Acoustic Hologram Optimisation Using Automatic Differentiation
This work provides an improved method for optimizing acoustic holograms, which could benefit various applications of phased array transducers (PATs) by enhancing their performance without requiring changes to existing hardware.
This paper introduces Diff-PAT, an acoustic hologram optimization algorithm utilizing automatic differentiation. It achieves superior accuracy compared to conventional methods for single-sided and single-axis arrays, and improves the peak noise-to-signal ratio of acoustic holograms in metamaterials by over 8 dB.
Acoustic holograms are the keystone of modern acoustics. It encodes three-dimensional acoustic fields in two dimensions, and its quality determine the performance of acoustic systems. Optimisation methods that control only the phase of an acoustic wave are considered inferior to methods that control both the amplitude and phase of the wave. In this paper, we present Diff-PAT, an acoustic hologram optimisation algorithm with automatic differentiation. We demonstrate that our method achieves superior accuracy than conventional methods. The performance of Diff-PAT was evaluated by randomly generating 1000 sets of up to 32 control points for single-sided arrays and single-axis arrays. The improved acoustic hologram can be used in wide range of applications of PATs without introducing any changes to existing systems that control the PATs. In addition, we applied Diff-PAT to acoustic metamaterial and achieved an >8 dB increase in the peak noise-to-signal ratio of acoustic hologram.