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163 results for “superconductivity”
Measured data of article "Superconducting NbN–Al hybrid technology for quantum devices"
<p>The folder contains raw data of figure 3 & 4 as well as a preprint of the article:</p> <p><em>Superconducting NbN–Al hybrid technology for quantum devices</em></p> <p>Authors: E. Mutsenik, S. Linzen, E. Il’ichev, M. Schmelz, M. Ziegler, V. Ripka, B. Steinbach, G. Oelsner, U. Hübner, and R. Stolz</p> <p>Journal: Low Temperature Physics/Fizyka Nyzkykh Temperatur, 2023, Vol. 49, No. 1, pp. 98–101</p>
Topological superconductivity in twisted bilayer WSe2: single band t-J model
<p>Dataset of results related with the theoretical analysis of topological unconventional superconducting state within the t-J model as applied to the description of the twisted bilayer WSe2. The code in c++ which was used to produce the data is also provided. This data set is a result of research which was founded by National Science Centre, Poland (NCN) according to decision 2021/42/E/ST3/00128. </p>
Dataset for Direct visualization of quasiparticle concentration around superconducting vortices
<p>Data for Jian-Feng Ge, et al. “Direct visualization of quasiparticle concentration around superconducting vortices”.</p> <p>The following data files are used for the following figures.</p> <p> Fig. 1 a Illustration figure, no data used<br> b qeff_vs_y_sim.py</p> <p> Fig. 2 a NbSe2_04_220202_0189.txt<br> b NbSe2_05_220503_dIdV_0017.txt<br> NbSe2_07_220822_dIdV_0045.txt<br> c 220210_NbSe2_04_2.3K_map_03.txt<br> d 220824_NbSe2_07_2.3K_spectrum_01.txt<br> 220910_NbSe2_07_2.3K_spectrum_06.txt<br> e 220210_NbSe2_04_2.3K_map_03_qeff.txt<br> f 220824_NbSe2_07_2.3K_spectrum_01_qeff.txt<br> 220910_NbSe2_07_2.3K_spectrum_06_qeff.txt</p> <p> Fig. 3 a NbSe2_04_220202_0180.txt<br> b 220210_NbSe2_04_2.3K_map_01_Rdyn.txt<br> c 220210_NbSe2_04_2.3K_map_01_noise.txt<br> d NbSe2_04_220202_0180_radave.txt<br> e 220210_NbSe2_04_2.3K_map_01_Rdyn_radave.txt<br> f 220210_NbSe2_04_2.3K_map_01_noise_radave.txt</p> <p> Fig. 4 a 220824_NbSe2_07_2.3K_map_01.txt<br> b 220824_NbSe2_07_2.3K_map_01_cuts.txt<br> c qmax_vs_B.txt</p>
Two-fold symmetric superconductivity in few-layer NbSe2
<p>Data for the following manuscript: </p> <p>Hamill, A., Heischmidt, B., Sohn, E. <em>et al.</em> Two-fold symmetric superconductivity in few-layer NbSe<sub>2</sub>. <em>Nat. Phys.</em> <strong>17, </strong>949–954 (2021). https://doi.org/10.1038/s41567-021-01219-x</p>
Data set for "Superconducting 2D NbS2 Grown Epitaxially by Chemical Vapor Deposition "
<p>Data set for the paper "Superconducting 2D NbS<sub>2</sub> Grown Epitaxially by Chemical Vapor Deposition"</p>
Abundance of Weyl points in semiclassical multi-terminal superconducting nanostructures
<p>Jupyter notebooks for generating and analysing the data. </p> <p>Data for statistics.</p> <p>Figures and plots.</p>
Raw data for High temperature superconductivity arising in a metal sheet full of holes
<p>All raw data for the paper entitled "High temperature superconductivity arising in a metal sheet full of holes" are deposited here, together with the GDSII file used for the sample patterning. Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC BY 4.0). Addition of the author as a responsible author and/or an inventor in any publication, including electronic publications, is prohibited.</p>
Data for the article "Topological lattices realized in superconducting circuit optomechanics"
<p>Here you will find all the raw data and data processing scripts for the plots presented in "Topological lattices realized in superconducting circuit optomechanics".</p>
Effect of low-temperature compression on crystal structure and superconductivity in strontium metal
<p>The superconducting and structural properties of elemental strontium metal were studies as a function of pressure to 60 GPa, while maintaining cryogenic conditions during the pressure application.</p> <p>This data set includes raw and analyzed electrical resistivity and xray diffraction data.</p>
Data and codes for "Decay-protected superconducting qubit with fast control enabled by integrated on-chip filters"
<p>Data and codes for "Decay-protected superconducting qubit with fast control enabled by integrated on-chip filters".</p>
