Find research datasets worth reusing

opencc-by-4.0Oct 2023View details →

Reproduction package for "A strong H− opacity signal in the near-infrared emission spectrum of the ultra-hot Jupiter KELT-9b"

This is a basic reproduction package for the paper "A strong H− opacity signalin the near-infrared emission spectrum of the ultra-hot Jupiter KELT-9b"by [Jacobs, B.; Désert, J. -M.; Pino, L. et al. (2022)](https://doi.org/10.1051/0004-6361/202244533). Abstract:We present the analysis of a spectroscopic secondary eclipse of the hottest transiting exoplanet detected to date, KELT-9b, obtained with the Wide Field Camera 3 aboard the Hubble Space Telescope. We complement these data with literature information on stellar pulsations and Spitzer/Infrared Array Camera and Transiting Exoplanet Survey Satellite eclipse depths of this target to obtain a broadband thermal emission spectrum. Our extracted spectrum exhibits a clear turnoff at 1.4 μm. This points to H− bound-free opacities shaping the spectrum. To interpret the spectrum, we perform grid retrievals of self-consistent 1D equilibrium chemistry forward models, varying the composition and energy budget. The model with solar metallicity and C/O ratio provides a poor fit because the H− signal is stronger than expected, requiring an excess of electrons. This pushes our retrievals toward high atmospheric metallicities ([M/H] = 1.98−0.21+0.19) and a C/O ratio that is subsolar by 2.4σ. We question the viability of forming such a high-metallicity planet, and therefore provide other scenarios to increase the electron density in this atmosphere. We also look at an alternative model in which we quench TiO and VO. This fit results in an atmosphere with a slightly subsolar metallicity and subsolar C/O ratio ([M/H] = −0.22−0.13+0.17, log (C/O) = −0.34−0.34+0.19). However, the required TiO abundances are disputed by recent high-resolution measurements of the same planet.

opencc-by-4.0Apr 2020View details →

Resampled Opacity Database for PICASO

Wavelength range of the opacities go from 0.3-15 microns. Opacities are resampled to R=15,000 from an original R=1e6 line by line calculation performed by Richard Freedman, Ehsan Gharib-Nezhad, and Roxana Lupu. This does not mean that these opacities are suitable for data at R=15k!!!! Instead, resampled opacities have to be convolved to data that are at a resolution of to 100x less than the original data. <a href="https://natashabatalha.github.io/picaso/notebooks/10_ResamplingOpacities.html">This tutorial shows the effects of under-sampling opacities. </a> TLDR: In general, this opacity dataset are suitable for data that is no higher than R=3000, if using the 60k database and R=100 if using the 20k database. It is not suitable for high resolution cross correlation studies.   Want higher sampling? Download version 2: <a href="https://zenodo.org/records/6928501">https://zenodo.org/record/3759675#.YuN4E-zMLvU</a>  Difference between this and V1? Addition of SO2, and updated CH4 (HITEMP as described in Mukherjee et al. 2024 https://ui.adsabs.harvard.edu/abs/2024ApJ...963...73M/abstract )  Using PICASO to download data PICASO get_data function can help you make sense of all of these files: https://natashabatalha.github.io/picaso/installation.html#autodownloads  "But my data is less then R=3000, is it possible to get a lower sampling?" Yes! <pre><code>import picaso.justdoit as jdi #will get everything as is opa = jdi.opannection(filename_db = "all_opacities_0.6_6_R60000.db") #will compute spectra for only a subset of wavelength opa = jdi.opannection(filename_db = "all_opacities_0.6_6_R60000.db", wave_ranage=[0.6,1]) #will compute spectra for a smaller resolution sampling opa = jdi.opannection(filename_db = "all_opacities_0.6_6_R60000.db", resample=2) #resample =2 decreases the sampling by a factor of 2 (e.g. R=60000 -> R=30000) </code></pre> Using PICASO to Query the data A <a href="https://natashabatalha.github.io/picaso/notebooks/10_QueryOpacities.html">full tutorial on querying the database</a> is available in the PICASO read the docs. Below is a brief example: <pre><code>import picaso.opacity_factory as opa db_filename = 'all_opacities_0.6_6_R60000.db' molecules, pt_pairs = opa.molecular_avail(db_filename) print(molecules) ['AlH', 'C2H2', 'C2H4', 'C2H6', 'CH4', 'CO', 'CO2', 'CaH', 'CrH', 'Cs', 'Fe', 'FeH', 'H2', 'H2O', 'H2S', 'H3+', 'HCN', 'K', 'Li', 'LiCl', 'LiF', 'LiH', 'MgH', 'N2', 'N2O', 'NH3', 'Na', 'O2', 'O3', 'OCS', 'PH3', 'Rb', 'SO2', 'SiO', 'TiH', 'TiO', 'VO'] pt_pairs[0:10] [(1, 1e-06, 75.0), (2, 3e-06, 75.0), (3, 1e-05, 75.0), (4, 3e-05, 75.0), (5, 0.0001, 75.0), (6, 0.0003, 75.0), (7, 0.001, 75.0), (8, 0.003, 75.0), (9, 0.01, 75.0), (10, 0.03, 75.0)]</code></pre> As you can see from the pt_pairs, our grid is computed on a specific pressure-temperature grid that has a total of 1460 points.  NOTE: A full table of references and citations is currently being compiled for publication with the <a href="https://zenodo.org/record/1309035#.XofEzS-ZN3k">Sonora Grid</a> (Marley+2020). PICASO Citation Tools PICASO can help you get out individual citations. If you do not want to look at code: <ul> <li><a href="https://github.com/natashabatalha/picaso/blob/master/reference/references/reference_list.json">you can find bibid's here for each molecule</a></li> <li><a href="https://github.com/natashabatalha/picaso/blob/master/reference/references/references.bib">corresponding PICASO bib file here </a></li> </ul> <a href="https://natashabatalha.github.io/picaso/notebooks/References.html">If you do want to look at code you can check out this tutorial. </a>(code snippet below) <pre><code>import picaso.references as pref refs = pref.References() opa_latex, bibdb = refs.get_opa(molecules=['H2O','CO2']) print(opa_latex) \begin{table*} \centering \begin{tabular}{c|c} H2O & \citet{Polyansky2018H2O} \\ CO2 & \citet{HUANG2014reliable} \\ \end{tabular} \caption{Line lists used to make PICASO Opacities} \label{tab:opas} \end{table*} pref.create_bib(bibdb, 'molecule.bib')#creates bibtex file</code></pre>

