Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Quantitative Dynamic Phase Mapping via Single-Arm Field-Correlation Ghost Imaging

Chaoran Wang, Jinquan Qi, Shuang Liu, Xingzhao Jiang, Shensheng Han

Abstract

We demonstrate a single-arm optical platform for phase-retrieval-free, quantitative dynamic phase mapping of continuous transparent media via field-correlation ghost imaging. By modeling the medium as a dynamic pure-phase object, we spatially encode and compress its two-dimensional (2D) complex transmittance into a single bucket detector. Balanced heterodyne detection downconverts the optical frequencies for direct digitization. Crucially, by mapping spatial information into the temporal domain, this single-pixel architecture exploits high-speed digitization to continuously resolve 2D phase dynamics, effectively bypassing the frame-rate bottlenecks of traditional array sensors. Coupled with intermediate-frequency spectral analysis, this establishes a direct linear mapping from the recorded signal to the physical phase. The complex amplitude is thus deterministically extracted via field-correlation, enabling the spatial reconstruction of 2D acoustic pressure distributions using a pseudo-inverse algorithm. Experimental validations in an acoustic levitator confirm that the optically extracted acoustic wavelengths strictly match theoretical dispersion models, exhibiting a robust linear correlation between the retrieved phase shift and local sound pressure levels. This deterministic methodology provides a real-time-capable metrological tool for characterizing rapidly evolving phenomena, including transient aeroacoustic flows, shockwaves, and microfluidic biological dynamics.

Quantitative Dynamic Phase Mapping via Single-Arm Field-Correlation Ghost Imaging

Abstract

We demonstrate a single-arm optical platform for phase-retrieval-free, quantitative dynamic phase mapping of continuous transparent media via field-correlation ghost imaging. By modeling the medium as a dynamic pure-phase object, we spatially encode and compress its two-dimensional (2D) complex transmittance into a single bucket detector. Balanced heterodyne detection downconverts the optical frequencies for direct digitization. Crucially, by mapping spatial information into the temporal domain, this single-pixel architecture exploits high-speed digitization to continuously resolve 2D phase dynamics, effectively bypassing the frame-rate bottlenecks of traditional array sensors. Coupled with intermediate-frequency spectral analysis, this establishes a direct linear mapping from the recorded signal to the physical phase. The complex amplitude is thus deterministically extracted via field-correlation, enabling the spatial reconstruction of 2D acoustic pressure distributions using a pseudo-inverse algorithm. Experimental validations in an acoustic levitator confirm that the optically extracted acoustic wavelengths strictly match theoretical dispersion models, exhibiting a robust linear correlation between the retrieved phase shift and local sound pressure levels. This deterministic methodology provides a real-time-capable metrological tool for characterizing rapidly evolving phenomena, including transient aeroacoustic flows, shockwaves, and microfluidic biological dynamics.
Paper Structure (2 sections, 10 equations, 4 figures)

This paper contains 2 sections, 10 equations, 4 figures.

Table of Contents

  1. Introduction
  2. Principle

Figures (4)

  • Figure 1: Schematic of the experimental CD-GI setup. Laser light, split by a fiber BS, forms the signal and LO paths. In the signal path, AOM-shifted light probes the dynamic acoustic target, with scattered light collected via an imaging system. In the modulation path, the LO is spatially encoded by a DMD, relayed by a 4f system, and combined with the signal at a BPD for heterodyne detection. Synchronous control ensures phase stability. (Abbreviations: SMF, single-mode fiber; BS, beam splitter; AOM, acousto-optic modulator; FL, focal length; DMD, digital micromirror device; M, mirror; BPD, balanced photodetector; OA, optical amplifier; Len, lens)
  • Figure 2: Experimental reconstructions of the acoustic pressure distributions at 40 kHz, demonstrating the imaging fidelity across different intermediate-frequency spectral components. (a)--(c) Reconstructions derived from the lower heterodyne sideband $Y_{-1}$ (Row 1), the central carrier $Y_0$ (Row 2), and the upper sideband $Y_{+1}$ (Row 3), respectively. Each row presents the retrieved acoustic field at five in-plane projection angles ($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, $135^{\circ}$, and $180^{\circ}$). Consistent with the theoretical model, the sideband reconstructions (Rows 1 and 3) exhibit significantly higher signal-to-noise ratios, whereas the carrier reconstruction (Row 2) is severely degraded by the constant DC background. The Magma colormap indicates the relative acoustic pressure amplitude. The white scale bar denotes a spatial length of 10 mm.
  • Figure 3: Comparison of experimental and simulated acoustic heatmaps at a $0^{\circ}$ projection angle. (a)--(c) CD-GI experimental reconstructions of the acoustic pressure field at 25 kHz, 31.25 kHz, and 40 kHz, respectively. (d)--(f) Corresponding numerical simulations performed using COMSOL Multiphysics comsol. The vertical white bars across all panels indicate an identical spatial length, serving as a uniform scale reference to illustrate the frequency-dependent spatial periodicity. The high spatial correlation validates the imaging fidelity across the operational frequency bandwidth.
  • Figure 4: Quantitative optical analysis of the CD-GI acoustic field reconstructions. (a) Fast Fourier Transform (FFT) spectra of the detected heterodyne signals at 25 kHz, 31.25 kHz, and 40 kHz, averaged over 100 repetitions. (b) Measured versus theoretical acoustic wavelength as a function of driving frequency, based on 100 repeated experiments. (c) Statistical distribution (histogram) of the morphological wavelengths extracted from 150 time-window segments across 100 repeated experiments. (d) Measured Sound Pressure Level (SPL) response versus drive voltage averaged across 100 repetitions, compared against theoretical curves. (e) Average measurement error (dB) for each targeted frequency, quantified over 100 independent experimental repetitions.