray mono-capillary lens based on an improved SCA-CSA...

Area of Science:

• Optics and Photonics
• Computational Science

Background:

• X-ray mono-capillary lenses require precise cutting for optimal performance.
• Traditional metaheuristic algorithms face limitations in achieving high precision for lens fabrication.

Purpose of the Study:

• To develop an efficient algorithm for selecting optimal cutting positions in x-ray mono-capillary lenses.
• To improve the accuracy and robustness of surface figure error evaluation in mono-capillary fabrication.

Main Methods:

• An improved sine cosine algorithm-crow search algorithm (SCA-CSA) was developed by combining sine cosine and crow search algorithms.
• Optical profiler measurements were used to obtain capillary profiles.
• The improved SCA-CSA algorithm was applied to evaluate surface figure errors in specific regions of interest.

Main Results:

• The improved SCA-CSA algorithm achieved a surface figure error of approximately 0.138 µm in the final capillary cut region.
• The algorithm demonstrated a runtime of 2.284 seconds.
• Compared to particle swarm optimization, the SCA-CSA algorithm improved the surface figure error metric by two orders of magnitude and its standard deviation by over ten orders of magnitude across 30 runs.

Conclusions:

• The proposed improved SCA-CSA algorithm offers superior performance and robustness for evaluating surface figure errors.
• This method provides significant support for the precise cutting and development of x-ray mono-capillaries.
• The enhanced algorithm leads to a substantial improvement in the accuracy of mono-capillary lens fabrication.