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

非技术总结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位的属性-量子比特对于存储和处理量子计算机中的数据非常重要。这些量子比特(量子比特)的基本元素是自旋态，即作为基本粒子(如电子)的量子力学属性的角动量。对这些构件的表征和研究有助于确定如何使量子计算机可靠和可扩展。PI将开发计算工具来了解不同材料及其量子比特的关键性质。这些特性包括支持复杂的计算机应用(量子相干)、读取高保真信息(量子读出)和高效传输信息(量子传输)的能力。对不同材料的这些属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)的表现，然后再进行实验来观察它们的行为。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暑期训练营加强物理化学本科生教育，通过新课程和REU计划发展计算材料研究，通过UCSC WISE计划通过组织咖啡时间和研讨会支持妇女和未被充分代表的群体。技术总结该项目的总体目标是开发第一原理计算平台来研究量子信息科学(QIS)中的关键物理过程-量子相干、读出和自旋量子比特的转换。理解激发态和自旋量子位弛豫与退相干的动力学是基于自旋的QIS的核心问题。量子相干决定了自旋态的持续时间或信息的完好无损；量子比特的读出效率决定了人们能否从量子比特中高保真地提取信息；量子传输决定了量子信息能否在量子比特之间进行远距离的传输和通信。所有这些性质都是特定于材料的，大部分都是通过简化的模型计算出来的，这些简化模型需要事先从实验中输入。在这个项目中，PI旨在开发一个完全第一原理的计算平台来解决自旋量子比特的这些问题，这些问题不需要事先输入参数。一般的方法是利用PI为解决环境耦合而开发的开放量子系统的从头算密度矩阵动力学框架，具有对自旋量子比特的量子弛豫和相干时间的预测能力，以及通过自旋-光子接口的自旋量子比特初始化和读出效率。后者将包括辐射、非辐射和包括多体相互作用在内的系统间交叉率的输入。从第一性原理对这些物理参数的准确预测将消除对一般系统预先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，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暑期训练营加强物理化学本科教育，通过新课程和REU计划发展计算材料研究，通过加州大学洛杉矶分校WISE计划组织咖啡时间和研讨会来支持妇女和代表性不足的群体。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.