论文标题

TurrORVB:用于{\ it It ibiO}电子模拟的多体工具包通过量子蒙特卡洛

TurboRVB: a many-body toolkit for {\it ab initio} electronic simulations by quantum Monte Carlo

论文作者

Nakano, Kousuke, Attaccalite, Claudio, Barborini, Matteo, Capriotti, Luca, Casula, Michele, Coccia, Emanuele, Dagrada, Mario, Genovese, Claudio, Luo, Ye, Mazzola, Guglielmo, Zen, Andrea, Sorella, Sandro

论文摘要

TurpOrvb是用于{\ IT i i i i}量子蒙特卡洛(QMC)模拟分子和散装电子系统的计算套件。该代码实现了两种已建立的QMC算法:变异蒙特卡洛(VMC)和扩散的蒙特卡洛在其稳健有效的晶格正则化变体中。代码的一个关键特征是使用密切相关的多体波函数的可能性。电子波函数(WF)是通过将jastrow因子应用于最通用的平均场基态的jastrow因子(将动态相关性考虑在内,要么以旋转平均配对为反对称的Geminal产品,要么以pfaffian的形式写成,或者包括单线和三重相关性。该波函数可以看作是所谓的共鸣价键(RVB)ANSATZ的有效实施,该键首先是由L. Pauling和P. W. Anderson在量子化学和浓缩物理学中提出的。在TurborVB中实施的RVB ANSATZ具有很大的变化自由,包括Jastrow相关的Slater决定因素是其最简单但非平凡的情况。此外,它具有可负担得起的计算成本的显着优势,该计算成本与用于评估单个Slater决定因素的花费成正比。该代码实现了伴随算法分化,该算法分化能够对能量衍生物进行非常有效的评估,包括离子力。因此,可以在VMC水平的规范NVT集合中执行结构优化和分子动力学。对于电子部分,由于最小的能量最小化随机算法,使全WF优化成为可能。该代码通过使用混合MPI-OPENMP协议有效地平行,这也是利用现代GPU加速器的计算能力的理想环境。

TurboRVB is a computational package for {\it ab initio} Quantum Monte Carlo (QMC) simulations of both molecular and bulk electronic systems. The code implements two types of well established QMC algorithms: Variational Monte Carlo (VMC), and Diffusion Monte Carlo in its robust and efficient lattice regularized variant. A key feature of the code is the possibility of using strongly correlated many-body wave functions. The electronic wave function (WF) is obtained by applying a Jastrow factor, which takes into account dynamical correlations, to the most general mean-field ground state, written either as an antisymmetrized geminal product with spin-singlet pairing, or as a Pfaffian, including both singlet and triplet correlations. This wave function can be viewed as an efficient implementation of the so-called resonating valence bond (RVB) ansatz, first proposed by L. Pauling and P. W. Anderson in quantum chemistry and condensed matter physics, respectively. The RVB ansatz implemented in TurboRVB has a large variational freedom, including the Jastrow correlated Slater determinant as its simplest, but nontrivial case. Moreover, it has the remarkable advantage of remaining with an affordable computational cost, proportional to the one spent for the evaluation of a single Slater determinant. The code implements the adjoint algorithmic differentiation that enables a very efficient evaluation of energy derivatives, comprising the ionic forces. Thus, one can perform structural optimizations and molecular dynamics in the canonical NVT ensemble at the VMC level. For the electronic part, a full WF optimization is made possible thanks to state-of-the-art stochastic algorithms for energy minimization. The code has been efficiently parallelized by using a hybrid MPI-OpenMP protocol, that is also an ideal environment for exploiting the computational power of modern GPU accelerators.

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