Quantum Reservoir Computer (QRC) Simulations

This repository contains the code replicating the results in the paper "Photon Number-Resolving Quantum Reservoir Computing" [10.1364/OPTICAQ.553294].

Reproduce the paper's results

On Linux, with Conda installed:

bash run_all.sh

Paper figures will be in figures/ and raw data in experiments/.

We recommend a sizable CPU and RAM. The results in the paper were generated using a machine with 28 cores and 256GB of RAM, and each definition.py file generates on order 100GB intermediate files. Less capable machines may be used by reducing the number of WORKERS and increasing the split_factors in each definition.py file (see experiments/).

Running

bash run_all.sh clean

will run all experiments, but delete some larger intermediate files to save disk space.

Setup

If you are unable to run the run_all.sh script, you can set up the environment manually.

We recommend using the provided environment file to create a new Conda environment. Miniforge is recommended for this purpose.

From root project directory:

conda env create -n qrc_paper -f environment.yml
conda activate qrc_paper
pip install .

Perceval

While we do rely on the Perceval library for the implementation of the SLOS algorithm, we have made some modifications which are requirements for running this code.

• Support for pickling of Exqalibur state objects.
• Support for vectorial probabilities/ amplitudes in these states, for efficient parallel tensor product operations.

These are performed in src/qrc/_compat.py where we monkey patch the specific version of Perceval given in the pyproject.toml file. Other versions of Perceval will likely work with some modification to ensure the patches are applied correctly.

Experiments

Each directory in experiments contains a definition.py file, which defines the particular experiment(s) to perform. To run a particular experiment, navigate to the directory containing the definition.py file and run the necessary tools from qrc.tools, i.e.

python -m qrc.tools.run_experiments
python -m qrc.tools.postprocess
python -m qrc.tools.eval_tasks

Figures

Once the data has been generated in the experiments directories, the figures for the paper are generated using the scripts in figures.

Citation

If you use this code in your research, please cite the following paper:

@article{Nerenberg:25,
  author = {Sam Nerenberg and Oliver D. Neill and Giulia Marcucci and Daniele Faccio},
  journal = {Optica Quantum},
  number = {2},
  pages = {201--210},
  publisher = {Optica Publishing Group},
  title = {Photon number-resolving quantum reservoir computing},
  volume = {3},
  month = {Apr},
  year = {2025},
  url = {https://opg.optica.org/opticaq/abstract.cfm?URI=opticaq-3-2-201},
  doi = {10.1364/OPTICAQ.553294},
}