Diabatic Quantum Annealing using XX-Catalysts
使用 XX 催化剂的非绝热量子退火
基本信息
- 批准号:2252587
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:英国
- 项目类别:Studentship
- 财政年份:2019
- 资助国家:英国
- 起止时间:2019 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
My proposed research will look at a quantum algorithm known as Quantum Annealing. This algorithm is used for solving combinatorial optimisation problems with the aim of reaching a solution faster than is classically achievable.Quantum Annealing works by encoding the optimal solution for such a problem into the ground state of what is called a Hamiltonian - essentially a mathematical object that defines the energy levels of a system. In this way, solving the optimisation problem becomes a matter of getting a quantum system into this ground state so that it can be measured. However, for any non-trivial problem this Hamiltonian will be incredibly complicated and so getting a quantum system into its ground state is not a simple task.In traditional Quantum Annealing, the system is initialised in the ground state of a simple Hamiltonian before slowly transitioning to the Hamiltonian defining the problem. By what is known as the Adiabatic theorem, the system will remain in the ground state throughout this transition provided it happens slowly enough and so the system ends in the ground state of the problem Hamiltonian. However, for some problems, this must occur intractably slowly to avoid transitions away from the ground state - destroying any chance of quantum speedup.My PhD will examine a potential solution to this problem in which transitions to higher energy states are allowed to occur but in such a way that ensures the system has returned to the ground state by the end of the algorithm. This is achieved through the introduction of a third Hamiltonian that facilitates these transitions back into the ground state. This so-called diabatic approach to quantum annealing has the potential to lead to dramatic speedup over its adiabatic counterpart and indeed over classical algorithms.
我提议的研究将着眼于一种被称为量子退火法的量子算法。该算法用于解决组合优化问题,目的是以比经典方法更快的速度获得解。量子退火法的工作原理是将此类问题的最优解编码为哈密顿量的基态,哈密顿量本质上是定义系统能级的数学对象。通过这种方式,解决优化问题就变成了让量子系统进入这个基态,以便可以测量它。然而,对于任何非平凡的问题,这个哈密顿量都将是令人难以置信的复杂的,所以让一个量子系统进入它的基态并不是一项简单的任务。在传统的量子退火法中,系统在一个简单的哈密顿量的基态中被初始化,然后慢慢过渡到定义这个问题的哈密顿量。根据所谓的绝热定理,系统在整个转变过程中将保持在基态,只要它发生得足够慢,因此系统结束于问题哈密顿量的基态。然而,对于一些问题,这必须发生得很慢,以避免远离基态的跃迁-破坏任何量子加速的机会。我的博士将研究这个问题的潜在解决方案,其中允许发生到更高能级的跃迁,但以确保系统在算法结束时返回到基态的方式。这是通过引入第三哈密顿量来实现的,该哈密顿量有助于这些转变回到基态。这种所谓的非绝热量子退火法有可能导致其绝热退火法甚至超过经典算法的显著加速。
项目成果
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
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LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
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2021 - 期刊:
- 影响因子:0
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吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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