This study introduces a novel framework that brings together two main Quantum Programming methodologies, gate-based Quantum Computing and Quantum Annealing, by applying the Model-Driven Engineering principles. This aims to enhance the adaptability, design and scalability of quantum programs, facilitating their design and operation across diverse computing platforms. A notable achievement of this research is the development of a mapping method for programs between gate-based quantum computers and quantum annealers which can lead to the automatic transformation of these programs. Specifically, this method is applied to the Variational Quantum Eigensolver Algorithm and Quantum Anneling Ising Model, targeting ground state solutions. Finding ground-state solutions is crucial for a wide range of scientific applications, ranging from simulating chemistry lab experiments to medical applications, such as vaccine development. The success of this application demonstrates Model-Driven Engineering for Quantum Programming frameworks's practical viability and sets a clear path for quantum Computing's broader use in solving intricate problems.

翻译：本研究引入了一种新颖框架，通过应用模型驱动工程原理，将门基量子计算与量子退火这两种主要量子编程方法相结合。该框架旨在增强量子程序的适应性、设计与可扩展性，促进其在不同计算平台上的设计与运行。本研究的一项重要成果是开发了门基量子计算机与量子退火器之间的程序映射方法，该方法可实现这些程序的自动转换。具体而言，我们将此方法应用于变分量子本征求解器算法与量子退火伊辛模型，以求解基态解。寻找基态解对广泛的科学应用至关重要，其范围涵盖从化学实验室实验模拟到疫苗开发等医学应用。该应用的成功证明了模型驱动工程在量子编程框架中的实际可行性，并为量子计算在解决复杂问题中的更广泛应用指明了清晰路径。