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639 results for “spin”
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 for: Hidden non-collinear spin-order induced topological surface states
<p>Rare-earth monopnictides are a family of materials simultaneously displaying complex magnetism, strong electronic correlation, and topological band structure. The recently discovered emergent arc-like surface states in these materials have been attributed to the multi-wave-vector antiferromagnetic order, yet the direct experimental evidence has been elusive. Here we report the observation of non-collinear antiferromagnetic order with multiple modulations using spin-polarized scanning tunneling microscopy. Moreover, we discover a hidden spin-rotation transition of single-to-multiple modulations 2 K below the Neel temperature. The hidden transition coincides with the onset of the surface state splitting observed by our angle-resolved photoemission spectroscopy measurements. Single modulation gives rise to a band inversion with induced topological surface states in a local momentum region while the full Brillouin zone carries trivial topological indices, and multiple modulation further splits the surface bands via non-collinear spin tilting, as revealed by our calculations. The direct evidence of the non-collinear spin order in NdSb not only clarifies the mechanism of the emergent topological surface states but also opens up a new paradigm of control and manipulation of band topology with magnetism.</p>
Data for the manuscript "Correlation between two distant quasiparticles in separate superconducting islands mediated by a single spin"
<p>Data for the manuscript "Correlation between two distant quasiparticles in separate superconducting islands mediated by a single spin", https://doi.org/10.48550/arXiv.2203.00104</p> <p>The archive contains the experimental data and the results of numerical calculations as well as plotting scripts/notebooks for the figures presented in the manuscript.</p>
Supplementary material to 'Exotic Symmetry Breaking Properties of Self-Dual Fracton Spin Models'
<p>I. GENERAL INFORMATION</p> <p>1. Title<br>Dataset of "Degeneracy and Scaling Properties of Self-Dual Fracton Spin Models"</p> <p>2. Author Information<br> <br>Giovanni Canossa [1,2], Lode Pollet [1,2], Miguel A. Martin-Delgado [3,4], Hao Song [5], and Ke Liu [1,2,6,7]<br>1. Arnold Sommerfeld Center for Theoretical Physics, University of Munich</p> <p>2. Munich Center for Quantum Science and Technology (MCQST)</p> <p>3. Departamento de Física Teórica, Universidad Complutense, 28040 Madrid, Spain</p> <p>4. CCS-Center for Computational Simulation, Universidad Politécnica de Madrid, Spain</p> <p>5. CAS Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China</p> <p>6. Hefei National Research Center for Physical Sciences at the Microscale, University of technology of China</p> <p>7. Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China</p> <p>Links to publications that cite or use the data:<br>TBA</p> <p>II. Files</p> <p>1. Convention</p> <p>Datas from the multicanonical MC simulations are stored in "Tetra-Ising" and "Fractal-Ising" folders.</p> <p>Lattice size: Each subfolder is named "L=value" where value denotes the linear system size.</p> <p>Multicanonical weights: Files "g_init_T=value.data" contains the set of log(weights) at a given temperature and lattice size, derived from the iterative weight-learning procedure.</p> <p>Datas: HDF5 files "name.out.h5" contain the results of the multicanonical MC simulation at a given lattice size.</p> <p><br>III. Data in HDF5 file</p> <p>1. Convention</p> <p>The results obtained at each temperature point is stored in a separate subdirectory of the .out.h5 file. Each of these subdirectories contains:</p> <p>Energy_Hist: normalized energy histograms obtained from the multicanonical MC simulation (unweighted)</p> <p>Energy_Hist_rw: normalized reweighted energy histograms. For each bin, Energy_Hist_rw[i] = Energy_Hist[i] * e**g[i] / norm, where norm = sum( Energy_Hist[i] * e**g[i] ).</p> <p>c: 1/norm. Gives an estimate of the ratio Z_muca/Z_ca.</p> <p>g: vector containing the weights used for the multicanonical MC simulation at that specific temperature. These are derived from reweighting the weights in "g_init_T=value.data" file.</p> <p>Energy, Energy_Susc, Energy_Kurt Q_x, Q_x_Susc, Q_x_Kurt: canonical expectation value of each relevant observables, along with their susceptibilities and Kurtosis, obtained by reweighting each measurement taken during the simulation by the appropriate weight. (NB: Energy and Q_x need to be multiplied by C in order to give the correct canonical expectation value.)</p> <p><br>2. Relevance</p> <p>These data reproduce Figs. 5 & 6 in the manuscript.</p> <p><br>III. Finite size scaling</p> <p>1. Convention</p> <p>All estimated transition temperatures with their respective uncertainties are stored in "fitting_Tetra" and "fitting_Fractal" folders in the fittemps.txt file.</p> <p>2. Relevance</p> <p>These data reproduce Figs. 3 & 4 in the manuscript.<br> </p> <p> </p>
