PyGW

PyGW is an electronic structure code for performing G0W0 and GW0 quasiparticle calculations on realistic materials. Implemented as a hybrid Fortran/Python code, it bridges computational efficiency with modern scripting capabilities for G…

2. TDDFT & EXCITED-STATE 2.3 GW Methods VERIFIED
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Overview

PyGW is an electronic structure code for performing G0W0 and GW0 quasiparticle calculations on realistic materials. Implemented as a hybrid Fortran/Python code, it bridges computational efficiency with modern scripting capabilities for GW calculations in condensed matter physics.

Reference Papers

Reference papers are not yet linked for this code.

Full Documentation

Official Resources

  • Homepage: https://github.com/lechifflier/PyGW
  • Documentation: https://github.com/lechifflier/PyGW#readme
  • Source Repository: https://github.com/lechifflier/PyGW
  • License: Open Source

Overview

PyGW is an electronic structure code for performing G0W0 and GW0 quasiparticle calculations on realistic materials. Implemented as a hybrid Fortran/Python code, it bridges computational efficiency with modern scripting capabilities for GW calculations in condensed matter physics.

Scientific domain: Quasiparticle band structures, band gap calculations, electronic excitations
Target user community: Condensed matter physicists studying electronic properties of materials

Theoretical Methods

  • G0W0 approximation
  • GW0 (eigenvalue self-consistent)
  • Many-body perturbation theory
  • Screened Coulomb interaction
  • Quasiparticle corrections
  • Plane-wave / pseudopotential framework

Capabilities (CRITICAL)

  • G0W0 quasiparticle energies
  • GW0 self-consistent eigenvalues
  • Band structure calculations
  • Band gap predictions
  • Quasiparticle corrections to DFT
  • Bulk materials
  • Semiconductor and insulator systems

Sources: Official GitHub repository

Key Strengths

Fortran/Python Hybrid:

  • Computational efficiency from Fortran
  • User-friendly Python interface
  • Modern workflow integration
  • Scriptable calculations

GW Implementations:

  • Standard G0W0 calculations
  • GW0 self-consistency
  • Proven methodology
  • Materials science focus

Realistic Materials:

  • Production-quality calculations
  • Plane-wave accuracy
  • Pseudopotential efficiency
  • Solid-state applications

Inputs & Outputs

  • Input formats:

    • DFT wavefunctions and eigenvalues
    • Pseudopotential files
    • Python configuration
  • Output data types:

    • Quasiparticle energies
    • Band structures
    • Band gaps
    • Self-energy data

Interfaces & Ecosystem

  • DFT Integration:

    • Requires DFT input (wavefunctions, eigenvalues)
    • Interfaces with plane-wave DFT codes
  • Python scripting:

    • Python driver scripts
    • Workflow automation
    • Post-processing capabilities

Performance Characteristics

  • Speed: Fortran computational core
  • Accuracy: Standard GW precision
  • System size: Typical GW scaling
  • Memory: Plane-wave requirements

Computational Cost

  • G0W0: Single-shot calculation
  • GW0: Multiple iterations for self-consistency
  • Scaling: O(N^4) typical GW scaling

Limitations & Known Constraints

  • Documentation: Limited compared to major codes
  • DFT interface: Requires specific input format
  • Development: Smaller community

Comparison with Other Codes

  • vs BerkeleyGW: PyGW smaller, BerkeleyGW more features
  • vs Yambo: Different interface and workflow
  • Unique strength: Fortran/Python hybrid design

Application Areas

Semiconductors:

  • Band gap calculations
  • Quasiparticle corrections
  • Electronic structure

Insulators:

  • Accurate band gaps
  • Beyond-DFT corrections
  • Materials screening

Community and Support

  • Open-source on GitHub
  • Academic development
  • Limited but growing documentation

Verification & Sources

Primary sources:

  1. Official GitHub: https://github.com/lechifflier/PyGW
  2. Active development (2024 commits)

Confidence: VERIFIED

  • GitHub repository: ACCESSIBLE
  • Active development: Yes
  • Working implementation: Confirmed

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