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14 results for “synthetic spectra”
sunset: A database of synthetic atmospheric-escape transmission spectra for nearly every transiting exoplanet
<div> <div> <p><strong>This sunset version belongs to the A&A paper. The sunset database belonging to the arXiv pre-print can be found as version 1 of this Zenodo repository.</strong></p> <p>This repository contains the sunset database of atmospheric-escape transmission spectra for most currently known transiting exoplanets. This database is described in Linssen et al. (2025). The complete zipped (unzipped) database is ~5GB (~28GB). To prevent a huge download just to access a specific single planet model, we have uploaded sunset in a few different batches. The "zip_dictionary.txt" file lists each planet and which zip batch it is in. </p> <p>For each planet, there are three files:<br>- The "info" file contains warnings that pertain to that planet specifically (for general warnings that apply to each planet, see Linssen et al. 2025). It also lists the used planetary parameters, and the transit depth, equivalent width, S/N prefactors and transmission spectroscopy metrics for a few spectral lines. Finally, it gives simple step-by-step instructions on how to reproduce the model results using sunbather.<br>- The "spectrum_sparse" file contains the transmission spectrum. In principle, the spectrum runs from 911 to 11,000 angstroms in 1,000,000 bins (translating to R~400,000). However, in large portions of this wavelength grid, there are no spectral lines and the transit spectrum is simply equal to the continuum. To keep the file size to a minimum, we have removed those continuum regions from the spectrum, resulting in a "sparse" spectrum.<br>- The "structure" file contains the radial atmospheric structure profiles of the density, velocity, temperature and mean molecular weight.</p> <p>Additionally, this repository includes "included_lines_by_species.txt" and "included_lines_by_wavelength.txt", which list all the spectral lines that are present in the transmission spectra. Lines are labeled by the specific ion that they originate from, as well as the energy level. The energy level is expressed as a number, where 1 is the ground state, 2 is the first excited state, etc. Translating this energy level into the atomic configuration can be done by looking in the sunbather source code: in the /sunbather/src/sunbather/RT_tables/ folder, each ion has a file such as "Fe+_levels_processed.txt", which lists the energy levels and their atomic configurations.</p> <p>Finally, there is a large tabular file called "sunset_overview.csv". This file includes the NASA Exoplanet Archive parameters of each exoplanet. Additionally, there are some columns that we added, with calculated variables such as the atmospheric mass-loss rate, the Parker wind temperature, and line depths, equivalent widths, S/N prefactors and TSM metrics for various spectral lines. See the file header for explanation of each column. The file can easily be read in Python using pandas.read_csv("sunset_overview.csv", comments="#")</p> </div> </div>
Continuum Normalized MARCS synthetic spectra (DR16)
<p>Continuum Normalized MARCS synthetic spectra (<a href="https://data.sdss.org/sas/dr16/apogee/spectro/speclib/synth/turbospec/marcs/solarisotopes/" target="_blank" rel="noopener">DR16 MARCS</a>) following the procedure described in Appendix A1 of the research article <strong>tonalli: an asexual genetic code to characterize APOGEE-2 stellar spectra. I. Validation with synthetic and solar spectra.</strong></p>
Synthetic mutational spectra with mixed and correlated mutational signatures SBS1 and SBS5
<p>Experience suggests that it harder to extract mutational signatures that always co-occur and that generate correlated numbers of mutations. Here we provide 12 data sets, each consisting of 500 synthetic mutational spectra with varying degrees of mixture and correlation between two mutational signatures. The signatures studied were SBS1, a "clock-like" signature due to deamination of 5-methyl cytosine that consists primarily of mutations from CG > TG, and SBS5, a relatively flat "clock-like" signature. By "clock-like" we mean that the numbers of mutations attributable to these signatures increase with patients' ages. The 12 data sets varied in two dimensions: (i) average ratio of the number of SBS1 to the number of SBS5 mutations in spectra in the data set and (ii) correlation between the number of SBS1 and the number of SBS5 mutations in spectra in the data set. The mutational signatures SBS1 and SBS5 are described at https://doi.org/10.7303/syn12025148 and https://doi.org/10.1101/322859. </p>
