Amy F. Brown and Daniel A. Lidar

This repository contains the aggregate data and notebooks to recreate the plots contained in the Chromatic-Hadamard Dynamical Decoupling (CHaDD) paper, "Efficient Chromatic-Number-Based Multi-Qubit Decoherence and Crosstalk Suppression," .

This repository is archived on Zenodo at the following DOI: .

The latest release and the history of releases can be found in the GitHub release archive: .

First, verify that you have Poetry installed and available in your $PATH. Poetry can be installed from the command line by running

curl -sSL https://install.python-poetry.org | python3 -

On MacOS, the poetry command can be added to your $PATH as follows:

export PATH="/Users/YOUR-USERNAME/.local/bin:$PATH"

To install chadd-paper, simply run the following command in the root repository directory:

poetry install

To install a Jupyter kernel for chadd-paper, run

poetry run python -m ipykernel install --user --name=chadd-paper

github.com/USCqserver/chadd-paper
├── README.md
├── notebooks/
│   └── plot_chadd_experiments.ipynb  # recreate plots in the CHaDD paper
├── chadd/
│   └── __init__.py  # utilities relating to CHaDD
├── data/
│   └── aggregate/
│       └── ibm_brisbane/
│           ├── experiment_samples.pickle
│           └── params.yaml
├── pyproject.toml  # dependencies
└── poetry.lock

To reproduce the plots contained in the CHaDD paper, run

jupyter notebook notebooks/plot_chadd_experiments.ipynb

This material is based upon work supported by, or in part by, the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF2310255. This research was supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) and the Army Research Office, under the Entangled Logical Qubits program through Cooperative Agreement Number W911NF-23-2-0216.

Please cite the CHaDD preprint and data repository as follows:

Efficient Chromatic-Number-Based Multi-Qubit Decoherence and Crosstalk Suppression
Amy F. Brown, Daniel A. Lidar
arXiv:2406.13901
DOI: 10.48550/arXiv.2406.13901

Data Repository for "Efficient Chromatic-Number-Based Multi-Qubit Decoherence and Crosstalk Suppression"
Amy F. Brown, Daniel A. Lidar
DOI: 10.5281/zenodo.15572005

BibTeX:

@misc{brown2025efficientchromaticnumberbasedmultiqubitdecoherence,
    title={Efficient Chromatic-Number-Based Multi-Qubit Decoherence and Crosstalk Suppression},
    author={Amy F. Brown and Daniel A. Lidar},
    year={2025},
    eprint={2406.13901},
    archivePrefix={arXiv},
    primaryClass={quant-ph},
    doi={10.48550/arXiv.2406.13901},
    url={https://doi.org/10.48550/arXiv.2406.13901},
}
@software{amy_f_brown_2025_15572005,
    title={Data Repository for "Efficient Chromatic-Number-Based Multi-Qubit Decoherence and Crosstalk Suppression"},
    author={Amy F. Brown and Daniel A. Lidar},
    month=jun,
    year=2025,
    publisher={Zenodo},
    doi={10.5281/zenodo.15572005},
    url={https://doi.org/10.5281/zenodo.15572005},
}