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Data and software code for "Information scrambling in quantum circuits"

Google AI Quantum and Collaborators

Published Oct 5, 2021• 0 citations
Publisher

Abstract

Data files named according to figures in the main text of the manuscript and extended data section of the Supplementary Materials. Code for generating OTOC circuits and acquiring data from Google Quantum Cloud Service is included in the folder "Recirq". Code for tensor-contraction algorithms used in the simulation of quantum circuits for OTOCs is included in the folder "hybridq". Note: Most up-to-date code for tensor-contraction is found at: https://github.com/nasa/hybridq

DOI
10.5281/zenodo.5548890

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Data files named according to figures in the main text of the manuscript and extended data section of the Supplementary Materials. Code for generating OTOC circuits and acquiring data from Google Quantum Cloud Service is included in the folder "Recirq". Code for tensor-contraction algorithms used in the simulation of quantum circuits for OTOCs is included in the folder "hybridq". Note: Most up-to-date code for tensor-contraction is found at: https://github.com/nasa/hybridq
This data repository contains the information necessary to reproduce the main results of the paper “Quantum computational displacement sensing”. The repository contains both the data required to generate the figures of the main manuscript and the supplemental material, as well as source code for running the experiments and simulations presented in the paper. There are two main folders: code_simulation (which consists of the training code and the baseline simulations) and code_experiment (which covers the experimental code). The corresponding requirements for running them are in the zipped folder. The data folder contains all simulation and experimental raw and processed data generated. The figures folder contains all the plots presented in the manuscript.
This data repository contains the information necessary to reproduce the main results of the paper “Exponential quantum advantage for learning signals with a single qubit”. The repository contains both the data required to generate the figures of the main manuscript and the supplemental material, as well as source code for running the experiments and simulations presented in the paper. There are two main folders: experiment_code (which contains all experimental scripts to calibrate device and run the protocols presented in the paper) and simulation_code (which contains simulation details of the dark matter and communication detection tasks) The data folder contains experimental raw and processed data generated. The figures folder contains all the plots presented in the manuscript.
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.
Underlying data and plotting for the publication 'Mid-Circuit correction of correlated phase errors using an array of spectator qubits', K. Singh, C.E. Bradley, S. Anand, V. Ramesh, R. White and H. Bernien, 2022. This directory contains: - "Data Analysis.ipynb": A jupyter notebook from which all plots presented in the main text and supplementary materials can be reproduced. - "Data.zip": A zip file containing the json files which are loaded into "Data Analysis.ipynb". These files contain x, y, and where appropriate, y error values for each plot. The notebook should be executed using python3.
Overview of data provided in support of Towards near-term quantum simulation of materials Contents of this folder: `analyse_materials_results.py`: script used to generate the summary tables and figures presented in the manuscript. `towards_quantum_simulation_data`: raw data used and produced when studying various 3D materials. `towards_quantum_simulation_analysis`: tables (in `.tex` format) and figures (as PDFs) presented in the manuscript. The contents of `towards_quantum_simulation_analysis` were generated by `analyse_materials_results.py`, i.e. the user need not run the script to produce the output files. Users can generate these analyses directly by running ```python analyse_materials_results.py```, though note the following packages will first need to be installed: `pandas >= 1.2.3` `numpy >= 1.23` `seaborn >= 0.11.1` `lfig >= 0.1.3` `matplotlib > 3.7.0` Included data Within `towards_quantum_simulation_data`, there are subfolders for each of the materials described in the manuscript, i.e. `SrVO3`, `GaAs`, `H3S`, `Si`, `Li2CuO2`. Within each material's folder are further subfolders for the `hamiltonian` and `encoding` used to represent the material, as well as subfolders for each of the `algorithms` studied. `hamiltonian`: files which specify the Hamiltonian for the material under study. There are a number of files `interactions.json` Hamiltonian terms in terms of Majorana monomials. `map_majorana_to_mode.json` keys are Majorana indices; values are the mode index to which they are associated. `map_mode_to_group.json` keys are mode indices; values are the group (or site) index to which they are associated. `map_group_to_position.json` keys are group indices; values are the corresponding 3D Cartesian coordinates of the lattice used to represent the material. `stage_data.json` contains key/value pairs of any other fields of interest. `encoding` files which specify the fermionic encoding which is customised for the material under study. `encoding.json` which details the edges of the hybrid compact encoding described in Section VI of the supplementary material. `precompiler.json` contains all the information which permits the encoding construction, including the Hamiltonian terms (`_interactions`) which match those in `hamiltonian/interactions.json`. The same mappings as present in the Hamiltonian data(a.g. `map_group_to_position`). `stage_data.json` contains key/value pairs of any other fields of interest. `algorithms` contains subfolders for each of the algorithms desribed in the manuscript Those explored for circuits depths: `TDSSplitTermsPriorityCircuitDepth` (TDS in the manuscript) `TDSSplitTermsPriorityCircuitDepthNoSwapNetwork` (TDS\*) `VQESplitTerms` (VQE) `VQESplitTermsNoSwapNetwork` (VQE*) each of which contain the files, inside the `circuitry` folder: `circuit_terms.csv`, which lists each individual term, together with their Pauli string and rotation angle, required to construct the corresponding quantum circuit `circuit_layers_to_implement.csv` groups the same terms into layers to achieve parallelism in the circuit. `stage_data.json` contains key/value pairs of any other fields of interest. and those used to compose measurement layers, as outlined in Section VII D of the supplementary material: `MeasurementCommutativity` `MeasurementNaiveQubitwise` `MeasurementNonCrossing` each of which contain the files, inside the `compilation` folder: `layers.csv` lists the terms which may be measured simultaneously to achieve the measurement strategies shown in Table S14. `stage_data.json` contains key/value pairs of any other fields of interest. CSV files In `towards_quantum_simulation_data`, there are unified CSV files containing the results of applying the procedures described in the manuscript to the target materials. `circuit_costs.csv`: results of running the circuit compiler described in the manuscript. `measurements.csv`: results of running the measurement compiler described in the manuscript. These CSVs are used in the analysis script `analyse_materials_results.py` to produce the figures and tables presented in the manuscript.