A magnet model for a hybrid undulator assembly.

Area of Science:

• Physics
• Engineering
• Computational Science

Background:

• Accurate prediction of magnetic fields is essential for undulator devices.
• Homogeneously polarized block models have limitations in predicting complex magnetic fields.

Purpose of the Study:

• To develop an improved modeling method for predicting magnet flux density.
• To enhance the predictability of undulator fields in hybrid devices.

Main Methods:

• A novel modeling approach divides single magnet blocks into multiple sub-blocks.
• Each sub-block is assumed to be homogeneously polarized.
• A genetic algorithm derives sub-block polarizations by fitting calculated flux density to measured values.

Main Results:

• The sub-block model significantly improves the prediction accuracy of magnet flux density within the undulator gap.
• This method offers better results compared to traditional homogeneously polarized block models.
• The model can also aid in identifying and discarding underperforming magnets.

Conclusions:

• Magnet inhomogeneities are a primary cause of poor undulator field predictability.
• The sub-block modeling method provides a more accurate representation of magnetic flux density.
• This technique is valuable for optimizing undulator performance and reliability.