Version 1.4.0 expands the N-layer and Mie workflows into documented, reproducible spectral-density pipelines with bundled reference data.

• Scan-layout spectral density now supports fixed-source Mie scan HDF5 files in mqed_calc_spec_dens and mqed_plot_spec_dens, preserving source/observer positions and selecting scan curves by physical distance.
• N-layer comparison examples add curated Green-tensor and spectral-density HDF5 files for direct quadrature, singularity-aware integration, and pole-aware hybrid DCIM comparisons.
• Reference plotting configs and figures provide ready-to-run direct-vs-singularity-aware and singularity-aware-vs-pole-aware hybrid DCIM spectral-density plots.
• New tutorials and theory pages document N-layer Sommerfeld integrals, singularity-aware pole extraction, hybrid DCIM, and Mie theory for spherical cavities.

See CHANGELOG.md for the full release notes.

git clone https://github.com/MQED-transport/Macroscopic-Quantum-Electrodynamics.git
cd Macroscopic-Quantum-Electrodynamics
conda env create -f environment.yaml
conda activate mqed
pip install -e .

conda install -c conda-forge mpi4py openmpi

# 1. Compute dyadic Green's function for an Ag planar interface
mqed_GF_Sommerfeld simulation.energy_eV=1.864

# 2. Compute dyadic Green's function for an N-layer planar stack
mqed_GF_NLayer --config-name GF_NLayer_five_layer

# 3. Run non-Hermitian dynamics
mqed_nhse

# 4. Plot mean-squared displacement
mqed_plot_msd

Override any parameter from the CLI:

mqed_nhse simulation.Nmol=50 simulation.d_nm=4.0

For step-by-step walkthroughs, see the Tutorials.

Tutorials and HTML documentation are still the best place for first-time users to learn the workflows. For quick terminal lookup, each installed command also supports Hydra's built-in help.

mqed_plot_msd --help
mqed_plot_msd --hydra-help
mqed_plot_msd --cfg job
mqed_plot_msd --info searchpath

• --help shows the app-level config view and common overrides.
• --hydra-help shows Hydra-specific flags such as --config-name and --multirun.
• --cfg job prints the composed job config without running the simulation.
• --info searchpath shows where Hydra is looking for configuration files.

All commands use Hydra YAML configs under configs/.

For personal workflows, you can also place local-only YAML files in local/configs/<group>/ and keep using the same command style:

mqed_plot_msd --config-name=my_msd
mqed_nhse --config-name=my_nhse

This keeps shared reproducible configs in configs/ while letting personal experiments live under local/ without changing your normal CLI habits. Keep local/ excluded locally with .git/info/exclude if those files should stay off GitHub.

See the Configuration Reference for full documentation.

Macroscopic-Quantum-Electrodynamics/
├── configs/           # Hydra YAML configurations
├── local/             # Personal local-only configs and notes (not tracked)
├── data/
│   └── example/       # Bundled example data (tracked in git)
│       ├── GF_data/   # Pre-computed Green's function caches
│       └── QD_data/   # Pre-computed quantum dynamics results
├── mqed/              # Package source
│   ├── Dyadic_GF/     # Fresnel / Sommerfeld integrals
│   ├── Lindblad/      # Lindblad & NHSE solvers
│   ├── analysis/      # RET, FE calculations
│   ├── plotting/      # MSD, IPR, RMSD, PR plots
│   ├── BEM/           # Boundary element method
│   └── utils/         # Shared helpers (units, HDF5 I/O, logging)
├── docs/              # Sphinx documentation source
├── test/              # Pytest test suite
└── environment.yaml   # Conda environment specification

Full documentation: https://mqed-qd.github.io/MQED-QD/

Build locally:

cd docs && make html
open build/html/index.html        # macOS
# xdg-open build/html/index.html  # Linux

If you use MQED-QD in your research, please cite:

@article{liu2026mqed,
  title={MQED-QD: An Open-Source Package for Quantum Dynamics Simulation in Complex Dielectric Environments},
  author={Liu, Guangming and Wang, Siwei and Chen, Hsing-Ta},
  journal={Journal of Chemical Theory and Computation},
  year={2026},
  publisher={ACS Publications}
}

1. Fork the repository
2. Create a feature branch (git checkout -b feature/my-feature)
3. Commit your changes
4. Open a Pull Request

This project is licensed under the MIT License.

• Issues: GitHub Issues
• Contact: gliu8@nd.edu