Collaborative Research: PIF: Scalable Quantum Computers in the Presence of Physical Noise: a Study of Surface Codes with Realistic Errors at the Algorithmic Level

合作研究：PIF：存在物理噪声时的可扩展量子计算机：算法层面具有现实错误的表面代码研究

• 批准号: 1415461
• 负责人: Kenneth Brown
• 金额: $ 24万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1415461&HistoricalAwards=false
• 关键词: Collaborative; Research; PIF; Scalable; Quantum

In principle, quantum computers can use the physics of atoms and molecules to perform calculations ranging from code-breaking to simulation of materials algorithmically faster than any conventional supercomputer. The main challenge for building a quantum computer is that quantum components are prone to error. Error correction can be used to overcome this challenge but it places stringent requirements on future quantum computer hardware. The primary goal of this research is to develop a path for bridging the gap between current physical hardware and large-scale quantum algorithms. Specifically how a state-of-the-art quantum error correction scheme, the surface code, behaves when mapped to realistic physical architectures will be examined. If successful, this research will help experimentalists build the first universal scalable quantum computer. The research will train graduate students and undergraduate students in the growing field of quantum information science and provide them with an opportunity to work with industrial collaborators at IBM. This proposal expands the frontiers of physics by exploring quantum computation at the intersection of experimental devices, computer architecture, and quantum information theory. Surface codes with a computational error threshold of 1% are a promising solution to the problem of decoherence and imperfections in quantum systems. Computation is performed by the creation, annihilation, and braiding of topological defects. Examining this process from the perspective of algorithms and architectures will help reveal common structures and provide a precise method for implementation of these ideas on real physical systems. Surface code implementations that account for realistic noise models and system-level constraints will be examined. This will leverage previous work in experimental device data, quantum circuit synthesis tools, computer architecture, and quantum programming languages and compilers. Additionally, there will be close collaboration with Sergey Bravyi at IBM (including summer internships at IBM for students) on the theoretical foundations of this work.

原则上，量子计算机可以利用原子和分子的物理原理来执行计算，从密码破译到材料模拟，其算法速度比任何传统超级计算机都快。 构建量子计算机的主要挑战是量子组件容易出错。纠错可以用来克服这一挑战，但它对未来的量子计算机硬件提出了严格的要求。这项研究的主要目标是开发一条弥合当前物理硬件和大规模量子算法之间差距的途径。具体来说，将检查最先进的量子纠错方案（表面代码）在映射到现实物理架构时的表现。 如果成功，这项研究将帮助实验者构建第一台通用可扩展量子计算机。该研究将为不断发展的量子信息科学领域的研究生和本科生提供培训，并为他们提供与 IBM 的工业合作者合作的机会。该提案通过探索实验设备、计算机体系结构和量子信息理论的交叉点的量子计算，扩展了物理学的前沿。计算误差阈值为 1% 的表面码是解决量子系统退相干和缺陷问题的有希望的解决方案。计算是通过拓扑缺陷的创建、消灭和编织来进行的。 从算法和架构的角度检查这个过程将有助于揭示常见的结构，并为在真实物理系统上实现这些想法提供精确的方法。将检查考虑实际噪声模型和系统级约束的表面代码实现。 这将利用之前在实验设备数据、量子电路综合工具、计算机体系结构以及量子编程语言和编译器方面的工作。 此外，我们还将与 IBM 的 Sergey Bravyi 就这项工作的理论基础进行密切合作（包括学生在 IBM 的暑期实习）。