SynIM: GPU-Accelerated Python Library for Next-Generation Adaptive Optics Calibration
Researchers have developed SynIM, an open-source Python library that uses GPU acceleration to compute synthetic calibration matrices for next-generation adaptive optics systems on large telescopes. The tool addresses the impracticality of experimental calibration for systems controlling thousands of actuators by using model-based synthetic calibration instead. SynIM is already being deployed for major telescope projects including the ELT's MORFEO and VLT's MAVIS systems, making it critical infrastructure for next-generation astronomical observations.
SynIM is a specialized computational tool designed to solve a key challenge in next-generation adaptive optics: creating accurate calibration matrices without time-consuming physical experiments. The library uses GPU acceleration via CuPy to handle the massive computational demands of high-order systems with thousands of actuators. A key innovation is its precise handling of spatial geometry through composite affine transformations and sub-pixel grid alignment, which minimizes interpolation errors that plague simpler geometric estimators. End-to-end simulations demonstrate that reconstructors built with SynIM achieve closed-loop adaptive optics performance equivalent to full physical optics models. The tool supports multiple adaptive optics configurations (SCAO, GLAO, MCAO, LTAO) and is currently driving design and operational strategies for five major telescope projects, including the Extremely Large Telescope and Very Large Telescope.
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- arXiv astro-phCenter
SynIM: a high-performance GPU-accelerated Python library for synthetic interaction and tomographic reconstruction matrices in next-generation adaptive optics
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