Data generated from calculations in "Gauge Field Dynamics in a Multilayer Kitaev Spin Liquid"
<p>The Kitaev honeycomb model hosts a quantum spin liquid in its ground state, where the excitations are gapless Majorana fermions and static <span><span><span><span><span><span><span>Z</span></span></span><span>2</span></span></span></span></span> gauge fluxes called visons. We consider Kitaev models stacked on top of each other, weakly coupled by Heisenberg interaction linear in <span><span><span><span><span>J</span><span>⊥</span></span></span></span></span>. This inter-layer coupling breaks the integrability of the model and makes the gauge fields dynamic. While single visons stay static in this model, an inter-layer pair of visons can hop with a hopping amplitude linear in <span><span><span><span><span>J</span><span><span><span>⊥</span></span></span></span></span></span></span>, but remains confined to a single plane. An intra-layer vison-pair, in contrast, is constrained to move along the stacking direction only. Depending on the anisotropy of the Kitaev couplings <span><span><span><span><span>K</span><span>x</span></span><span>,</span><span><span>K</span><span>y</span></span><span>,</span><span><span>K</span><span>z</span></span></span></span></span>, the intra-layer vison pairs show completely different dynamical behaviours. While coherent intra-layer tunnelling is possible for sufficiently strong anisotropies, only incoherent processes are possible in the isotropic case. When a magnetic field opens a gap for Majorana fermions, one can identify two types of intra-layer vison pairs, one bosonic and one fermionic. Only the bosonic pair obtains a hopping rate linear in <span><span><span><span><span>J</span><span>⊥</span></span></span></span></span>. We argue that our results can be used to identify leading instabilities of the Kitaev phase induced by the inter-layer coupling.</p>
Dataset for: AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures
<p>Data used in the publication: AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures</p>
Dynamics of magnetization at infinite temperature in a Heisenberg spin chain
<p>Transferred magnetization data presented in arxiv.org/abs/2306.09333. </p> <p>The files are named according to the parameters mu, which describes the initial magnetization imbalance, and Delta, which describes the relative strengths of XX+YY and ZZ in the Hamiltonian. Each file contains a dictionary with the following keys (see manuscript for further details):</p> <p>n: Number of qubits<br>mu: Initial magnetization imbalance parameter<br>theta: fSim-gate parameter controlling XX+YY coupling<br>phi: fSim-gate parameter controlling ZZ coupling<br>mean: Mean magnetization transfer as a function of circuit depth<br>d_mean: Uncertainty in mean magnetization transfer<br>moments: n-th central moments for as a function of circuit depth, starting with n=0<br>d_moments: Uncertainty in central moments<br>skewness: Skewness of distribution of transferred magnetization as a function of circuit depth<br>d_skewness: Uncertainty in skewness as a function of circuit depth<br>kurtosis: Kurtosis of distribution of transferred magnetization as a function of circuit depth<br>d_kurtosis: Uncertainty in kurtosis as a function of circuit depth<br>Z: Expectation value of Z for each initial state, qubit and circuit depth<br>nTrials: Number of different initial states investigated</p> <p>In addition, the file `numerical_simulation_results.zip` contains the results of classical statevector simulations of our experiment, up to cycle 18.</p>
Higher order spin interactions mediated by the substrate
<p>Raw data for the plots used in the paper. Every file has the x axis as the first column and the appropriate interaction as the second column. To obtain the same values as in the paper, normalize the second column by the hopping (t = 0.5). </p> <p>The expression for the fourth order expansion term was obtained using the SNEG package (http://nrgljubljana.ijs.si/sneg/) but can be handled by Mathematica. </p> <p> </p> <p>nc is the non-commutative multiplication</p> <p> </p> <p>Electron field operators are expressed with the following subscripts:</p> <p>c[type, site, time, spin] </p> <p>type: 0 - creation; 1 - annihilation</p> <p>site: from i_1 to i_4</p> <p>time: imaginary time from t_1 to t_4</p> <p>spin: 1,2,3 representing x,y,z</p> <p> </p> <p>Spin operators are expressed with the following subscripts:</p> <p>S[site,spin]</p> <p>site: from i_1 to i_4</p> <p>spin: 1,2,3 representing x,y,z</p>
Control of Charge-Spin Interconversion in van der Waals Heterostructures with Chiral Charge Density Waves
Open the record for dataset details and reuse information.
