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252 results for “Atomic data”
ATom: Data Stream for Modeling the Reactivity of ATom Air Parcels, 2016-2018
This dataset provides Modeling Data Stream (MDS) and Reactivity Data Stream (RDS) products for each of the four ATom campaigns conducted from 2016 to 2018. MDS files contain the atmospheric constituents needed to model the RDS of the air parcels along ATom flight paths. The MDS is a continuous data stream (every 10 seconds) of the atmospheric content of these key chemical species derived from the in-situ measurements collected along ATom flight paths (as reported in the comprehensive related dataset ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols). Values for chemical species measured by multiple instruments were selected from the instrument with better coverage and/or greater precision. Missing values were filled using interpolation for short gaps. For long gaps owing to instrument failure, values were estimated using multiple linear regressions from comparable parallel flights from other ATom campaigns. All species were flagged for instrument source and values were flagged for gap-filling status. In combination, MDS and RDS provide, in essence, a photochemical climatology for each air parcel along ATom flight paths containing the reactive species that control the loss of methane and the production and loss of ozone.
ATom: Ultra-High Sensitivity Aerosol Spectrometer Calibration and Performance Data
This dataset provides extensive calibration and in-flight performance data for two Ultra-High Sensitivity Aerosol Spectrometers (UHSAS) used for particle size distribution and volatility measurements during the NASA Atmospheric Tomography Mission (ATom) airborne campaign. UHSAS-1 was equipped with a compact thermodenuder operating at 300 degrees C and UHSAS-2 was operated without a thermodenuder to determine the number and volume fraction of volatile particles. Laboratory studies utilized aerosols from limonene ozonolysis (limon), atomization of ammonium sulfate (AS), and atomization of 2-diethylhexyl (dioctyl) sebacate (DOS). Data include: UHSAS detection efficiency, sizing calibration, performance at a range of pressures and at a range of thermodenuder temperatures, comparison of UHSAS-2 and condensation particle counter (CPC) particle number concentrations, comparisons of UHSAS-1 and UHSAS-2 for dry particle number concentration, surface area and volume collected onboard of a NASA DC-8 aircraft during August 2016, and dry aerosol size distributions for thermodenuded and non-thermodenuded instrument collected in February 2017.
ATom: Aircraft Flight Track and Navigational Data
This dataset provides flight track and aircraft navigation data from the NASA Atmospheric Tomography Mission (ATom). Flight track information is available for the four ATom campaigns: ATom-1, ATom-2, ATom-3, and ATom-4. Each ATom campaign consists of multiple individual flights and flight navigational information is recorded in 10-second intervals. Data available for each flight includes research flight number, date, and start and stop time of each 10-second interval. In addition, latitude, longitude, altitude, pressure and temperature is included at each 10-second interval. NASA's ATom campaign deploys an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Flights occurred in each of 4 seasons from 2016 to 2018. During each campaign, flights originate from the Armstrong Flight Research Center in Palmdale, California, fly north to the western Arctic, south to the South Pacific, east to the Atlantic, north to Greenland, and return to California across central North America. ATom establishes a single, contiguous, global-scale dataset. One intended use of this flight track data is to facilitate to mapping model results from global models onto the precise ATom flight tracks for comparison.
