Abstract
Efforts on enhancing the ghost imaging speed and quality are intensified when the debate around the nature of ghost imaging (quantum vs. classical) is suspended for a while. Accordingly, most of the studies these years in the field fall into the improvement regarding these two targets by utilizing the different imaging mediums. Nevertheless, back to the raging debate occurred but with different focus, to overcome the inherent difficulties in the classical imaging domain, if we are able to utilize the superiority that quantum information science offers us, the ghost imaging experiment may be implemented more practically. In this study, a quantum circuit implementation of ghost imaging experiment is proposed, where the speckle patterns and phase mask are encoded by utilizing the quantum representation of images. To do this, we formulated several quantum models, i.e. quantum accumulator, quantum multiplier, and quantum divider. We believe this study will provide a new impetus to explore the implementation of ghost imaging using quantum computing resources.
Highlights
Leveraging on its immense potentials for applications that require minimal computing resources, speed, security, etc., quantum mechanics has exploded beyond its utility in optics to exciting applications in computer science and engineering
We attempt to utilize the proven potency of quantum information science; we focus on aspects used in quantum image processing (QIP), in a new paradigm for ghost imaging
The results reported support earlier claims that many of the properties of quantum computing that are exploited provide our proposed quantum ghost imaging (QGI) protocol with the potency to accelerate sorting large size of images and mask image with high demands for speckle patterns
Summary
Leveraging on its immense potentials for applications that require minimal computing resources, speed, security, etc., quantum mechanics has exploded beyond its utility in optics (including laser technology [15] and remote sensing technology [29]) to exciting applications in computer science and engineering (e.g., machine learning [9] and artificial intelligence [28]) This has led to inter-disciplinary explorations, such as quantum ghost imaging (QGI) [4] and quantum image processing (QIP) [31], etc. MODULAR APPROACH TO BASIC QUANTUM ARITHMETIC OPERATIONS Traditionally, the arithmetic operations of addition, subtraction, multiplication, and division are employed to operate on two or more numbers Considering their utility, it is important to extend classical execution of these operations to our QGI framework. We formalize, from established literature, the notion of an image as used on the quantum computing paradigm
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