Synthetic urban gamma-ray spectra for training spectral detection and identification models
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Raw MPIA/1DNLTE Synthetic Spectra
<p>This dataset comprises the raw high-resolution MPIA/1DNLTE synthetic spectra (using MAFAGS-OS model atmospheres), created with the online tool nlte.mpia.de/, for the purpose of predicting parameters for Gaia-ESO Survey FLAMES-UVES spectra. The NLTE corrections were made for H, O, Mg, Si, Ca, Ti, Cr, Mn, Fe, and Co. The wavelength range is 4830-5400A, and the parameter range is as follows:</p> <ul> <li>4600K ≤ <strong>T<sub>eff</sub></strong> ≤ 8800K, step size 200K</li> <li>1.0 ≤ <strong>log<em>g</em></strong> ≤ 5.0, step size 0.2 dex</li> <li>-4.8 ≤ <strong>[Fe/H]</strong> ≤ 0.9, step size 0.3 dex</li> <li>-0.25 ≤ <strong>[α/Fe]</strong> ≤ 0.5, step size 0.25 dex (α elements considered<strong>: </strong>O, Ne, Mg, Si, S, Ar, Ca, and T)</li> <li>1 km/s ≤ <strong>v<sub>micro</sub></strong> ≤ 2 km/s, step size 1 km/s</li> </ul> <p> </p> <p> </p>
Synthetic Pelagic Biomass Size Spectra of the Tropical and Subtropical Atlantic - biovolume and carbon biomass data
<p>Synthetic Pelagic Biomass Size Spectra of the Tropical and Subtropical Atlantic</p> <p>Normalized size spectra data are presented for (a) biovolume and (b) for carbon contents for the following ecosystem components: Phytoplankton, zooplankton and micronekton</p> <p>Dataset Biovolume_NBSS contains the following variables, three heading lines</p> <table> <tbody> <tr> <td> <p>COLUMN</p> </td> <td> <p>HEADER</p> </td> <td> <p>DESCRIPTION</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>ConsecutiveNumber</p> </td> <td> <p>Control number</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>Cruise</p> </td> <td> <p>Cruise name</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>Reference</p> </td> <td> <p>Cruise/data record reference</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>CruiseID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>StationID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>Net_index</p> </td> <td> <p>ID, opt.</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>Date</p> </td> <td> <p>YYYY-MM-DD</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>Longitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>9</p> </td> <td> <p>Latitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>10</p> </td> <td> <p>Target organisms</p> </td> <td> <p>Phytoplankton</p> <p>Zooplankton</p> <p>Detritus + zooplankton (only for UVP)</p> <p>Mesopelagic fishes</p> <p>invMicronekton – invertebrate micronekton only</p> <p>totMicronekton – mesopelagic fishes + invertebrate Micronekton</p> </td> </tr> <tr> <td> <p>11</p> </td> <td> <p>Gear</p> </td> <td> <p>Gear applied</p> </td> </tr> <tr> <td> <p>12</p> </td> <td> <p>Operation mode</p> </td> <td> <p>Gear operation mode</p> </td> </tr> <tr> <td> <p>13</p> </td> <td> <p>Catching Depth max [m]</p> </td> <td> <p>Catching depth maximum</p> </td> </tr> <tr> <td> <p>14</p> </td> <td> <p>Catching Depth min [m]</p> </td> <td> <p>Catching depth minimum</p> </td> </tr> <tr> <td> <p>15</p> </td> <td> <p>Biomass determination</p> </td> <td> <p>Biomass Determination method</p> </td> </tr> <tr> <td> <p>16</p> </td> <td> <p>Contact Person</p> </td> <td> <p>Contact person</p> </td> </tr> <tr> <td> <p>17</p> </td> <td> <p>Day/night</p> </td> <td> <p>Sampling time</p> </td> </tr> <tr> <td> <p>18</p> </td> <td> <p>Region</p> </td> <td> <p>Region affiliation</p> </td> </tr> <tr> <td> <p>19-74</p> </td> <td>mm3 m-3 mm-3</td> <td> <p>Biovolume data normalized, additionally with reference to "Size class interval (mm-mm]" and "log mm3/individual"</p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p>Dataset Carbon_NBSS contains the following variables, three heading lines</p> <table> <tbody> <tr> <td> <p>COLUMN</p> </td> <td> <p>HEADER</p> </td> <td> <p>DESCRIPTION</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>ConsecutiveNumber</p> </td> <td> <p>Control number</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>Cruise</p> </td> <td> <p>Cruise name</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>Reference</p> </td> <td> <p>Cruise/data record reference</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>CruiseID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>StationID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>Net_index</p> </td> <td> <p>ID, opt.