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34 results for “Quantum systems”
Raw data to "Series expansions in closed and open quantum many-body systems with multiple quasiparticle types"
<p>This collection of data is complementary to the publication "Series expansions in closed and open quantum many-body systems with multiple quasiparticle types", Lea Lenke, Andreas Schellenberger, Kai Phillip Schmidt, <a href="https://arxiv.org/abs/2302.01000">arXiv:2302.01000</a> (<a href="https://arxiv.org/abs/2302.01000">https://arxiv.org/abs/2302.01000</a>).</p> <p>It contains all data used for Figure 2 given in the file `Figure_2_complementary_data.yaml` and all needed data to recalculate the energies of the visualized modes in the files `Figure_2_coefficients_expectation_values.yaml` and `Figure_2_broad_signum_coefficients_expectation_values.yaml`.</p> <p>For the last two files, we used a program to calculate the coefficients. The source code for coefficient calculation is openly available under GitHub (<a href="https://github.com/FAU-kpslab/pcstpp_CoefficientGenerator">https://github.com/FAU-kpslab/pcstpp_CoefficientGenerator</a>) including configuration files to reproduce the coefficients given here.</p> <p>All files are self-consistent, for further information we recommend the comments directly in the files.</p> <p>For further details on the used method pcst<sup>++ </sup>and discussion of the results we refer to the linked publication.</p> <p>If any question may arise, you are highly welcome to contact us (see e.g. contact information on the publication).</p>
Dataset underlying the manuscript: MAViS: Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays
<p>Datasets underlying the manuscript. Information on how to run the scripts is detailed in the README file.</p>
Dataset for "Estimating truncation effects of quantum bosonic systems using sampling algorithms"
<p>Markov Chain Monte Carlo simulation data for the preprint.</p> <p>T010ad***S10000M*_1.txt: simulation history for a_{dig} = 0.3, 0.5, 0.7, m^2 = 1, -1, B_max = 5000, used for Table 1 and Figure 1.</p> <p>T010R100L401S10000M1_1.txt: simulation history for a_{dig} = 0.5, m^2 = 1, B_max = 1, used for Figure 2.</p> <p>Table2.zip: contains simulation history for Table 2 and Figure 3. File name "T1a0.2S1250M1L4s2101.txt" indicates that the temperature is 1, a_{dig} = 0.2, Delta = 1250, m^2 = 1, lattice size is 4 * 4, and the random seed is 2101. Lines contain the expectation values of the potential energy and the two correlation functions obtained for successive steps. The largest estimated auto-correlation length d_q, which is used for the analysis, is as follows:</p> <table align="center"> <tbody> <tr> <td><em>a</em><sub>dig</sub></td> <td><em>d</em><sub>(0,0)</sub></td> <td><em>d</em><sub>(π,π)</sub></td> </tr> <tr> <td>0.2</td> <td>37</td> <td>4</td> </tr> <tr> <td>0.25</td> <td>38</td> <td>4</td> </tr> <tr> <td>0.3</td> <td>37</td> <td>4</td> </tr> <tr> <td>0.4</td> <td>41</td> <td>4</td> </tr> <tr> <td>0.5</td> <td>59</td> <td>5</td> </tr> <tr> <td>0.6</td> <td>130</td> <td>7</td> </tr> <tr> <td>0.7</td> <td>369</td> <td>15</td> </tr> <tr> <td>0.8</td> <td>968</td> <td>55</td> </tr> <tr> <td>0.9</td> <td>2174</td> <td>148</td> </tr> <tr> <td>1.0</td> <td>4491</td> <td>319</td> </tr> </tbody> </table> <p>The initial 10 d_q steps are discarded as a burn-in period, regardless of whether we conducted a warm-up run prior to the steps contained in this dataset.</p>
Data Repository Accompanying "Controllable single Cooper pair splitting in hybrid quantum dot systems"
<p>Code and datasets associated with the manuscript " Controllable single Cooper pair splitting in hybrid quantum dot systems". With the code and data included here, all necessary fits and analysis can be conducted to produce the figures given in the manuscript and its supplementary material. The only exception is that we include the results of the quantum dot stability diagram simulation, however this simulation involves no new physics and the procedure is described in detail in the manuscript's supplementary information.</p>
Scripts, Data, and Figures for "MesoHOPS: Size-invariant scaling calculations of multi-excitation open quantum systems"
<div> <p>This archive contains the scripts required to run all calculations presented in "MesoHOPS: Size-invariant scaling calculations of multi-excitation open quantum systems," the figure generation scripts and attendant processed data, and a copy of MesoHOPS version 1.4.0, as used in the paper.</p> </div>
Data of publication "Simulating the dynamics of large many-body quantum systems with Schrödinger-Feynman techniques"
