libdlr: Efficient imaginary time calculations using the discrete Lehmann representation

• DOI: 10.1016/j.cpc.2022.108458
• Publication Date: 2022-07-08T05:03:23Z
• Authors: Jason Kaye; Kun Chen; Hugo U.R. Strand
• Keywords: The Imaginary; Representation; Imaginary time

We introduce libdlr, a library implementing the recently introduced discrete Lehmann representation (DLR) of imaginary time Green's functions. The DLR basis consists collection exponentials chosen by interpolative decomposition to ensure stable and efficient recovery functions from or Matsbuara frequency samples. provides subroutines build grids, carry out various standard operations. simplicity makes it straightforward incorporate into existing codes as replacement for less representations functions, libdlr is intended facilitate this process. written in Fortran, C header interface, contains Python module pydlr. also stand-alone Julia implementation, Lehmann.jl.