pawpyseed

Official Resources

• Homepage: https://github.com/kylebystrom/pawpyseed
• GitHub: https://github.com/kylebystrom/pawpyseed
• Documentation: https://pawpyseed.readthedocs.io/
• PyPI: https://pypi.org/project/pawpyseed/
• License: BSD 3-Clause License

Overview

pawpyseed is a parallel C/Python package for numerical analysis of PAW (Projector Augmented Wave) DFT wavefunctions from VASP calculations. It enables reconstruction of all-electron wavefunctions from pseudo-wavefunctions and PAW projectors, essential for accurate defect analysis and wavefunction overlap calculations.

Scientific domain: Wavefunction analysis, PAW method, defect physics Target user community: Researchers studying defects, core-level properties, and wavefunction character in VASP calculations

Theoretical Background

pawpyseed implements PAW wavefunction reconstruction:

• All-electron wavefunction: |ψ_AE⟩ = |ψ̃⟩ + Σ_i (|φ_i⟩ - |φ̃_i⟩)⟨p̃_i|ψ̃⟩
• Pseudo-wavefunction from WAVECAR
• PAW projectors from POTCAR
• Core reconstruction for accurate overlaps
• Defect wavefunction localization analysis

Capabilities (CRITICAL)

• Wavefunction Reconstruction: Full all-electron wavefunctions from PAW
• PAW Analysis: Projector function handling and core reconstruction
• Overlap Calculations: Accurate wavefunction overlaps including core
• Defect Analysis: Defect wavefunction characterization and localization
• Band Decomposition: Decompose defect states into bulk bands
• Charge Analysis: Core and valence charge separation
• Parallel Processing: C backend for performance

Key Strengths

PAW Reconstruction:

• Full all-electron wavefunctions
• Core state reconstruction
• Accurate for core-level properties
• Proper PAW augmentation

Defect Physics:

• Defect wavefunction localization
• Bulk band decomposition
• Transition level analysis
• Configuration coordinate diagrams

Performance:

• C backend for speed
• Parallel processing
• Efficient WAVECAR reading
• Memory-optimized

Python Interface:

• Clean Python API
• NumPy integration
• Scriptable analysis
• Jupyter compatible

Inputs & Outputs

• Input formats:

  • WAVECAR (pseudo-wavefunctions)
  • POTCAR (PAW projectors)
  • POSCAR (structure)

• Output data types:

  • All-electron wavefunctions
  • Overlap matrices
  • Charge densities
  • Decomposition coefficients

Interfaces & Ecosystem

• Python integration:

  • NumPy for arrays
  • SciPy for linear algebra
  • Matplotlib for visualization

• VASP compatibility:

  • Standard VASP output files
  • PAW pseudopotentials
  • Gamma and k-point calculations

Installation

pip install pawpyseed

From source (for development):

git clone https://github.com/kylebystrom/pawpyseed.git
cd pawpyseed
pip install -e .

Usage Examples

from pawpyseed.core.wavefunction import Wavefunction
from pawpyseed.core.projector import Projector

# Load wavefunction
wf = Wavefunction.from_directory("path/to/vasp/calc")

# Get all-electron wavefunction
ae_wf = wf.get_ae_wavefunction(band=0, kpoint=0, spin=0)

# Calculate overlap
overlap = wf.band_overlap(wf2, band1=0, band2=0)

# Defect analysis
from pawpyseed.analysis.defect import DefectAnalysis
defect = DefectAnalysis(bulk_wf, defect_wf)
decomposition = defect.get_decomposition()

Performance Characteristics

• Speed: C backend, parallel processing
• Memory: Efficient for large WAVECAR files
• Accuracy: Full PAW reconstruction
• Scalability: Handles large supercells

Limitations & Known Constraints

• VASP-specific: Only works with VASP PAW calculations
• POTCAR required: Needs PAW projector data
• Memory: Large supercells need significant RAM
• Compilation: C extension requires compiler

Comparison with Other Tools

• vs pymatgen: pawpyseed specialized for PAW wavefunctions
• vs VaspBandUnfolding: Different focus (PAW vs unfolding)
• Unique strength: Full all-electron PAW reconstruction, defect analysis

Application Areas

• Point defect characterization
• Defect transition levels
• Core-level spectroscopy
• Wavefunction localization
• Band decomposition analysis
• Configuration coordinate diagrams

Best Practices

• Use consistent POTCAR for bulk and defect
• Check wavefunction normalization
• Verify overlap convergence
• Use appropriate supercell size

Community and Support

• GitHub issue tracker
• Documentation with examples
• Active development

Verification & Sources

Primary sources:

1. GitHub repository: https://github.com/kylebystrom/pawpyseed
2. K. Bystrom et al., related publications

Confidence: VERIFIED

Verification status: ✅ VERIFIED

• Official homepage: ACCESSIBLE
• Documentation: AVAILABLE
• Source code: OPEN (GitHub, BSD 3-Clause)
• Developer: Kyle Bystrom
• Active development: Maintained