ATOMIC Simulations and Experimental Data for Sodium and Copper Mixtures
<p>This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [1]. Our overall suite of simulations contains 12 sets of simulations: training and validation sets of simulations for each of two resolutions of each of sodium, copper, and mixtures of the two. The training data were produced using a 500-run design that varies input parameters temperature (T), electron density (Ne), proportion of sodium (pNa), and proportion of copper (pCu). The latter two variables sum to one and are unused in the single-element simulations. The validation data was produced with a 25-run design. The coarse simulations produce spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. The fine resolution simulations produce spectra over a range of 550nm to 600nm and were produced to mimic the included experimental results. The experimental results cover four mixtures of sodium and copper. All data sets are kept in zip files whose names indicate the elemental composition (NaCu, Na, or Cu), resolution (coarse or fine), and purpose (training or validation) with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file. See attached abstract for figures.</p> <p><br> [1] J Colgan, EJ Judge, DP Kilcrease, and JE Bare6eld II. Ab-initio modeling of an iron laser-induced plasma: Comparison between theoretical and experimental atomic emission spectra. Spectrochimica Acta Part B: Atomic Spectroscopy, 97:65– 73, 2014.</p> <p>[2] Elizabeth J Judge, James Colgan, Keri Campbell, James E Bare6eld II, Heather M Johns, David P Kilcrease, and Samuel Clegg. Theoretical and experimental investigation of matrix effects observed in emission spectra of binary mixtures of sodium and copper and magnesium and copper pressed powders. Spectrochimica Acta Part B: Atomic Spectroscopy, 122:142–148, 2016.</p>
3x 1 µs all-atom MD trajectories; AMBER ff15ipq & SPC/Eb; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>3 x 1 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff15ipq with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: SPC/Eb</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>3 x GROMACS .xtc trajectory files for 3 independent simulations</li> <li>3 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2020). Predicting NMR relaxation of proteins from molecular dynamics simulations with accurate methyl rotation barriers. <em>Journal of Chemical Physics</em>, <em>152</em>(8). https://doi.org/10.1063/1.5135379</p>
5x 1 µs all-atom MD trajectories; AMBER ff99SB*-ILDN & TIP4P/2005; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>5 x 1 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff99SB*-ILDN with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: TIP4P/2005</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>5 x GROMACS .xtc trajectory files for 5 independent simulations</li> <li>5 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2018). Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields. <em>The Journal of Physical Chemistry B</em>, <em>122</em>(19), 5038–5048. https://doi.org/10.1021/acs.jpcb.8b02769</p>
3x 5 µs all-atom MD trajectories; AMBER ff99SB*-ILDN & TIP4P/2005; T4 Lysozyme; 'Fitting side-chain NMR relaxation data using molecular simulations'
<p>Simulation data for "Fitting side-chain NMR relaxation data using molecular simulations" (https://doi.org/10.1101/2020.08.18.256024).</p> <ul> <li>3 x 5 µs all-atom MD simulations of T4 Lysozyme</li> <li>Force field: AMBER ff99SB*-ILDN with modified methyl rotation barriers<sup>1</sup></li> <li>Water model: TIP4P/2005</li> <li>Compressed protein coordinates saved every 1 ps to enable calculation of side-chain NMR relaxation parameters</li> </ul> <p>Contains:</p> <ul> <li>3 x GROMACS .xtc trajectory files for 3 independent simulations</li> <li>3 x corresponding GROMACS .tpr topology files</li> </ul> <p><sup>1</sup> Hoffmann, F., Mulder, F. A. A., & Schäfer, L. V. (2018). Accurate Methyl Group Dynamics in Protein Simulations with AMBER Force Fields. <em>The Journal of Physical Chemistry B</em>, <em>122</em>(19), 5038–5048. https://doi.org/10.1021/acs.jpcb.8b02769</p>
ATOMIC Simulations and Experimental Data for Basalt-like Compounds
