Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
235
datasets available to search
ShareScore release 0.9.0
Dataset results
235 results for “spectroscopic”
Supporting dataset with respect to Raman spectroscopic analysis of Palaeogene charcoals from Malcolm's Point, Isle of Mull, Scotland.
<p>Raman spectroscopic data (raw and processed) for Palaeogene charcoal samples A1, A2, B, and A1 thin section (A1-TS), including application of FWHMRa geothermometry as per <strong>Theurer et al. (2022)</strong>. Spectral data collected and processed in <em>Renishaw</em> WiRE 3.4 software. Those data presented in sheet 'HDHG Method 3' refer to spectral data processed in MATLAB, implementing 'peak-fit' and secondary deconvolution codes, as per <strong>O'Haver (2015, 2022)</strong> and <strong>Schito et al. (2020, 2022)</strong>, respectively.</p> <p><strong>O'Haver, T. (2015)</strong>. A Pragmatic Introduction to Signal Processing [Online]. Retrieved from https://terpconnect.umd.edu/~toh/spectrum/CurveFittingC.html</p> <p><strong>O'Haver, T. (2022)</strong>. peakfit.m [Code]. <em>MATLAB Central File Exchange</em>. Retrieved from https://www.mathworks.com/matlabcentral/fileexchange/23611-peakfit-m</p> <p><strong>Schito, A. & Corrado, S. (2020)</strong>. An automatic approach for characterization of the thermal maturity of dispersed organic matter Raman spectra at low diagenetic stages. <em>Journal of the Geological Society of London - Special Publications</em>. 484, 107–119. doi: 10.1144/SP484.5</p> <p><strong>Schito, A., Pensa, A., Corrado, S., Vona, A., Trolese, M., Morgavi, D., <em>et al. </em>(2022)</strong>. Calibrating carbonization temperatures of wood fragments embedded within pyroclastic density currents through Raman spectroscopy. <em>Minerals</em>, 12, 203. doi: 10.3390/min12020203</p> <p><strong>Theurer, T., Naszarkowski, N., Muirhead, D. K., Jolley, D. & Mauquoy, D. (2022)</strong>. Assessing modern Calluna heathland fire temperatures using Raman spectroscopy: Implications for past regimes and geothermometry. <em>Frontiers in Earth Science</em>, 10, 827933. doi: 10.3389/feart.2022.827933</p>
DATASET FOR: A multimodal spectroscopic approach combining mid-infrared and near-infrared for discriminating Gram-positive and Gram-negative bacteria
<h4>Description:</h4> <p>This dataset comprises a comprehensive set of files designed for the analysis and 2D correlation of spectral data, specifically focusing on ATR and NIR spectra. It includes MATLAB scripts and supporting functions necessary to replicate the analysis, as well as the raw datasets used in the study. Below is a detailed description of the included files:</p> <ol> <li> <p><strong>Data Analysis</strong>:</p> <ul> <li><strong>File Name</strong>: <code>Data_Analysis.mlx</code></li> <li><strong>Description</strong>: This MATLAB Live Script file contains the main script used for the classification analysis of the spectral data. It includes steps for preprocessing, analysis, and visualization of the ATR and NIR spectra.</li> </ul> </li> <li> <p><strong>2D Correlation Data Analysis</strong>:</p> <ul> <li><strong>File Name</strong>: <code>Data_Analysis_2Dcorr.mlx</code></li> <li><strong>Description</strong>: This MATLAB Live Script file is similar to the primary analysis script but is specifically tailored for performing 2D correlation analysis on the spectral data. It includes detailed steps and code for executing the 2D correlation.</li> </ul> </li> <li> <p><strong>Functions</strong>:</p> <ul> <li><strong>Folder Name</strong>: <code>Functions</code></li> <li><strong>Description</strong>: This folder contains all the necessary MATLAB function files required to replicate the analyses presented in the scripts. These functions handle various preprocessing steps, calculations, and visualizations.</li> </ul> </li> <li> <p><strong>Datasets</strong>:</p> <ul> <li><strong>File Names</strong>: <code>ATR_dataset.xlsx</code>, <code>NIR_dataset.xlsx</code>, <code>Reference_data.csv</code></li> <li><strong>Description</strong>: These Excel files contain the raw spectral data for ATR and NIR analyses, as well as reference datasets. Each file includes multiple sheets with detailed measurements and metadata.</li> </ul> </li> </ol> <h4>Usage Notes:</h4> <ul> <li><strong>Software Requirements</strong>: <ul> <li>MATLAB is required to run the .mlx files and utilize the functions.