Wave-scattering processes: path-integrals designed for the numerical handling of complex geometries.

Area of Science:

• Computational physics
• Electromagnetism
• Wave scattering theory

Background:

• Wave scattering from complex 3D objects presents significant analytical challenges.
• Existing methods often struggle with intricate geometries and statistical distributions of scatterers.

Purpose of the Study:

• To develop a novel statistical perspective on wave single-scattering.
• To address interpretative difficulties in analyzing scatterer distributions.
• To enhance computational efficiency in electromagnetic scattering problems.

Main Methods:

• Application of Feynman-Kac path-integral methodology.
• Implementation on Schiff approximation, Born approximation, and rigorous Born series models.
• Statistical analysis of scattering moments over various scatterer properties (size, orientation, shape).

Main Results:

• A new statistical framework for wave single-scattering is established.
• The approach effectively handles interpretative difficulties related to scatterer distributions.
• Computational benefits comparable to the Monte Carlo method are demonstrated for complex geometries.

Conclusions:

• The Feynman-Kac path-integral method offers a powerful statistical tool for wave scattering.
• This approach improves the analysis of scattering from complex objects.
• It provides a computationally efficient alternative for electromagnetic scattering simulations.