频谱差距优化用于增强的亚亚巴特状态准备的光谱差距优化
Kshiti Sneh Rai1,2, Jin-Fu Chen1,2, Patrick Emonts1,2,3,4
1Universiteit Leiden, Instituut-Lorentz, P.O. Box 9506, 2300 RA Leiden, The Netherlands.
Physical review letters
|September 15, 2025
概括
我们提出了一个高效的adiabatic算法来准备复杂的量子状态使用张量网络状态 (TNSs). 这种方法最大化了光谱间隙,克服了当前量子算法对多体物理学的局限性.
科学领域:
- 量子多体物理学 量子多体物理学
- 量子信息科学 量子信息科学
- 计算物理 计算物理
背景情况:
- 准备非微不足道的量子状态对于研究量子多体物理学至关重要.
- 阿迪亚巴特量子算法是一种常见的方法,但受到光谱间隙的限制.
- 张量网络状态 (TNSs) 提供了一个强大的框架来表示复杂的量子状态.
研究的目的:
- 提出一种高效的方法,以adiabatically准备张量网络状态 (TNSs).
- 为了克服在亚亚巴特量子算法中的光谱差距限制.
- 为了证明该方法对各种TNS和量子状态的适用性.
主要方法:
- 开发一个高效的adiabatic算法用于TNS准备.
- 通过优化父哈密尔顿构造来最大化光谱间隙.
- 将该方法应用于一个维度的随机TNS,AKLT状态和GHZ状态.
- 将哈密尔顿优化扩展到注射式和非注射式张量,利用对称性.
主要成果:
- 成功演示了一种有效的基基算法来准备TNSs.
- 在各种例子中展示了该方法的有效性,包括随机的TNS,AKLT和GHZ状态.
- 证明了哈密尔顿优化的适用于注射式和非注射式张量.
结论:
- 提出的高效的增益算法显著提高了TNSs的准备.
- 这种方法为生成与多体物理学相关的复杂量子状态提供了一个强大的方法.
- 哈密尔顿优化技术在量子状态准备中提供了灵活性和广泛的应用.
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