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Photonic systems utilized as components for optical computing promise thepotential of enhanced computational ability over current computerarchitectures. Here, an all-dielectric photonic metastructure is investigatedfor application as a quantum algorithm emulator (QAE) in the terahertzfrequency regime; specifically, we show implementation of the Deustsh-Joszaalgorithm. The design for the QAE consists of a gradient-index (GRIN) lens asthe Fourier transform subblock and silicon as the oracle subblock. First, wedetail optimization of the metastructure through numerical analysis. Then, weemployed inverse design through a machine learning approach to further optimizethe structural geometry. In particular, we improved the lens thickness, inorder to enhance the resulting output signal for both balanced and constantfunctions. We show that by optimizing the thickness of the gradient-index lensthrough ML, we enhance the interaction of the incident light with themetamaterial leading to a stronger focus of the outgoing wave resulting in moreaccurate implementation of the desired quantum algorithm in the terahertz.

Emulating the Deutsch-Josza algorithm with an inverse-designed terahertz gradient-index lens