论文标题
快速，稳定的决定量量子蒙特卡洛
Fast and stable determinant quantum Monte Carlo
论文作者
论文摘要
我们评估了费米的多体量子蒙特卡洛模拟中使用的数值稳定方法。特别是，我们从经验上比较各种矩阵分解和反转方案，以控制对确定性量子蒙特卡洛（DQMC）框架中相等时间和时间脱落的绿色功能的计算中产生的数值不稳定性。基于此比较，我们确定了一个基于枢轴QR分解的过程，该过程既有效又准确，既适合机器精度。 Julia编程语言用于评估和实现所有讨论的算法，并在开放式软件库Statbabledqmc.jl [http://github.com/crstnbr/stabledqmc.jl]中提供。
We assess numerical stabilization methods employed in fermion many-body quantum Monte Carlo simulations. In particular, we empirically compare various matrix decomposition and inversion schemes to gain control over numerical instabilities arising in the computation of equal-time and time-displaced Green's functions within the determinant quantum Monte Carlo (DQMC) framework. Based on this comparison, we identify a procedure based on pivoted QR decompositions which is both efficient and accurate to machine precision. The Julia programming language is used for the assessment and implementations of all discussed algorithms are provided in the open-source software library StableDQMC.jl [http://github.com/crstnbr/StableDQMC.jl].
