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235 results for “Lattices”
FCC-ee lattice
<p>Repository containing the FCC-ee lattices.</p>
Determination of sub-ps lattice dynamics in FeRh thin films
<p>Open Access Data for "Determination of sub-ps lattice dynamics in FeRh thin films" published in Scientific Reports <strong>12</strong>, 8584 (2022)</p> <p>https://doi.org/10.1038/s41598-022-12602-w</p> <p> </p> <p>Raw data from the XFEL experiment are accessible at https://doi.psi.ch/detail/10.16907%2F85ff2f32-f561-4413-a02a-74abc65cc82b</p>
EXAMPLE: Lattice-based equation of state tables with three conserved charges (BSQ)
<p>These table is intended to provide an example format of the equation of state expected for the CCAKE hydrodynamic code which propagates conserved charge densities for baryon number <span class="math-tex">\(B\)</span>, net strangeness <span class="math-tex">\(S\)</span>, and electric charge <span class="math-tex">\(Q\)</span>. They are included primarily for demonstration purposes and no claim is made as to the accuracy of their contents.</p>
Supplemental Dataset: Seismological evidence for girdled olivine lattice-preferred orientation in oceanic lithosphere and implications for mantle deformation processes during seafloor spreading
<p>This repository contains supplementary datasets for the manuscript titled "Seismological evidence for girdled olivine lattice-preferred orientation in oceanic lithosphere and implications for mantle deformation processes during seafloor spreading", published in G-Cubed. All files are Microsoft Excel tables containing olivine fabric data.</p> <p>ds01_strain_data_ol60.xlsx: Anisotropy magnitude and fast directions for sample data shown in Figure 3 of the main text, assuming 60% olivine and 40% pyroxene (see methods for details).</p> <p>ds02_strain_data_ol100.xlsx: Anisotropy magnitude and fast directions for sample data shown in Figure 3 of the main text, assuming pure olivine.</p> <p>ds03_fabric_data_ol75.xlsx: Anisotropy fabric data shown in Figure 5 of the main text, assuming 75% olvine and 25% pyroxene (see methods for details).</p> <p>ds04_fabric_data_ol100.xlsx: Anisotropy fabric data shown in Figure 5 of the main text, assuming pure olivine.</p> <p> </p>
Confs N_f=2+1 physical point fullQCD T=230 MeV, lattice = 40^3 x 10
<p>README (Written by Claudio Bonanno: claudio.bonanno@fi.infn.it)</p> <p>Archives of thermalized and well-decorrelated gauge configurations</p> <p>Discretization: Symanzik-improved gauge action & N_f = 2+1 flavors of rooted stout staggered fermions with physical quark masses<br> and physical pion mass</p> <p>Theory details: T=230 MeV, 40^3 x 10 lattice with a lattice spacing a = 0.0857 fm.</p> <p>Algorithm: standard RHMC.</p> <p>Conf name: stored_conf.${conf_ID} where conf_ID is equal to the RHMC step the conf has been saved.</p> <p>Conf have been saved every 30 RHMC seps in binary files according to the ILDG format for standard C programs.</p> <p>For more details about the ILDG format see, e.g., https://www-zeuthen.desy.de/~pleiter/ildg/ildg-file-format-1.1.pdf</p>
Supplemental data for the report "Optimisation of lattice simulations energy efficiency"
<p>Supplemental data for the report <a href="http://doi.org/10.5281/zenodo.7057319">"Optimisation of lattice simulations energy efficiency"</a>. Also available as a <a href="https://git.dev.dirac.ed.ac.uk/portelli/tursa-energy-efficiency">git repository</a>.</p> <p>It contains:</p> <ul> <li>Full copy of benchmark run directories</li> <li>Power monitoring scripts</li> <li>Power monitoring raw measurements</li> <li>Power monitoring data analysis and results used in the report</li> </ul> <p>For a more complete description, please see the README.md file.</p>
Raw data from the pCUT+MC approach for the antiferromagnetic Heisenberg square lattice bilayer model with (non-frustrating) long-range interactions
