EDIpack

Official Resources

• Homepage: https://edipack.github.io/EDIpack/
• Documentation: https://edipack.github.io/EDIpack/
• Source Repository: https://github.com/EDIpack/EDIpack
• License: GNU General Public License v3.0

Overview

EDIpack is a massively parallel exact diagonalization solver for generic quantum impurity problems. It uses Lanczos-based methods to solve multi-orbital impurity models, providing an alternative to quantum Monte Carlo approaches. EDIpack is particularly suited for problems where exact solutions are needed or where QMC suffers from sign problems, and it can handle electron-phonon coupling.

Scientific domain: Exact diagonalization, quantum impurity solvers, DMFT
Target user community: Researchers needing exact impurity solutions or studying systems with sign problems

Theoretical Methods

• Exact diagonalization (ED)
• Lanczos algorithm
• Massively parallel execution
• Multi-orbital Anderson impurity model
• Electron-phonon coupling
• Zero-temperature and finite-temperature
• Superconducting states
• Spin-non-conserving problems

Capabilities (CRITICAL)

• Exact diagonalization impurity solver
• Multi-orbital quantum impurity problems
• Massively parallel (MPI parallelization)
• Zero-temperature solutions
• Finite-temperature properties
• Electron-phonon coupling support
• Superconducting (s-wave) systems
• Spin-non-conserving Hamiltonians
• Green's functions and observables
• Spectral functions (no analytical continuation needed)
• Real-frequency results
• Integration with DMFT frameworks

Sources: Official EDIpack documentation (https://edipack.github.io/EDIpack/), A. Amaricci et al., Comput. Phys. Commun. 273, 108261 (2022)

Inputs & Outputs

Input formats:

• Bath parameters
• Interaction parameters
• Impurity Hamiltonian
• Configuration files

Output data types:

• Green's functions (real and imaginary frequencies)
• Self-energies
• Spectral functions
• Observables
• Energy levels and eigenstates
• Partition function

Interfaces & Ecosystem

• DMFT frameworks: Can be used as impurity solver
• Fortran: Fortran-based with library interface
• MPI: Distributed memory parallelization
• SciFortran: Uses SciFortran library

Limitations & Known Constraints

• Limited to relatively small Hilbert spaces
• Bath discretization required
• Memory intensive for large problems
• Computational cost scales exponentially with system size
• Truncation of Hilbert space necessary for large problems
• Not suitable for very large multi-orbital systems
• Real-frequency only (advantage: no analytical continuation)

Performance Characteristics

• Massively Parallel: Designed for distributed memory systems using MPI, scaling to large core counts.
• Sub-linear Scaling: Optimized Fock basis organization minimizes inter-processor communication.
• Efficiency: Uses Lanczos and Arnoldi algorithms (with internal restarts) for efficient ground state and spectral calculations.
• Memory Management: Distributed storage of the Hamiltonian and vectors.

Comparison with Other Codes

Verification & Sources

Primary sources:

1. Official documentation: https://edipack.github.io/EDIpack/
2. GitHub repository: https://github.com/EDIpack/EDIpack
3. A. Amaricci et al., Comput. Phys. Commun. 273, 108261 (2022) - EDIpack paper

Secondary sources:

1. EDIpack tutorials and examples
2. Published applications using EDIpack
3. Exact diagonalization literature
4. Confirmed in 6/7 source lists (claude, g, gr, k, m, q)

Confidence: VERIFIED - Appears in 6 of 7 independent source lists

Verification status: ✅ VERIFIED

• Official homepage: ACCESSIBLE
• Documentation: COMPREHENSIVE
• Source code: OPEN (GitHub, GPL v3)
• Active development: Regular updates
• Academic citations: Growing user base
• Massively parallel: Significant scalability