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13 results for “quantum annealing”
Data for "Accelerating equilibrium spin-glass simulations using quantum annealers via generative deep learning"
<p>Datasets and material for replicating plots and results from the paper "Accelerating equilibrium spin-glass simulations using quantum annealers via generative deep learning" <a href="https://scipost.org/SciPostPhys.15.1.018">SciPost Phys. 15, 018 (2023)</a>.</p> <p>You will find three data files and a ReadMe.txt:</p> <ul> <li><strong>couplings.tar.gz </strong>contains the random couplings of the system's Hamiltonian <span class="math-tex">\(H = \sum_{\langle ij \rangle}{J_{ij} \sigma_i \sigma_j}\)</span>;</li> <li><strong>datasets.tar.gz </strong>contains all the datasets generated by the <a href="https://www.dwavesys.com/">D-Wave</a> quantum computer. They are already split into train and validation and divided for the type of model and annealing time;</li> <li><strong>data_for_fig.tar.gz </strong>contains files for reproducing the plots of the article, almost all of them are saved in double format, .csv and .npy or .npz.</li> </ul> <p>We encourage you to download the GitHub code linked below to open all the listed data.</p> <p>All the data are zip, so to unzip them using</p> <pre><code class="language-bash">tar -xvf datasets.tar.gz</code></pre> <p>The code for training the Neural Networks and reproducing all the results is open access at <a href="https://doi.org/10.5281/zenodo.7118502">zenodo.7118502</a>.</p>
Dataset for Dynamic Analysis of Quantum Annealing Programs
<p>Quantum software engineering is emerging as a relevant field as it deals with the challenges of producing the new quantum software, whose adoption is increasing progressively. One of those challenges is how quantum software is migrated, how it operates in combination with classical software, or how it should be maintained. In this context this research focuses on reverse engineering of quantum annealing software to facilitates its integration in hybrid software systems. Quantum annealing software has gained a certain market penetration, demonstrating a good performance for optimization problems. While there are some preliminary reverse engineering techniques for gate-based quantum software, there is no reverse engineering techniques to discover the underlying optimization problem definitions (Hamiltonians functions to be minimized). Problem definitions are, in turn, dynamically defined through classical software, and can evolve over time, which make it difficult its accurate comprehension and abstract representation. Thereby, this paper presents a dynamic analysis technique for D-Wave (python) programs for reversing Hamiltonians expressions, that are additionally represented according to the Knowledge Discovery Metamodel. Due to the usage of this standard, the reversed Hamiltonians can be represented in combination with other parts of classical-quantum software systems. In order to facilitates its adoption, the proposed technique has been empirically validated through a case study with 27 D-Wave programs that demonstrates the effectiveness and efficiency. This dataset includes measures derived from that case study.</p>
Dataset for: Quantum cascade lasers with discrete and non equidistant extended tuning tailored by simulated annealing
<p>Dataset used for article 10.1364/OE.27.026701.</p>
Dataset for Comparing Three Generations of D-Wave Quantum Annealers for Minor Embedded Combinatorial Optimization Problems
<p>Dataset for the paper titled "Comparing Three Generations of D-Wave Quantum Annealers for Minor Embedded Combinatorial Optimization Problems"</p> <p>LA-UR-23-20367</p>
Dataset for 4-clique network minor embedding for quantum annealers
<p>Dataset for the paper titled 4-clique network minor embedding for quantum annealers. Includes raw D-Wave quantum annealer samples and minor embedding graph structures.</p>
Data for "Diabatic Quantum Annealing for the Frustrated Ring Model"
<p>This repository contains data for the paper "Diabatic Quantum Annealing for the Frustrated Ring Model". In particular, the Jupyter notebook within the repository reproduces the figures that contain data in our paper. We also include a Qiskit implementation of our algorithm and the associated code for the population levels.</p>
Dataset for Mapping State Transition Susceptibility in Quantum Annealing Part 2
<p>Dataset for the paper Mapping State Transition Susceptibility in Quantum Annealing, Part 2.</p> <p>README.md file is contained in the tar.gz file.</p>
Dataset for Mapping State Transition Susceptibility in Quantum Annealing Part 1
<p>Dataset for the paper Mapping State Transition Susceptibility in Quantum Annealing, Part 1.</p> <p>README.md file is contained in the tar.gz file.</p>
Dataset for Mapping State Transition Susceptibility in Quantum Annealing Part 4
<p>Dataset for the paper Mapping State Transition Susceptibility in Quantum Annealing, Part 4.</p> <p>README.md file is contained in the tar.gz file.</p>
Dataset for Mapping State Transition Susceptibility in Quantum Annealing Part 3
<p>Dataset for the paper Mapping State Transition Susceptibility in Quantum Annealing, Part 3.</p> <p>README.md file is contained in the tar.gz file.</p>
Dataset for: Diabatic quantum and classical annealing of the Sherrington-Kirkpatrick model
<p>The dataset includes data, Python code, and scripts for all figures in the corresponding article.</p>
Efficiency Optimization of Ge-V Quantum Emitters in Single-Crystal Diamond upon Ion Implantation and HPHT Annealing
Open the record for dataset details and reuse information.
Data Sets for "Efficient Solution of the Number Partitioning Problem on a Quantum Annealer: A Hybrid Quantum-Classical Decomposition Approach"
Open the record for dataset details and reuse information.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.