</li> <li><strong>PLS_Toolbox</strong>: Necessary for certain preprocessing and analysis steps.</li> <li><strong>MIDAS 2010</strong>: Available at <a href="https://www.mathworks.com/matlabcentral/fileexchange/32384-midas-2010" target="_new" rel="noreferrer">MIDAS 2010</a>, required for the 2D correlation analysis.</li> </ul> </li> <li><strong>Replication</strong>: Users can replicate the analyses by running the <code>Data_Analysis.mlx</code> and <code>Data_Analysis_2Dcorr.mlx</code> scripts in MATLAB, ensuring that the <code>Functions</code> folder is in the MATLAB path.</li> <li><strong>Data Handling</strong>: The datasets are provided in .xlsx format, which can be easily imported into MATLAB or other data analysis software.</li> </ul>
A spectroscopic and photometric investigation of the mercury-manganese star KIC 6128830
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.474.2467H/abstract">Hümerich et al. (2018)</a>. MESA version 8677.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/stx2974">10.1093/mnras/stx2974</a></p>
A Photometric, Spectroscopic, and Apsidal Motion Analysis of the F-type Eclipsing Binary BW Aquarii from K2 Campaign 3
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018AJ....156....8L/abstract">Lester & Gies (2018)</a>. MESA version 10108.</p> <p>Publication DOI: <a href="https://doi.org/10.3847/1538-3881/aac2ea">10.3847/1538-3881/aac2ea</a> </p>
How accurate are the spectroscopic classification tools of transients? - Study with 4,646 SEDMachine spectra
<div> <div> <div> <p>Performance evaluation metrics for SNID, NGSF, and DASH used for Fig. 6 of the paper.</p> </div> </div> </div>
Dataset for publication: "Structural and spectroscopic studies of lithium tetraborate glass co-doped with Sm and Cu"
<p>Dataset for the article: B.V. Padlyak, I.I. Kindrat, V.T. Adamiv, A. Drzewiecki, B. Cieniek, I. Stefaniuk, Structural and spectroscopic studies of lithium tetraborate glass co-doped with Sm and Cu, Phys. Chem. Chem. Phys. 26 (2024) 22006–22022, https://doi.org/10.1039/d4cp01633e.</p>
Photophysical and Spectroscopic dataset for Carrier Dynamics and Recombination in Ag-In-Zn-S Quantum Dots
<p>(1) HR-TEM images of alloyed AgIn<sub>1.5</sub>Zn<sub>1.9</sub>S<sub>3.6</sub> (A1) and AgIn<sub>1.5</sub>Zn<sub>4.4</sub>S<sub>6.8</sub> (A2) nanocrystals.</p> <p>(2) Energy-dispersive spectra of alloyed AgIn<sub>1.5</sub>Zn<sub>1.9</sub>S<sub>3.6</sub> (A1) and AgIn<sub>1.5</sub>Zn<sub>4.4</sub>S<sub>6.8</sub> (A2) nanocrystals.</p> <p>(3) UV-vis-NIR spectra of A1 nanocrystals and A1-MV, where the nanocrystals are conjugated with methyl viologen (MV2+) molecules.</p> <p>(4) (a) Normalized PL decays of A1 nanocrystals measured at various detection wavelengths, (b and c) PL decays measured at room temperature for A1 and A2 nanocrystals, (d and e) PL decays measured at various temperatures for A1 and A2 nanocrystals.</p> <p>(5) Transient absorption (TA) spectra for A1 nanocrystals for various pump-probe delays.</p> <p> </p> <p>This work was supported by National Science Centre Poland Grant No. 2019/35/B/ST3/04235.</p> <p>P.K., P.B., and A.P. acknowledge the financial support from the National Science Centre of Poland, Grant No. 2022/45/B/ST5/02120.</p>
Dataset of "Unraveling the Mechanism of the CO2-Assisted Oxidative Dehydrogenation of Propane over VOx/CeO2: An Operando Spectroscopic Study"
<p>This zip file contains the dataset of the publication "Unraveling the Mechanism of the CO2-Assisted Oxidative Dehydrogenation of Propane over VOx/CeO2: An Operando Spectroscopic Study". The authors are Leon Schumacher, Marius Funke and Christan Hess*. The zip file includes the data for figures 1-8 in the manuscript and the data for figures S1-S11 in the SI.</p> <p>*christian.hess@tu-darmstadt.de</p>
Bonding mechanism of cyanoacrylate on SiO2 and Au: Spectroscopic studies of the interface
<p>Cyanoacrylates form a highly reactive class of adhesives that develop significant adhesive strength to surfaces within a few seconds. Despite their commercial use, the exact bonding mechanism is virtually unknown. In the present work, we spin coat nm-thin films of ethyl cyanoacrylate on the two model substrates gold and silicon dioxide. The objective of the studies is to identify chemical interactions at the interface between adhesive and metal (oxide) which are possible reasons for film adhesion on the macroscopic scale. For this purpose, thin films of ethyl cyanoacrylate are investigated by X-Ray photoelectron spectroscopy.</p>
