EAGER: QSA: Approximating the Ground States of Non-Stoquastic Hamiltonians Using the Variational Quantum Eigensolver

EAGER:QSA:使用变分量子本征求解器逼近非随机哈密顿量的基态

基本信息

  • 批准号:
    2037755
  • 负责人:
  • 金额:
    $ 19.94万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-01-01 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

Quantum algorithms utilize the unique properties of quantum physics to perform computational tasks, and for certain tasks they can do so more efficiently than algorithms restricted to the laws of classical physics. Quantum computers that can implement such algorithms are now publicly available, but these devices remain limited in the size and length of computations they can perform, keeping quantum algorithms with proven quantum advantages out of reach. Hybrid algorithms that use both quantum and classical hardware have been proposed as one approach to address this challenge, and this project aims to study the viability of hybrid approaches in delivering a quantum advantage by performing a systematic computational cost comparison with state-of-the-art classical algorithms. If advantages are possible using near-term quantum computers, it would dramatically enhance our ability to understand and predict complex systems across the physical sciences. The project highlights the multi-disciplinary nature of quantum computing and will train students to have a diverse toolbox to tackle emerging challenges in the field. This approach is at the heart of the project's efforts to develop a new curriculum to prepare a 'quantum-ready' workforce to address the call of the National Quantum Initiative Act of 2018.The task of approximating the ground state of many-body non-stoquastic Hamiltonians, a class of quantum Hamiltonians that describes many relevant model systems such as fermionic and sign-problematic Hamiltonians, manifests itself in a range of disciplines, from high energy physics to quantum chemistry. Current classical approaches for tackling this problem are computationally prohibitive at relevant system sizes, and overcoming or mitigating this computational bottleneck would enable new simulations of important model systems with far-reaching impacts across the physical sciences. To what degree present quantum hardware can achieve this remains an open question. This project addresses this possibility by performing a side-by-side comparison of the computational cost of hybrid quantum-classical variational algorithms and state-of-the-art classical algorithms using well-defined problem classes of non-stoquastic Hamiltonians of varying difficulty. A key objective of this assessment is to understand the differences and similarities between the optimization landscapes of the hybrid and purely-classical approaches, which may provide insight into the conditions under which the hybrid approach can achieve an advantage. The research combines lessons from spin glass theory, Hamiltonian complexity, numerical simulations, and rigorous benchmarking experience in order to make an assessment of the viability of achieving a quantum advantage on near-term quantum hardware.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
量子算法利用量子物理的独特性质来执行计算任务,对于某些任务,它们可以比受限于经典物理定律的算法更有效地执行任务。可以实现这种算法的量子计算机现在已经公开上市,但这些设备在可执行的计算大小和长度方面仍然受到限制,使具有已被证明的量子优势的量子算法遥不可及。同时使用量子和经典硬件的混合算法已被提出作为解决这一挑战的一种方法,本项目旨在通过与最先进的经典算法进行系统的计算成本比较,研究混合方法在提供量子优势方面的可行性。如果使用近期量子计算机的优势是可能的,它将极大地增强我们理解和预测跨物理科学的复杂系统的能力。该项目突出了量子计算的多学科性质,并将培训学生拥有多样化的工具箱,以应对该领域新出现的挑战。这一方法是该项目开发新课程的核心,该课程旨在为应对2018年《国家量子倡议法案》的号召,培养一支“准备好量子”的劳动力队伍。近似多体非等规哈密顿算符的基态的任务体现在从高能物理到量子化学的一系列学科中。多体非等夸哈密顿算符是描述费米子和符号问题哈密顿算符等许多相关模型系统的量子哈密顿算符。当前解决这一问题的经典方法在相关系统大小的计算上是令人望而却步的,克服或缓解这一计算瓶颈将使对重要模型系统的新模拟能够对物理科学产生深远影响。目前的量子硬件能在多大程度上实现这一点仍是一个悬而未决的问题。这个项目通过对混合量子经典变分算法和最先进的经典算法的计算成本进行并排比较,使用不同难度的明确定义的非平方哈密顿量问题类来解决这种可能性。这项评估的一个关键目标是了解混合方法和纯经典方法的优化前景之间的区别和相似之处,这可能有助于深入了解混合方法能够取得优势的条件。这项研究结合了自旋玻璃理论、哈密顿复杂性、数值模拟和严格的基准测试经验,以评估在近期量子硬件上实现量子优势的可行性。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Diabatic quantum annealing for the frustrated ring model
受挫环模型的非绝热量子退火
  • DOI:
    10.1088/2058-9565/acfbaa
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    6.7
  • 作者:
    Côté, Jeremy;Sauvage, Frédéric;Larocca, Martín;Jonsson, Matías;Cincio, Lukasz;Albash, Tameem
  • 通讯作者:
    Albash, Tameem
Quantum-inspired tempering for ground state approximation using artificial neural networks
使用人工神经网络进行基态近似的量子启发回火
  • DOI:
    10.21468/scipostphys.14.5.121
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    5.5
  • 作者:
    Albash, Tameem;Smith, Conor;Campbell, Quinn;Baczewski, Andrew D.
  • 通讯作者:
    Baczewski, Andrew D.
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Tameem Albash其他文献

Tameem Albash的其他文献

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  • 批准号:
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