EAGER-QAC-QCH: NSF-BSF: Quantum Computation as a Non-Equilibrium Dynamical Many-Body System

EAGER-QAC-QCH：NSF-BSF：量子计算作为非平衡动态多体系统

• 批准号: 2037654
• 负责人: Alex Kamenev
• 金额: $ 29.11万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2037654&HistoricalAwards=false
• 关键词: EAGER; QAC; QCH; NSF; BSF

Non-technical Summary This award is made on an EAGER proposal invited through the Quantum Algorithm Challenge Dear Colleague Letter. It supports research and education to study new concepts for how quantum mechanical states can be prepared and manipulated to perform computation which includes protocols or algorithms required to use a quantum computer to solve a problem. Quantum computing hardware has significantly advanced over the past few years. Both Google and IBM have recently demonstrated devices with about 50 fully controlled superconducting qubits with high fidelity and long coherence times. The number of qubits may be expected to increase even further, but the number of independent external controls presents a crucial bottleneck in scaling up the modern quantum computing architecture. This means that near-term quantum computers are not going to operate the way classical processors do. The PI aims to develop specific operating protocols, which will allow already existing quantum devices to perform particular optimization tasks, which are exponentially hard for conventional classical algorithms. The latter suffer from being trapped into sub-optimal solutions for extremely long times. Quantum tunneling allows for simultaneous exploration of multiple potentially optimal configurations, and ultimately enables finding the true unique optimum. This project is aimed to investigate theoretical limits for efficiency of these quantum algorithms. Practical demonstration schemes will be conceptualized and possibly implemented on existing prototypical quantum devices. NSF funds will provide training for a graduate student research assistant and (partially) a postdoctoral fellow. Both will be trained in the theoretical apparatus underlying construction of algorithms for quantum computation. The results of the project will be incorporated in graduate classes at the University of Minnesota as well as at regular summer schools, which the PI co-organizes through the Fine Theoretical Physics Institute. Part of the project will be conducted in close cooperation with Prof. Yuval Gefen of the Weizmann Institute, who will be funded separately by BSF. The BSF part will provide training for another postdoctoral fellow. Technical Summary This award is made on an EAGER proposal invited through the Quantum Algorithm Challenge Dear Colleague Letter. It supports research and education to study new concepts for how quantum mechanical states can be prepared and manipulated to perform computation which includes protocols or algorithms required to use a quantum computer to solve a problem. The PI will consider quantum approximate optimization algorithms (QAOA) and quantum image recognition schemes. Both are based on the idea of an information processing engine, which repeatedly performs a particular cycle. The cycle involves coupling and decoupling of the active quantum system, which can be modeled by a Sherrington-Kirkpatrick spin glass encoded with a desired optimization problem, with the information bath. A qubit realization of the Sachdev-Ye-Kitaev (SYK) model will be explored as a model for the information bath. The SYK system, being a holographic dual of a black hole, possesses a finite entropy down to the exponentially small temperature. This allows quantum tunneling among multiple local minima of the spin glass. The quantum measurement operation, performed in the end of each cycle, provides a progressively improving set of candidate optimal spin configurations. A goal of the project is to evaluate the probability of finding the true optimum within such a set. Another goal is to optimize the cycle to determine theoretical bounds for efficiency of the information engine. The NSF-BSF part of the project will deal with a theoretical description in terms of the reduced density matrix of the working substance. We expect to find a Lindblad-like evolution equation. It will allow for an efficient analysis of computation schemes using existing powerful field-theoretical and computational techniques.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.

