Scanning Probe Fabrication and Readout of Atomically Precise Silicon Quantum Technologies

原子级精确硅量子技术的扫描探针制造和读出

• 批准号: 75574
• 金额: $ 23.35万
• 依托单位: NANOLAYERS RESEARCH COMPUTING LTD
• 依托单位国家: 英国
• 项目类别: Responsive Strategy and Planning
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=75574
• 关键词: Scanning; Probe; Fabrication; Readout; Atomically

Quantum computing promises tremendous advances in a number of applications, including finance, medicine, cryptography, and materials simulation. The fundamental computation element of a quantum computer is the quantum bit, or qubit, and to perform calculations that are truly transformative, huge numbers of qubits (potentially millions) are required. We propose to develop a process for fabricating many more qubits than have previously been made. Furthermore, we will do so using the material system silicon, which is directly compatible with the only ready-made industry currently available for largescale market production of a many qubit quantum computer.Our qubits will be made from impurity atoms in silicon, known as dopants. This is done using a scanning tunnelling microscope (STM), which "feels" the atoms on a surface with an extremely sharp probe tip, much like an audio record player feels the grooves of a vinyl record. Previously, only a pair of dopant qubits have been made, and with no route to scaling-up to a useful number. In order to move and see the millions of individual dopant atoms that will make up a quantum computer, we require advanced machine controls and data processing tools. Nanolayers Research Computing will use the proprietary machine learning software they have pioneered to train the STM to perform control and processing tasks on its own, without human user intervention. The use of this type of data processing, also known as artificial intelligence (AI), is particularly well-suited to image processing and pattern recognition, and can be used to find the proverbial "needle in a haystack". This is exactly what needs to be done when we use a scanning tunnelling microscope to move and then see a large collection of atoms in a silicon quantum computer component. In short, this project uses artificial intelligence to control an atomic resolution microscope and precisely position a large number of individual impurity atoms in silicon. This technology will enable the eventual fabrication of a silicon-based quantum computer.

量子计算有望在许多应用中取得巨大进展，包括金融，医学，密码学和材料模拟。量子计算机的基本计算元素是量子位，或者量子位，为了执行真正具有变革性的计算，需要大量的量子位（可能是数百万）。我们建议开发一种制造比以前制造的更多量子比特的方法。此外，我们将使用硅材料系统来实现这一目标，硅材料系统与目前唯一可用于大规模市场生产多量子比特量子计算机的现成工业直接兼容。我们的量子比特将由硅中的杂质原子制成，称为掺杂剂。这是使用扫描隧道显微镜（STM）完成的，它用一个非常锋利的探针尖端“感觉”表面上的原子，就像录音机感觉黑胶唱片的凹槽一样。以前，只制造了一对掺杂剂量子比特，并且没有扩大到有用数量的途径。为了移动和观察组成量子计算机的数百万个掺杂剂原子，我们需要先进的机器控制和数据处理工具。Nanolayers Research Computing将使用他们开创的专有机器学习软件来训练STM，使其能够在没有人类用户干预的情况下自行执行控制和处理任务。使用这种类型的数据处理，也被称为人工智能（AI），特别适合图像处理和模式识别，可以用来找到谚语中的“大海捞针”。这正是当我们使用扫描隧道显微镜移动，然后看到硅量子计算机组件中的大量原子时需要做的事情。简而言之，该项目利用人工智能控制原子分辨率显微镜，精确定位硅中大量单个杂质原子。这项技术将使硅基量子计算机的最终制造成为可能。