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123 results for “qubits”
Quantum critical dynamics in a 5000-qubit programmable spin glass: data repository
<p>Supporting data for "Quantum critical dynamics in a 5000-qubit programmable spin glass", Nature, 2023.</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>
Data for publication "Measuring the environment of a Cs qubit with dynamical decoupling sequences"
<p>Data sets as plotted in the preprint "Measuring the environment of a Cs qubit with dynamical decoupling sequences" are uploaded.<br> The zip file "data" contains a folder for each figure in the preprint (named after the figure). Each folder contains the data for all graphs in the respective figure.</p>
A Binary Integer Programming-based Method for Qubit Mapping in Sparse Architectures
<p>Qubit Mapping Based on MIP</p>
Data of "A network-ready random-access qubits memory"
<p>Data published in "<em>A network-ready random-access qubits memory</em>"</p> <p><em>npj Quantum Information</em></p>
Data of "Nondestructive detection of photonic qubits"
<p>Data published in "<em> Nondestructive detection of photonic qubits</em>"</p>
Dataset for Exploring the Organometallic Route to Molecular Spin Qubits: the [CpTi(cot)] case
<p>ASCII file in X,Y format of data reported in Figure 2, 3, and 4 of publication</p> <p>Exploring the Organometallic Route to Molecular Spin Qubits: The [CpTi(cot)] Case</p> <p>L. C. de Camargo, M. Briganti, F. S. Santana, D. Stinghen, R. R. Ribeiro, G. G. Nunes, J. F. Soares, E. Salvadori, M. Chiesa, S. Benci, R. Torre, L. Sorace, F. Totti, R. Sessoli,</p> <p>Angew. Chem. Int. Ed. 2021, 60, 2588-2593.</p> <p>https://doi.org/10.1002/anie.202009634</p>
Assessment of error variation in high-fidelity two-qubit gates in silicon
<p>The data and the analysis files for the paper titled: "Assessment of the errors of high-fidelity two-qubit gates in silicon quantum dots" https://arxiv.org/abs/2303.04090 Analysis files written in python and in matlab. Some files need the PyGSTi to run.</p>
Universal quantum gate set for Gottesman-Kitaev-Preskill logical qubits
<p>The Excel files contain experimental data corresponding to figures 2,3,4 of the paper "Universal Quantum Gate Set for Gottesman-Kitaev-Preskill Logical Qubits", available at <a href="https://arxiv.org/abs/2409.05455">arxiv:2409.05455</a> </p> <p>The contents of the files are described in README.txt.</p>
Data for "Qubit fractionalization and emergent majorana liquid in the honeycomb floquet code induced by coherent errors and weak measurements"
<p>From the perspective of quantum many-body physics, the Floquet code of Hastings and Haah can be thought of as a measurement-only version of the Kitaev honeycomb model where a periodic sequence of two-qubit XX, YY, and ZZ measurements dynamically stabilizes a toric code state with two logical qubits. However, the most striking feature of the Kitaev model is its intrinsic fractionalization of quantum spins into an emergent gauge field and itinerant Majorana fermions that form a Dirac liquid, which is absent in the Floquet code. Here we demonstrate that by varying the measurement strength of the honeycomb Floquet code one can observe features akin to the fractionalization physics of the Kitaev model at finite temperature. Introducing coherent errors to weaken the measurements we observe three consecutive stages that reveal qubit fractionalization (for weak measurements), the formation of a Majorana liquid (for intermediate measurement strength), and Majorana pairing together with gauge ordering (for strong measurements). Our analysis is based on a mapping of the imperfect Floquet code to random Gaussian fermionic circuits (networks) that can be Monte Carlo sampled, exposing two crossover peaks. With an eye on circuit implementations, our analysis demonstrates that the Floquet code, in contrast to the toric code, does not immediately break down to a trivial state under weak measurements, but instead gives way to a long-range entangled Majorana liquid state.</p>
Data underpinning "Chaotic fluctuations in a universal set of transmon qubit gates"