opencc-by-4.0Sep 2022View details →

Dataset of "Vertical-Wind-Induced Cloud Opacity Variation in Low Latitudes Simulated by a Venus GCM"

This dataset contains the GrADS data of Venus GCM results used for figures in the paper "Vertical-Wind-Induced Cloud Opacity Variation in Low Latitudes Simulated by a Venus GCM" by H. Karyu et al. (2022).  The file 'dataset_day1' contains the three-dimensional (X: longitude, Y: latitude, Z:altitude (km)) data of temperature (unit: K), zonal wind velocity (unit: m/s), meridional wind velocity (unit: m/s), vertical wind velocity (unit: m/s), geopotential height (unit: m), cloud mass mixing ratio of mode 1, 2, 2', 3 particles, mass mixing ratio of sulfuric acid, air density (unit: kg/m3), cloud mass mixing ratio changing rate of mode 1, 2, 2', 3 particles (unit: 1/s), in snapshots of every 3 hours for the periods of the first Venusian days (117 Earth days). The file 'dataset_day2' contains the same for the second Venusian days. The file 'cloudtau-wc' contains three-dimensional (X: longitude, Y: latitude, Z:altitude (km)) data of column-integrated optical depth (COD) of mode 1, 2, 2' 3 particles and column mass abundance of mode 1, 2, 2' 3 particles (unit: kg/m2), in snapshots of every 3 hours for the periods of 2 Venusian days (234 Earth days). The COD at each altitude corresponds to the integrated value from the top of the atmosphere, and the column mass abundance of each altitude corresponds to the integrated value from the bottom of the atmosphere.  The COD is calculated with the cloud mass mixing ratio stored in the file ‘dataset’ and extinction efficiency shown in the paper. The file 'stf-wc' contains two-dimensional (Y: latitude, Z:altitude (km)) data of mass stream function (unit: kg/s) and residual mass stream function (unit: kg/s), in snapshots of every 3 hours for the periods of 2 Venusian days (234 Earth days). One should refer to Holton (2004) for the definition of the (residual) mass stream function. The files 'dataset_comp' and 'taudataset_comp' are composite mean data of 'dataset' and 'cloudtau-wc', respectively, in snapshots of every 3 hours for the period of 30 days starting from day 86 of the simulation (Earth day). The composite mean is calculated by averaging atmospheric parameters with respect to the frame moving at the rotation period of 7.1-day. The file ‘scripts’ contains FORTRAN scripts and some additional files to derive the atmospheric parameters stored in 'cloudtau-wc’, 'stf-wc’, 'dataset_comp' and ‘taudataset_comp' from the GCM output file ‘dataset’. Please refer to the ‘README.txt’ contained in ‘scripts’ for how to use FORTRAN scripts, required input files and their output. The .tar.xz files can be extracted in Linux with 'tar Jxvf' command, and .grd and .ctl files with the same stem are generated.