<p>This directory contains the data from the pCUT+MC approach for the antiferromagnetic Heisenberg square lattice bilayer model with (non-frustrating) long-range interactions.</p> <p>To get an overview of the organization of the directory and a description of the data we recommend the README.md file.</p> <p>The data is published in P. Adelhardt, J. A. Koziol, A. Langheld, and K. P. Schmidt, "Monte Carlo based techniques for quantum magnets with long-range interactions", <a href="https://arxiv.org/abs/2403.00421">arXiv:2403.00421</a></p>
A series of pathological macromolecular crystallography datasets with twinning and other lattice disorders - part II
<p>This entry is linked to a previous deposition with DOI : 10.5281/zenodo.54568 which is discussed in the same manuscript </p> <p> </p>
Angle-dependent magnetization dynamics with mirror-symmetric excitations in artificial quasicrystalline nanomagnet lattices
<p>The file ManscuriptDataFiles.7z contains RAW spectroscopy data, origin plot file, micromagnetic simulation MIF files at 100 mT used in the manuscript entitiled "Angle-dependent magnetization dynamics with mirror-symmetric excitations in artificial quasicrystalline nanomagnet lattices" that appeared in Physical Review B, <strong>98</strong>, 174408 (2018).</p> <p>Manuscript Abstract: We report angle-dependent spin-wave spectroscopy on aperiodic quasicrystalline magnetic lattices, i.e., Ammann, Penrose P2 and P3 lattices made of large arrays of interconnected Ni<sub>80</sub>Fe<sub>20</sub> nanobars. Spin-wave spectra obtained in the nearly saturated state contain distinct sets of resonances with characteristic angular dependencies for applied in-plane magnetic fields. Micromagnetic simulations allow us to attribute detected resonances to mode profiles with specific mirror symmetries. Spectra in the reversal regime show systematic emergence and disappearance of spin-wave modes indicating reprogrammable magnonic characteristics.</p>
Data for Nguyen Le at al. ""Topological phases of a dimerized Fermi-Hubbard model for semiconductor nano-lattices"
<p>Codes and simulation data used in Nguyen Le at al. "“Topological phases of a dimerized Fermi-Hubbard model for semiconductor nano-lattices."</p>
Dataset from the paper entitled "Linking Lattice Strain and Fractal Dimensions to Non-Monotonic Volume Changes in Irradiated Nuclear Graphite"
<p>Dataset from the paper entitled "Linking Lattice Strain and Fractal Dimensions to Non-Monotonic Volume Changes in Irradiated Nuclear Graphite". The dataset includes the small angle X-ray scattering measurements, the wide-angle X-ray scattering measurements, and the fitting parameters. Please see the included Readme file for more detail on the organization. </p>
Hall-Littlewood polynomials, affine Schubert series, and lattice enumeration
<p>Data accompanying the paper <em>J. Maglione, C. Voll, Hall-Littlewood polynomials, affine Schubert series, and lattice enumeration. <a href="https://arxiv.org/abs/2410.08075">https://arxiv.org/abs/2410.08075</a></em></p>
Cubic insulin data set collected from multiple lattices on i03 at Diamond Light Source
<p>Dataset collected as part of routine commissioning work, found to have more than one crystal present at the point where data were collected, allowing multiple lattices to be processed. </p> <p> </p> <p>While three lattices are present one is substantially weaker than the other two.</p> <p> </p> <p>Uploading to enable methods development and also to use for tutorials on how to use dials software.</p> <p> </p> <p>Processing data with the usual dials scripts (which will point to this deposition) result in statistics shown below. Tutorial to be uploaded to https://github.com/graeme-winter/dials_tutorials when available.