Spectroscopic data and DFT coordinates for "The three-spin intermediate at the O–O cleavage and proton pumping junction in heme–Cu oxidases"
<p>This dataset includes spectroscopic data and atomic coordinates of DFT structures in the manuscript titled "The three-spin intermediate at the O–O cleavage and proton pumping junction in heme–Cu oxidases". Spectroscopic data included are from magnetic circular dichroism (MCD), variable-temperature variable-field MCD, absorption and resonance Raman spectroscopies.</p>
The Complicated Case of δ Scuti Pulsations and Rotation in KIC 6951642; a long-orbit Single-lined Spectroscopic Binary Star
<p>Abstract: More than four years of HERMES observations have confirmed KIC 6951642 is a very long orbit (≈1770 d) single-lined spectroscopic binary (F0-type) with a fast-rotating companion (vsin i = 123±3 Km/s). The Fourier spectrum of its four-year photometric observations includes plenty of significant frequencies (594) in low- and high-frequency regions. The high-frequency modes appear with various time-delay patterns. We detected several rotationally split 𝛿 Scuti pulsations centered at 13.96 per day (and average frequency spacing of Δ𝑓= 0.723±0.006 per day) for KIC 6951642. The detailed study of all significant low frequencies, extended from 0.72 to 3.60 per day, revealed that the two most dominant frequencies (with the same amplitude and larger than of p-modes) are a combina3on the lowest-frequency modes (𝑓<sub>3</sub> = 𝑓< 0.17 per day), i.e. 𝑓<sub>orhrm</sub> + 𝑚𝑓<sub>orhrm </sub>(𝑚 = 12,14). We suggest the lowest-frequency modes are very large harmonics (orders of 10) of orbital frequency (≈0.0006 per day). We verified the other most dominant low-frequencies as harmonics of rotation frequency 0.721 per day and its combinations. Finally, we reject the probability of hybrid pulsations in the fast-rotating companion of KIC 6951642. We introduce it as a 𝛿 Scuti pulsator with a candidate rotation frequency of 0.721 per day.</p>
Stellar chromospheric activity database of solar-like stars based on the LAMOST Low-Resolution Spectroscopic Survey
<p>A stellar chromospheric activity database of solar-like stars is constructed based on the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Low-Resolution Spectroscopic Survey (LRS). The database contains spectral bandpass fluxes and indexes of Ca II H and K lines derived from 1,330,654 high-quality LRS spectra of solar-like stars. We measure the mean fluxes at line cores of the Ca II H and K lines using a 1 Å rectangular bandpass and a 1.09 Å FWHM triangular bandpass, as well as the mean fluxes of two 20 Å wide pseudocontinuum bands on the two sides of the lines. Three activity indexes of Ca II H and K lines, <em>S</em><sub>rec</sub> based on the 1 Å rectangular bandpass and <em>S</em><sub>tri</sub> and <em>S<sub>L</sub></em> based on the 1.09 Å FWHM triangular bandpass, are evaluated from the measured fluxes to quantitatively indicate the chromospheric activity level. The uncertainties of all the obtained parameters are estimated. We also produce spectrum diagrams of Ca II H and K lines for all the spectra in the database. This database, with more than one million high-quality LAMOST LRS spectra of Ca II H and K lines and basal chromospheric activity parameters, can be further used for investigating activity characteristics of solar-like stars and solar-stellar connection.</p> <p> </p> <p>The entity of the database is composed of (1) a catalog of spectral sample and activity parameters, and (2) a library of spectrum diagrams of Ca II H and K lines.