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Data for: Non-local edge mode hybridization in the long-range interacting Kitaev chain

David Haink, Benedikt Fauseweh, Andreas Alexander Buchheit

Published Jul 13, 2026• 1 citation
Publisher

Abstract

Code and Data to the paper with the same title. It can be used to reproduce the plots with the corresponding notebook. All results of the paper can be computed with this code. For this, no further support is given. Update: Fixed requirements.txt to include jaxopt and used versions. We thank Daniel Seibel for sharing his LBFGS optimizer for this problem.

DOI
10.5281/zenodo.21334819

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Engineered non-Gaussian Coherence as a Thermodynamic Resource for Quantum Batteries

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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.

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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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Evaluation Data for "HyRoNA: Hybrid Routing for Neutral Atoms by Leveraging Gate- and Shuttling-based Strategies"

Schmid, Ludwig, Park, Sunghye, Robert Wille

Abstract Processors based on Neutral Atoms (NAs) combine long-range, native multi-qubit interactions with high-fidelity atom transport, enabling multiple, complementary routing modalities. Yet most compilers target only a single capability. We present HyRoNA, an adaptive framework that combines gate-based routing with atom transport to leverage the full spectrum of capabilities of NA devices.HyRoNA combines interaction-aware initial mapping with fast, capability-specific cost models and an as soon as possible scheduler that honors hardware-specific constraints, emitting hardware-native programs with optional video visualizations. Across diverse benchmarks and hardware settings, HyRoNA improves the expected success probability over single-modality baselines by selecting per gate and per layer what best fits the hardware and circuit context.While designed for NISQ hardware, we discuss how the routing methodologies can be generalized to fault-tolerant computations using error-corrected encodings, which offer transversal entangling gates.The complete code with documentation is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/cda-tum/mqt-qmap. Evaluation Data This repository includes the scripts to create the data, plots, and tables of the paper "HyRoNA: Hybrid Routing for Neutral Atoms by Leveraging Gate- and Shuttling-based Strategies". Just install the requirements.txt (you might replace the version of QMAP with the current available version) and run the corresponding Python script to create the data (the dataset used for the paper is in the output directory). Then use the Jupyther notebook to create the plots/tables.

•Dec 2, 2025•0 citations
Code and Data to the paper with the same title. It can be used to reproduce the plots with the corresponding notebook. All results of the paper can be computed with this code. For this, no further support is given. Update: Fixed requirements.txt to include jaxopt and used versions. We thank Daniel Seibel for sharing his LBFGS optimizer for this problem.
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.
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.
Abstract Processors based on Neutral Atoms (NAs) combine long-range, native multi-qubit interactions with high-fidelity atom transport, enabling multiple, complementary routing modalities. Yet most compilers target only a single capability. We present HyRoNA, an adaptive framework that combines gate-based routing with atom transport to leverage the full spectrum of capabilities of NA devices.HyRoNA combines interaction-aware initial mapping with fast, capability-specific cost models and an as soon as possible scheduler that honors hardware-specific constraints, emitting hardware-native programs with optional video visualizations. Across diverse benchmarks and hardware settings, HyRoNA improves the expected success probability over single-modality baselines by selecting per gate and per layer what best fits the hardware and circuit context.While designed for NISQ hardware, we discuss how the routing methodologies can be generalized to fault-tolerant computations using error-corrected encodings, which offer transversal entangling gates.The complete code with documentation is publicly available in open-source as part of the Munich Quantum Toolkit (MQT) at https://github.com/cda-tum/mqt-qmap. Evaluation Data This repository includes the scripts to create the data, plots, and tables of the paper "HyRoNA: Hybrid Routing for Neutral Atoms by Leveraging Gate- and Shuttling-based Strategies". Just install the requirements.txt (you might replace the version of QMAP with the current available version) and run the corresponding Python script to create the data (the dataset used for the paper is in the output directory). Then use the Jupyther notebook to create the plots/tables.