量子逆算法通过自适应变量量子线性解析器:应用到一般 Eigenstates 的应用
Takahiro Yoshikura1, Seiichiro L Ten-No1, Takashi Tsuchimochi1,2
1Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo 657-8501, Japan.
The journal of physical chemistry. A
|July 29, 2023
概括
我们介绍了量子反向算法 (QInverse),用于直接找到量子自态. 这种无奇点的方法准确地准激发状态,优于量子能量水平确定的变化方法.
科学领域:
- 量子计算是一种量子计算.
- 量子算法 量子算法 量子算法
- 计算化学计算化学
- 量子信息科学 量子信息科学
背景情况:
- 确定一般的量子固有状态,特别是激发状态,对于理解分子和材料特性至关重要.
- 现有的变量方法经常在激发状态的收和准确性方面扎,经常陷入局部最小值的困境.
- 折叠频谱法是一种常见的方法,但在可靠地预测目标激发状态方面存在局限性.
研究的目的:
- 开发一种新的量子算法,量子反向 (QInverse),用于直接确定一般量子自态.
- 为了应对处理强烈纠的逆功率状态和由此产生的兴奋状态的挑战.
- 提供一种无奇点的准确方法,用于针对特定能量转移附近的兴奋状态.
主要方法:
- 提出了量子反向算法 (QInverse),利用反复应用一个移动的哈密尔顿数的反向数.
- 通过使用浅量子电路以变化和自适应地解决底层线性方程,以获得忠实的逆功率状态.
- 引入了子空间扩张方法,以加快固有价值决定的收.
主要成果:
- QInverse成功地获得了能量最接近转移 ω 的目标兴奋状态,克服了变化方法的局限性.
- 子空间扩张方法在确定两个最近的固有值时表现出有效性,当它们同样接近 ω 时.
- 与折叠频谱方法相比,QInverse显示了系统可改进的成功率和准确性,避免了局部最小问题.
结论:
- QInverse提供了一种强大而准确的方法,用于直接计算一般量子自态,包括挑战激发状态.
- 为逆功率状态提出的变化和适应性解决方案使得在浅量子电路中能够准备忠实状态.
- QInverse和子空间扩张方法代表了量子计算化学和量子模拟的重大进步.
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