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Simultaneous imaging and element differentiation by resonant neutron ghost imaging
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DOI：10.15302/frontphys.2025.032203.png)
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Abstract
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We present a proof-of-principle demonstration of energy-resolved resonant neutron ghost imaging. Based on the resonant absorption dips of different elements, we simultaneously image and distinguish the composition of three differently shaped components of an object. The initial neutron beam is spatially and energy selectively modulated by a series of Hadamard matrix masks of pixel width 100 mu m. The spectral intensity transmitted through an object is measured by a Li-6 glass single-pixel detector. Through integration of the total counts within resonant dips and correlating them with the corresponding Hadamard patterns, isotope-specific images of In, Ag and W objects are obtained at an effective spatial resolution of similar to 200 mu m. Reconstruction algorithms based on compressed sensing or convolutional neural networks can greatly reduce the data acquisition time by similar to 70% with respect to the full set of 1024 patterns, as well as enhance the image quality. Incorporating ghost imaging into energy-resolved neutron imaging thus has great potential for the simultaneous realization of fine spatial and spectral resolution, which has important value for the noninvasive analysis of material composition and distribution not only in basic research but also in industrial applications.
Keywords:
ghost imaging
neutron imaging
energy-resolved
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