参数估计、模型降阶与量子滤波
Parameter Estimation, Model Reduction and Quantum Filtering
摘要:
本论文主要研究量子滤波中的参数估计和模型降阶问题。第2章和第3章提供了经典和量子概率论,随机微积分和过滤的审查。第四章研究了量子参数估计问题,介绍了量子粒子滤波作为一种实用的连续测量参数估计计算方法。第五章将这些技术应用于地磁测量,并研究了双通原子磁力仪中的估计不确定度标度。第六章提出了一种有效的连续时间量子纠错反馈控制器。第七章给出了集体量子比特系统对称过程的精确模型。
英文摘要:
This dissertation explores the topics of parameter estimation and model reduction in the context of quantum filtering. Chapters 2 and 3 provide a review of classical and quantum probability theory, stochastic calculus and filtering. Chapter 4 studies the problem of quantum parameter estimation and introduces the quantum particle filter as a practical computational method for parameter estimation via continuous measurement. Chapter 5 applies these techniques in magnetometry and studies the estimator's uncertainty scalings in a double-pass atomic magnetometer. Chapter 6 presents an efficient feedback controller for continuous-time quantum error correction. Chapter 7 presents an exact model of symmetric processes of collective qubit systems.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。