<p>This data consists of simulations and experimental measurements of laser-induced breakdown spec- troscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [2]. The makeup of the plasma was considered to be divided into some proportion water, some proportion Martian atmosphere (CO2), and some proportion target (from the rock or object impacted by the laser), where these proportions add to 1. Based on expert knowledge, the proportion of water was kept in the range [0.0,0.5] and the proportion of atmosphere was kept in the range [0.02, 0.9]. Our overall suite of simulations contains six sets of simulations that differ in which elements were considered to make up the target. Within each set, we used uniformly drawn temperatures and log mass densities within pre-specified ranges. The temperature range was [0.5,1.5] eV and the log (base 10) mass density range was [−7,−4]. The proportion of water, atmosphere, and target were drawn from a symmetric Dirichlet distribution, but draws in which the propor- tion of water or atmosphere exceeded the pre-specified limits were rejected from the design. Up to eleven constituent elements (Si, Al, Fe, Mg, Ca, O, Ti, Mn, Na, K, P) were considered for the target, as they are the most common elements found in basalt compounds and were used in [1]. For each run, the proportions of the constituent elements making up the target were drawn from a symmetric Dirichlet distribution. We ran 1,350 simulations that included nonzero proportions of all eleven elements. We also ran simulations which excluded some of these elements. In particular, we ran 1,000 simulations that only included nonzero proportions for the six most common elements (Si, Al, Fe, Mg, Ca, O). We also ran five sets, each with 500 simulations, that only included nonzero proportions for five of the six most common elements (but where all sets included O). Thus, we generated a total of 4,850 spectra representing basalt-like compounds in which the target was comprised of oxygen and between four and ten other elements. The ATOMIC code produced spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. Each spectra had 32,000 wavelengths split across three spectrometer ranges (to mimic ChemCam). The experimental data, described in [1], measures a prepared basalt sample. All files are kept in directories whose names indicate the set of elements considered for the target with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file which contains a header with measurement information, followed by a collection of 50 shots across a collection of wavelengths, along with the computed median and mean across shots.</p>
Computational data on "Proton Affinity and Conformational Integrity in a 24-atom Triazine Macrocycle Across Physiologically-relevant pH"
<p>The archive contains 5 different folders:<br><br>1. mdp_files, that contains all the input files for the minimization, equilibration and molecular dynamics run (in gromacs format);<br>2. topologies, that contains the equilibrated configurations and topology of the 2 systems studied -protonated and deprotonated macrocycles- (in gromacs format);<br>3. trajectories, that contains the coordinates of the macrocycles during the metadynamics calculations and the relevant metadynamics output files (hills file and energy file);<br>4. plumed_input, that contains the input file for the metadynamics calculations.<br>5. gaussian, that contains input and output for the single-point charge calculations.</p>
Data and materials for "Crystallization kinetics of atomic crystals revealed by a single-shot and single-particle X-ray diffraction experiment"
<p>XFEL diffraction data and simulation codes associated with publication "Crystallization kinetics of atomic crystals revealed by a single-shot and single-particle X-ray diffraction experiment" (https://doi.org/10.1073/pnas.2111747118). <a href="https://zenodo.org/api/files/6b7e2270-da94-43ea-8cb7-24db901d6d47/Fig1A.txt?versionId=22020722-9489-427b-b2a3-8a5577542679">Fig1A.txt</a> is the 2D array data of the accumulated diffraction image. <a href="https://zenodo.org/api/files/6b7e2270-da94-43ea-8cb7-24db901d6d47/Fig2A.txt?versionId=f53f0a51-20f0-4aaa-b2f3-7ac284e5a39a">Fig2A.txt</a>, <a href="https://zenodo.org/api/files/6b7e2270-da94-43ea-8cb7-24db901d6d47/Fig2B.txt?versionId=a7a31743-446f-4b60-84fc-8d06383bd852">Fig2B.txt</a>, <a href="https://zenodo.org/api/files/6b7e2270-da94-43ea-8cb7-24db901d6d47/Fig2C.txt?versionId=d79d2068-2530-4ee6-95fc-b38b4ee8bda5">Fig2C.txt</a> are the 2D arrays of the single-shot diffraction images. The unit is electronvolt per pixel. <a href="https://zenodo.org/api/files/6b7e2270-da94-43ea-8cb7-24db901d6d47/Python%20script.ipynb">Python script.ipynb</a> includes the simulation codes for the single-shot streak patterns and the integrated powder diffraction pattern. </p>
