libdlr: Efficient imaginary time calculations using the discrete Lehmann representation

We introduce libdlr, a library implementing the recently introduced discrete Lehmann representation (DLR) of imaginary time Green's functions. The DLR basis consists of a collection of exponentials chosen by the interpolative decomposition to ensure stable and efficient recovery of Green's functions from imaginary time or Matsubara frequency samples. The library provides subroutines to build the DLR basis and grids, and to carry out various standard operations. The simplicity of the DLR makes it straightforward to incorporate into existing codes as a replacement for less efficient representations of imaginary time Green's functions, and libdlr is intended to facilitate this process. libdlr is written in Fortran, provides a C header interface, and contains a Python module pydlr. We also introduce a stand-alone Julia implementation, Lehmann.jl.我们提出libdlr库，该库实现了新近提出的虚时格林函数的离散勒曼表示（discrete Lehmann representation, DLR）。DLR基由一组通过插值分解选取的指数函数构成，可确保从虚时或松原频率采样数据中稳定且高效地重构格林函数。该库提供了构建DLR基与网格、以及执行各类标准运算的子程序。DLR的简洁性使其可直接集成到现有代码中，作为虚时格林函数低效表示方法的替代方案，而libdlr正是为了简化这一流程而开发的。libdlr采用Fortran语言编写，提供C头文件接口，并包含Python模块pydlr。我们同时推出了独立的Julia语言实现Lehmann.jl。