Optimal Quantum Circuit Design via Unitary Neural Networks

• URL: http://arxiv.org/abs/2408.13211v1
• Date: Fri, 23 Aug 2024 16:41:15 GMT
• Title: Optimal Quantum Circuit Design via Unitary Neural Networks
• Authors: M. Zomorodi, H. Amini, M. Abbaszadeh, J. Sohrabi, V. Salari, P. Plawiak,
• Abstract summary: We present an automated method for synthesizing the functionality of a quantum algorithm into a quantum circuit model representation. We demonstrate that this trained model can effectively generate a quantum circuit model equivalent to the original algorithm.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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