Data Sharing for: ''RNA folding landscapes from explicit solvent all-atom simulations"
<p>Data required to reproduce the figures and analysis in the paper: ''RNA folding landscapes from explicit solvent all-atom simulations".</p>
Computational Data - Role of Molecular Orientation: Comparison of Nitrogenous Aromatic Small Molecule Inhibitors for Area-Selective Atomic Layer Deposition
<p><span><span>Area-selective atomic layer deposition (AS-ALD) shows great potential for meeting the stringent demands of the semiconductor industry for precision nanopatterning. Small molecule inhibitors (SMIs) have recently proven to be a promising, industry-compatible means of achieving AS-ALD. In this work, we compare three nitrogenous aromatic SMIs – aniline, pyrrole, and pyridine – for their ability to block Al</span></span><sub><span><span>2</span></span></sub><span><span>O</span></span><sub><span><span>3</span></span></sub><span><span> ALD on copper with (CuO</span></span><sub><span><span>x</span></span></sub><span><span>) and without (Cu) a native oxide. We find that pyrrole and aniline perform much better as inhibitors than does pyridine. Furthermore, when redosed on copper before every ALD cycle in an ABC scheme, pyrrole and aniline provide outstanding inhibition, facilitating the selective deposition of over 11 nm of Al</span></span><sub><span><span>2</span></span></sub><span><span>O</span></span><sub><span><span>3</span></span></sub><span><span> on an SiO</span></span><sub><span><span>2</span></span></sub><span><span> growth surface in the presence of Cu with 99.9% selectivity. By combining both theory and experiment, we provide new understanding of the mechanisms by which selectivity is prolonged and lost. First, we show that the CuO</span></span><sub><span><span>x</span></span></sub><span><span> surface is inherently more reactive than the Cu surface, leading to an eventual loss of selectivity, even when the inhibitor is redosed. Second, we find that whereas pyrrole and aniline adsorb in a planar bonding orientation, pyridine binds upright at the copper surface and we propose that the upright orientation is the origin of the ineffective inhibition of pyridine. Finally, we observe that redosing of aniline protects the copper surface from undesired oxidation, whereas the redosing of pyridine does not. As such, we posit that a likely benefit of redosing is preventing oxidation and thus reducing reactive site formation during ALD. Through this work, we demonstrate the capability of nitrogenous aromatics to serve as SMIs for AS-ALD, and we contribute valuable insights regarding the impact of ALD process parameters on selectivity. </span></span></p>
Integrative determination of atomic structure of mutant huntingtin exon 1 fibrils implicated in Huntington disease — data files
<div>This zenodo entry contains MD and solid-state NMR data files for the paper:</div> <div> </div> <div><strong><em>Mahdi Bagherpoor Helabad et al. (2024) Integrative determination of atomic structure of mutant huntingtin exon 1 fibrils implicated in Huntington disease</em></strong></div> <div> </div> <h2> </h2> <h2>MD datasets and code</h2> <div>We provide here (in <strong>MD_simulations_data_codes.zip</strong>) the MD simulations files for the MD runs and also data, and their respective codes, shown in the figures of the above papers.