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917 results for “Theory”
Three-dimensional super-Yang--Mills theory on the lattice and dual black branes --- data release
<p>This HDF5 file collects data and analysis results for non-perturbative lattice field theory calculations investigating three-dimensional maximally supersymmetric SU(N) Yang--Mills theory on a skewed euclidean torus, and its holographic connection to dual D2-brane solutions in supergravity. See the README for further information.</p>
Nonperturbative phase diagram of two-dimensional N=(2,2) super-Yang--Mills theory --- data release
<p>This HDF5 file collects data and analysis results for non-perturbative lattice field theory calculations investigating two-dimensional supersymmetric SU(N) Yang--Mills theory with four supercharges. See the README for further information.</p>
Datasets for: Generalizing Monin-Obukhov Similarity Theory (1954) for Complex Atmospheric Turbulence, Stiperski and Calaf 2023, PRL
<p>Scaling variables for the generalized flux-variance scaling relations that include turbulence anisotropy. Dataset is a companion to the manuscript Stiperski, I., Calaf, M., 2023: Generalizing Monin-Obukhov similarity theory (1954) for complex atmospheric turbulence. Physical Review Letters, 130 (12), 124001, https://doi.org/10.1103/PhysRevLett.130.124001</p> <p>The dataset contains the turbulence statistics from 13 datasets: AHATS, Cabauw, CASES-99, METCRAX II campaign (NEAR and RIM towers), T-Rex campaign (Central tower - TRexC, West tower - TRexW) and i-Box measurement network (CCS-VF0 tower - i-Box0, CS-SF1 tower - i-Box1, CS-NF10 tower - i-Box10, CS-NF27 tower - i-Box27, CS-MT21 tower - i-BoxTop, im Hinteren Eis tower - imHint).</p> <p><br>Data are organized in csv files for each datasets and only contain high quality (for applied criteria see the Supplemental Material of the companion paper, https://journals.aps.org/prl/supplemental/10.1103/PhysRevLett.130.124001) data with 30 min averaging for unstable stratification and 1 min for stable stratification. Since the data were used for scaling, there is no reference to time, but the measurement height is provided as an additional variable. </p> <p>Meaning of variables:</p> <p>zeta - z/L where z is height above ground and L is the local Obukhov length</p> <p>SigmaU - $\overline{u'u'}/u_*$ scaled standard deviation of streamwise velocity, where $u_*$ is the local friction velocity</p> <p>SigmaU - $\overline{v'v'}/u_*$ scaled standard deviation of spanwise velocity</p> <p>SigmaU - $\overline{v'v'}/u_*$ scaled standard deviation of surface-normal velocity</p> <p>SigmaT - $\overline{T'T'}/T_*$ scaled standard deviation of sonic temperature, where $T_*$ is the local temperature scale</p> <p>SigmaEpsU - scaled dissipation rate of the streamwise velocity</p> <p>SigmaEpsW - scaled dissipation rate of the surface-normal velocity </p>
Dataset of "Asparagine-Modified Magnetic Graphene Oxide: An Efficient and Green Nanocatalyst for Synthesis of 5-oxodihydropyrano[3,2-c]chromenes and dihydropyrano[2,3- c]pyrazole derivatives and the Density functional theory calculation".
<p>The primary focus of this study involved the fabrication of a novel nanocatalyst Fe3O4-supported asparagine functionalized graphene oxide (Fe3O4@GO-N-(Asparagine)). The catalyst was synthesized through a four-step procedure.</p>
CATCH-EyoU: Exploiting European data and testing the integrated theory of youth active EU citizenship: EACEA subset analysis
<p>This dataset was created within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme, Grant Agreement No 649538. Work Package 4 of this project (Exploiting European data and testing the integrated theory of youth active EU citizenship) is focused on the re-analysis of existing European data. This dataset contains a subset of data originally collected within the project “<em>EACEA 2010/03: Youth Participation in Democratic Life</em>”, coordinated by the London School of Economic and Political Science. Specifically, an online questionnaire survey in seven European countries was conducted among young people age 15-30 in 2011. This dataset contains a subset of 22 variables that were employed for the reanalysis within the CATCH-EyoU project.</p>
Density functional theory calculations of coherent bcc Fe-Cu interfacial energy densities
<p>File contains the data required to calculate interfacial energy densities of {100}, {110}, {111}, {210}, {211} and {221} orientated coherence bcc Fe-Cu interfaces.</p> <p>Data produced for the study detailed in: Cu nanoprecipitate morphologies and interfacial energy densities in bcc Fe from density functional theory (DFT) A.M. Garrett and C.P. Race.</p> <p>Submitted to Computational Materials Science.</p> <p>.txt files contain the total energies calculated for relaxed interface-containing and bulk simulation cells at a range of interfacial spacings. This data can be used to calculate the size independent interfacial energy densities for a range of Fe-Cu interface orientations using standard fitting approaches. Columns of the tables in the .txt files are no. atoms, interface-containing simulation cell length, interfacial area, total energy of the relaxed interface-containing simulation cell, total energy of the reference bulk Fe and total energy of the reference bulk Cu. Lengths are in Angstrom and energies are in eV.</p>
Topological Data Analysis of Monopoles in U(1) Lattice Gauge Theory — Data Release
<div>This release contains data used to prepare the publication <a href="https://arxiv.org/abs/2403.07739">X. Crean, J. Giansiracusa and B. Lucini, Topological Data Analysis of Monopoles in U(1) Lattice Gauge Theory (2024)</a>. There exists an <a href="https://doi.org/10.5281/zenodo.10806185">accompanying software release</a> that explains in detail how to extract and use the compressed data files on a Linux distribution (or compatible environment).</div>
Supporting data "Scaling theory for the statistics of slip at frictional interfaces"
<p>Principle data supporting "Scaling theory for the statistics of slip at frictional interfaces"</p> <p>T. W. J. de Geus and M. Wyart (2022), <em>Phys. Rev. E</em>, 106(6):065001.</p> <ul> <li>See code at <a href="../doi/10.5281/zenodo.10723197">doi: 10.5281/zenodo.10723197</a> (and its documentation) for workflow, detailed information of the data, and further dependencies. </li> <li>The files <code>N=*_Run*.zip</code> contain fully restorable events for event-driven athermal quasi-static shear. Sequentually numbered files contain different parts of a single dataset.</li> <li>The file <code>summary.zip</code> contains an extract of the key variables of these runs, and of triggers at different stresses. Finally, it contains "flow" data acquired by driving at finite rate. </li> <li>The files <code>N=3^6x4_Trigger_EnsemblePack.zip</code> contain fully restorable triggers at different stresses in the largest system. The sequentially numbered files correspond to one dataset split in different<em> </em><code>.h5</code> files.</li> <li>Highly specific (and poorly documentated) plotting functions are available upon request.</li> </ul>
Probing center vortices and deconfinement in SU(2) lattice gauge theory with persistent homology — data release
<p>This release contains all data used to prepare the publication <a href="https://arxiv.org/abs/2207.13392">Probing center vortices and deconfinement in SU(2) lattice gauge theory with persistent homology</a>.</p> <p>Included are:</p> <ul> <li>The raw log output from the simulations and computed persistence images for the analysis in Section IV.B of the <a href="https://arxiv.org/abs/2207.13392">paper</a> in 'raw_data.zip'.</li> <li>The values of the action and Polyakov loop from the above logs, along with the persistence images restructured into netCDF4 format for convenience, in the files 'Nt=*_Ns=*_pis_actions_polyakovs.nc'.</li> <li>The values of the observable m_2 (as defined in the <a href="https://arxiv.org/abs/2207.13392">paper</a>) for configurations for the twisted boundary conditions analysis in netCDF4 format in 'Nt=4_Ns=12_16_20_m2.nc'.</li> <li>The example persistence diagrams used in the <a href="https://arxiv.org/abs/2207.13392">paper</a> in netCDF4 format in 'Nt=4_Ns=12_example_pds.nc'.</li> </ul>
A phenomenological law for complex granular materials from Mohr-Coulomb theory
<p>The compressed directory contains the data in .csv format used for the PCA analysis for each dataset (1, 2 and 3). </p>
Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac–Coulomb(–Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states: Figures
<p>This entry contains the figures included in the paper titled "Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states", by Avijit Shee, Trond Saue, Lucas Visscher and Andre Severo Pereira Gomes.</p> <p>It accompanies the dataset found at the DOI: 10.5281/zenodo.1320320</p> <p>There are three figures that use the (original) png files included in <a href="https://zenodo.org/api/files/7bda2e2b-ac69-41aa-a21e-821e88bfb973/original-figures.tar.bz2">original-figures.tar.bz2 </a>:</p> <p>figure 1: Potential energy curves of the spin-orbit split X<sup>2</sup>Π and A<sup>2</sup>Π states of the XO molecules, obtained with EOM-IP and the <sup>2</sup>DCG<sup>M</sup> Hamiltonian.</p> <p>figure 2: Internuclear distances (in Angstrom), harmonic vibrational frequencies (in cm<sup>−1</sup>) and the vertical Ω = 3/2 − 1/2 energy difference (in eV) for the X<sup>2</sup>Π and A<sup>2</sup>Π states of the XO molecules, obtained with EOM-IP and the <sup>2</sup>DCG<sup>M</sup> Hamiltonian.</p> <p>figure 3: SO-ZORA/QZ4P/Hartree-Fock (ADF) spinor magnetization plots (isosurfaces at 0.03 a.u.) and energies (in Eh) for the valence spinors of the XO<sup>−</sup> species (from left to right: X = Cl, Br, I, At, Ts).</p>
Theory and a heuristic for the minimum path flow decomposition problem
<p>This is the data used in the following paper:</p> <p>Shao, Mingfu, and Carl Kingsford. "Theory and A Heuristic for the Minimum Path Flow Decomposition Problem." <em>IEEE/ACM Transactions on Computational Biology and Bioinformatics </em>(2017).</p>
Predictive simulations of ionization energies of solvated halide ions with relativistic embedded Equation of Motion Coupled-Cluster Theory: Figures
<p>This entry contains the sources for the figures included in the body of the paper titled "Predictive simulations of ionization energies of solvated halide ions with relativistic embedded Equation of Motion Coupled-Cluster Theory", by Yassine Bouchafra, Avijit Shee, Florent Réal, Valérie Vallet and André Severo Pereira Gomes, as well as those found in the supplementary information.</p> <p>It accompanies the dataset found at the DOI: 10.5281/zenodo.1477004</p> <p> </p> <p> </p>
Radar and Lidar scattering lookup tables for atmospheric hydrometeors using a T-Matrix method and a Mie theory
<h2>Overview</h2> <p>The database includes text files containing the scattering amplitude matrices for single spherical/nonspherical particles for radar and lidar. They are the lookup tables used for calculating radar and lidar observables in the Cloud-Resolving Radar Simulator (Oue et al. 2020). The radar scattering properties were calculated for several hydrometeor categories using a T-matrix method proposed by Mishchenko (2000) accounting for incident angles, scattering direction (forward and backward), polarimetry (horizontally (H) and vertically (V) polarized waves), particle aspect ratio, phase (liquid or ice), bulk density, temperature, particle size, and radar frequency. The lidar scattering properties at a vertical incidence were calculated for spherical liquid or ice particles using the BHMIE Mie code (Bohrean and Hyffman,1998) accounting for lidar wavelength, temperature, and bulk density. The hydrometeor categories are commonly used for cloud resolving models employing bulk microphysical schemes (e.g., cloud, rain, ice cloud, snow aggregates, and graupel). Detailed descriptions are also available in the CR-SIM user guide (https://github.com/marikooue/CR-SIM/releases/tag/crsim-v3.34).</p> <h2>Data structure</h2> <p>The data files are arranged and zipped every hydrometeor types. The names of the tar-zipped directories under the top directory LLUT3 represents the hydrometer type.<br>For lidar scattering, the following directories are included:<br>ceilo: Ceilometer lidar backscatter properties at a wavelength of 905 nm<br>mpl: Micropulse lidar (MPL) backscatter properties at wavelengths of 353 and 532 nm</p> <p>For radar scattering, the following hydrometer types are included:<br>cloud: Radar scattering for liquid cloud droplets (spherical shape)<br>raina: Radar scattering for raindrops with the aspect ratio model proposed by Andsager et al. (1999)<br>rainb: Radar scattering for raindrops with the aspect ratio model proposed by Brandes et al (2002)<br>ice_ar0.90: Radar scattering for cloud ice with an aspect ratio of 0.9<br>ice_ar0.20: Radar scattering for cloud ice with an aspect ratio of 0.2<br>smallice: Radar scattering for spherical cloud ice particles<br>snow_ar0.60: Radar scattering for snowflakes with an aspect ratio of 0.6<br>graupel_ar0.60: Radar scattering for graupel particles with an aspect ratio of 0.6<br>graupel_ar0.80: Radar scattering for graupel particles with an aspect ratio of 0.8<br>graupel: Radar scattering for spherical graupel particles<br>gh_ryzh: Radar scattering for graupel particles with the graupel aspect ratio model proposed by Ryzhkov et al (2011)<br>unrimedice_ar0.40: Radar scattering for unrimed ice particles with an aspect ratio of 0.4<br>unrimedice_ar0.60: Radar scattering for unrimed ice particles with an aspect ratio of 0.6<br>unrimedice_ar0.80: Radar scattering for unrimed ice particles with an aspect ratio of 0.8<br>unrimedice: Radar scattering for spherical unrimed ice particles<br>partrimedice_ar0.40: Radar scattering for partially rimed ice particles with an aspect ratio of 0.4<br>partrimedice_ar0.60: Radar scattering for partially rimed ice particles with an aspect ratio of 0.6<br>partrimedice_ar0.80: Radar scattering for partially rimed ice particles with an aspect ratio of 0.8<br>partrimedice: Radar scattering for partially rimed spherical ice particles </p> <h2>The file name convention </h2> <p>For lidar scattering data, each file name has the following format:<br>[hydrometeor type]_[instrument name]_ [wavelength in nm]_[phase ID]_d[bulk density in kg m-3].dat<br>The hydrometeor type shows: 1) ‘cld’ for liquid cloud droplets, and 2) ‘ice’ for ice particles. The phase ID shows: 1) ‘p25’ for ceilometer liquid cloud, 2) ‘p20’ for MPL lidar liquid cloud, and 3) ‘m30’ for MPL lidar ice. </p> <p>For radar scattering data, each file name has the following format.<br>[hydrometeor type]_fr[frequency in GHz]GHz_t[temperature in K]_rho[bulk density in kg m-3]_el[elevation angle in degree].dat<br>The hydrometeor type follows the directory name presented above.</p> <h2>Format of the data files</h2> <p>Line 1: Wavelength in mm<br>Line 2: Temperature in K<br>Line 3: Refractive index (real and imaginary)<br>Line 4: Number of radii calculated and number of elevation angles<br>Line 6: Incident angle and scattered angle in degrees<br>Line 7: Radius in mm and aspect ratio<br>Line 8: Forward scattering amplitude for co-polarization VV and HH (complex number)<br>Line 9: Backward scattering amplitude for co- and cross polarizations VV, VH, HV, HH (complex number) <br>Line 10 to the end of file: Repeat Line 7 to Line 9 with different radii until the maximum radius.</p>
Videos, audio transcriptions and closed captions for the workshop: Introduction to Wikidata for Maastricht University, Theory and Pratice - 15 October 2024
<h1><strong>Videos, audio transcriptions and closed captions for the workshop: Introduction to Wikidata for Maastricht University, Theory and Pratice - 15 October 2024</strong></h1> <h3><a href="https://theplant.maastrichtuniversity.nl/event/navigating-the-world-of-wikidata-for-research-science-and-cultural-heritage-2"><em>Navigating the World of Wikidata for Research, Science and Cultural Heritage</em></a></h3> <h3><em><a href="https://www.wikidata.org/wiki/Wikidata:Twelfth_Birthday/Workshop_in_Maastricht" target="_blank" rel="noopener">Wikidata's Twelfth Birthday: Workshop in Maastricht </a></em></h3> <p>Wikidata is a free, collaborative, multilingual database, collecting structured open data for anyone in the world to use. It also plays a crucial role in supporting Wikimedia projects, such as Wikipedia and Wikimedia Commons. Over the last 12 years it has strongly increased in popularity among the scientific and cultural heritage communities.</p> <p>In this 2,5 hours workshop you will learn the basics of working with Wikidata, both in theory and practice. You will learn</p> <ol> <li>The basics of Wikidata: A first look at what Wikidata is and how it works, both technically and socially (Wikidata community)</li> <li>How Wikidata can be relevant for research, science and cultural heritage (GLAM), and</li> <li>First steps in contributing to Wikidata yourself, with a focus on the topic of UM professors from past and present.</li> </ol> <p>As part of the <a title="Wikidata:Twelfth Birthday" href="https://www.wikidata.org/wiki/Wikidata:Twelfth_Birthday">Wikidata 12th Birthday celebrations</a> this workshop is open to academics, researchers, students, and professionals interested in working with Wikidata in the intersection of open data, research, and science. Whether you are new to Wikidata or looking to deepen your understanding, this session will provide valuable insights for improving your work.</p> <h2><strong>Workshop outline</strong></h2> <h3><strong>Part 1: Theory, Wikidata basics (45-60 minutes) </strong></h3> <ul> <li><strong><a href="https://zenodo.org/records/13984149/files/Wikidata%20Workshop%20-%20Theoretical%20part%20-%20Maastricht%20University%20-%2015%20October%202024.webm" target="_blank" rel="noopener">Video</a> (.webm) including <a href="https://zenodo.org/records/13984149/files/WikidataWorkshop_MaastrichtUniversity_15October2024_TheoreticalPart.txt?download=1" target="_blank" rel="noopener">audio transcription </a>(.txt) and <a href="https://zenodo.org/records/13984149/files/Wikidata%20Workshop%20-%20Theoretical%20part%20-%20Maastricht%20University%20-%2015%20October%202024.webm.en.srt?download=1" target="_blank" rel="noopener">closed captions</a> (.srt) are available below</strong></li> </ul> <p><strong>Additional materials</strong></p> <ul> <li><strong>Slides in <a href="https://zenodo.org/records/13837957/files/WikidataWorkshop_MaastrichtUniversity_15October2024_TheoreticalPart.pptx?download=1" rel="nofollow">PowerPoint</a> or <a href="https://zenodo.org/records/13837957/files/Wikidata%20Workshop%20-%20Theoretical%20part%20-%20Maastricht%20University%20-%2015%20October%202024.pdf?download=1" rel="nofollow">PDF</a> are available from <a href="https://zenodo.org/records/13837957" target="_blank" rel="noopener">https://zenodo.org/records/13837957</a></strong></li> </ul> <p><em>1) Wikidata basics</em></p> <ul> <li>What is Wikidata?</li> <li>What are the principles of Wikidata?</li> <li>How are things described in Wikidata?</li> <li>Who builds Wikidata? - The Wikidata community</li> </ul> <p><em>2) Wikidata for research, science and cultural heritage</em></p> <ul> <li>To what extent is Wikidata used throughout science, research and GLAM?</li> <li>Six anecd<em>a</em>tic cases <ol> <li>Scientometrics - Scholia</li> <li>Life and biomedical sciences</li> <li>Astronomy</li> <li>Language technology / AI / LLMs</li> <li>GLAM – KB collection highlights</li> <li>Representation of (female) scientists</li> </ol> </li> </ul> <h3><strong>Break (15 minutes)</strong></h3> <h3><strong>Part 2: Practice, contributing to Wikidata (75-90 minutes) </strong></h3> <ul> <li><strong><a href="https://zenodo.org/records/13984149/files/Wikidata%20Workshop%20-%20Practical%20part,%20UM%20professors%20-%20Maastricht%20University%20-%2015%20October%202024.webm?download=1" target="_blank" rel="noopener">Video</a> (.webm) including <a href="https://zenodo.org/records/13984149/files/WikidataWorkshop_MaastrichtUniversity_15October2024_PracticalPart_UMprofessors.txt?download=1" target="_blank" rel="noopener">audio transcription </a>(.txt) and <a href="https://zenodo.org/records/13984149/files/Wikidata%20Workshop%20-%20Practical%20part,%20UM%20professors%20-%20Maastricht%20University%20-%2015%20October%202024.webm.en.srt?download=1" target="_blank" rel="noopener">closed captions</a> (.srt) are available below</strong></li> </ul> <p><strong>Additional materials</strong></p> <ul> <li><strong>Slides in <a href="https://zenodo.org/records/13837957/files/WikidataWorkshop_MaastrichtUniversity_15October2024_PracticalPart_UMprofessors.pptx?download=1" rel="nofollow">PowerPoint</a> or <a href="https://zenodo.org/records/13837957/files/Wikidata%20Workshop%20-%20Practical%20part,%20UM%20professors%20-%20Maastricht%20University%20-%2015%20October%202024.pdf?download=1" rel="nofollow">PDF</a> are available from <a href="https://zenodo.org/records/13837957" target="_blank" rel="noopener">https://zenodo.org/records/13837957</a></strong></li> <li><strong>Handout for participants in <a href="https://zenodo.org/records/13837957/files/WikidataWorkshop_MaastrichtUniversity_15October2024_PracticalPart_HandoutForParticipants.docx?download=1" rel="nofollow">Word</a> or <a href="https://zenodo.org/records/13837957/files/WikidataWorkshop_MaastrichtUniversity_15October2024_PracticalPart_HandoutForParticipants.pdf?download=1" rel="nofollow">PDF</a></strong> <strong>are available from <a href="https://zenodo.org/records/13837957" target="_blank" rel="noopener">https://zenodo.org/records/13837957</a></strong></li> </ul> <p><strong> </strong>The goals of this hands-on part are:</p> <ul> <li>Get familiar with basic data editing via the Wikidata interface</li> <li>Understand WD data models and structures related to professors (of Maastricht University)</li> <li>Extend existing <a title="Wikidata:Wiki-wetenschappers/Universiteit Maastricht/hoogleraren" href="https://www.wikidata.org/wiki/Wikidata:Wiki-wetenschappers/Universiteit_Maastricht/hoogleraren">Wikidata items about UM professors</a>, based on information in public sources.</li> <li>If time allows: Create new Wikidata items about UM professors</li> </ul> <p>The visual slides and the textual handout explain the same content, blocks and exercises, albeit in a slightly different order.<strong> </strong></p> <h2><strong>Required preparation</strong></h2> <p>To make optimal use of our time, participants must create a Wikidata account in the weeks before the workshop. See <a href="https://www.wikidata.org/w/index.php?title=Special:CreateAccount" target="_blank" rel="noopener">https://www.wikidata.org/w/index.php?title=Special:CreateAccount</a>.</p> <p>This is important because very fresh accounts may have limited editing rights. Furthermore only 6 Wikidata accounts can be created per day from UM IP addresses, so creating a lot of new accounts during the workshop might overstretch this limit.</p> <h2><strong>Workshop leader</strong></h2> <p>This workshop was given by <a href="https://www.kb.nl/over-ons/experts/olaf-janssen">Olaf Janssen</a>, the Wikimedia coordinator of the <a href="https://www.kb.nl/over-ons/experts/olaf-janssen">Koninklijke Bibliotheek</a>, the national library of the Netherlands.</p> <p>In this role he stimulates and facilitates collaboration between the collections, knowledge, open data and staff of the KB on the one hand, and the projects of the Wikimedia movement, such as Wikipedia, Wikimedia Commons and Wikidata on the other. He is also active as a volunteer within the community. Feel free to contact Olaf via olaf.janssen(at)<a href="http://kb.nl">kb.nl</a></p> <h2><strong>Materials on Wikimedia Commons</strong></h2> <p>Photos , videos and presentations related to this event can be found on Wikimedia Commons: <a title="c:Category:Wikidata Workshop at Maastricht University, 15 October 2024" href="https://commons.wikimedia.org/wiki/Category:Wikidata_Workshop_at_Maastricht_University,_15_October_2024">Category:Wikidata Workshop at Maastricht University, 15 October 2024</a></p> <h2>Relevant URLs </h2> <ul> <li><a href="https://www.wikidata.org/wiki/Wikidata:Twelfth_Birthday/Workshop_in_Maastricht">https://www.wikidata.org/wiki/Wikidata:Twelfth_Birthday/Workshop_in_Maastricht </a></li> <li><a href="https://theplant.maastrichtuniversity.nl/event/navigating-the-world-of-wikidata-for-research-science-and-cultural-heritage-2" target="_blank" rel="noopener">https://theplant.maastrichtuniversity.nl/event/navigating-the-world-of-wikidata-for-research-science-and-cultural-heritage-2</a> + <a href="https://web.archive.org/web/20240926154021/https://theplant.maastrichtuniversity.nl/event/navigating-the-world-of-wikidata-for-research-science-and-cultural-heritage-2/">archived version</a></li> <li><a href="https://www.linkedin.com/feed/update/urn:li:activity:7244614063102529536/">https://www.linkedin.com/feed/update/urn:li:activity:7244614063102529536/</a></li> <li><a href="https://www.linkedin.com/feed/update/urn:li:activity:7245329234385059843/" target="_blank" rel="noopener">https://www.linkedin.com/feed/update/urn:li:activity:7245329234385059843/</a></li> </ul> <p>Earlier LinkedIn posts (April-May 2024, before rescheduling the worlshop to October)</p> <ul> <li><a href="https://www.linkedin.com/feed/update/urn:li:activity:7188470390858428416/" target="_blank" rel="noopener">https://www.linkedin.com/feed/update/urn:li:activity:7188470390858428416/</a></li> <li><a href="https://www.linkedin.com/feed/update/urn:li:activity:7188180802021543936/" target="_blank" rel="noopener">https://www.linkedin.com/feed/update/urn:li:activity:7188180802021543936/</a></li> <li><a href="https://www.linkedin.com/feed/update/urn:li:activity:7189276985267826691/" target="_blank" rel="noopener">https://www.linkedin.com/feed/update/urn:li:activity:7189276985267826691/</a></li> </ul> <h3> </h3>
A Fully-Parameterized Object-Side Light Field Dataset and Theory for Using Entrance and Exit Pupils as Natural Light Field Reference Planes for an Unfocused Plenoptic Camera
<p>We describe a dataset of light fields with full object-side parameterizations. The dataset contains PNG and ESLF files for all 32 images. 12 of them additionally contain depth maps and point clouds.</p>
Novel estimates of the leaf relative uptake rate of carbonyl sulfide from optimality theory
<p>Data and Matlab scripts for repeating the analysis presented in the paper. In addition, global monthly climatological LRUs are provided at 0.05° resolution for the period 2001-2010 as nc-files. </p>
Data: Learning Lattice Quantum Field Theories with Equivariant Continuous Flows
<p>Network parameters of continuous normalizing flows trained for the <span class="math-tex">\(\varphi^4\)</span> theory.</p> <p>Corresponding article: Learning Lattice Quantum Field Theories with Equivariant Continuous Flows [<a href="https://arxiv.org/abs/2207.00283">2207.00283</a>]</p> <p>Abstract: We propose a novel machine learning method for sampling from the high-dimensional probability distributions of Lattice Field Theories, which is based on a single neural ODE layer and incorporates the full symmetries of the problem. We test our model on the <span class="math-tex">\(\varphi^4\)</span> theory, showing that it systematically outperforms previously proposed flow-based methods in sampling efficiency, and the improvement is especially pronounced for larger lattices. Furthermore, we demonstrate that our model can learn a continuous family of theories at once, and the results of learning can be transferred to larger lattices. Such generalizations further accentuate the advantages of machine learning methods.</p>
Dataset for the published article "Quantum version of the integral equation theory based dielectric scheme for strongly coupled electron liquids"
<p>The data contained in the zip file constitute the main research data of the article entitled as "<em>Quantum version of the integral equation theory based dielectric scheme for strongly coupled electron liquids</em>", published in the Journal of Chemical Physics as a Communication. In this article, a novel dielectric scheme is proposed for strongly coupled electron liquids that handles quantum mechanical effects beyond the random phase approximation level and treats electronic correlations within the integral equation theory of classical liquids. This self-consistent scheme features a complicated dynamic local field correction functional and yields unprecedently accurate results for the static structure factor without featuring any adjustable or empirical parameters.</p> <p>In particular, the datasets contain the static structure factors of the paramagnetic electron liquid as computed by four schemes of the self-consistent dielectric formalism and as extracted from state-of-the-art path integral Monte Carlo (PIMC) simulations. The dielectric schemes of interest are all tailor-made for the strongly coupled regime of the finite temperature uniform electron fluid (UEF; also known as jellium or quantum one-component plasma). These are the newly proposed quantum version of the integral equation theory based scheme (qIET), the newly proposed quantum version of the hypernetted-chain based scheme (qHNC), the integral equation theory based scheme (IET) [1,2] and the hypernetted-chain based scheme (HNC) [3,4].</p> <p>The static structure factors are provided for 20 paramagnetic UEF state points defined by (r<sub>s</sub>,Θ)={(50,0.50),(60,0.50),(70,0.50),(80,0.50),(90,0.50),(100,0.50),(100,0.75),(100,1.00),(100,2.00),(100,4.00),(110,0.50),(125,0.50),(125,0.75),(125,1.00),(125,1.50),(125,2.00),(150,0.50),(150,1.00),(200,0.50),(200,1.00)} where r<sub>s</sub> is the quantum coupling parameter and Θ is the degeneracy parameter. </p> <p>In the qIET, qHNC, IET and HNC datasets; the first column corresponds to the wavenumber normalized to the Fermi wavenumber and the second column corresponds to the static structure factor value. In the PIMC datasets, the first column corresponds to the wavenumber multiplied by the first Bohr radius, the second column corresponds to the static structure factor value and the third column corresponds to the associated error bars.</p> <p>[1] P. Tolias, F. Lucco Castello and T. Dornheim, J. Chem. Phys. 155, 134115 (2021).<br> [2] F. Lucco Castello, P. Tolias and T. Dornheim, EPL 138, 44003 (2022).<br> [3] S. Tanaka, J. Chem. Phys. 145, 214104 (2016).<br> [4] T. Dornheim, T. Sjostrom, S. Tanaka and J. Vorberger, Phys. Rev. B 101, 045129 (2020).</p>
Dataset for "Light Scalar Meson and Decay Constant in SU(3) Gauge Theory with Eight Dynamical Flavors"
<p><strong>Decoding File Names</strong>: Consider the file name f8l24t48b48m00889_S0.csv. We will break down the meaning of the various pieces of the filename</p> <ul> <li>"f8" means 8 Dirac flavors.</li> <li>"l24t48" means 24<sup>3</sup>×48 lattice.</li> <li>"b48" means beta=4.8, related to the inverse bare gauge coupling.</li> <li>"m00889" means fermion mass m=0.00889.</li> <li>"S" means flavor-singlet scalar meson. Other options are "P" for flavor non-singlet pseudoscalar meson and "C" for flavor non-singlet scalar meson.</li> <li>"0" an integer from 0 to 4 proportional to the squared length of the spatial momentum vector of the correlation function.</li> </ul> <p><strong>Columns of the CSV files</strong>: Each line of the CSV file should contain 41 entries, separated by commas. Refer to the Eq. (8) which defines model A in the accompanying paper to understand the physical interpretation of these parameters.</p> <ol> <li>Model number: 1 is model A, 2 is model B, 3 is model C.</li> <li>n<sub>max</sub>: the number of non-oscillating states in the fit.</li> <li>j<sub>max</sub>: the number of oscillating states in the fit.</li> <li>t<sub>min</sub>: the minimum t value used in the fit.</li> <li>t<sub>max</sub>: the maximum t value used in the fit.</li> <li>𝜒<sup>2</sup> of the fit.</li> <li><span class="math-tex">\(\log\ p\left(\left.M\right|D\right)\)</span>: log of model probability used in Bayesian model averaging.</li> <li>fit value for c<sub>0</sub> (model A) or <span class="math-tex">\(\overline{c}_0\)</span> (model B).</li> <li>fit error for c<sub>0</sub> (model A) or <span class="math-tex">\(\overline{c}_0\)</span> (model B).</li> <li>fit value for c<sub>1</sub>.</li> <li>fit error for c<sub>1</sub>.</li> <li>fit value for c<sub>2</sub>.</li> <li>fit error for c<sub>2</sub>.</li> <li>fit value for c<sub>3</sub>.</li> <li>fit error for c<sub>3</sub>.</li> <li>fit value for c<sub>4</sub>.</li> <li>fit error for c<sub>4</sub>.</li> <li>fit value for <span class="math-tex">\(c_1^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_1^\prime\)</span></li> <li>fit value for <span class="math-tex">\(c_2^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_2^\prime\)</span>.</li> <li>fit value for <span class="math-tex">\(c_3^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_3^\prime\)</span>.</li> <li>fit value for <span class="math-tex">\(c_4^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_4^\prime\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_2 - E_1)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_2-E_1)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_3-E_2)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_3-E_2)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_4-E_3)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_4-E_3)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_2^\prime - E_1^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_2^\prime - E_1^\prime)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_3^\prime - E_2^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_3^\prime - E_2^\prime)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_4^\prime - E_3^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_4^\prime - E_3^\prime)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_1)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_1)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_1^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_1^\prime)\)</span>.</li> </ol>
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.