CAREER: Quantum Coherence, Optical Readout, and Quantum Transduction for Spin Qubits from First-Principles Calculations

该奖项支持研究和教育，以开发计算方法来研究最小计算单元-量子比特的特性，量子比特对于在量子计算机中存储和操作数据非常重要。这些量子比特（量子位）具有自旋状态，角动量是基本粒子（如电子）的量子力学特性，是它们的基本元素。对这些构建块的描述和研究有助于确定如何使量子计算机可靠和可扩展。PI将开发计算工具来理解不同材料及其量子比特的关键特性。这些特性包括它们支持复杂计算机应用（量子相干性）、读取高保真信息（量子读出）和有效传输信息（量子转导）的能力。在进行实验观察它们的行为之前，对不同材料的这些特性进行建模将有助于预测它们在不同条件下（例如，不同温度下）的行为。该项目开发的方法将加速发现有望用于可扩展量子计算的材料。教育和推广计划包括通过夏季训练营加强物理化学本科教育，通过新课程和REU项目发展计算材料研究，并通过UCSC WiSE项目组织咖啡时间和研讨会支持妇女和代表性不足的群体。本项目的总体目标是开发第一性原理计算平台，以研究量子信息科学（QIS）中的关键物理过程-量子相干性，读出和自旋量子位的转导。理解激发态动力学和自旋量子比特的弛豫和退相干是基于自旋的量子信息系统的核心问题。量子相干性决定了自旋状态持续多久，或者信息将保持完整；量子比特读出效率决定了能否高保真地从量子比特中提取信息；量子转导决定了量子信息能否在量子比特之间长距离传输和通信。所有这些特性都是材料特有的，并且大多是通过简化模型计算出来的，这些模型需要事先从实验中输入。在这个项目中，PI的目标是开发一个完全的第一性原理计算平台，以解决不需要事先输入参数的自旋量子比特的这些问题。一般的方法是利用PI开发的开放量子系统的ab-initio密度矩阵动力学框架来解决环境耦合，具有自旋量子比特的量子弛豫和相干时间的预测能力，以及自旋量子比特初始化和通过自旋光子接口读出效率。后者将包括辐射、非辐射和系统间交叉速率的输入，包括多体相互作用。从第一原理对这些物理参数的准确预测将消除对一般系统的先验输入参数或简化模型的需要，并为设计新的量子材料开辟道路，例如新的自旋缺陷和量子比特网络，这将为量子信息科学的应用创造前所未有的性能。教育和推广计划包括通过夏季训练营加强物理化学本科教育，通过新课程和REU项目发展计算材料研究，并通过UCSC WiSE项目组织咖啡时间和研讨会支持妇女和代表性不足的群体。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

NONTECHNICAL SUMMARYThis award supports research and education to develop computational methods to investigate properties of smallest computation units – quantum bits that are important for storing and manipulating data in quantum computers. These quantum bits (qubits) have a spin state, an angular momentum that is a quantum mechanical property of an elementary particle, such as an electron, as their basic element. Characterizations and study of these building blocks help in determining how to make quantum computers dependable and scalable. The PI will develop computational tools to understand critical properties of different materials and their qubits. These properties include their ability to support complex computer applications (quantum coherence), to read high-fidelity information (quantum readout) and to transfer information efficiently (quantum transduction). Modelling these properties of different materials will help in predicting how they will behave in different conditions (for example, different temperatures) before performing experiments to observe their behavior. Methods developed in this project will accelerate discovery of materials that show promise for scalable quantum computing.The education and outreach plan includes strengthening undergraduate education on physical chemistry through summer bootcamp and developing computational materials research through new courses and REU programs, and supporting women and underrepresented groups through organizing coffee hours and seminars through UCSC WiSE program.TECHNICAL SUMMARYThe overarching goal of this project is to develop first-principles computational platforms to study critical physics processes in quantum information science (QIS) - quantum coherence, readout, and transduction of spin qubits. Understanding kinetics of excited states and spin qubit relaxation and decoherence is the core issue of spin-based QIS. Quantum coherence determines how long the spin state will last or the information will be intact; qubit readout efficiency determines if one can extract information from qubit with high fidelity; quantum transduction determines if quantum information can be transferred and communicated among qubits over a long range. All these properties are materials-specific, and have been mostly computed by simplified models which require prior inputs from experiments. In this project the PI aims to develop a fully first-principles computational platform to tackle these issues for spin qubits, which do not require prior input parameters.The general approach is to leverage the ab-initio density-matrix dynamics framework for open quantum systems that the PI has developed to resolve environmental couplings, have predictive capabilities for quantum relaxation and coherence time of spin qubit, as well as spin qubit initialization and readout efficiency through spin-photon interface. The latter will incorporate inputs of radiative, nonradiative and intersystem-crossing rates including many-body interactions. Accurate predictions of these physical parameters from first-principles will eliminate the need for prior input parameters or simplified models for general systems and open the path for designing novel quantum materials, such as new spin-defects and qubit network, which will create unprecedented performance for applications in quantum information science. The education and outreach plan include strengthening undergraduate education on physical chemistry through summer bootcamp and developing computational materials research through new courses and REU programs, and supporting women and underrepresented groups through organizing coffee hours and seminars through UCSC WiSE program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.