</p> <p> </p> <p><code> -------------Summary of merging statistics-------------- </code></p> <p><code> Suggested Low High Overall</code><br><code>High resolution limit 1.51 4.10 1.51 1.48</code><br><code>Low resolution limit 54.89 54.93 1.54 54.89</code><br><code>Completeness 98.9 100.0 83.7 95.3</code><br><code>Multiplicity 54.7 78.1 4.6 53.5</code><br><code>I/sigma 18.9 89.2 0.3 18.4</code><br><code>Rmerge(I) 0.139 0.060 1.423 0.139</code><br><code>Rmerge(I+/-) 0.138 0.060 1.316 0.138</code><br><code>Rmeas(I) 0.140 0.061 1.590 0.140</code><br><code>Rmeas(I+/-) 0.140 0.060 1.609 0.140</code><br><code>Rpim(I) 0.016 0.007 0.683 0.016</code><br><code>Rpim(I+/-) 0.023 0.009 0.894 0.023</code><br><code>CC half 1.000 1.000 0.271 1.000</code><br><code>Anomalous completeness 97.8 100.0 67.8 92.3</code><br><code>Anomalous multiplicity 28.7 43.6 2.6 28.3</code><br><code>Anomalous correlation 0.038 0.276 -0.050 0.049</code><br><code>Anomalous slope 0.667 </code><br><code>dF/F 0.060 </code><br><code>dI/s(dI) 0.629 </code><br><code>Total observations 669615 52255 2342 670277</code><br><code>Total unique 12231 669 507 12529</code></p>
Tau accelerates tubulin exchange in the microtubule lattice
<p>This dataset contains the data and source code for Figures 1-4 and and the source code for Supplementary Figures S5-S10 from the following publication: </p> <div> <p>Tau accelerates tubulin exchange in the microtubule lattice</p> </div> <div>by</div> <div> </div> <div>Subham Biswas, Rahul Grover, Cordula Reuther, Chetan S. Poojari, M. Reza Shaebani, Mona Grünewald, Amir Zablotsky, Jochen S. Hub, Stefan Diez, Karin John, Laura Schaedel</div> <div> </div> <div>doi: https://doi.org/10.1101/2024.10.05.616777</div>
Lattice kinetic Monte Carlo model to simulate RNA polymerase II clusters
<p>This data set includes Python scripts (numerical simulation and analysis) and already generated simulation data for RNA polymerase II clusters. RNA polymerase II particles as single lattice sites and chromatin with regulatory region as connected polymer.</p>
[Dataset] Lattice Metamaterials with Mesoscale Motifs: Exploration of Property Charts by Bayesian Optimisation
<p>[Dataset] Lattice Metamaterials with Mesoscale Motifs: Exploration of Property Charts by Bayesian Optimisation</p> <p>Roman Kulagin*, Patrick Reiser, Kyryl Truskovskyi, Arnd Koeppe, Yan Beygelzimer, Yuri Estrin, Pascal Friederich, Peter Gumbsch</p> <p>[*] Dr. R. Kulagin, Institute of Nanotechnology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany. E-Mail: roman.kulagin@kit.edu</p> <p>Dr. Patrick Reiser, Institute of Nanotechnology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany; Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Engler-Bunte-Ring 8, 76131 Karlsruhe, Germany.</p> <p>Kyryl Truskovskyi, Georgian, Toronto, Canada</p> <p>Dr. Arnd Koeppe, Institute for Applied Materials (IAM-MMS), Karlsruhe Institute of Technology, Straße am Forum 7, 76131 Karlsruhe, Germany.</p> <p>Prof. Pascal Friederich, Institute of Nanotechnology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany; Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Engler-Bunte-Ring 8, 76131 Karlsruhe, Germany.</p> <p>Prof. Y. Beygelzimer, Donetsk Institute for Physics and Engineering named after A.A. Galkin, National Academy of Sciences of Ukraine, Nauki ave., 46, 03028 Kyiv, Ukraine.</p> <p>Prof. Y. Estrin, Department of Materials Science and Engineering, Monash University, 22 Alliance Lane, Clayton 3800, Australia; Department of Mechanical Engineering, The University of Western Australia, Crawley 6009, Australia.</p> <p>Prof. P. Gumbsch, Institute for Applied Materials, Karlsruhe Institute of Technology, Straße am Forum 7, 76131, Karlsruhe, Germany; Fraunhofer Institute for Mechanics of Materials, Freiburg, Wöhlerstraße 11, 79108 Freiburg, Germany.</p> <p>Part of the work was supported by the German Research Foundation (DFG, Deutsche Forschungsgemeinschaft) through the POLiS Cluster of Excellence (grant no. UP 33/1) under project ID 390874152 and by the Helmholtz association under the KNMFi program (grant no. 43.31.01).</p>
Simulation of free fermion transport on 2D lattice using constant-depth quantum circuits