opencc-by-4.0Aug 2023View details →

Optical constants of CO and CO2 in the IR ans THz ranges and code to calculate the opacity of icy interstellar grains

Data set of optical constants of CO and CO2 in the IR and THz ranges (0.3–12.0 THz). These data are used to compute the opacity of coated materials in an astrophysical context in our accepted article for publication in A&A, 2022. The following link provides access to the "qabs" open access code and its source to calculate the opacity using the optical constants. The code computes Qabs, Qsca, and Qext from the refractive index or the dielectric constant using Mie's theory: https://bitbucket.org/tgrassi/compute_qabs/src/master/ The link redirects you to an open-access environment where to execute the code properly.

opencc-by-4.0Aug 2023View details →

AESOPUS 2.0: Low-Temperature Opacities with Solid Grains

In this repository we include the optical constants of all dust species listed in Table 1,  as  well as Rosseland mean opacity tables for widely used scaled-solar chemical compositions (GS98, C11, AAG21, MBS22) with  metallicities encompassing the range 0 <= Z <= 0.3, and several  hydrogen abundance values. Additional opacity tables with different grain sizes, porosities, and shapes can be computed and uploaded in the same repository upon user request. All of the details can be found in a companion paper published in The Astrophysical Journal.

opencc-by-4.0Feb 2020View details →

Large 3D Line Sets for Opacity-Based Rendering

Four different large, space-filling 3D line sets used in the paper "A Comparison of Rendering Techniques for 3D Line Sets with Transparency" by Kern et al., 2020" in the context of rendering 3D line sets with transparency. Each line set consists of a myriad of streamlines (10K - 400K trajectories) generated from physical simulations. Note that the data sets were originally used to conduct benchmark tests using different CPU and GPU line rendering algorithms and different transparency settings for each line set.

opencc-by-4.0Mar 2024View details →

MESA model files, scripts, and opacity tables for: 'An Expanded Set of Los Alamos OPLIB Tables in MESA: Type-1 Rosseland-mean Opacities and Solar Models'

MESA model files and plotting scripts, and opacity tables as seen in 'An Expanded Set of Los Alamos OPLIB Tables in MESA: Type-1 Rosseland-mean Opacities and Solar Models'.  <a href="https://iopscience.iop.org/article/10.3847/1538-4357/ad4355" target="_blank" rel="noopener noreferrer">https://iopscience.iop.org/article/10.3847/1538-4357/ad4355</a> Models were run using MESA version r22.11.1, with fixes to the bugs documented at https://docs.mesastar.org/en/release-r24.03.1/known_bugs.html#r22-11-1. We use mesasdk-x86_64-linux-22.6.1.tar.gz  sdk available at http://user.astro.wisc.edu/~townsend/resource/download/mesasdk OPLIB type-1 opacity tables are now available here, in MESA release version r24.08.1+, and at http://aphysics2.lanl.gov/opacity/lanl. The splined tables are on a uniform grid whereas the raw tables are not. The splined tables also replaces nan edge values (at high temperatures) using interpolation. Modify the python spline script if you'd like to spline the opacities onto a different size grid.  *(In future solar modeling work, we recommend users use 'rmid' (cell centered radius in Rsun) instead of 'radius' (cell edge/face radius in Rsun) as all structural variables are typically defined at the cell center. Look into $MESA_DIR/star/defaults/profile_columns.list and ensure you are always consistently using cell centered or cell-faced variables with each other.)*

opencc-by-4.0May 2021View details →

Repacked ExoMol Opacity Line Lists

Repacked ExoMol Opacity Line Lists using the REPACK code (<a href="https://ui.adsabs.harvard.edu/abs/2017ApJ...850...32C">Cubillos 2017, ApJ, 850</a>) Version 3: <ul> <li>Updated C2H4, CH4, NH3, VO line lists.</li> <li>Replaced CO2 Exomol linelist with Ames list.</li> <li>Added H2S, OCS, KOH, SiH4 line lists.</li> </ul> See also part 2 for the PH3 line list: <a href="https://zenodo.org/records/17167393">https://zenodo.org/records/17167393</a>

