AutoHF：一种利用自动微分直接能量最小化的通用哈特里-福克求解器
AutoHF: a general Hartree-Fock solver utilizing direct energy minimization with automatic differentiation
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中文总结 AI 辅助
介绍AutoHF这一通用平均场求解器，能绕过解读多体哈密顿量平均场形式过程，通过直接最小化变分能量找到最优斯莱特行列式，利用自动微分和优化工具，方便求解量子多费米子哈密顿量。
中文摘要 AI 辅助
我们展示了AutoHF，一种用于量子多费米子哈密顿量的通用且易于使用的平均场求解器。它允许用户绕过为每个多体哈密顿量\(H\)解读平均场形式的过程，避免为每个\(H\)编写定制程序。AutoHF通过直接最小化变分能量\(\langle H \rangle\)来找到最优斯莱特行列式\(|\Psi\rangle\)，其基于轨道系数并受对称约束。通过采用这种变分方法，AutoHF利用了机器学习社区开发的自动微分和优化工具不断增长的能力。
英文摘要
We present autohf, a general, easy-to-use mean-field solver for quantum many-fermion Hamiltonians. It allows the user to bypass the process of deciphering the mean-field form for each many-body Hamiltonian $H$ and thus avoid setting up a tailored program for each $H$. Rather, autohf finds the optimal Slater determinant $|Ψ\rangle$, written in terms of orbital coefficients and subject to symmetry constraints, by directly minimizing the variational energy $\langle H \rangle$. By embracing this variational approach, autohf makes use of the growing power of automatic differentiation and optimization tools developed by the machine learning community.