</p> <p>(1) Catalog of Spectral Sample and Activity Parameters<br> CaIIHK_Sindex_LAMOST_DR7_LRS.csv<br> (see Table3 in the paper 2022_ApJS_263_12 for description of the columns)</p> <p>(2) Library of Spectrum Diagrams of Ca II H and K lines<br> spectrum_diagrams_000-049.zip (46 subfolders)<br> spectrum_diagrams_050-099.zip (40 subfolders)<br> spectrum_diagrams_100-149.zip (47 subfolders)<br> spectrum_diagrams_150-174.zip (25 subfolders)<br> spectrum_diagrams_175-199.zip (24 subfolders)<br> spectrum_diagrams_200-224.zip (24 subfolders)<br> spectrum_diagrams_225-249.zip (23 subfolders)<br> spectrum_diagrams_250-259.zip (10 subfolders)<br> spectrum_diagrams_260-274.zip (12 subfolders)<br> spectrum_diagrams_275-299.zip (23 subfolders)<br> spectrum_diagrams_300-349.zip (41 subfolders)<br> spectrum_diagrams_350-374.zip (20 subfolders)<br> spectrum_diagrams_375-399.zip (19 subfolders)<br> spectrum_diagrams_400-424.zip (23 subfolders)<br> spectrum_diagrams_425-449.zip (22 subfolders)<br> spectrum_diagrams_450-499.zip (35 subfolders)<br> spectrum_diagrams_500-549.zip (27 subfolders)<br> spectrum_diagrams_550-599.zip (38 subfolders)<br> spectrum_diagrams_600-649.zip (32 subfolders)<br> spectrum_diagrams_650-699.zip (26 subfolders)<br> spectrum_diagrams_700-749.zip (28 subfolders)</p>
Optical polarimetric, photometric and spectroscopic observations of the TDE AT 2020mot with Nordic Optical Telescope
<p>The dataset contains:</p> <p>1. Polarization data from November 10th, 2020: raw FITS images of the tidal disruption event <a href="https://www.wis-tns.org/object/2020mot">AT 2020mot</a> (polAT2020mot.zip), master bias, master flat-fields (calibs.zip) and raw FITS images of a polarization standard stars (polstandards.zip) that can be used for the instrumental polarization correction.</p> <p>2. The imaging data from February 19th, 2021: raw fits images of the tidal disruption event <a href="https://www.wis-tns.org/object/2020mot">AT 2020mot</a> (imaging.zip) , master bias, master flat-fields (imagingcalibs.zip) and reduced and summed R+i image (TDEsum.fits) that was used to fit the host galaxy profile.</p> <p>3. The spectra from February 19th, 2021: raw fits of the spectra obtained using grisms #7 and #20 (spectroscopy.zip, includes calibration files) and the reduced spectra (TDE.fits).</p> <p>The dataset was obtained with the Nordic Optical Telescope (NOT).</p>
Exploratory investigation of historical decorative laminates by means of vibrational spectroscopic techniques
<p>This dataset contains the data used for the publication entitled "Exploratory investigation of historical decorative laminates by means of vibrational spectroscopic techniques".</p>
Spectroscopic identification of water emission from a main-belt comet: Supporting data and code
<p>Reduced data, source files, and code used in the analysis of JWST spectroscopy of comet 238P/Read, by Kelley et al. (2023, Nature 619, 720. 10.1038/s41586-023-06152-y).</p>
A Raman Spectroscopic Study of Lightning-Induced Glass Produced from Five Mineral Phases Dataset
<p>Dataset contains raw and corrected Raman spectra for five common mineral < 32 µm powders (albite, labradorite, augite, hornblende, and magnetite) before and after high-current impulse experiments conducted at peak currents of 25 and 40 kA.</p>
Dataset of H-alpha activity indices of F-, G-, and K-type stars observed by the LAMOST Medium-Resolution Spectroscopic Survey
<p>This dataset of H-alpha activity indices is for investigation of stellar H-alpha chromospheric activity based on the LAMOST Medium-Resolution Spectroscopic Survey (MRS). High signal-to-noise ratio MRS coadded spectra of F-, G-, and K-type stars (4000-7000 K) from LAMOST Data Release 8 are utilized in the dataset (329,294 spectra in total). The H-alpha activity index (I_halpha) and the H-alpha R-index (R_halpha) are evaluated for the MRS spectra. The values of the H-alpha indices and their uncertainties, as well as the related spectroscopic parameters from the LAMOST catalogs, are stored in a CSV-format file (file name: Halpha_activity_indices_LAMOST_MRS_DR8.csv).</p> <p> </p> <p>Columns included in the dataset:</p> <p>obsid - unique observation identifier of LAMOST MRS</p> <p>ra - right ascension of the observed object (unit: degree)</p> <p>dec - declination of the observed object (unit: degree)</p> <p>obsdate - UTC date of the observation (format: YYYY-MM-DD)</p> <p>fitsname - MRS FITS data file name</p> <p>sn_B - signal-to-noise ratio of the blue band of MRS</p> <p>sn_R - signal-to-noise ratio of the red band of MRS</p> <p>band_para - indicating which band of MRS is used by the LASP to determine the stellar atmospheric parameters; ‘B’ representing the blue band and ‘R’ representing the red band</p> <p>teff - effective