Data and fitting script for "Direct measurement of a sin(2φ) current phase relation in a graphene superconducting quantum interference device"
<p>This repository contains data and Python analysis scripts used for the publication "Direct measurement of a sin(2\phi) current phase relation in a graphene superconducting quantum interference device (https://doi.org/10.48550/arXiv.2405.13642).</p> <p>The repository is organized as follows: the raw data are encapsulated in a QCoDes database (https://microsoft.github.io/Qcodes/) named 'D-SQUID-06.db'. Post-treated critical current data are included as .csv files and are indexed by measurement ids.</p> <p>The principal analysis is realized in the Jupyter notebook 'Fits_and_Figures.ipynb', which includes all article figures as well as fit functions for fitting both critical currents Ic- and Ic+ simulatenously, first using analytical expression from equation 3 then using numerical expression from equation 5. All fits mentionned in the article are performed there. The repository includes a generic notebook "Extract_Critical_Current.ipynb" used to explore the raw data in the Qcodes database and features an enhanced peak detection script that we used to automatically extract critical current data despite having some artifacts on raw differential conductance versus bias current and magnetic field.</p> <p>We acknowledge the contribution of R. Kerjouan for developing the Python fitting script.</p>
Data for Superconductivity in the Hubbard model and its interplay with next-nearest hopping t'
<p>The results for <a href="https://arxiv.org/abs/1806.01465">https://arxiv.org/abs/1806.01465</a></p> <p>"Superconductivity in the Hubbard model and its interplay with next-nearest hopping t'",</p> <p>including both manuscript and supplemental material.</p>
Fig. 1 in Imperfect nanorings with superconducting correlations
Fig. 1. Fragments of the stolon system of the Crustoidea. Wysoczki outcrop (Holy Cross Mts., Poland), upper Tremadocian. SEM micrographs. A, B, D. Specimens with two nodes (ZPAL G.36/1–3). C, E. Specimens with one node (ZPAL G.36/4–5). s., stolon.
Data set of "Large superconducting diode effect in ion-beam patterned Sn-based superconductor nanowire/topological Dirac semimetal planar heterostructures"
<p><span>Superconductor/topological material heterostructures are intensively studied as a platform for topological superconductivity and Majorana </span><span>physics</span><span>. However, the high cost of nanofabrication and the difficulty of preparing high-quality interfaces between the two dissimilar materials are common obstacles that hinder the observation of intrinsic physics and </span><span>the </span><span>realisation of scalable topological devices and circuits. </span><span>Here, we demonstrate an innovative method to directly draw nanoscale superconducting </span><span><span>beta-tin (</span></span><span><span>β-Sn</span></span><span><span>)</span></span><span><span> patterns of any shape in the plane of a topological Dirac </span></span><span><span>semimetal</span></span><span><span> (TDS) </span></span><span><span>alpha-tin (</span></span><span><span>α-Sn</span></span><span><span>)</span></span><span><span> thin </span></span><span><span>film</span></span><span><span> by irradiating a focused ion beam (FIB</span></span><span><span>). We utilise</span></span><span><span> the property that α-Sn undergoes a phase transition to superconducting β-Sn upon heating by FIB. </span></span><span><span>In β-Sn nanowires embedded in a TDS α-Sn thin film, we observe large </span></span><span><span>non-reciprocal</span></span><span><span> superconducting transport, where the critical current changes by 69% upon reversing the current direction. The superconducting diode rectification ratio <em>η</em> reaches a maximum of 35% when the magnetic field is applied parallel to the current, </span></span><span><span>distinguishing</span></span><span><span> itself from all the previous reports</span></span><span><span>. Moreover, it</span></span><span><span> oscillates between alternate signs with increasing magnetic field strength. </span></span><span><span>The angular</span></span><span><span> dependence of <em>η</em> on the magnetic field and current directions is similar to that of the chiral anomaly effect in TDS α-Sn, suggesting that the </span></span><span><span>SDE</span></span><span><span> may occur at the α-Sn/</span></span><span><span>β</span></span><span><span>-Sn interfaces where the TDS α-Sn becomes superconducting by a proximity effect.