</div> <div> </div> <div>Data file structure: </div> <p><strong>MD_data </strong></p> <ul> <li>The MD simulation run files for three fully periodic systems—PolyQ15 and HTTex1—include the following: .gro files for both minimization and final structures, production .tpr files, force field parameters, GROMACS .mdp files, and position and dihedral restraint files. <ul> <li>fully_periodic_systems</li> <li>polyQ15</li> <li>HTTex1</li> </ul> </li> </ul> <p><strong>Figs_Data_Codes</strong></p> <div> <ul> <li>The data and in-house Python scripts associated with creating the figures: <ul> <li>Fig2B_S4 for Figure 2B and Supplementary Figure 4</li> <li>Fig2D_S5 for Figure 2D and Supplementary Figure 5</li> <li>Fig3C_S10 for Figure 3C and Supplementary Figure 10</li> <li>Fig4_S12_S13_S14 for Figure 4C and Supplementary Figures 12–14</li> <li>Fig6C for Figure 6C</li> <li>FigS3B_S6 for Supplementary Figures 3B and 6</li> <li>FigS8 for Supplementary Figure 8</li> <li>FigS9_S11 for Supplementary Figures 9–11</li> <li>FigS16_to_S21 for Supplementary Figures 16–21</li> <li>FigS22 for Supplementary Figure 22</li> <li>readMe.txt <div> </div> </li> </ul> </li> </ul> </div> <div><strong>Fig6_c_barplot_data.xlsx</strong></div> <div> <ul> <li>Excel file with data plotted in Figure 6C.</li> </ul> <p><strong>N17_SecStr_convergence.xlsx</strong></p> <div> <ul> <li>Excel file with convergence data for N17 domain.</li> </ul> </div> </div> <h2>Solid-state NMR data</h2> <div>We provide here the solid-state NMR spectrum files for the data shown in figures of the above paper.</div> <div> </div> <div>Data file structure:</div> <div> </div> <div><strong>SSNMR_data_listing_20241011a.txt</strong></div> <div> <ul> <li>text file describing the ssNMR data files</li> </ul> </div> <div><strong>SSNMR_data.zip</strong></div> <ul> <li>Figure_1 - data for Figure 1F</li> <li>Figure_5 - data for Figure 5</li> <li>Figure_6 - data for Figure 6</li> <li>Figure_S7 - data for Figure 2G and Supplementary Figure 7</li> <li>Figure_S15 - NMR data for HDX ssNMR of fibrils – Supplementary Figure 15</li> </ul> <div><strong>Fig6_b_barplot_data.xlsx</strong></div> <div> <ul> <li>Excel file with data plotted in Figure 6B, based on previously reported results (DOI 10.1038/ncomms15462)</li> </ul> </div> <div> </div> <div>Data are provided in either Bruker Topspin format, or in NMRPIPE format (ft2 extension).</div> <div>Experimental parameters are described in the published paper and its Supplementary Information files. In general, these are all data from magic-angle-spinning (MAS) NMR studies of intact amyloid fibrils made with isotope labeled HTTex1 fibrils. Experimental types include 2D CP-DARR, 2D TOBSY, 2D HETCOR spectra as well as relaxation measurements. Aside from NMR datafiles, also documents with interpreted and integrated data are included, used to make data curves in the figure (e.g. for Prism software).</div> <div> </div> <div> </div> <div> </div>
Data and code for "High-field superconductivity from atomic-scale confinement and spin-orbit coupling at (111)LaAlO3/KTaO3 interfaces"
<p>This folder contains the raw data and scripts used to prepare the figures of the main text and supplemetary. </p>
Supplemental data for "Polarons in two-dimensional atomic crystals"
<p>Supplemental data for "Polarons in two-dimensional atomic crystals"</p>
Computational data on "A Model for the Rapid Assessment of Solution-Structures for 24-Atom Macrocycles: The Impact of β-Branched Amino Acids on Conformation"
<p>The archive contains 5 different folders:<br> <br> 1. mdp_files, that contains all the input files for the minimization, equilibration and molecular dynamics run (in gromacs format);<br> 2. topologies, that contains the equilibrated configurations and topology of the 4 systems studied (in gromacs format);<br> 3. trajectories, that contains the coordinates of the macrocycles during the metadynamics calculations and the relevant metadynamics output files (hills file and energy file);<br> 4. plumed_input, that contains the input file for the metadynamics calculations.<br> 5. gaussian, that contains input and output for the single-point charge calculations.</p>
Atom Probe Tomography dataset of pure Aluminum (Raw data)
<p>Atom Probe Tomography dataset of pure Aluminum (Raw data). The experiment was done with Oxcart a custom-made APT instrument. The data was recorded by pyccapt control module.</p>
IBEX High Energy Neutral Atom Imager (ENA-Hi) Data Release 10, not Compton-Getting corrected, Survival Probability corrected, Ram direction, West Longitude Ecliptic Maps, 1 year averaged data, Level H3
