Improving Zero-Noise Extrapolation via Physically Bounded Models

This repository contains supplementary material for the paper "Improving Zero-Noise Extrapolation via Physically Bounded Models".

Installation

This project uses pyproject.toml for dependency management. The experiments reported in the paper were conducted using Python 3.12. The codebase in this repository is compatible with Python 3.11 and 3.12.

With venv and pip:

1. Create and activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate

2. Install the package and runtime dependencies:

   pip install -e .

3. (Optional) Install test dependencies:

   pip install -e ".[test]"

With uv:

1. Sync the runtime environment:

   uv sync

2. (Optional) Sync test dependencies:

   uv sync --extra test

3. Activate the environment if needed:

   source .venv/bin/activate

Repository Structure

src/

• bounded_methods.py: implementations of bounded extrapolation routines for zero-noise estimation:
  • bounded_polynomial_extrapolation: constrained polynomial model with bounded intercept.
  • bounded_exp_extrapolation: constrained exponential model.
  • bounded_polyexp_extrapolation: constrained polynomial--exponential model.

tests/

• test_bounded_methods.py: unit tests for bounded_methods.py.

notebooks/

• 00_demo_zne_methods.ipynb: demonstrates ZNE methods and example analysis flow.
• 01_access_qasm.ipynb: shows how to access and inspect circuit files in QASM archives.
• 02_access_measurements.ipynb: shows how to read synthetic and real-device measurement records from compressed JSONL files.
• 03_access_evaluations.ipynb: shows how to access evaluation result archives (synthetic and real-device) stored as parquet datasets.

Data Setup (Required for notebooks 01_, 02_, 03_)

Notebooks with prefixes greater than 00_ require local data files under data/.

1. Download the required archives/files from Zenodo using your preferred method (web browser, wget, curl, etc.).

2. Place all downloaded files into the data/ directory.

3. Unpack the zip archives listed below inside data/:

   • evaluation_archive.zip
   • evaluation_real_archive.zip

   For example, using:

   unzip data/evaluation_archive.zip -d data/evaluation_archive
   unzip data/evaluation_real_archive.zip -d data/evaluation_real_archive

Testing

Run unit tests using:

pytest

Citation

If you use or study the code, please cite it as follows.

@article{miranskyy2026improving,
      title={Improving Zero-Noise Extrapolation via Physically Bounded Models}, 
      author={Andriy Miranskyy and Adam Sorrenti and Jasmine Thind and Claude Gravel},
      year={2026},
      journal={arXiv preprint arXiv:2604.24475},
      url={https://arxiv.org/abs/2604.24475}, 
      doi={10.48550/arXiv.2604.24475}
}

License

This project is licensed under the Apache License 2.0 -- see the LICENSE file for details.