非技术摘要 该奖项是根据量子算法挑战亲爱同事信邀请的 EAGER 提案颁发的。它支持研究和教育，研究如何准备和操纵量子力学状态以执行计算的新概念，其中包括使用量子计算机解决问题所需的协议或算法。量子计算硬件在过去几年中取得了显着进步。 Google 和 IBM 最近都展示了具有约 50 个完全受控超导量子位的设备，这些设备具有高保真度和长相干时间。量子位的数量预计会进一步增加，但独立外部控制的数量成为扩大现代量子计算架构的关键瓶颈。这意味着近期量子计算机将不会像经典处理器那样运行。 PI 的目标是开发特定的操作协议，这将允许现有的量子设备执行特定的优化任务，这对于传统的经典算法来说是指数级的困难。后者会在很长一段时间内陷入次优解决方案中。量子隧道允许同时探索多个潜在的最佳配置，并最终能够找到真正独特的最佳配置。该项目旨在研究这些量子算法效率的理论极限。实际的演示方案将被概念化，并可能在现有的原型量子设备上实施。 NSF 资金将为研究生研究助理和（部分）博士后研究员提供培训。两人都将接受量子计算算法构建基础理论工具的培训。该项目的成果将纳入明尼苏达大学的研究生课程以及 PI 通过精细理论物理研究所共同组织的常规暑期学校。该项目的一部分将与魏茨曼研究所的 Yuval Gefen 教授密切合作进行，该教授将由 BSF 单独资助。 BSF 部分将为另一名博士后提供培训。技术摘要 该奖项是根据量子算法挑战赛《亲爱同事的信》邀请的一项 EAGER 提案而颁发的。它支持研究和教育，研究如何准备和操纵量子力学状态以执行计算的新概念，其中包括使用量子计算机解决问题所需的协议或算法。 PI 将考虑量子近似优化算法 (QAOA) 和量子图像识别方案。两者都基于信息处理引擎的思想，该引擎重复执行特定的循环。该循环涉及活性量子系统的耦合和解耦，可以通过用信息浴编码所需的优化问题的谢林顿-柯克帕特里克自旋玻璃来建模。将探索 Sachdev-Ye-Kitaev (SYK) 模型的量子位实现作为信息浴的模型。 SYK 系统是黑洞的全息对偶，在低至指数级的小温度下拥有有限的熵。这允许在自旋玻璃的多个局部最小值之间产生量子隧道。在每个周期结束时执行的量子测量操作提供了一组逐渐改进的候选最佳自旋配置。该项目的目标是评估在这样的集合中找到真正最优值的概率。另一个目标是优化循环以确定信息引擎效率的理论界限。该项目的 NSF-BSF 部分将根据工作物质的约化密度矩阵进行理论描述。我们期望找到一个类似 Lindblad 的进化方程。它将允许使用现有强大的场论和计算技术对计算方案进行有效的分析。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点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

One-dimensional scattering of two-dimensional fermions near quantum criticality

接近量子临界点的二维费米子的一维散射

• DOI: doi:10.1103/physrevb.103.214519
• 发表时间: 2021-06
• 期刊: Physical review
• 作者: Dimitri Pimenov; Alex Kamenev
• 通讯作者: Alex Kamenev

Coulomb Drag and Heat Transfer in Strange Metals

奇怪金属中的库仑阻力和传热

• DOI: 10.1103/physrevlett.131.096501
• 发表时间: 2023-08
• 期刊: Physical Review Letters
• 影响因子: 8.6
• 作者: Chudnovskiy, A. L.;Levchenko, Ale;Kamenev, Ale
• 通讯作者: Kamenev, Ale

Superconductor-Insulator Transition in a Non-Fermi Liquid

非费米液体中的超导-绝缘体转变

• DOI: 10.1103/physrevlett.129.266601
• 发表时间: 2022-12
• 期刊: Physical Review Letters
• 影响因子: 8.6
• 作者: Chudnovskiy, A. L.;Kamenev, Ale
• 通讯作者: Kamenev, Ale

Emptiness formation in polytropic quantum liquids

多变量子液体中空洞的形成

• DOI: 10.1088/1751-8121/ac47b1
• 发表时间: 2022-01
• 期刊: Journal of physics
• 作者: Hsiu

Shot noise does not always provide the quasiparticle charge

散粒噪声并不总是提供准粒子电荷

• DOI: 10.1038/s41567-022-01758-x
• 发表时间: 2022-12
• 期刊: Nature Physics
• 影响因子: 19.6
• 作者: Biswas, Sourav;Bhattacharyya, Rajarshi;Kundu, Hemanta Kumar;Das, Ankur;Heiblum, Moty;Umansky, Vladimir;Goldstein, Moshe;Gefen, Yuval
• 通讯作者: Gefen, Yuval