temperature determined by the LASP (unit: K)</p> <p>teff_err - uncertainty of teff (unit: K)</p> <p>logg - surface gravity determined by the LASP (unit: dex)</p> <p>logg_err - uncertainty of logg (unit: dex)</p> <p>feh - metallicity determined by the LASP (unit: dex)</p> <p>feh_err - uncertainty of feh (unit: dex)</p> <p>rv_r0 - radial velocity determined based on the red band data of MRS (unit: km/s)</p> <p>rv_r0_err - uncertainty of rv_r0 (unit: km/s)</p> <p>category* - ‘main-sequence’ or ‘giant’ or ‘intermediate-zone’</p> <p>I_halpha* - H-alpha activity index</p> <p>I_halpha_err* - uncertainty of I_halpha</p> <p>chi* - χ factor for calculating R_halpha from I_halpha (unit: 1/Å)</p> <p>chi_err* - uncertainty of chi (unit: 1/Å)</p> <p>R_halpha* - H-alpha R-index</p> <p>R_halpha_err* - uncertainty of R_halpha</p> <p>(Note: The columns marked with an asterisk are provided by this dataset. Other columns are from the catalogs of LAMOST DR8 v1.1. LASP is an acronym for the LAMOST Stellar Parameter Pipeline. A value of -9999.0 in the dataset indicates that it is not available.)</p> <p> </p> <p> </p>
Spectroscopic Data for Thallium Sorbed to Manganese Oxides
<p>This dataset includes X-ray diffraction (XRD), Raman spectroscopy, and X-ray absorption near edge structure (XANES) data from Phillips et al. (2023)- "The role of manganese oxide mineralogy in thallium isotopic fractionation upon sorption". This project aimed to determine the degree of Thallium (Tl) isotope fractionation upon sorption to Mn oxide minerals triclinic birnessite and todorokite. The XRD and Raman spectra indicate structural changes in the mineralogy of triclinic birnessite upon Tl sorption. The XANES spectra show that Tl and Mn oxidation states remain relatively constant before and after Tl sorption, indicating that no Tl oxidation or Mn reduction occurs during Tl sorption to triclinic birnessite or todorokite. </p>
MMT/Binospec Spectroscopic Survey of Two z~0.8 Galaxy Clusters: Galaxy Spectra Figures and FITS Data
<p>This dataset includes MMT/Binospec spectra of all 371 galaxies observed in 2019 and 2022, which were already discussed in the research paper (J. Di et al.) where you just got this dataset link. To quickly look at our spectra, we reduced our spectra in the JPG format. We also attached the raw FITS format 1D and 2D spectra of two years' observations.</p>
A case study for measuring the relativistic dipole of a galaxy cross-correlation with the Dark Energy Spectroscopic Instrument: Data Repository
<p>This repository contains the synthetic catalogue for the DESI Bright Galaxy Survey produced wit the N-body code <em>gevolution</em>, which is analysed in the manuscript "<a href="https://arxiv.org/abs/2306.04213">A case study for measuring the relativistic dipole of a galaxy cross-correlation with the Dark Energy Spectroscopic Instrument</a>", as well as the raw data of the analysis results. The catalogue "catalogue.csv.bz2" is in the CSV format and can be directly read using the pandas library of python, for example. The columns in the catalogue contain the following information:</p> <p>0. Column index<br> 1. Comoving coordinate x (in units of Mpc/h)<br> 2. Comoving coordinate y (in units of Mpc/h)<br> 3. Comoving coordinate z (in units of Mpc/h)<br> 4. Observed redshift<br> 5. Cosine of the observed polar angle measured with respect to the axis pointing in the direction (1,1,1) along the box diagonal (the original comoving coordinate system has been rotated with an intrinsic z-y-z Euler rotation, first rotating along the z-axis with <span class="math-tex">\(\phi_1 = \pi/4\)</span>, then rotating along the new y axis with <span class="math-tex">\(\theta_2 = \mathrm{arccos}(1/\sqrt{3})\)</span> and setting the final rotation angle to zero, <span class="math-tex">\(\phi_3 = 0\)</span>; hence to get the unperturbed mu and phi coordinates, one needs to rotate the comoving x, y and z coordinates with the corresponding inverse Euler rotation matrix)<br> 6. Observed azimuthal angle phi measured with respect to axis pointing in the direction (1,1,1) along the box diagonal (the original comoving coordinate system has been rotated with an intrinsic z-y-z Euler rotation, first rotating along the z-axis with <span class="math-tex">\(\phi_1 = \pi/4\)</span>, then rotating