numericcoholography

Numericcoholography is a computational approach that combines holography principles with numerical simulation and data processing to model, synthesize, and reconstruct holographic wavefronts. It treats light as a complex field and uses numerical propagation operators to simulate holograms from object fields and to reconstruct object information from recorded interference patterns. Core methods include Fourier optics, the angular spectrum method, and Fresnel diffraction, applied in digital form to manipulate, propagate, and invert holographic data.

The concept emerges from digital holography and computational imaging, where computer-based workflows complement or replace purely optical paths. Numericcoholography aims to optimize hologram generation and reconstruction, study coherence and noise effects, and enable flexible design of computer-generated holograms. It is widely used in research settings to develop phase retrieval algorithms, denoise and regularize reconstructions, and explore trade-offs between sampling, resolution, and computational cost.

Key techniques involve transform-based propagation, numerical phase retrieval, and optimization driven by fidelity and regularization criteria. It often accounts for partial coherence, spectral bandwidth, and detector characteristics, integrating models of the imaging system with iterative algorithms. Computational resources and hardware acceleration (such as GPUs) are commonly employed to handle large holographic datasets and time-sensitive reconstructions.

Applications of numericcoholography span holographic displays and virtual or augmented reality, digital holographic microscopy, optical metrology, data storage, and 3D visualization. The field emphasizes cross-disciplinary collaboration among optics, computer science, and applied mathematics, with ongoing work to improve accuracy, reduce computation time, and enable real-time holographic processing on consumer and industrial platforms.