<p>The development of powerful numerical techniques has drastically improved our understanding of quantum matter out of equilibrium. Inspired by recent progress in the area of noisy intermediate-scale quantum devices, this paper highlights hybrid Schrödinger-Feynman techniques as an innovative approach to efficiently simulate certain aspects of many-body quantum dynamics on classical computers. To this end, we explore the nonequilibrium dynamics of two large subsystems, which interact sporadically in time, but otherwise evolve independently from each other. We consider subsystems with tunable disorder strength, relevant in the context of many-body localization, where one subsystem can act as a bath for the other. Importantly, studying the full interacting system, we observe that signatures of thermalization are enhanced compared to the reference case of having two independent subsystems. Notably, with the here proposed Schrödinger-Feynman method, we are able to simulate the pure-state survival probability in systems significantly larger than accessible by standard sparse-matrix techniques.</p> <div> </div> <div> </div>
Supplemental Data for "Localization renormalization and quantum Hall systems"
<p>Scripts and data to supplement the paper "Localization renormalization and quantum Hall systems".</p>
Laser cooling a membrane-in-the-middle system close to the quantum ground state from room temperature
<p>This dataset contains processed data corresponding to the figures in the main text of our paper "Laser cooling a membrane-in-the-middle system close to the quantum ground state from room temperature"</p> <p>The dataset consists of 10 .csv files and a jupyter notebook for generating the figures in the main text.</p>
Data associated to the paper "Reduced basis surrogates for quantum spin systems based on tensor networks"
<p>Within the reduced basis methods approach, an effective low-dimensional subspace of a quantum many-body Hilbert space is constructed in order to investigate, e.g., the ground-state phase diagram. The basis of this subspace is built from solutions of snapshots, i.e., ground states corresponding to particular and well-chosen parameter values. Here, we show how a greedy strategy to assemble the reduced basis and thus to select the parameter points can be implemented based on matrix-product-state calculations. Once the reduced basis has been obtained, observables required for the computation of phase diagrams can be computed with a computational complexity independent of the underlying Hilbert space for any parameter value. We illustrate the efficiency and accuracy of this approach for different one-dimensional quantum spin-1 models, including anisotropic as well as biquadratic exchange interactions, leading to rich quantum phase diagrams.</p>
Dataset for the manuscript "Realization of an atomic quantum Hall system in four dimensions", arXiv:2210.06322
<p>Dataset for the manuscript "Realization of an atomic quantum Hall system in four dimensions", arXiv:2210.06322</p>
Code generation for classical-quantum software systems modelled in UML - Dataset and EGL Transformation
<p>This dataset contains all the elements necessary for carry out the EGL transformation from UML models to Hybrid and Quantum code, as well as to carry its validation. </p> <blockquote> <p><em>Quantum computing is gaining an increasing interest since it can solve certain problems exponentially faster than classical computing. Thus, many organizations are researching and launching investments for integrating quantum software into their existing systems. Software modernization (as based on Model-Driven Engineering) has been proposed to migrate from/to the so-called hybrid software systems, which integrate classical and quantum software. In that process, both, reverse engineering and restructuring phases, have already been investigated. However, forward engineering phase for generating hybrid source code from high-level design models has not yet been addressed. Thus, this research proposes a quantum code generation technique from extended UML design models. It consists of a set of Model-to-Text transformations (defined through Epsilon Generation Language) to generate both Python and Qiskit code, which respectively integrate classical and quantum code. The transformation has been validated through a multi-case study with 7 hybrid software systems modelled in UML, which demonstrated that the transformation is effective and efficient. The implication of this work is that the software modernization process for hybrid software systems can be completed by tackling forward engineering phase, and that Model-Driven Engineering can therefore globally facilitate industry adoption of quantum software.</em></p> </blockquote>
Code and data for Nguyen Le et al. "Robust optimal control of interacting multi-qubit systems for quantum sensing"
<p>This is the code and simulation data for the paper "Robust optimal control of interacting multi-qubit systems for quantum sensing" by Nguyen Le et al.</p>
Theoretical analysis and simulations of two-dimensional Fourier transform spectroscopy performed on exciton-polaritons of a quantum-well microcavity system
