Finding the optimal cluster state configuration. Minimization of one-way quantum computation errors

Quantum Process Tomography via L1-norm Minimization

For an initially well designed but imperfect quantum information system, the process matrix is almost sparse in an appropriate basis. Existing theory and associated computational methods (L1-norm minimization) for reconstructing sparse signals establish conditions under which the sparse signal can be perfectly reconstructed from a very limited number of measurements (resources). Although a direct extension to quantum process tomography of the L1-norm minimization theory has not yet emerged, the numerical examples presented here, which apply L1-norm minimization to quantum process tomography, s…

张量分解用于非克莱因门最小化

Tensor Decomposition for Non-Clifford Gate Minimization

本文提出利用张量分解方法优化Toffoli门和T计数，提升量子计算的容错性能。

利用人工神经网络最小化离子微运动

Minimization of ion micromotion with artificial neural network

针对线性Paul阱中离子微运动最小化的繁琐耗时问题，提出基于人工神经网络的机器学习方法，结合rf-光子关联技术快速找到电极最优电压以最小化微运动，实现高精度控制且可推广至其他阱构型。

High-performance Energy Minimization with Applications to Adiabatic Quantum Computing

Energy minimization of Ising spin-glasses has played a central role in statistical and solid-state physics, facilitating studies of phase transitions and magnetism. Recent proposals suggest using Ising spin-glasses for non-traditional computing as a way to harness the nature's ability to find min-energy configurations, and to take advantage of quantum tunneling to boost combinatorial optimization. Laboratory demonstrations have been unconvincing so far and lack a non-quantum baseline for definitive comparisons. In this work we (i) design and evaluate new computational techniques to simulate na…