Accelerated Computational Physics Algorithms for Optical Simulations

Core Focus Areas
• Wavefront analysis
o Efficient computation and propagation of wavefront data
o Optimization of sampling, interpolation, or reconstruction techniques
• Point Spread Function (PSF) computation
o Acceleration of diffraction-based calculations
o Optimization of Fourier transform workflows or convolution operations
• Modulation Transfer Function (MTF) evaluation
o Efficient derivation from PSF or direct computation
o Resolution vs performance tradeoff analysis
Algorithmic & Technical Exploration
The team will explore one or more of the following:
• Numerical optimization techniques (sampling strategies, convergence acceleration)
• Vectorization and parallelization (multi-core CPU, GPU, or portable frameworks)
• Efficient data structures and memory handling for large datasets
• Reduction of computational complexity in key kernels
• AI-assisted methods (optional), such as:
o Surrogate models for rapid approximation
o Data-driven acceleration of expensive steps
o Intelligent sampling or adaptive resolution methods
Implementation Approach
• Use modern programming languages and frameworks (e.g., Python, C/C++, GPU frameworks, or similar)
• Build modular, testable prototypes (not tied to proprietary product code)
• Use synthetic or non-confidential test cases to validate performance