This IBEX-Hi data set is from Release 10 of all-sky map data for the first seven years, 2009-2015, in the form of ram direction Hydrogen, H, energetic neutral atom fluxes with no Compton-Getting corrections for spacecraft motion and with corrections for ENA survival probability between 1 and 100 AU. All-sky maps have been compiled for each consecutive 1 year time interval. The Interstellar Boundary Explorer, IBEX, has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 14 releases of IBEX-Hi and/or IBEX-Lo data covering 2009-2017. The data consist of all-sky maps in Solar Ecliptic Longitude, east and west, and Latitude angles for Energetic Neutral Atom, ENA, Hydrogen fluxes from IBEX-Hi from energy band 2 through energy band 6, see the first table below, in numerical data form. This particular data set is from IBEX Release 10 which includes observation from the first seven years, 2009-2015, of the IBEX mission. Details of the data and enabled science from Release 10 are given in the following journal publication: McComas, D.J., et al. (2017), Seven Years of Imaging the Global Heliosphere with IBEX, Astrophys. J. Supp. Ser., 229(2), 41 (32 pp.), http://doi.org/10.3847/1538-4365/aa66d8 The IBEX-Hi band/channel center energies and full width half maximum, FWHM, energy ranges are listed in a table below: +-----------------------------------------------------+ Energy Band Center Energy Energy Range ----------------------------------------------------- Channel 2 ~0.71 keV 0.52 keV to 0.95 keV Channel 3 ~1.11 keV 0.84 keV to 1.55 keV Channel 4 ~1.74 keV 1.36 keV to 2.50 keV Channel 5 ~2.73 keV 1.99 keV to 3.75 keV Channel 6 ~4.29 keV 3.13 keV to 6.00 keV +-----------------------------------------------------+ This particular IBEX-Hi CDF data product was constructed from the original ascii files named using the pattern hvset_tabular_ram_yearN for N=1,7, includes pixel map data from the ram direction, with no corrections, nocg, for the Compton-Getting effect corrections, sp, for ENA survival probability between 1 AU and 100 AU, and a map compilation cadence equal to 1 year. In all, there are 12 IBEX-Hi Release 10 CDF data products resulting from the multiplication of options for two Compton-Getting correction settings by two survival probability settings by three directional settings: antiram, ram, omni. The table below defines how the file naming pattern is constructed for each data product. Note that "ibex_h3_ena_hi_r10" is the file naming pattern root for all twelve of these IBEX-Hi CDF data products. The asterisk symbols in the last column of the table shows the line corresponding to this CDF data product within the expanded file naming pattern schema. +-----------------------------------------------------------------------------------------------------+ C-G Corr. SP Corr. Dir. Acronym Map Cadence File Naming Pattern for 1 yr Skymaps ----------------------------------------------------------------------------------------------------- cg nosp antiram 1 year ibex_h3_ena_hi_r10_cg_nosp_antiram_1yr cg sp antiram 1 year ibex_h3_ena_hi_r10_cg_sp_antiram_1yr nocg nosp antiram 1 year ibex_h3_ena_hi_r10_nocg_nosp_antiram_1yr nocg sp antiram 1 year ibex_h3_ena_hi_r10_nocg_sp_antiram_1yr ----------------------------------------------------------------------------------------------------- cg nosp ram 1 year ibex_h3_ena_hi_r10_cg_nosp_ram_1yr cg sp ram 1 year ibex_h3_ena_hi_r10_cg_sp_ram_1yr nocg nosp ram 1 year ibex_h3_ena_hi_r10_nocg_nosp_ram_1yr nocg sp ram 1 year ibex_h3_ena_hi_r10_nocg_sp_ram_1yr *** ----------------------------------------------------------------------------------------------------- cg nosp omni 6 months ibex_h3_ena_hi_r10_cg_nosp_omni_6mo cg sp omni 6 months ibex_h3_ena_hi_r10_cg_sp_omni_6mo nocg nosp omni 6 months ibex_h3_ena_hi_r10_nocg_nosp_omni_6mo nocg sp omni 6 months ibex_h3_ena_hi_r10_nocg_sp_omni_6mo +-----------------------------------------------------------------------------------------------------+ The first column in the above table shows whether Compton-Getting, C-G, corrections have been applied to the data. C-G corrections account for how ENA measurements are affected by the the orientation of the IBEX spacecraft velocity vector relative to the arrival direction of the ENAs. cg: Compton-Getting corrections applied nocg: Compton-Getting corrections not applied The second column in the above table shows whether Survival Probability, SP, corrections have been applied to the data. SP corrections account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they