<p>In these simulations, we consider a fermion initialized on a reference lattice site, and observe how it evolves freely through a two-dimensional (2D) lattice. The lattice comprises 16 sites with closed boundary conditions, and lattice site '0' is considered our reference site, where the fermion is initialized. We examine transport of a fermion on this 16-site lattice both with and without disorder. To do this, we track the occupation number at varying distances $M$ from the reference site as the fermion evolves freely through time. When there is no disorder in the system, we expect the fermion to behave ballistically and oscillate back and forth within the lattice. The file '4x4_2DFF_mu=0.0_nsteps=900_t=90.0_backend=ibm_washington_shot=50000_nis_ps_DD_M3.txt' has the results from simulating a free fermion on a 2D lattice with no disorder on the ibmq_washington QPU, while '4x4_2DFF_mu=0.0_nsteps=900_t=90.0_backend=qasm_sim_shot=100000_nis.txt' has the results from the noise-free quantum simulator. </p> <p>When there is large random disorder in the system, we expect the fermion to exhibit Anderson localization. '4x4_2DFF_mu=10.0_nsteps=900_t=90.0_backend=ibm_washington_shot=50000_nis_ps_DD_M3_Anderson_loc.txt' shows results from simulating a free fermion on a 2D lattice with large random disorder on the ibmq\_washington QPU, while '4x4_2DFF_mu=10.0_nsteps=900_t=90.0_backend=qasm_sim_shot=100000_nis.txt' shows results from the noise-free quantum simulator. </p> <p>Simulations on the the noise-free quantum simulator were performed with 100,000 shots. Simulations on the QPU were performed with 50,000 shots and any shot that did not conserve particle number was discarded. Two straightforward error mitigation techniques were also used to reduce noise in the results from the QPU. The first was a scalable readout error mitigation method implemented with the mthree package, which reduces errors in quantum measurement via calibration. The second was dynamical decoupling, a method that can suppress qubit decoherence via the application of a set of pulses (which together amount to application of the identity operator) to idling qubits which cancels the system-environment interaction.</p>
Lattice kinetic Monte Carlo model to simulate RNA polymerase II clusters during stem cell differentiation
<p>This data set includes Python scripts (numerical simulation and analysis) and already generated simulation data for RNA polymerase II clusters during stem cell differentiation. It includes the whole data to recreate panels.</p>
Symplectic lattice gauge theories on Grid: approaching the conformal window---data release
<p>This is the data release relative to the paper "Symplectic lattice gauge theories on Grid: approaching the conformal window" (arXiv:2306.11649).</p> <p>It contains pre-analysed data that can be plotted, and raw data that can be analysed and plotted through the analysis code in doi:10.5281/zenodo.8136514.</p>
Discovery of enhanced lattice dynamics in a single-layered hybrid perovskite
<p>This repository presents the raw data for the paper "<strong>Discovery of enhanced lattice dynamics in a single-layered hybrid perovskite</strong>", published as an open-access article in <em>Science Advances</em> at <a href="https://www.science.org/doi/10.1126/sciadv.adg4417">https://www.science.org/doi/10.1126/sciadv.adg4417</a>.</p> <p>Data presented in the Supplementary Materials will be provided upon request. For such requests or general questions regarding the paper, please contact Zhuquan Zhang (<a href="mailto:zhuquan@mit.edu">zhuquan@mit.edu</a>), Keith Nelson (<a href="mailto:kanelson@mit.edu">kanelson@mit.edu</a>), or Edoardo Baldini (<a href="mailto:edoardo.baldini@austin.utexas.edu">edoardo.baldini@austin.utexas.edu</a>).</p>
ScienceDex guides
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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.