</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>Date</p> </td> <td> <p>YYYY-MM-DD</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>Longitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>9</p> </td> <td> <p>Latitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>10</p> </td> <td> <p>target organisms</p> </td> <td> <p>Phytoplankton</p> <p>Zooplankton</p> <p>Mesopelagic fishes</p> <p>invMicronekton – invertebrate micronekton only</p> <p>totMicronekton – mesopelagic fishes + invertebrate Micronekton</p> </td> </tr> <tr> <td> <p>11</p> </td> <td> <p>Gear</p> </td> <td> <p>Gear applied</p> </td> </tr> <tr> <td> <p>12</p> </td> <td> <p>Operation mode</p> </td> <td> <p>Gear operation mode</p> </td> </tr> <tr> <td> <p>13</p> </td> <td> <p>Catching Depth max [m]</p> </td> <td> <p>Catching depth maximum</p> </td> </tr> <tr> <td> <p>14</p> </td> <td> <p>Catching Depth min [m]</p> </td> <td> <p>Catching depth minimum</p> </td> </tr> <tr> <td> <p>15</p> </td> <td> <p>Biomass determination</p> </td> <td> <p>Biomass Determination method</p> </td> </tr> <tr> <td> <p>16</p> </td> <td> <p>Contact Person</p> </td> <td> <p>Contact person</p> </td> </tr> <tr> <td> <p>17</p> </td> <td> <p>filtered volume [m3]</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>18</p> </td> <td> <p>Day/night</p> </td> <td> <p>Sampling time</p> </td> </tr> <tr> <td> <p>19</p> </td> <td> <p>SST (C)</p> </td> <td> <p>In situ SST</p> </td> </tr> <tr> <td> <p>20</p> </td> <td> <p>Temperature (C)</p> </td> <td> <p>In situ temperature</p> </td> </tr> <tr> <td> <p>21</p> </td> <td> <p>Salinity</p> </td> <td> <p>In situ salinity (PSU)</p> </td> </tr> <tr> <td> <p>22</p> </td> <td> <p>Oxygen (umol/kg)</p> </td> <td> <p>In situ oxygen (µmol/kg)</p> </td> </tr> <tr> <td> <p>23</p> </td> <td> <p>Region</p> </td> <td> <p>Region affiliation</p> </td> </tr> <tr> <td> <p>24-79</p> </td> <td>gC m-3 g-1C</td> <td> <p>Carbon biomass data normalized, additionally with reference to " Size class number" and "</p> <p>Exponent"</p> </td> </tr> </tbody> </table> <p> </p>
Synthetic ground motions to support the Fennoscandian GMPEs. Supporting information – Response spectra dataset in excel format
<p>This dataset has been created in the NKS project: ”Synthetic ground motions to support the Fennoscandian GMPEs”, contract: NKS-R(18)126/5. The data is RotD50 (Boore, 2010, doi: <a href="https://doi.org/10.1785/0120090400">10.1785/0120090400</a>), pseudo-acceleration response spectra calculated from synthetic ground motions generated using physics-based modeling of Fennoscandian earthquakes. The earthquake magnitude range is 4.3-5.6; the rupture distance range 2-30km and the hypocenter depth range 2-20km. The response spectra is in mm/s2 and should be used up to 25Hz.</p> <p>Cite the data as part of the research report: Fülöp, L., Jussila, V., Fälth, B., Voss, P., Lund, B. 2019. Synthetic ground motions to support the Fennoscandian GMPEs. NKS - Nordic Nuclear Safety Research NKS-424, ISBN: ISBN 978-87-7893-514-4</p> <p>Methods used to generate the data are described in:</p> <p>Fülöp, L., Jussila, V., Lund, B., Fälth, B., Voss, P., Puttonen, J., Saari, J., and Heikkinen, P. 2017. Modelling as a Tool to Augment Ground Motion Data in Regions of Diffuse Seismicity – Final report. NKS - Nordic Nuclear Safety Research NKS-394, ISBN: 978-87-7893-482-6</p> <p>Fülöp, L., Jussila, V., Lund, B., Fälth, B., Voss, P., Puttonen, J., Saari, J., 2016. Modelling as a tool to augment ground motion data in regions of diffuse seismicity - Progress 2015. NKS Nordic Nuclear Safety Research, ISBN: 978-87-7893-448-2</p>
A database of synthetic inelastic neutron scattering spectra from molecules and crystals
<p>This database contains simulated inelastic neutron scattering (INS) spectra for 10,000+ inorganic crystals and 20,000+ organic molecules. The INS database for inorganic crystals is based on the phonon database at Kyoto University by Atsushi Togo (http://phonondb.mtl.kyoto-u.ac.jp/). The INS database for organic molecules is based on the QM8 dataset (http://quantum-machine.org/datasets/).</p> <p>Entry lists can be found in crystals.dat and molecules.dat. After unzipping the tar.gz files, data for each structure model can be found in a subfolder. </p> <p>For the inorganic crystal database, each subfolder contains five files: a structure.cif file for the crystal structure, a vis_inc_0K.csv file containing the simulated VISION/TOSCA spectra, a powder_2Dmesh_coh_0K.csv file containing the simulated powder S(Q,E), a vis_nwdos.csv file containing the neutron weighted PDOS, a vis_dos.csv file containing the true PDOS, and a gamma_modes.xyz file containing the displacements of gamma point phonons for visualization (with Jmol, http://jmol.sourceforge.net/).</p> <p>For the QM8 molecular database, there are five files in each subfolder: an INFO-* file containing the SMILES string as well as the IUPAC name (if available) for this molecule, a *.com file containing the input for Gaussian simulation (which also contains the atomic coordinates), a *vis_inc_0K.csv file containing the simulated INS spectra, a *.xyz file containing the atomic displacement of each vibrational modes (can be visualized with Jmol), and a *modes.csv file containing the calculated INS intensity for each normal mode. </p> <p>A python script (plot_ins.py) to plot the INS data files is provided<br> Usage: plot_ins.py *.csv {-s [1,2] -x [0:100] -y [0:100] -z [0:2.5]}<br> -s : spectrum index, -x/y/z : range to plot </p> <p><br> The manual for the OCLIMAX software used for INS simulations is also provided for reference.</p>
Synthetic and measured emission spectra for testing and validation of MEC-BP
<p>The data contain synthetic and measured (spark discharge) emission spectra in order to test and validate the results of the so called multi-element combinatory Boltzmann plot method. This is an OES-based approach to deduce the number concentration ratio of two elements present in a spark discharge plasma employed for binary NP generation in the gas phase. It is aimed to provide a tool for investigating the evolution of the concentration ratio corresponding to the ablated electrode materials in spark-based NP generators under real operational conditions. The method is based on the construction of a Boltzmann plot for the spectral line intensity ratios at every combination. The produced plots (the so-called multi-element combinatory Boltzmann plots, MEC-BPs) are directly related to the LTE plasma temperature and the number concentration ratio of the neutral atoms. The total concentration ratio – including ions – is calculated from a simple plasma model, without requiring further measurements.</p> <p>The python project in which the method is implemented can be found here: https://pypi.org/project/spark-mec-bp/0.1.0/</p>
uFTIR test spectra for known synthetic and natural materials
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[Dataset and Software] Altitude-dependent plasma parameter variations of synthetic EISCAT UHF and VHF incoherent scatter spectra calculated from TIE-GCM results
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Spectra and light curves presented in Double detonations: variations in Type Ia supernovae due to different core and He shell masses – II. Synthetic observables
<p>Dataset containing simulated spectra and light curves presented in the paper "Double detonations: variations in Type Ia supernovae due to different core and He shell masses – II. Synthetic observables" (<a href="https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.5289C/abstract">ADS</a>).</p> <p> </p>
Grid of 3D NLTE synthetic spectra for the Na I lines in FGK-type dwarf stars.
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WP2: Synthetic XUV spectra
<p>Set of XUV (0.01 - 10 keV) spectra, computed from parameterized plasma Emission Measure Distributions vs. temperature, for stars with different activity levels and plasma metallicities. Read the Introduction for more details. These spectra are intended as input for models of photochemistry and photoevaporation of exoplanetary atmospheres.</p>
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