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Simulation codes and datasets related to the article "Master Equation for Quantum Self-Organization of Atoms and Molecules in Cavities"

Tom Schmit

Published Sep 8, 2025• 1 citation
Publisher

Abstract

Simulation codes and datasets used for generating Figs. 2 and 3 of the article "Master Equation for a Quantum Gas of Polarizable Particles in Cavities", published under the reference Phys. Rev. A 113, 033719 (2026) (DOI: https://doi.org/10.1103/dlf7-9yl4) and available on ArXiv (arXiv:2508.07853 [quant-ph]). Please refer to the README.md file for further information about the different files provided in this repository.

DOI
10.5281/zenodo.17078206

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This repository provides the figure data and numerical simulation codes supplement to the manuscript “Dynamical freezing and enhanced magnetometry in an interacting spin ensemble” (arXiv:2507.22982). Contents:--Main_text_figures--Extended_Data_figures Each folder contains the numerical or experimental data used to generate the corresponding figures in the manuscript. All figures can be reproduced by straightforward plotting of the included .csv files. A short description of each dataset is provided within the file headers. --Exact_diagonalization_code--Discrete_truncated_Wigner_approximation_code These directories contain the codes used in the numerical simulations presented in the paper. Each code package includes a detailed README file explaining the workflow, parameters, and usage.

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Work-minimizing protocols in driven-dissipative quantum systems: An impulse-ansatz approach - Data and code

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This repository contains datasets and Python scripts used to generate the numerical results related to [M. Tokieda, Work-minimizing protocols in driven-dissipative quantum systems: An impulse-ansatz approach, arXiv:2511.15084 [quant-ph]]. Parts of the manuscript and computational procedures have been revised. An updated version of the manuscript is available as manuscript.pdf in this repository. Note: Unicode characters (e.g., τ, β) in filenames may not render correctly in Zenodo’s web preview. The downloaded archive should be unaffected. If you experience any issues accessing or extracting the files, please do not hesitate to contact the author.

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Code and datasets for "Shortcuts to adiabaticity with a quantum control field"

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Shortcuts to adiabaticity with a quantum control field — Code & data========================================================== This repository contains a Jupyter notebook and supporting data files (csv) to reproduce the numerical results and figures in our manuscript (arXiv 2508.06304), which investigates adiabatic shortcuts mediated by a quantum control field.The code implements a Landau–Zener two-level system coupled to a spectator qubit, time evolution of the full system (LZ qubit + spectator) via QuTiP, parameter sweeps (parallelized with joblib), and plotting utilities for the manuscript figures. Related publication----------------------------This code is complementary to the preprint: https://arxiv.org/abs/2508.06304. Requirements---------------------The simulations were developed for and tested on Python 3.9+. Recommended packages and minimum versions: - Python >= 3.9- numpy >= 1.22- scipy >= 1.8- matplotlib >= 3.5- qutip >= 4.6 (install a recent stable qutip; some installations require `pip install qutip` or `conda` channels)- joblib >= 1.2- tqdm >= 4.60- pandas (optional, for CSV handling)- jupyterlab / notebook (for interactive use) Running the notebook (interactive) Open the notebook with JupyterLab or Jupyter Notebook. Execute cells sequentially in the order indicated by the notebook outline.The sections “Definitions” and “Figure imports and setup” must be executed before generating any data or figures, as they define all operators, and helper functions. The notebook is organized into separate sections for each figure of the manuscript, allowing you to re-run only the figure(s) of interest. Note: Figure 4 (Density plot) is configured to load precomputed data files to reduce computational cost. To reproduce Figure 4 without recomputing the full dataset, ensure the required .csv files are downloaded and located in the same directory as the notebook. To explore different parameter regimes: Modify the relevant parameter definitions (e.g., anneal_window, g, epsilon, omega_c, x0, x0_vals, q_vals). To include dissipation of the spectator (ancilla) qubit, set the parameter kappa> 0. For questions about reproducing the figures or about parameter choices used in the paper, contact the corresponding authors listed in the preprint. If you reuse this data/code, please cite the associated preprint and this code archive.

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Simulation data for "Optimal control transport of neutral atoms in optical tweezers at finite temperature"

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Data and plotting scripts of the manuscript "Optimal control transport of neutral atoms in optical tweezers at finite temperature" (arXiv preprint 2402.17831). The plots are available in Figshare. Download the data and look at the README.md file for a detailed description of the data structure and guidelines for the plotting scripts. To run the plotting scripts the library qu_transport is required. The software is available at https://baltig.infn.it/qpd/quantum_transport_simulation.