</span></span><span><span> As superconducting TDSs are expected candidates for topological superconductivity and harboring Majorana bound states,</span></span><span><span> t</span></span><span><span>he ion-beam patterned Sn-based superconductor/TDS planar structures thus </span></span><span><span>show promise</span></span><span><span> as a universal platform for investigating novel quantum physics and devices based on topological superconducting circuits of any shape.</span></span></p>
Original data and code for "Wave-function engineering on superconducting substrates: Chiral Yu-Shiba-Rusinov molecules"
<p>We provide all experimental data and the code to simulate the tight-binding YSR patterns in the paper "Wave-function engineering on superconducting substrates: Chiral Yu-Shiba-Rusinov molecules"</p>
Datasets for Manuscript: Neural-Network-Assisted Detection of Superconducting Topological Semimetals
<p>This file contains datasets for an original machine-learning-approach that we developed for the identification of superconducting topological semimetals.</p>
Reproduction package to "Phonon-Trapping Enhanced Energy Resolution in Superconducting Single-Photon Detectors"
<p>This is a reproduction package to the paper "Phonon-Trapping Enhanced Energy Resolution in Superconducting Single-Photon Detectors", which is published in <a href="https://doi.org/10.1103/PhysRevApplied.16.034051">Physical Review Applied</a>. It contains all data and code to reproduce the figures in this paper.</p>
Chiral surface superconductivity in half-Heusler semimetals
<p>Input and relevant output files for the VASP first-principles calculations on LuPtBi half-Heusler semimetal shown in the manuscript.</p>
Data used in the article "High-Q magnetic levitation and control of superconducting microspheres at millikelvin temperatures"
<p>Data used in the article "High-Q magnetic levitation and control of superconducting microspheres at millikelvin temperatures".</p>
The source data for "Inductively shunted transmon: A superconducting qubit with flux noise insensitive plasmon states and a protected fluxon decay exceeding 3 hours"
<p>The following folder contains all the raw data, analysis Mathematica notebook and ScQubits python codes used to generate the results in “Inductively shunted transmon: A superconducting qubit with flux noise insensitive plasmon states and a protected fluxon decay exceeding 3 hours” in nature communications. Please follow the instruction below for proper navigation through the data:</p> <p>Fig. 1 folder:</p> <ol> <li>Run “Color map of Matrix element Vs energy parameters” to generate “x.dat”, “y.dat”, ”M.dat”(respectively EJ/EL, EJ/EC and the matrix element of the first flux transition). <strong>Make sure to correct the address where these file should be saved</strong>.</li> <li>The mathematica notebook plots the dispersion in IST limit and the matrix element gray scale color map contours separately and the full image was constructed in illustrator later. The green dots on the dispersion plot represent the position of other qubits on the color map. </li> </ol> <p>Fig. 2&3 folder:</p> <ol> <li>The python file “paper figures” uses ScQubits to generate different studies in IST limit presented in Fig. 2&3 and generates the following files:</li> </ol> <p>Fig. 2a:</p> <p>“fluxonium.hdf5”: The spectrum of a typical fluxonium</p> <p>“fluxoniumME.hdf5”: The matrix element of all transition in “fluxonium.hdf5”</p> <p> </p> <p>Fig. 2d:</p> <p>“case1.hdf5”: The spectrum of fluxonium with EJ/EC=6.6</p> <p>“ME1.hdf5”: The matrix element of transition in “case1.hdf5”</p> <p>“case2.hdf5”: The spectrum of fluxonium with EJ/EC=13</p> <p>“ME2.hdf5”: The matrix element of transition in “case2.hdf5”</p> <p>.</p> <p>.</p> <p>“case6.hdf5”: The spectrum of fluxonium with EJ/EC=200</p> <p>“ME6.hdf5”: The matrix element of transition in “case6.hdf5”</p> <p>“IST.hdf5”: The spectrum of the IST qubit</p> <p>“ISTME.hdf5”: The matrix element of transition in “IST.hdf5”</p> <p>“transmon.hdf5”: The spectrum of a transmon with the same EJ and EC as IST qubit</p> <p>Fig. 3a</p> <p>“Waveamp.hdf5”: The wave functions and eigenenergies of the IST qubit</p> <p>“WaveampT.hdf5”: The wave functions and eigenenergies of the transmon</p> <p> </p> <p>Fig. 3b:</p> <p>“ELcase1.hdf5”: The spectrum of IST qubit with EL=2 GHz</p> <p>“ELME1.hdf5”: The matrix element of transition in “ELcase1.hdf5”</p> <p>“ELcase2.hdf5”: The spectrum of IST qubit with EL=1.5 GHz</p> <p>“ELME2.hdf5”: The matrix element of transition in “ELcase2.hdf5”</p> <p>.