Scalable Qubit Array Detection for Rydberg Quantum Computers
Scalable Qubit Array Detection for Rydberg Quantum Computers
批准号:
10075055
负责人:
金额:
$54.15万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
该项目的重点是提高量子计算机的计算能力。这些新型计算机基于称为量子比特的构建模块,将能够模拟新材料和药物,优化物流和金融,并解决传统计算机无法处理的其他复杂问题。然而,目前的量子计算机还没有强大到足以执行这样的任务-量子比特的数量需要增长到数万甚至更多,以及使用量子比特执行操作并读取结果所需的光学和电子系统。在这个项目中,来自加拿大和英国的三家领先公司- Nuvu Cameras,Infleqtion和Riverlane将合作开发系统,以极大地改善特定类型量子位状态的读出:单个原子的阵列。在激光脉冲的照射下,这些原子根据其状态发出不同颜色或强度的光。因此,读取量子位的有效方法是基于拍摄这种阵列照片的高性能相机。这些相机必须具有高灵敏度,以精确确定每个量子位的状态,并将收集到的图像快速发送到控制电子设备,以便快速执行量子操作。Nuvu Cameras已经开发出相机,可在包含多达256个量子位的阵列的速度下提供高保真检测。这些相机必须能够扩展以实现更大阵列的高速读出,例如Infleqtion演示的1225量子位系统。此外,Nuvu的相机和Infleqtion管理量子计算机的电子设备之间必须实现紧密集成,以确保快速数据传输。Riverlane正在开发一种用于控制量子位和数据管理的新软件,该软件可扩展到数千个量子位,并将能够执行复杂的操作,例如纠正由量子位的噪声性质引起的潜在计算错误。Riverlane的控制系统将连接到Nuvu的摄像机和Infleqtion的量子位,在其可扩展的平台上展示高精度和快速的量子位读出。Infleqtion,Nuvu和Riverlane之间的合作伙伴关系将允许在量子计算供应链的这一领域进行合作开发,帮助Nuvu开发针对下一代QC的摄像机,Riverlane为其量子控制系统配备先进的读出能力,Infleqtion用于验证必要的硬件控制层。总之,这将使中性原子量子计算的持续长期增长成为可能。
英文摘要
This project focuses on improving the computational power of quantum computers. These new types of computers, based on building blocks called qubits, will be able to simulate new materials and medicines, optimize logistics and finance, and solve other problems that are too complex for classical computers to handle. However, current quantum computers are not yet powerful enough to perform such tasks -- the number of qubits needs to grow to tens of thousands and beyond, together with the optical and electronic systems needed to perform operations with qubits and read the results.In this project, three leading companies from Canada and the UK -- Nuvu Cameras, Infleqtion and Riverlane -- will collaborate to develop systems to greatly improve the readout of the status of a particular type of qubits: arrays of individual atoms. Illuminated by laser pulses, these atoms respond by shining light of different colour or intensity depending on their status. An effective way to read the qubits is thus based on high performing cameras that take pictures of such arrays. These cameras must be highly sensitive, to precisely determine the status of each qubit, and rapidly send the collected images to the control electronics, to allow execution of quantum operations at speed.Nuvu Cameras has already developed cameras providing high-fidelity detection at speed of arrays containing up to 256 qubits. These cameras must scale to enable high-speed readout of larger arrays, such as the 1225 qubit systems demonstrated by Infleqtion. Moreover, tight integration between Nuvu's cameras and Infleqtion's electronics managing the quantum computer must be realised to ensure fast data transfer. Riverlane is developing a new software for the control of qubits and data management that is scalable to thousands of qubits and will enable the execution of complex operations such as the correction of potential computational errors caused by the noisy nature of qubits. Riverlane's control system will connect to both Nuvu's cameras and Infleqtion's qubits, demonstrating qubit readout with high accuracy and at speed also in their scalable platform.The partnership between Infleqtion, Nuvu and Riverlane will allow for collaborative development in this area of the quantum computing supply chain, helping Nuvu to develop cameras targeting the next generation of QCs, Riverlane to equip their quantum control systems with advanced readout capabilities and Infleqtion to validate the necessary hardware control layer. Together, this will enable the continued long-term growth of neutral atom quantum computing.
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国内基金
海外基金
量子Qubit神经树网络模型的优化研究
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批准号:61502283
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项目类别:青年科学基金项目
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资助金额:20.0万元
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批准年份:2015
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负责人:齐峰
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依托单位: