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1,880 results for “Dimensionality”
Data of the publication "Absence of Localization in Two-Dimensional Clifford Circuits"
<p>We analyze a Floquet circuit with random Clifford gates in one and two spatial dimensions. By using<br> random graphs and methods from percolation theory, we prove in the two-dimensional (2D) setting that<br> some local operators grow at a ballistic rate, which implies the absence of localization. In contrast, the<br> one-dimensional model displays a strong form of localization, characterized by the emergence of left- and<br> right-blocking walls in random locations. We provide additional insights by complementing our analytical results with numerical simulations of operator spreading and entanglement growth, which show the<br> absence (presence) of localization in two dimensions (one dimension). Furthermore, we unveil how the<br> spectral form factor of the Floquet unitary in 2D circuits behaves like that of quasifree fermions with<br> chaotic single-particle dynamics, with an exponential ramp that persists up to times scaling linearly with<br> the size of the system. Our work sheds light on the nature of disordered Floquet Clifford dynamics and<br> their relationship to fully chaotic quantum dynamics.</p>
Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method
<p>Supporting data for Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method</p> <p>Matlab Codes to reconstruct the subsurface structures (Codes without Figure_*.m) and plot the figures (Figure_*.m) in the manuscript. The file in Netcdf format is our reconstructed 3D density and currents.</p> <p> </p>
Data and Supplementary Material for "Insights into Lightning K-Leader Initiation and Development from Three Dimensional Broadband Interferometric Observations" by Jensen et al.
<p>Data and Supplementary Material for the manuscript “Insights into Lightning K-Leader Initiation and Development from Three Dimensional Broadband Interferometric Observations” by Jensen et al., submitted to Journal of Geophysical Research: Atmospheres. Further description in included PDF (01file_description.pdf)</p>
Data from: Arm waving in stylophoran echinoderms: three-dimensional mobility analysis illuminates cornute locomotion
<p>The locomotion strategies of fossil invertebrates are typically interpreted on the basis of morphological descriptions. However, it has been shown that homologous structures with disparate morphologies in extant invertebrates do not necessarily correlate with differences in their locomotory capability. Here, we present a new methodology for analysing locomotion in fossil invertebrates with a rigid skeleton through an investigation of a cornute stylophoran, an extinct fossil echinoderm with enigmatic morphology that has made its mode of locomotion difficult to reconstruct. We determined the range of motion of a stylophoran arm based on digitized three-dimensional morphology of an early Ordovician form, <i>Phyllocystis crassimarginata</i>. Our analysis showed that efficient arm-forward epifaunal locomotion based on dorsoventral movements, as previously hypothesized for cornute stylophorans, was not possible for this taxon; locomotion driven primarily by lateral movement of the proximal aulacophore was more likely. 3D digital modelling provides an objective and rigorous methodology for illuminating the movement capabilities and locomotion strategies of fossil invertebrates.</p>
Data for "Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis"
<p>The files named <code>df_scran.csv</code>, <code>df_seurat.csv</code>, <code>df_zinbwave.csv</code>, <code>df_dca.csv</code>, and <code>df_scvi.csv</code> contain one row per configuration that we ran successfully.</p> <p>The files named <code>DATASET.METHOD.h5ad</code> are encoded with anndata <code>v0.7.0</code> (be careful as they are not readable with previous versions) and contain 100 embeddings each. The embeddings are in the <code>obsm</code> attribute of the object. All the embeddings can be listed with the <code>obsm_keys()</code> method. The name of the embedding contains the parameters used to generate that embedding and are written like that <code>method=zinbwave.dims=10.epsilon=1000.features=300.gene_covariate=0</code>.</p> <p> </p> <p>For questions on this dataset please contact fraimundo@google.com</p>
Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3.0T
<p>3D MR Fingerprinting T1/T2/M0 maps of twelve healthy volunteers obtained in eight different sites (1.5T and 3.0T scanners, single vendor). Each subject/site dataset includes two acquisitions (test-retest) to assess repeatability of the measurement.</p>
Data for: On-the-fly ab initio semiclassical evaluation of third-order response functions for two-dimensional electronic spectroscopy
<p>Data for publication: T. Begusic, J. Vanicek, On-the-fly ab initio semiclassical evaluation of third-order response functions for two-dimensional electronic spectroscopy, <em>J. Chem. Phys.,</em> <strong>153</strong>, 184110 (2020).</p> <p>Contains simulated linear and two-dimensional spectra of the S<sub>1</sub> - S<sub>0</sub> electronic transition of phenol, excited-state and ground-state ab initio trajectories at the PBE0/6-311G(d,p) level of theory, and other supporting data related to the abovementioned publication.</p>
SWASH Model Files from Modeled Three-Dimensional Currents and Eddies on an Alongshore-Variable Barred Beach
