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

原则上，量子计算机可以利用原子和分子的物理特性来执行从密码破译到材料模拟的各种计算，其算法速度比任何传统的超级计算机都要快。建造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种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，我们将研究最先进的量子纠错方案，即表面代码，在映射到现实的物理架构时是如何表现的。如果成功，这项研究将帮助实验学家建造第一台通用的可扩展量子计算机。这项研究将培养量子信息科学领域的研究生和本科生，并为他们提供与IBM的工业合作者合作的机会。本提案通过探索实验设备，计算机架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%的表面编码是解决量子系统退相干和缺陷问题的一种很有前途的方法。计算通过拓扑缺陷的创建、消除和编织来完成。从算法和体系结构的角度检查这个过程将有助于揭示共同的结构，并为在真实的物理系统上实现这些思想提供精确的方法。我们将探索考虑到现实噪声模型和系统级约束的表面代码实现。我们的工作将利用我们之前在实验设备数据，量子电路合成工具，计算机体系结构，量子编程语言和编译器方面的工作。此外，我们将与IBM的Sergey Bravyi密切合作（包括我们的学生在IBM的暑期实习），为这项工作奠定理论基础。

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 we will examine how a state-of-the-art quantum error correction scheme, the surface code, behaves when mapped to realistic physical architectures. 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 our 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. We will explore surface code implementations that account for realistic noise models and system-level constraints. Our work will leverage our previous work in experimental device data, quantum circuit synthesis tools, computer architecture, and quantum programming languages and compilers. Additionally, we will collaborate closely with Sergey Bravyi at IBM (including summer internships at IBM for our students) on the theoretical foundations of this work.