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arXiv · 2408.13211

Optimal Quantum Circuit Design via Unitary Neural Networks

M. Zomorodi·H. Amini·M. Abbaszadeh·J. Sohrabi·V. Salari·P. Plawiak
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Abstract

The process of translating a quantum algorithm into a form suitable for implementation on a quantum computing platform is crucial but yet challenging. This entails specifying quantum operations with precision, a typically intricate task. In this paper, we present an alternative approach: an automated method for synthesizing the functionality of a quantum algorithm into a quantum circuit model representation. Our methodology involves training a neural network model using diverse input-output mappings of the quantum algorithm. We demonstrate that this trained model can effectively generate a quantum circuit model equivalent to the original algorithm. Remarkably, our observations indicate that the trained model achieves near-perfect mapping of unseen inputs to their respective outputs.

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M. Zomorodi, H. Amini, M. Abbaszadeh, J. Sohrabi, V. Salari, P. Plawiak. 2024-08-23. Optimal Quantum Circuit Design via Unitary Neural Networks. https://arxiv.org/abs/2408.13211

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