Dataset for "Reconfigurable spin-wave platform based on interplay between nanodots and waveguide in hybrid magnonic crystal"
<p>The dataset consist of the data used to prepare the figures for the manuscript: </p> <p>Krzysztof Szulc, Mateusz Zelent, Maciej Krawczyk<br><em>Reconfigurable spin-wave platform based on interplay between nanodots and waveguide in hybrid magnonic crystal.</em></p> <p>together with animated version of two figures: Figure 4 and Figure S1.</p> <p>Please read README.txt file to see the description of the data in the files.</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>
Data for: Intervalley coherence and intrinsic spin-orbit coupling in rhombohedral trilayer graphene
<p>Data files and data fitting code for manuscript "Intervalley coherence and intrinsic spin-orbit coupling in rhombohedral trilayer graphene." Analysis files Figure3.ipynb and Extracting_lambda.ipynb generate processed data for Fig 3 and extract values of lambda (spin orbit coupling strength) respectively. </p>
Gate-Tunable Spin Hall Effect in Trilayer Graphene/Group-IV Monochalcogenide van der Waals Heterostructures
Open the record for dataset details and reuse information.
Data for "Observation of Generalized t-J Spin Dynamics with Tunable Dipolar Interactions"
<p>Calculated dipole parameters, experimental and theoretical data and code needed to reproduce all plots of the paper, and separate csv files with data points of main figures. </p> <p> </p>
Single-Shot Three-Dimensional Orientation Imaging of Nanorods Using Spin to Orbital Angular Momentum Conversion_experimental_dataset
<p>This is the datafile containing the raw experimental data to the article Fordey et al., Single-Shot Three-Dimensional Orientation Imaging of Nanorods Using Spin to Orbital Angular Momentum Conversion, <em>Nano Lett.</em> 2021, 21, 17, 7244–7251. </p>
Data and Code for Spin and Orbital Spectroscopy in the Absence of Coulomb Blockade in Lead Telluride Nanowire Quantum Dots
<p>This repository contains combined data for two papers. </p> <p>Growth of PbTe nanowires by Molecular Beam Epitaxy<br> Authors: Sander G. Schellingerhout, Eline J. de Jong, Maksim Gomanko, Xin Guan, Yifan Jiang, Max S.M. Hoskam,<br> Sebastian Koelling, Oussama Moutanabbir, Marcel A. Verheijen, Sergey M. Frolov, Erik P.A.M. Bakkers</p> <p><br> Spin and Orbital Spectroscopy in the Absence of Coulomb Blockade in Lead Telluride Nanowire Quantum Dots<br> Authors: M. Gomanko, E.J. de Jong, Y. Jiang, S.G. Schellingerhout, E.P.A.M. Bakkers, and S.M. Frolov</p> <p><br> Content of this repository: </p> <p>Readme file. </p> <p>/RawData/<br> Original data obtained at the time of measurement separated into 3 folders from different chips/cooldowns<br> Data from devices 1,3 and 4 can be found in "RawData/PbTe_chip1", device 2 in "RawData/PbTe_chip2" and devices 5-8 in "RawData/PbTe_GBg"</p> <p>/Measurement notebooks/<br> OneNote notebook with 4 different sections for 3 chips (two sections for backgate chip). Pages in these sections contain the device number in the name.<br> Also, the same notebook is exported in pdf format for convenience.</p> <p>/Data processing/<br> Readme file, Jupiter notebooks, data files, and pictures, that were used to extract g-factors for different field orientations in device2.</p> <p>/Data summaries/<br> Powerpoints, that were used to overview data during the measurement stage.