Code and Data Repository for Two-Stage Estimation and Variance Modeling for Latency-Constrained Variational Quantum Algorithms
提出一种两阶段估计算法，通过分别构建目标函数及其方差的局部模型，减少与量子计算机的通信次数并应对非凸优化问题，适用于QAOA等变分量子算法。
The key idea behind the proposed algorithm involves constructing two separate local models in each iteration: a model of the objective function, and a model of the variance of the objective function. Exploiting the variance model allows us to both restrict the number of communications with the quantum computer, and also helps navigate the nonconvex objective landscapes typical in the QAOA optimization problems.