学术报告
Quantum state tomography via linear regression estimation
题目： Quantum state tomography via linear regression estimation
报告人：齐 波 （中国科学院数学与系统科学研究院系统科学研究所副研究员）
摘要： In this talk, we first present a simple yet efficient state reconstruction algorithm of linear regression estimation (LRE) for quantum state tomography. For static state tomography, we can give an asymptotic mean squared error (MSE) upper bound for all possible states to be estimated, which depends explicitly upon the involved measurement bases. This analytical MSE upper bound can guide one to choose optimal measurement sets. The computational complexity of LRE is O(d^4) where d is the dimension of the quantum state. Numerical simulations show that LRE is much faster than the maximum-likelihood estimation. We further develop the LRE method to present a recursively adaptive quantum state tomography (RAQST) protocol that can greatly improve the precision of tomography. This RAQST protocol has been experimentally implemented on 2-qubit systems. Finally, we report a latest development that we can reconstruct a 14-qubit state within 4 hours by combing our LRE method with the parallel graphic processing unit programming.
时间：2016年1月6日（周三）10:30-11:30
地点：首都师范大学北一区文科楼510教室
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