</p> <p>.</p> <p>“ELcase6.hdf5”: The spectrum of IST qubit with EL=0.25 GHz</p> <p>“ELME6.hdf5”: The matrix element of transition in “ELcase6.hdf5”</p> <p> </p> <p>Fig. 3b inset:</p> <p>“WaveampEL.hdf5”contains the wave functions for El={2,1.5,1,0.75,0.5,0.25}GHz.</p> <p> </p> <p>Fig. 3c:</p> <p>“EC.hdf5” contains numerical simulation of an IST qubit with fixed EJ and Ec while EL is changing to calculate anharmonicity.</p> <ol> <li>The Mathematica notebook “Theory_figures” runs based on the files above and plot the result presented in the paper.</li> </ol> <p>Fig. 5 folder:</p> <ol> <li>Fig. 5a&b folder contains the raw data of spectroscopy of the IST qubit with different temperature and the Mathematica notebook “Tempsweeps_figa&b” simply plots the data. In the data set the I and Q quadrature as well as the amplitude and power of the signal coming back from cavity is provided.</li> <li>Fig. 5c folder contains several sweeps of both spectroscopy and resonator performed at fridge base temperature (7mK) labeled as “specge#.txt” and “Res_VNA_*.txt” respectively. The ScQubits python code “IST_Device” provides a fit for the data using the fit procedure explained in Supplementary Note 4 and generates the bare spectrum of the device saved in “Fit.h5”. The Mathematica notebook “spec_analysis” uses all spectroscopy data and the fit file to plot Fig. 5c.</li> </ol> <p>Fig. 6 folder: Contains all the raw data of T1 and T2 experiment at different flux positions across a flux quantum. The Mathematica notebook “T1&2” performs all the analysis presented in Fig. 6 for devices A, B and C.</p> <p>Fig. 7 folder:</p> <ol> <li>Fig. 7a: In this folder the we provide the raw data for fidelity experiment. The data is in the “*.mat” format and contains 40000 single shot I&Q bins collected with measurement band width of 2MHz and integration time of 500ns. The files names indicate whether the data was taken with qubit prepared in ground/excited state by having “_g_”/”_e_”. Following the state preparation condition, the measurement power at which the data was taken is indicated. The Mathematica notebook “fidelity_sweep” takes the data and extract the fidelities shown in Fig. 7a and the 2D histogram plots presented in Supplementary Figure 5d.</li> <li>Fig. 7b: The raw data for QND-ness experiment is presented in this folder. Each file contains 500 time traces of the two consecutive pulses applied to the resonator to study the non-QND effects of the IST qubit in high power. The Qubit preparation condition is apparent in the file name along with the power at which the measurement was performed. The Mathematica notebook “QND_ness” extracts the QND_ness and plots the results shown in Fig. 7b</li> </ol> <p> </p> <p>Fig. 8 folder:</p> <ol> <li>Fig. 8a: This folder contains the spectroscopy sweeps conditions by the fluxon state using a strong microwave pulse applied to the resonator. The Mathematica notebook “sweeps” plots the data.</li> <li>Fig. 8c: This folder contains the raw data for long fluxon decays collected using quantum machines (QM). In this experiment the fluxon excitation pulse was applied and repeated until a successful fluxon state is detected. Afterwards, the experiment enters monitoring stage where every 30s we check the fluxon state until a tunneling to fluxon ground state is detected. This event is logged and the QM repeats the fluxon excitation immediately followed by a monitoring stage and logging the time it took for tunneling to occur. The raw data of every 30 second monitoring stage is saved in files with “_raw_” in their labels. The files containing “_taus_” in their names have only the logged tunneling time events. The Mathematica notebook “qubit analysis” takes the data for three external flux bias and, by loading the “_taus_” files, reconstructs the quasi quantum jump traces and finally the decay traces presented in Fig. 8c.</li> </ol>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.