论文标题
变化量子非正交优化
Variational Quantum Non-Orthogonal Optimization
论文作者
论文摘要
当前的通用量子计算机的嘈杂量表数量有限。因此，很难使用它们来解决大规模的复杂优化问题。在本文中，我们通过提出一种量子优化方案来解决此问题，其中离散的经典变量在量子系统的非正交状态中编码。我们开发了非正交量子态状态的情况，量子计算机上的单个量子位处理多个位经典变量。将这个想法与变异量子本素层（VQE）和量子状态层析成像相结合，我们表明，可以显着减少量子硬件所需的量子数量，以解决复杂的优化问题。我们通过仅使用15个QUBITS成功优化8度和15个变量的多项式来基准我们的算法。我们的建议在当今有限的量子硬件中开辟了解决现实生活中有用的优化问题的道路。
Current universal quantum computers have a limited number of noisy qubits. Because of this, it is difficult to use them to solve large-scale complex optimization problems. In this paper we tackle this issue by proposing a quantum optimization scheme where discrete classical variables are encoded in non-orthogonal states of the quantum system. We develop the case of non-orthogonal qubit states, with individual qubits on the quantum computer handling more than one bit classical variable. Combining this idea with Variational Quantum Eigensolvers (VQE) and quantum state tomography, we show that it is possible to significantly reduce the number of qubits required by quantum hardware to solve complex optimization problems. We benchmark our algorithm by successfully optimizing a polynomial of degree 8 and 15 variables using only 15 qubits. Our proposal opens the path towards solving real-life useful optimization problems in today's limited quantum hardware.
