标题： 基于变分量子搜索的量子全局最小值查找器 显示英文标题

标题： Quantum Global Minimum Finder based on Variational Quantum Search

摘要： 寻找全局最小值是工程、金融和人工智能等多个领域中的关键挑战，尤其是在具有多个局部最优值的非凸函数中，这使得优化工作变得更加复杂。我们引入了量子全局最小值查找器（QGMF），这是一种创新的量子计算方法，能够高效地识别全局最小值。QGMF结合二进制搜索技术将目标函数转移到合适的位置，然后利用变分量子搜索精确地定位此目标子空间内的全局最小值。QGMF设计为低深度电路架构，针对噪声中等规模量子（NISQ）设备进行了优化，利用二进制搜索的对数优势来提高可扩展性和效率。这项工作展示了QGMF在提升量子计算能力以有效克服复杂非凸优化挑战方面的影响。 显示英文摘要

摘要： The search for global minima is a critical challenge across multiple fields including engineering, finance, and artificial intelligence, particularly with non-convex functions that feature multiple local optima, complicating optimization efforts. We introduce the Quantum Global Minimum Finder (QGMF), an innovative quantum computing approach that efficiently identifies global minima. QGMF combines binary search techniques to shift the objective function to a suitable position and then employs Variational Quantum Search to precisely locate the global minimum within this targeted subspace. Designed with a low-depth circuit architecture, QGMF is optimized for Noisy Intermediate-Scale Quantum (NISQ) devices, utilizing the logarithmic benefits of binary search to enhance scalability and efficiency. This work demonstrates the impact of QGMF in advancing the capabilities of quantum computing to overcome complex non-convex optimization challenges effectively.