IBEX Low Energy Neutral Atom Imager (Lo) Data Release 04, Compton-Getting corrected, Survival Probability corrected, Antiram direction, West Longitude Ecliptic Maps, Level H3 (H3), three year average Data
* 1: The Interstellar Boundary Explorer (IBEX) has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 16 releases of IBEX-HI and/or IBEX-LO data covering 2009-2019.* 2: This data set is from the Release 4 (3-year-average of 6-month-cadence maps) IBEX-Lo map data for the first three years 2009-2012 in the form of antiram-directional ENA (hydrogen) fluxes with Compton-Getting correction (cg) of flux spectra for spacecraft motion and correction for ENA survival probability (sp) between 1 and 100 AU.* 3: The data consist of all-sky maps in Solar Ecliptic Longitude (east and west) and Latitude angles for ENA (hydrogen) fluxes from IBEX-Lo energy bands 1-8 in numerical data form. Energy channels 1-8 have FWHM center-point energies at 0.015, 0.029, 0.055, 0.11, 0.209, 0.439, 0.872, 1.821 keV, respectively. Details of the data and enabled science from Release 10 are given in the following journal publication:* 4: S.A. Fuselier et al., The IBEX-Lo Sensor. Space Sci Rev (2009) 146: 117...147; DOI 10.1007/s11214-009-9495-8* 5: https://link.springer.com/article/10.1007/s11214-009-9495-8* 6. The following codes are used to define dataset types:- cg = Compton-Getting corrections have been applied to the data to account for the speed of the spacecraft relative to the direction of arrival of the ENAs.- nocg = no Compton-Getting corrections- sp = survival probability corrections have been applied to the data to account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they stream through the heliosphere. This correction scales the data out from IBEX at 1 AU to ~100 AU. In the original data this mode is denoted as Tabular.- noSP - no survival probability corrections have been applied to the data.- omni = data from all directions.- ram = data was collected when the spacecraft was ramming into the incoming ENAs.- antiram = data was collected when the spacecraft was moving away from the incoming ENAs.* 7. The following list associates Release 10 map numbers (1-14) with mission year (1-7), orbits (11-310b), and dates (12/25/2008-12/23/2015):- Map 1: Map2009A, year 1, orbits 11-34, dates 12/25/2008-06/25/2009- Map 2: Map2009B, year 1, orbits 35-58, dates 06/25/2009-12/25/2009- Map 3: Map2010A, year 2, orbits 59-82, dates 12/25/2009-06/26/2010- Map 4: Map2010B, year 2, orbits 83-106, dates 06/26/2010-12/26/2010- Map 5: Map2011A, year 3, orbits 107-130a, dates 12/26/2010-06/25/2011- Map 6: Map2011B, year 3, orbits 130b-150a, dates 06/25/2011-12/24/2011- Map 7: Map2012A, year 4, orbits 150b-170a, dates 12/24/2011-06/22/2012- Map 8: Map2012B, year 4, orbits 170b-190b, dates 06/22/2012-12/26/2012- Map 9: Map2013A, year 5, orbits 191a-210b, dates 12/26/2012-06/26/2013- Map 10: Map2013B, year 5, orbits 211a-230b, dates 06/26/2013-12/26/2013- Map 11: Map2014A, year 6, orbits 231a-250b, dates 12/26/2013-06/26/2014- Map 12: Map2014B, year 6, orbits 251a-270b, dates 06/26/2014-12/24/2014- Map 13: Map2015A, year 7, orbits 271a-290b, dates 12/24/2014-06/24/2015- Map 14: Map2015B, year 7, orbits 291a-310b, dates 06/24/2015-12/23/2015* 8: The energy resolution is delta-E/E = 0.8 for all channels:Energy channel 1: center energy = 0.015 keVEnergy channel 2: center energy = 0.029 keVEnergy channel 3: center energy = 0.055 keVEnergy channel 4: center energy = 0.11 keVEnergy channel 5: center energy = 0.209 keVEnergy channel 6: center energy = 0.439 keVEnergy channel 7: center energy = 0.872 keVEnergy channel 8: center energy = 1.821 keV* 9: This particular data set, denoted in the original ascii files in the map_wake folder, includes pixel map data from antiram direction (antiram-directional), CG, SP, 3 year cadence.