<br> Not all data from these powerpoints are present in the repository or paper (specifically excluding early data used in "additional backgate devices.pptx" and "PbTe 3rd device.pptx").</p> <p>Data file types:</p> <p>data_NNN.dat - the original data file obtained at the time of the experiment<br> dataNNN.py - the original QTLab data acquisition script saved with data<br> data_NNN.set - settings of measurement instruments at the time of measurement<br> data_NNN.meta - auxillary file necessary for plotting data using SpyView (see below) <br> data_NNN.MTX - a simple 2D/3D matrix format developed for Spyview</p> <p>NNN stands for dataset number, automatically indexed by QTLab</p> <p><br> How to plot data:</p> <p>1) Spyview - a free data plotting program written by Gary Steele</p> <p>Data in this repository can be simply dropped into Spyview for plotting. </p> <p>Spyview also produces and can read .mtx files which are available for some of the data in this repository.</p> <p>https://nsweb.tn.tudelft.nl/~gsteele/spyview/</p> <p><br> 2) QTPlot - a Python plotter written by Ruben van Gulik</p> <p>Data in this repository can be directly opened with QTPlot, which will read axis labels.</p> <p>https://github.com/Rubenknex/qtplot</p> <p>Note: requires PyQT4</p>
Spin-voltage-driven efficient terahertz spin currents from the magnetic Weyl semimetals Co2MnGa and Co2MnAl
<p>We study ultrafast optically driven spin injection from thin films of the magnetic Weyl semimetals Co<sub>2</sub>MnGa and Co<sub>2</sub>MnAl into an adjacent Pt layer by means of terahertz emission spectroscopy. The following datasets are provided: THz waveforms, THz emission-signal amplitudes (rms) vs pump power, scaled THz signals as a figure of merit in terms of spin-injection efficiency, corresponding broadband spectra and extracted spin currents.</p>
Spin-Charge Conversion in Fe/Au/Sb2Te3 Heterostructures as Probed By Spin Pumping Ferromagnetic Resonance (data)
<p>This dataset contains the raw data files connected with the figures included in the paper "<em>Spin-Charge Conversion in Fe/Au/Sb<sub>2</sub>Te<sub>3</sub> Heterostructures as Probed By Spin Pumping Ferromagnetic Resonance</em>" by <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/admi.202101244">E. Longo et al.<em>, </em><em>Adv. Mater. Interfaces</em> 2021, 2101244</a>.</p>
Frequency multiplication by collective nanoscale spin wave dynamics
<p>This dataset contains all primary data used in the manuscript.</p>
CW EPR data supporting : Twenty-three–millisecond electron spin coherence of erbium ions in a natural-abundance crystal
<p>Continuous Wave electron spin resonance. Data corresponding to supporting information. Sample: CaWO4 recorded at 8K</p> <p>Dataset for the reference :</p> <p>Twenty-three–millisecond electron spin coherence of erbium ions in a natural-abundance crystal</p> <p>https://doi.org/10.1126/sciadv.abj9786</p> <p> </p> <p><strong>Marianne Le Dantec</strong><strong>, Miloš Rančić</strong><strong>, Sen Lin</strong><strong>, Eric Billaud</strong><strong>, Vishal Ranjan</strong><strong>,<br> Daniel Flanigan, Sylvain Bertaina</strong><strong>, Thierry Chanelière</strong><strong>, Philippe Goldner</strong><strong>, Andreas Erb</strong><strong>, </strong><br> <strong>Ren Bao Liu , Daniel Estève , Denis Vion , Emmanuel Flurin , Patrice Bertet * </strong></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
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.