论文标题
针对部分微分方程的量子风格的变分算法：应用于金融衍生品定价
Quantum-inspired variational algorithms for partial differential equations: Application to financial derivative pricing
论文作者
论文摘要
变异量子蒙特卡洛（VMC）与神经网络量子状态结合使用，在特定类别的部分微分方程（PDES）中遇到的差异性象征性的攻击角度具有新颖的攻击角度；也就是说，相关的时间依赖于时间依赖的schrödinger方程。在本文中，我们提出了适用于任意时间依赖性PDE的VMC的简单概括，展示了多项资产黑choles PDE中的技术，用于定价欧洲选项，包括许多相关的基础资产。
Variational quantum Monte Carlo (VMC) combined with neural-network quantum states offers a novel angle of attack on the curse-of-dimensionality encountered in a particular class of partial differential equations (PDEs); namely, the real- and imaginary time-dependent Schrödinger equation. In this paper, we present a simple generalization of VMC applicable to arbitrary time-dependent PDEs, showcasing the technique in the multi-asset Black-Scholes PDE for pricing European options contingent on many correlated underlying assets.
