论文标题
关于解决优化问题的比较研究，量子较少
A Comparative Study On Solving Optimization Problems With Exponentially Fewer Qubits
论文作者
论文摘要
量子量子优化算法（例如变异量子本质量（VQE）或量子近似优化算法（QAOA））是研究最多的量子算法之一。在我们的工作中，我们根据VQE评估和改进了算法，该算法与QAOA相比使用量子较少。我们强调了通过将问题编码到变异的ANSATZ中而产生的数值不稳定性，并提出了一个经典优化程序，以更少或更好或类似的目标以更少的迭代方式找到ANSATZ的地面。此外，我们比较了对二次无约束的二进制优化和图形分配问题的各种ANSATZ的经典优化器。
Variational Quantum optimization algorithms, such as the Variational Quantum Eigensolver (VQE) or the Quantum Approximate Optimization Algorithm (QAOA), are among the most studied quantum algorithms. In our work, we evaluate and improve an algorithm based on VQE, which uses exponentially fewer qubits compared to the QAOA. We highlight the numerical instabilities generated by encoding the problem into the variational ansatz and propose a classical optimization procedure to find the ground-state of the ansatz in less iterations with a better or similar objective. Furthermore, we compare classical optimizers for this variational ansatz on quadratic unconstrained binary optimization and graph partitioning problems.
