AOM Announces the Launch of Morpheus™ Data Processing Software: Streamline the Metrology Data Reduction Process!

Arizona Optical Metrology LLC is proud to introduce our advanced CGH measurement data reduction software, Morpheus^™, designed to streamline metrology workflows for complex optical surfaces. With an intuitive user interface and powerful data analysis capabilities, Morpheus software enables efficient convergence of deterministic finishing of optics, making accurate and confident measurements easier than ever.

Revolutionizing CGH Measurement Processing

Morpheus is a one-click solution for CGH measurement data reduction, offering a seamless approach to analyzing and processing optical test data. By leveraging advanced algorithms and an intuitive analysis interface, Morpheus ensures that manufacturers and engineering teams can achieve precise, reliable results every time.

Key features include:

• Comprehensive Data Processing – Automates measurement data reduction enabling efficient convergence on deterministic optical finishing and surface correction runs
• Intuitive UI – User-friendly interface for streamlined operation with rich visualization to ensure each processing step is performed as expected
• Enhanced Accuracy – Includes substrate correction, mapping correction, and misalignment correction to optimize measurement precision
• Seamless Integration – Compatible with most interferometer systems, supporting standard file formats
• Digital Twin CGH File – Provides an exact digital representation of the nominal CGH test, pre-loaded with factory calibration data and test analyses all in one place

Who Benefits from Morpheus?

Morpheus is designed for manufacturing and engineering teams looking to streamline their metrology processes. Whether dealing with freeform optics, aspheres, conics, or other complex surfaces, Morpheus provides a reliable and efficient solution for CGH-based measurement analysis.

Availability

Morpheus software is included with the purchase of a CGH file from AOM. Customers can also explore its capabilities with sample data sets before full implementation.