Silicon Photonics for Quantum Computing

用于量子计算的硅光子学

• 批准号: RGPIN-2021-03163
• 负责人: Chrostowski, Lukas
• 金额: $ 5.54万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752068
• 关键词: Silicon; Photonics; Quantum; Computing

The most ambitious application for silicon photonics - Chrostowski's expertise - is in quantum computing. Quantum computing is expected to deliver the next leap in information technology, with anticipated impacts as significant as the development of silicon integrated circuits and the Internet. Quantum computing (QC) differs from classical computing in that particles (electrons, photons) that store bits of information (a quantum bit or "qubit") can exist as a linear combination of states (called superposition), whereas a classical bit can only be in one state. Superposition, together with correlations between qubits (entanglement), offer quantum computers (QCs) an exponential advantage over classical computers, where even 100 qubit QCs would outperform supercomputers with trillions of classical transistors. This would allow us to solve some of the world's most pressing computational and societal problems that are unsolvable by classical computers. QC will enable breakthroughs in fields as diverse as chemical design (e.g. enzymes for carbon capture), material design (e.g. batteries), precision health, optimization, and artificial intelligence. There are several hardware approaches being pursued in industry: the leading contenders are based on superconducting (IBM, Google) and trapped ion (IonQ, Honeywell) qubits. New contenders are based on spins in silicon (Intel) and photonics (PsiQuantum, Xanadu). These silicon-based approaches offer the potential for scaling to millions of qubits owing to the small device size and wafer-scale manufacturing. There are now two prominent silicon photonics QC start-ups, PsiQuantum in California, and Xanadu in Toronto, which have raised $509M and $36M, respectively. This proposal aims to develop a new architecture that has the potential to solve the challenges faced by the above approaches. We propose to develop a silicon-based platform that uses implanted donors as electron spin qubits with photonics used for the interconnects. This hybrid electro-optic approach makes use of two key advantages - electrons make excellent memories (qubits), while photons are excellent for communication (entanglement). This research program will fund 4 PhD, 3 MASc and 8 undergraduate students to design, fabricate, and test photonic devices for quantum computing using silicon donor spin qubits, with the long-term goal of developing all ingredients necessary to build a scalable fault-tolerant QC. Trainees will build experimental apparatus for testing at cryogenic temperatures, design novel nano-photonic components for quantum information processing (single photon sources and detectors, spin qubit to photon coupling using resonators, low-loss optical switches), develop novel fabrication techniques using infrastructure from a recent CFI Innovation grant, and demonstrate qubit operation in a scalable architecture. The HQP trained will be in a position to translate the research and technology into new commercial enterprises.

硅光子学最雄心勃勃的应用是量子计算，这也是克罗斯特斯基的专长。量子计算有望带来信息技术的下一个飞跃，其预期影响与硅集成电路和互联网的发展一样重要。量子计算（QC）与经典计算的不同之处在于，存储信息比特（量子比特或“量子位”）的粒子（电子、光子）可以作为状态的线性组合（称为叠加）存在，而经典比特只能处于一种状态。叠加以及量子比特之间的相关性（纠缠）为量子计算机（qc）提供了比经典计算机指数级的优势，在经典计算机中，即使是100个量子比特的量子计算机也会超过拥有数万亿个经典晶体管的超级计算机。这将使我们能够解决一些世界上最紧迫的计算和社会问题，这些问题是经典计算机无法解决的。QC将在化学设计（如用于碳捕获的酶）、材料设计（如电池）、精准健康、优化和人工智能等多个领域实现突破。工业上正在追求几种硬件方法：主要的竞争者是基于超导（IBM， b谷歌）和捕获离子（IonQ，霍尼韦尔）量子比特。新的竞争者基于硅（英特尔）和光子学（PsiQuantum, Xanadu）的自旋。由于器件尺寸小和晶圆级制造，这些基于硅的方法提供了扩展到数百万量子位的潜力。现在有两家著名的硅光子学QC初创公司，加州的PsiQuantum和多伦多的Xanadu，分别筹集了5.09亿美元和3600万美元。本提案旨在开发一种新的架构，该架构具有解决上述方法面临的挑战的潜力。我们建议开发一种基于硅的平台，该平台使用植入的供体作为电子自旋量子比特，并使用光子学用于互连。这种混合电光方法利用了两个关键优势——电子具有出色的存储能力（量子比特），而光子具有出色的通信能力（纠缠）。该研究项目将资助4名博士，3名MASc和8名本科生设计，制造和测试使用硅供体自旋量子比特的量子计算光子器件，其长期目标是开发构建可扩展容错QC所需的所有成分。学员将建立用于低温测试的实验装置，设计用于量子信息处理的新型纳米光子组件（单光子源和探测器，使用谐振器的自旋量子比特到光子耦合，低损耗光开关），利用最近获得的CFI创新资助的基础设施开发新型制造技术，并演示可扩展架构中的量子比特操作。受过培训的HQP将能够将研究和技术转化为新的商业企业。