IBEX High Energy Neutral Atom Imager (Hi) Data Release 04, not Compton-Getting corrected, not Survival Probability corrected, Omnidirectional, West Longitude Ecliptic Maps, Level H3 (H3), three year average Data
* 1: The Interstellar Boundary Explorer (IBEX) has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 14 releases of IBEX-HI and/or IBEX-LO data covering 2009-2011.* 2: This data set is from the Release 4 (3 year-cadence) IBEX-Hi map data for the years 2009-2011 in the form of omnidirectional ENA (hydrogen) fluxes with no Compton-Getting correction (nocg) of flux spectra for spacecraft motion and no correction for ENA survival probability (nosp) between 1 and 100 AU.* 3. The data consist of all-sky maps in Solar Ecliptic Longitude (east and west) and Latitude angles for ENA (hydrogen) fluxes from IBEX-Hi energy bands 2-6 in numerical data form. Energy channels 2-6 have FWHM ranges of 0.52-0.95, 0.84-1.55, 1.36-2.50, 1.99-3.75, 3.13-6.00 keV, respectively. The corresponding center-point energies are 0.71, 1.11, 1.74, 2.73, and 4.29 keV. Details of the data and enabled science from Release 10 are given in the following journal publication:* 4: McComas, D. J., et al. (2017), Seven Years of Imaging the Global Heliosphere with IBEX, Astrophys. J. Supp. Ser., 229(2), 41 (32 pp.),* 5: http://doi.org/10.3847/1538-4365/aa66d8* 6. The following codes are used to define dataset types:- cg = Compton-Getting corrections have been applied to the data to account for the speed of the spacecraft relative to the direction of arrival of the ENAs.- nocg = no Compton-Getting corrections- sp = survival probability corrections have been applied to the data to account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they stream through the heliosphere. This correction scales the data out from IBEX at 1 AU to ~100 AU. In the original data this mode is denoted as Tabular.- noSP - no survival probability corrections have been applied to the data.- omni = data from all directions.- ram = data was collected when the spacecraft was ramming into the incoming ENAs.- antiram = data was collected when the spacecraft was moving away from the incoming ENAs.* 7. The following list associates Release 4 map numbers (1-6) with mission year (1-3) each year is associated with two consecutive maps:- Map 1: Map2009A, year 1, orbits 11-34, dates 12/25/2008-06/25/2009- Map 2: Map2009B, year 1, orbits 35-58, dates 06/25/2009-12/25/2009- Map 3: Map2010A, year 2, orbits 59-82, dates 12/25/2009-06/26/2010- Map 4: Map2010B, year 2, orbits 83-106, dates 06/26/2010-12/26/2010- Map 5: Map2011A, year 3, orbits 107-130a, dates 12/26/2010-06/25/2011- Map 6: Map2011B, year 3, orbits 130b-150a, dates 06/25/2011-12/24/2011* 8: This particular data set, denoted in the original ascii files as comb-year123, includes pixel map data from all directions (omnidirectional), noCG, noSP, 3 year cadence.
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