•Jun 25, 2024•1 citation
Simulation codes and datasets used for generating Figs. 2 and 3 of the article "Master Equation for a Quantum Gas of Polarizable Particles in Cavities", published under the reference Phys. Rev. A 113, 033719 (2026) (DOI: https://doi.org/10.1103/dlf7-9yl4) and available on ArXiv (arXiv:2508.07853 [quant-ph]). Please refer to the README.md file for further information about the different files provided in this repository.
This repository provides the figure data and numerical simulation codes supplement to the manuscript “Dynamical freezing and enhanced magnetometry in an interacting spin ensemble” (arXiv:2507.22982). Contents:--Main_text_figures--Extended_Data_figures Each folder contains the numerical or experimental data used to generate the corresponding figures in the manuscript. All figures can be reproduced by straightforward plotting of the included .csv files. A short description of each dataset is provided within the file headers. --Exact_diagonalization_code--Discrete_truncated_Wigner_approximation_code These directories contain the codes used in the numerical simulations presented in the paper. Each code package includes a detailed README file explaining the workflow, parameters, and usage.
This repository contains the numerical data and computational codes supporting the results presented in the manuscript: "Engineered non-Gaussian Coherence as a Thermodynamic Resource for Quantum Batteries". The archive (data_QB.zip) includes all datasets, Jupyter notebooks, and figure files required to reproduce the results reported in both the main text and the Supplemental Material. Each figure is organised in a separate directory containing the corresponding data (.txt), code (.ipynb), and generated plots (.png/.pdf). The provided materials are sufficient to reproduce all figures and results without restriction. Detailed instructions and directory structure are described in the accompanying README.txt file. This dataset is made openly available to ensure transparency and reproducibility of the reported results.
This repository contains datasets and Python scripts used to generate the numerical results related to [M. Tokieda, Work-minimizing protocols in driven-dissipative quantum systems: An impulse-ansatz approach, arXiv:2511.15084 [quant-ph]]. Parts of the manuscript and computational procedures have been revised. An updated version of the manuscript is available as manuscript.pdf in this repository. Note: Unicode characters (e.g., τ, β) in filenames may not render correctly in Zenodo’s web preview. The downloaded archive should be unaffected. If you experience any issues accessing or extracting the files, please do not hesitate to contact the author.
Shortcuts to adiabaticity with a quantum control field — Code & data========================================================== This repository contains a Jupyter notebook and supporting data files (csv) to reproduce the numerical results and figures in our manuscript (arXiv 2508.06304), which investigates adiabatic shortcuts mediated by a quantum control field.The code implements a Landau–Zener two-level system coupled to a spectator qubit, time evolution of the full system (LZ qubit + spectator) via QuTiP, parameter sweeps (parallelized with joblib), and plotting utilities for the manuscript figures. Related publication----------------------------This code is complementary to the preprint: https://arxiv.org/abs/2508.06304. Requirements---------------------The simulations were developed for and tested on Python 3.9+. Recommended packages and minimum versions: - Python >= 3.9- numpy >= 1.22- scipy >= 1.8- matplotlib >= 3.5- qutip >= 4.6 (install a recent stable qutip; some installations require `pip install qutip` or `conda` channels)- joblib >= 1.2- tqdm >= 4.60- pandas (optional, for CSV handling)- jupyterlab / notebook (for interactive use) Running the notebook (interactive) Open the notebook with JupyterLab or Jupyter Notebook. Execute cells sequentially in the order indicated by the notebook outline.The sections “Definitions” and “Figure imports and setup” must be executed before generating any data or figures, as they define all operators, and helper functions. The notebook is organized into separate sections for each figure of the manuscript, allowing you to re-run only the figure(s) of interest. Note: Figure 4 (Density plot) is configured to load precomputed data files to reduce computational cost. To reproduce Figure 4 without recomputing the full dataset, ensure the required .csv files are downloaded and located in the same directory as the notebook. To explore different parameter regimes: Modify the relevant parameter definitions (e.g., anneal_window, g, epsilon, omega_c, x0, x0_vals, q_vals). To include dissipation of the spectator (ancilla) qubit, set the parameter kappa> 0. For questions about reproducing the figures or about parameter choices used in the paper, contact the corresponding authors listed in the preprint. If you reuse this data/code, please cite the associated preprint and this code archive.