论文标题
热对流流的杂交量子古典储层计算
Hybrid quantum-classical reservoir computing of thermal convection flow
论文作者
论文摘要
我们通过混合量子 - 古典储层计算模型模拟了洛伦兹型模型的非线性混沌动力学，以3和8度的自由度。高维量子储层动力学是由旋转并纠缠张量量量子态的单个量子位的通用量子门确定的。量子储层计算模型与其经典对应物的比较表明，经典储层的相同预测和重建功能可以通过一些强烈的纠缠Qubits获得数千个感知者。我们证明，当将储层分解为可分离的Qubits子集时，量子储层计算算法的测试阶段中模型输出和地面真相之间的均一误差增加。此外，量子储层计算模型是在真正的噪声IBM量子计算机上实现的，最多可以使用7 QUAT。因此，我们的工作为在高维相空间中使用算法有效地在高维相空间中建模的动力学打开了大门，该算法需要少量的Qubits。
We simulate the nonlinear chaotic dynamics of Lorenz-type models for a classical two-dimensional thermal convection flow with 3 and 8 degrees of freedom by a hybrid quantum--classical reservoir computing model. The high-dimensional quantum reservoir dynamics are established by universal quantum gates that rotate and entangle the individual qubits of the tensor product quantum state. A comparison of the quantum reservoir computing model with its classical counterpart shows that the same prediction and reconstruction capabilities of classical reservoirs with thousands of perceptrons can be obtained by a few strongly entangled qubits. We demonstrate that the mean squared error between model output and ground truth in the test phase of the quantum reservoir computing algorithm increases when the reservoir is decomposed into separable subsets of qubits. Furthermore, the quantum reservoir computing model is implemented on a real noisy IBM quantum computer for up to 7 qubits. Our work thus opens the door to model the dynamics of classical complex systems in a high-dimensional phase space effectively with an algorithm that requires a small number of qubits.