<p>This archive contains SWASH model input, MATLAB processing scripts, and the model output used to produce the figures in “Modeled Three-Dimensional Currents and Eddies on an A longshore-Variable Barred Beach."</p> <p>Support was provided by the Washington Royalty Research Fund, the National Science Foundation, the Office of Naval Research, a National Defense Science and Engineering Graduate Fellowship, a Vannevar Bush Faculty Fellowship, the United States Army Corps of Engineers, the United States Coastal Research Program, Sea Grant, and the WHOI Investment in Science Fund.</p> <p> </p> <p>The model inputs, scripts, and data are contained in three zip files: </p> <ul> <li>model_input.zip: input files for all simulations presented in this paper</li> <li>model_output_processing.zip: MATLAB model output processing scripts.</li> <li>model_data.zip: model output used to produce the figures</li> </ul> <p> </p> <p>SWASH is an open source code and can be download at <a href="http://swash.sourceforge.net/home.htm">http://swash.sourceforge.net/home.htm</a>. Please contact C.M. Baker at cmbaker9@uw.edu with questions. </p>
Data and MATLAB Code for the paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow"
<p>This link includes the data and MATLAB code files for the research paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow" by Zhou, J.W.; Bro, W.M.; Tick*, G.R.; Mofatakari, H.; Li, Y.; and Cheng, L., which has been submitted to the Journal of Fluids Engineering. These files are edited under the GB18030 character set standard.</p>
Unique dynamics and exocytosis properties of GABAergic synaptic vesicles revealed by three-dimensional single vesicle tracking
<p>This data set includes x, y, and z trajectories of all GABAergic synaptic vesicles that we used for the study. These GABAergic synaptic vesicles in inhibitory presynaptic terminals of living primary hippocampal neurons were labeled by single quantum dots (QDs) conjugated with anti-VGAT antibody under electrical stimulation, and were tracked three-dimensionally by using a dual-focus imaging in real-time. Each trajectory data indicates x, y, and z positions (nanometer-scale) over time from the start of imaging to the moment of vesicle fusion. The electrical stimulation to the neurons was applied for 120 s, starting from 20 s.</p>
Two-dimensional Xene Heterostructures by Epitaxy
<p>The synthesis of new Xenes and their potential applications prototypes have achieved significant milestones so far. However, to date the realization of Xene heterostructures in analogy with the well-known van der Waals heterostructures remains an unresolved issue. Here, we introduce a Xene heterostructure concept based on the epitaxial combination of silicene and stanene on Ag(111), and demonstrate how one Xene layer enables another Xene layer of different nature to grow on top. We synthesized single-phase (4 x 4) silicene using stanene as a template, and managed to grow stanene on top of silicene on the other way around. In both heterostructures <em>in situ</em> and <em>ex situ</em> probes confirm layer-by-layer growth without intercalations and intermixing. Modelling via Density Functional Theory (DFT) shows that the atomic layers in the heterostructures are strongly interacting and hexagonal symmetry conservation in each individual layer is sequence-selective. Our results provide a substantial step towards currently missing Xene heterostructures and open the door to a new frontier of atomic-scale materials engineering. </p>
Data from: Transformation of measurement uncertainties into low-dimensional feature vector space
<p>Advances in technology allow the acquisition of data with high spatial and temporal resolution. These datasets are usually accompanied by estimates of the measurement uncertainty, which may be spatially or temporally varying and should be taken into consideration when making decisions based on the data. At the same time, various transformations are commonly implemented to reduce the dimensionality of the datasets for post-processing, or to extract significant features. However, the corresponding uncertainty is not usually represented in the low-dimensional or feature vector space. A method is proposed that maps the measurement uncertainty into the equivalent low-dimensional space with the aid of approximate Bayesian computation, resulting in a distribution that can be used to make statistical inferences. The method involves no assumptions about the probability distribution of the measurement error and is independent of the feature extraction process as demonstrated in three examples. In the first two examples Chebyshev polynomials were used to analyse structural displacements and soil moisture measurements; while in the third, principal component analysis was used to decompose global ocean temperature data. The uses of the method range from supporting decision making in model validation or confirmation, model updating or calibration and tracking changes in condition, such as the characterisation of the El Niño Southern Oscillation. </p>
Datasets used in the thesis "Contributions to High-Dimensional Pattern Recognition"
<p>Datasets used in the thesis "Contributions to High-Dimensional Pattern Recognition" and related publications.</p>
Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - methods
<p>We reconstruct the 3D shape of microvasculature in human bone marrow specimen.</p> <ul> <li> Files "2016-07-01_Methodenvideo_....mp4" detail on the novel embedding process of our specimen. The video details on material preparation, special embedding device and devised procedure, the sectioning and further processes. For convinience, a high-resolution ....FullHD.mp4 and low-resolution .....SD.mp4 versions are provided.</li> <li>Files "2016-07-27 Manual Quality Control - ...mp4" details on the computer-based verification of final mesh and initial (registered) image stack. We can observe some blind ends or interrruptions in the reconstruction, this tools allows us to evaluate the suspective areas. There is a FullHD encode, and a SD version.</li> </ul>
Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - final data
<p>These are the meshes used to render the videos in 10.5281/zenodo.57834 and 10.5281/zenodo.57754</p> <p>The file names are:</p> <p>R[n]_[kind].ply</p> <p>where</p> <p>n is the ROI number, 1-4<br> kind is the diameter mesh or the overview mesh.</p> <p>The diameter meshes have additionally removed inner components and also other small non-connected components, as described in the paper.</p>
Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - difference between meshes
<p>The difference between the overview mesh and mesh used for SDF for all ROI.</p> <p>Black is no difference, i.e. baseline, objects removed for SDF processing are red.</p>
Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - diameters
<p>We reconstruct blood vessels in human bone marrow specimen. These videos show the diameters of blood vessels.</p> <p>Red is under 12 µm, green is over 30 µm, in-between is the gradient from red to green. The coloring is based on the SDF computation and the accompanying MeshLab Quality Mapper file.</p>
Quantum Fluctuations in Quasi-One-Dimensional Dipolar Bose-Einstein Condensates
<p>Raw data for the depicted graphs in the given paper/letter</p>
Three-dimensional GNSS Time Series Data for Terrestrial Water Storage Changes Inversion in Yunnan, China
<p>The dataset includes three-dimensional GNSS time series data featured in the publication "Using the global navigation satellite system and precipitation data to establish the propagation characteristics of meteorological and hydrological drought in Yunnan, China", published in 'Water Resources Research'.</p> <p>Reference:<br>Zhu, H., Chen, K., Hu, S., Liu, J.,Shi, H., Wei, G., et al. (2023). Using the global navigation satellite system and precipitation data to establish the propagation characteristics of meteorological and hydrological drought in Yunnan, China. Water Resources Research, 59, e2022WR033126. https:// doi.org/10.1029/2022WR033126</p> <p><br>The sitelist file lists basic information about all the utilized stations, including their names and geographic coordinates. <br>The Time.mat file contains the time vectors of the data employed. <br>The Filter_time_series_N/E/U.mat files showcase the filtered time series, which have been processed using Independent Component Analysis (ICA) for the inversion of terrestrial water storage in Yunnan, after removing the effects of outliers, steps, and non-tidal atmospheric/oceanic loading.</p>
A dataset of 8-dimensional Q-factorial Fano toric varieties of Picard rank 2
<p>This is a dataset of randomly generated 8-dimensional Q-factorial Fano toric varieties of Picard rank 2.</p><p>The data is divided into four plain text files:</p><ul><li>bound_7_terminal.txt</li><li>bound_7_non_terminal.txt</li><li>bound_10_terminal.txt</li><li>bound_10_non_terminal.txt</li></ul><p>The numbers 7 and 10 in the file names indicate the bound on the weights used when generating the data. Those varieties with at worst terminal singularities are in the files "bound_N_terminal.txt", and those with non-terminal singularities are in the files "bound_N_non_terminal.txt". The data within each file is de-duplicated, however the data in different files may contain duplicates (for example, it is possible that "bound_7_terminal.txt" and "bound_10_terminal.txt" contain some identical entries).</p><p> </p><p>Each line of a file specifies the entries of a (2 x 10)-matrix. For example, the first line of "bound_7_terminal.txt" is:</p><blockquote><p>[[5,6,7,7,5,2,5,3,2,2],[0,0,0,1,1,2,6,4,3,3]]</p></blockquote><p>and this corresponds to the 8-dimensional Q-factorial Fano toric variety with weight matrix</p><blockquote><p>5 6 7 7 5 2 5 3 2 2</p><p>0 0 0 1 1 2 6 4 3 3</p></blockquote><p>and stability condition given by the sum of the columns, which in this case is</p><blockquote><p>44</p><p>20</p></blockquote><p>It can be checked that, in this case, the corresponding variety has at worst terminal singularities. In this example the largest occurring weight in the matrix is 7.</p><p> </p><p>The number of entries in each file is:</p><ul><li>bound_7_terminal.txt: 5000000</li><li>bound_7_non_terminal.txt: 5000000</li><li>bound_10_terminal.txt: 10000000</li><li>bound_10_non_terminal.txt: 10000000</li></ul><p> </p><p>For details, see the paper:</p><blockquote><p>"Machine learning detects terminal singularities", Tom Coates, Alexander M. Kasprzyk, and Sara Veneziale. Neural Information Processing Systems (NeurIPS), 2023.</p></blockquote><p> </p><p>Magma code capable of generating this dataset is in the file "terminal_dim_8.m". The bound on the weights is set on line 142 by adjusting the value of 'k' (currently set to 10). The target dimension is set on line 143 by adjusting the value of 'dim' (currently set to 8). It is important to note that this code does not attempt to remove duplicates. The code also does not guarantee that the resulting variety has dimension 8. Deduplication and verification of the dimension need to be done separately, after the data has been generated.</p><p> </p><p>If you make use of this data, please cite the above paper and the DOI for this data:</p><p>doi:10.5281/zenodo.10046893</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.