A Learned Born Series for Highly-Scattering Media

TL;DR

The paper introduces the learned Born series (LBS), a data-driven method for solving the wave equation in highly-scattering media, achieving higher accuracy with fewer iterations compared to traditional methods.

Contribution

It presents a novel learned Born series approach that improves accuracy in wave scattering problems by training components, outperforming classical series in high-contrast media.

Findings

LBS outperforms the convergent Born series in accuracy.

LBS maintains similar computational complexity.

Errors decrease with more learned iterations.

Abstract

A new method for solving the wave equation is presented, called the learned Born series (LBS), which is derived from a convergent Born Series but its components are found through training. The LBS is shown to be significantly more accurate than the convergent Born series for the same number of iterations, in the presence of high contrast scatterers, while maintaining a comparable computational complexity. The LBS is able to generate a reasonable prediction of the global pressure field with a small number of iterations, and the errors decrease with the number of learned iterations.