<p>Dataset of the publication “Theoretical analysis and simulations of two-dimensional Fourier transform spectroscopy performed on exciton-polaritons of a quantum-well microcavity system“, H. Rose, J. Paul, J. K. Wahlstrand, A. Bristow, and T. Meier, Proceedings of the SPIE 11684, 1168414 (2021) ( <a href="https://doi.org/10.1117/12.2576696">https://doi.org/10.1117/12.2576696</a> ). The zip file includes the data on which the plots shown in figure 2 are based.</p>
Dataset for: Estimating heating times in periodically driven quantum many-body systems via avoided crossing spectroscopy
<p>The dataset includes data and Python scripts for all figures in the corresponding article.</p> <p>The data is organized into self-contained folders for each individual figure (possibly consisting of multiple subplots) and should be accessible using standard libraries for scientific Python. The included scripts can serve as a guide for accessing and plotting the data.</p>
Data for "Long-range electron-electron interactions in quantum dot systems and applications in quantum chemistry"
<p>This dataset contains the data files and plotting scripts for figures of "Long-range electron-electron interactions in quantum dot systems and applications in quantum chemistry".</p> <p>Questions can be addressed to: johannes.knoerzer@eth-its.ethz.ch and c.j.vandiepen@tudelft.nl</p>
Scaling theory of wave confinement in classical and quantum periodic systems
<p>Data repository to manuscript 'Scaling theory of wave confinement in classical and quantum periodic systems'. The upload contains the file "README.txt" explaining the content of the upload.</p>
Data: Characterization of Overparameterization in Simulation of Realistic Quantum Systems
<p>Raw data, figures, plot settings, and simulation settings for "Characterization of Overparameterization in Simulation of Realistic Quantum Systems" Phys. Rev. A 109, 062607 (2024) <a href="https://doi.org/10.1103/PhysRevA.109.062607">https://doi.org/10.1103/PhysRevA.109.062607</a></p>
Dataset of the Paper "Architecture Decisions in Quantum Software Systems: An Empirical Study on Stack Exchange and GitHub"
<p>This dataset was collected from GitHub and Stack Exchange (including Stack Overflow, Quantum Computing Stack Exchange, and Computer Science Stack Exchange) to conduct an empirical study on architecture decisions in quantum software systems. We provide below a brief description of each file:</p><p><strong>1. Dataset (GitHub).xlsx</strong></p><p>contains selected quantum software projects from GitHub with project names, issue IDs, and issue URLs and the data extracted from the GitHub issues that are related to architecture decisions in quantum software development.</p><p><strong>2. Dataset (SO).xlsx</strong></p><p>contains the IDs and URLs of Stack Overflow (SO) labeled posts and the extracted data from the Stack Overflow posts that are related to architecture decisions in quantum software development.</p><p><strong>3. Dataset (QC).xlsx</strong></p><p>contains the IDs and URLs of Quantum Computing (QC) Stack Exchange labeled posts and the extracted data from the Quantum Computing Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p><strong>4. Dataset (CS).xlsx</strong></p><p>contains the IDs and URLs of Computer Science (CS) Stack Exchange labeled posts and the extracted data from the Computer Science Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p><strong>5. Extracted Data (GitHub+SO+QC+CS).xlsx</strong></p><p>provides the final results of data extracted from the related GitHub issues, SO posts, QC posts, and CS posts.</p>
Supplementary data for the doctoral thesis "Graph decomposition techniques for quantum spin systems with multi-spin interactions"
<p>This upload contains data for the doctoral thesis of Matthias Mühlhauser with the title "Graph decomposition techniques for quantum spin systems with multi-spin interactions". <br>This doctoral thesis has been written at Friedrich-Alexander-Universität Erlangen-Nürnberg under the supervision of Professor Kai P. Schmidt.</p> <p>The given folders contain: </p> <p>XC-HPF.zip:<br> The series expansion about the high-field limit of the X-Cube model in a general parallel field.<br> <br>NLCE-TFIM-LF.zip:<br> The NLCE data for the TFIM in the low-field limit on the triangular and on the square lattice.<br><br>All folders contain a file README.txt explaining the provided data.</p>
Steady states of Λ-type three-level systems excited by quantum light with various photon statistics in lossy cavities
<p>Dataset of the publication "Steady states of Λ-type three-level systems excited by quantum light with various photon statistics in lossy cavities" H. Rose, O. V. Tikhonova, T. Meier, and P. R. Sharapova, New J. Phys.<strong> 24</strong>, 063020 (2022). ( https://doi.org/10.1088/1367-2630/ac74d8 ). The zip file includes the data on which the plots shown in figures 2,4,5,6,7, B1, and B2 are based.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.