along the new y axis with <span class="math-tex">\(\theta_2 = \mathrm{arccos}(1/\sqrt{3})\)</span> and setting the final rotation angle to zero, <span class="math-tex">\(\phi_3 = 0\)</span>; hence to get the unperturbed mu and phi coordinates, one needs to rotate the comoving x, y and z coordinates with the corresponding inverse Euler rotation matrix)<br> 7. Logarithm of the luminosity in units of solar luminosity <span class="math-tex">\(L_\odot\)</span><br> 8. Observed flux (in units of <span class="math-tex">\(L_\odot/\mathrm{Mpc}^2\)</span>)<br> 9. Number of particles in each object, plus a uniform noise between 0 and 1. This quantity is the proxy of the mass that was used to assign luminosity to the objects.<br> 10. Flag that identifies the selected objects within each redshift bin. The Flag is 0 for objects not included in the catalogue, and equal to the mean redshift of the bins <span class="math-tex">\(\bar{z} = 0.25, 0.35, 0.45\)</span> for the selected objects. <br> 11. Flag that identifies the bright and faint objects for case 1 (50% bright, 50% faint, no flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 12. Flag that identifies the bright and faint objects for case 2 (90% bright, 10% faint, no flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 13. Flag that identifies the bright and faint objects for case 3 (50% bright, 50% faint, with flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 14. Flag that identifies the bright and faint objects for case 4 (90% bright, 10% faint, with flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.</p> <p>The example script "example-script.ipynb" demonstrates how to query the catalogue to extract e.g. the redshift distribution of the objects for the different cases considered in Table 4 of the manuscript.</p> <p>Additionally, the measured dipole data vectors with the jackknife covariance matrices (<span class="math-tex">\(\mathrm{cov}^\mathrm{JK}_{ij}\)</span>), as well as the theoretical data vectors with the theoretical measurement covariance (<span class="math-tex">\(\mathrm{cov}^\mathrm{th}_{ij}\)</span>) and the theoretical prediction covariance (<span class="math-tex">\(\mathrm{cov}^\mathrm{pred}_{ij}\)</span>) are provided within this repository:</p> <ul> <li>In the measurements.tar.gz archive, the measured data for the flux-limited case can be found in the /flux-limit subdirectory, while the data for the case without flux-limit is in /no-flux-limit. The data vectors are named "dipole_<redshift bin>_<% of bright galaxies>.txt. The first column in each of those files is the separation bin <span class="math-tex">\(d\)</span> in <span class="math-tex">\(\mathrm{Mpc}/h\)</span>, the second column is the mean two-point correlation function dipole of the 100 jackknife subsamples, and the third column is the square root of the diagonal part of the jackknife covariance matrix (<span class="math-tex">\(\mathrm{cov}^\mathrm{JK}_{ij}\)</span>). The corresponding jackknife covariance matrices are named "cov_<redshift bin>_<% of bright galaxies>.txt.</li> <li>In the theory.tar.gz archive, the theoretical predictions are found in /flux-limit for the case with flux limit and in /no-flux-limit for the case without flux limit. The theoretical data vectors are named "dipole_<% of bright galaxies>B_z<redshift bin>_gevol.dat". The first column in each of those files is the separation bin <span class="math-tex">\(d\)</span> in <span class="math-tex">\(\mathrm{Mpc}/h\)</span>, the second column the theoretical two-point correlation function dipole and the third column is the square root of the diagonal part of the theoretical prediction covariance matrix (<span class="math-tex">\(\mathrm{cov}^\mathrm{pred}_{ij}\)</span>) . The theoretical measurement covariance matrices are named "covariance_Lp6_<% of bright galaxies>B_z<redshift bin>_gevol.dat", and the theoretical prediction covariance matrices are named "covtheo_<% of bright galaxies>B_z<redshift bin>_gevol.dat". </li> </ul> <p>The example script also demonstrates how to use these data files to reproduce plots of the dipole measurement vs the theoretical prediction like in Figures 6, 7, C1 and C2. The archives need to be unpacked before using the example script to access the data.</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.