Pomerol

Official Resources

• Homepage: https://github.com/pomerol-ed/pomerol
• Documentation: https://github.com/pomerol-ed/pomerol/wiki
• Source Repository: https://github.com/pomerol-ed/pomerol
• License: GNU General Public License v2.0

Overview

Pomerol is an exact diagonalization (full ED) code written in C++ for solving condensed matter second-quantized models of interacting fermions and bosons on finite size lattices at finite temperatures. It is designed to produce single and two-particle Green's functions and can be used as an impurity solver in DMFT calculations. Pomerol uses Lehmann representation for efficient computation.

Scientific domain: Exact diagonalization, quantum impurity solvers, DMFT
Target user community: Researchers needing exact solutions for small quantum systems

Theoretical Methods

• Exact diagonalization (full ED)
• Lehmann representation
• Finite size lattices
• Finite temperature formalism
• Fermions and bosons
• Green's function calculations
• Two-particle correlation functions

Capabilities (CRITICAL)

• Exact diagonalization for quantum models
• Single-particle Green's functions
• Two-particle Green's functions
• Finite temperature calculations
• Fermionic and bosonic systems
• Impurity solver for DMFT
• Real-frequency spectral functions (no analytical continuation)
• Lehmann representation for efficiency
• C++ implementation
• Python interface (pomerol2triqs)
• Integration with TRIQS

Sources: Official Pomerol repository (https://github.com/pomerol-ed/pomerol), confirmed in 6/7 source lists

Inputs & Outputs

Input formats:

• Hamiltonian definition (C++ or Python)
• System parameters
• Temperature
• Frequency grids

Output data types:

• Green's functions (real and Matsubara frequencies)
• Two-particle correlation functions
• Spectral functions
• Observables
• Energy eigenvalues

Interfaces & Ecosystem

• TRIQS: pomerol2triqs provides TRIQS interface
• DCore: Can use Pomerol as impurity solver
• C++: Native C++ implementation
• Python: Python bindings available
• libcommute: Uses libcommute for operator algebra

Limitations & Known Constraints

• Limited to small systems (exponential scaling)
• Hilbert space must be manageable
• Memory intensive
• Not suitable for large multi-orbital systems
• Bath discretization affects accuracy
• Exact solver: computationally expensive
• Best for small clusters or impurity problems

Comparison with Other Codes

Verification & Sources

Primary sources:

1. GitHub repository: https://github.com/pomerol-ed/pomerol
2. Documentation: https://github.com/pomerol-ed/pomerol/wiki
3. pomerol2triqs: https://github.com/pomerol-ed/pomerol2triqs

Secondary sources:

1. TRIQS benchmarks (includes Pomerol)
2. DCore documentation (lists Pomerol as solver)
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 repository: ACCESSIBLE (GitHub)
• Documentation: ACCESSIBLE (Wiki)
• Source code: OPEN (GitHub, GPL v2)
• TRIQS integration: CONFIRMED (pomerol2triqs)
• Active development: Regular updates
• C++ implementation: Efficient
• Exact solver: No approximations