2021. 06. 08

Acoustic Hologram Optmisation based on Automatic Differentiation and Stochastic Gradient Descent


Acoustic holograms are the keystone of modern acoustics. They encode three-dimensional acoustic fields in two dimensions, and their quality determines 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 platform with automatic differentiation. We show that in the most fundamental case of optimizing the output amplitude to match that of the target amplitude; our method with only phase modulation achieves better performance than conventional algorithm with both amplitude and phase modulation. 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. This optimisation platform for acoustic hologram can be used in a wide range of applications of PATs without introducing any changes to existing systems that control the PATs. In addition, we applied Diff-PAT to a phase plate and achieved an increase of >8 dB in the peak noise-to-signal ratio of the acoustic hologram.


Tatsuki Fushimi*, Kenta Yamamoto*, Yoichi Ochiai

* Equal Contribution (共同第一著者)