Quantum-inspired variational algorithms for partial differential equations: application to financial derivative pricing
将变分量子蒙特卡洛方法推广到任意时间依赖的偏微分方程，并用多资产Black-Scholes方程演示了欧洲期权定价，旨在缓解高维诅咒。
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.