Open-source tools for imaginary-time Green's functions in quantum many-body physics: compact representations (intermediate representation, discrete Lehmann representation, minimal pole representations), sparse sampling, and analytic continuation.

Website: spm-lab.github.io, the entry point to everything below.

Start at the sparse-ir documentation: an overview, the history and comparison of IR, DLR and MiniPole, the shared notation, and a guide to the libraries.

• Tutorial (Python and Julia notebooks): sparse-ir-tutorial

sparse-ir-rs is the shared backend: its C API is what sparse-ir (via pylibsparseir) and SparseIR.jl (via libsparseir_jll) call, and it ships the Fortran bindings. New features, such as MiniPole/ESPRIT and the DLR built without an IR basis, land there first.

• MiniPole (recommended) — minimal pole representation, in sparse-ir-rs
• SpM — sparse modeling analytic continuation (C++)
• pySpMAC — sparse modeling analytic continuation (Python)
• admmsolver — a general ADMM solver (Python)
• Nevanlinna.jl — Nevanlinna analytic continuation (Julia); not recommended, as it is very sensitive to noise in the input data. Use MiniPole instead.

These are superseded and kept for reference:

Open them in SpM-lab/.github. Issues about a single library belong in that library's repository.