<p>Transmon qubits arise from the quantization of nonlinear resonators, systems that are prone to the buildup of strong, possibly even chaotic, fluctuations. One may wonder to what extent fast gate operations, which involve the transient population of states outside the computational subspace, can be affected by such instabilities. We<br>here consider the eigenphases and -states of the time evolution operators describing a universal gate set, and analyze them by methodology otherwise applied in the context of many-body physics. Specifically, we discuss their spectral statistic, the distribution of time dependent level curvatures, and state occupations in- and outside the computational subspace. We observe that fast entangling gates, operating at speeds close to the so-called quantum speed limit, contain transient regimes where the dynamics indeed becomes partially chaotic. We find that for these gates even small variations of Hamiltonian or control parameters lead to large gate errors and speculate on the consequences for the practical implementation of quantum control.</p>
Data for the article "Capacitive coupling of coherent quantum phase slip qubits to a resonator"
<p>Zip file containing data for the article "Capacitive coupling of coherent quantum phase slip qubits to a resonator" published in the New Journal of Physics. The data used in the figures and tables are saved in separate txt files.</p>
Capacitive crosstalk in gate-based dispersive sensing of spin qubits
<p>supporting data from paper 'Capacitive crosstalk in gate-based dispersive sensing of spin qubits' by E. G. Kelly, A. Orekhov, N. Hendrickx, M. Mergenthaler, F. Schupp, S. Paredes, R. S. Eggli, A. V. Kuhlmann, P. Harvey-Collard, A. Fuhrer and G. Salis</p>
Tomography of entangling two-qubit logic operations in exchange-coupled donor electron spin qubits
<p>Scalable quantum processors require high-fidelity universal quantum logic operations in a manufacturable physical platform. Donors in silicon provide atomic size, excellent quantum coherence and compatibility with standard semiconductor processing, but no entanglement between donor-bound electron spins has been demonstrated to date. Here we present the experimental demonstration and tomography of universal 1- and 2-qubit gates in a system of two weakly exchange-coupled electrons, bound to single phosphorus donors introduced in silicon by ion implantation. We surprisingly observe that the exchange interaction has no effect on the qubit coherence. We quantify the fidelity of the quantum operations using gate set tomography (GST), and we use the universal gate set to create entangled Bell states of the electrons spins, with fidelity ≈ 93%, and concurrence 0.91 ± 0.08. These results form the necessary basis for scaling up donor-based quantum computers.</p>
Data accompanying: Sweet-spot operation of a germanium hole spin qubit with highly anisotropic noise sensitivity
<p>These are the data accompanying the publication titled: 'Sweet-spot operation of a germanium hole spin qubit with highly anisotropic noise sensitivity'.</p>
Numerical dataset for quantum trajectory simulations of a dissipative qubit under continuous measurement and feedback
<p>The data consist of numerical results obtained from quantum trajectory simulations of a dissipative qubit under continuous measurement and feedback.</p> <p>These data are used in the preprint titled <em>"Heat current and fluctuations between a dissipative qubit and a monitor under continuous measurement and feedback."</em></p> <p>We performed numerical simulations of the stochastic master equation using the supercomputer at ISSP.</p> <p>The contents are as follows:</p> <ul> <li>Numerical results for the correlation functions (<code>F*.dat</code>).</li> <li>Numerical results for the Fano factor and the power spectrum (<code>fano_factor*.dat</code>).</li> <li>Python code to calculate the Fano factor and the power spectrum from the correlation functions (<code>fano_factor_v6.py</code>).</li> <li>Figures illustrating the Fano factor and the power spectrum (<code>fig*.eps</code>).</li> </ul>
Data from "Hardware-efficient quantum error correction using concatenated bosonic qubits"
<p>Includes data for characterizing the bit-flip and logical phase-flip rates of the logical memory. See the README for more details.</p>
Source data for the publication "Ultra-dispersive resonator readout of a quantum-dot qubit using longitudinal coupling"
<div> <p>This repository contains data and source code for the publication "Ultra-dispersive resonator readout of a quantum-dot qubit using longitudinal coupling."</p> </div>
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>
Dataset: "Generalized scaling of spin qubit coherence in over 12,000 host materials"
<p>Accompanying data for the main text and supplemental materials of <strong><em>Generalized scaling of spin qubit coherence in over 12,000 host materials</em></strong></p>
ScienceDex guides
Understand access before you commit
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.