opencc-by-4.0Apr 2022View details →

Opacities for atoms and molecules relevant to the spectra of hot rocky planets

This dataset contains opacities for atoms and molecules that are relevant to the sector of hot rocky planets, such as magma ocean planets, post-giant impact atmospheres, or planets in ultra-short period orbits. These species can arise above a magma ocean with a composition specific to the continental crust or bulk silicate earth. We do not include opacities for major species that are not specific to hot rocky planet atmospheres, such as water, methane, carbon dioxide, ammonia, etc., as these can be found elsewhere, for example in datasets related to brown dwarf and hot Jupiter atmospheres.  Most of the species included in this dataset can be seen in the attached plot, hot_spectra.pdf, which shows a secondary eclipse model of a lava planet and the contributions of individual species to this spectrum. The references for the line lists used to generate these opacities can be found in the file reference_table.pdf. Each *.zip file contains a set of 1060 opacity layers in ASCII format, each identified with the temperature and pressure it corresponds to. Each layer file contains a header showing the layer number, the temperature (in K), and pressure (in mbar). The data consists of to columns: wavelength in microns and opacity in cm2/molecule. The wavelength grid goes from 0.4 to 50 microns. A list of all the layers calculated for each molecule is given in the file layer_list. Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.

opencc-by-4.0Mar 2019View details →

Dust formation and mass loss around intermediate-mass AGB stars with initial metallicity Zini ≤ 10-4 in the early Universe - I. Effect of surface opacity on stellar evolution and the dust-driven wind

MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017MNRAS.466.1709T">Dust formation and mass loss around intermediate-mass AGB stars with initial metallicity Zini ≤ 10-4 in the early Universe - I. Effect of surface opacity on stellar evolution and the dust-driven wind</a>

Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 4/4

<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118 <h3>Contents</h3> Trajectories of positions and forces  with corresponding input files of systems with 550 water molecules on 2D materials: <ul> <li>MoS2/water</li> <li>MoS2/MoS2/water</li> <li>graphene/MoS2/water</li> <li>MoS2/graphene/water</li> <li>MoS2/hBN/water</li> <li>hBN/MoS2/water</li> <li>graphene/water</li> <li>hBN/water</li> </ul>

Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 3/4

<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118 <h3>Contents</h3> Trajectories of positions and forces  with corresponding input files of systems with 550 water molecules on 2D materials: <ul> <li>graphene/graphene/water</li> <li>hBN/hBN/water</li> <li>graphene/hBN/water</li> <li>hBN/graphene/water</li> </ul>

Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 1/4

<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118 <h3>Contents</h3> Trajectories of positions and forces  with corresponding input files of systems with 120 water molecules confined between 2D materials: <ul> <li>graphene/water/graphene</li> <li>hBN/water/hBN</li> <li>graphene/graphene/water/graphene/graphene</li> <li>hBN/hBN/water/hBN/hBN</li> <li>graphene/hBN/water/hBN/graphene</li> <li>hBN/graphene/water/graphene/hBN</li> </ul>

Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials, part 2/4

<h2>Supplementary data for paper "Slip Opacity and Fast Osmotic Transport of Hydrophobes at Aqueous Interfaces with Two-Dimensional Materials" </h2> Maria Bilichenko, Marcella Iannuzzi, and Gabriele Tocci, ACS Nano, 2024, DOI: 10.1021/acsnano.4c05118 <h3>Contents</h3> Trajectories of positions and forces  with corresponding input files of systems with 120 water molecules confined between 2D materials: <ul> <li>MoS2/water/MoS2</li> <li>MoS2/MoS2/water/MoS2/MoS2</li> <li>graphene/MoS2/water/MoS2/graphene</li> <li>MoS2/graphene/water/graphene/MoS2</li> </ul>

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov36/100

A Registry for Patients With Multifocal Ground Glass Opacities (GGOs)

ClinicalTrials.gov study NCT03802981. IPD Sharing: YES. Countries: 2. Publications: 0.

opencc-by-4.0Dec 2010View details →

Monochromatic opacity data from the Opacity Project (OP) for use with MESA.

Monochromatic opacity data from the Opacity Project (OP) for use with MESA. The OP_mono opacities use data and code from the OP website as modified by Haili Hu. Since the file is large, it is not included in the standard mesa download. If you use these opacities, you should cite Seaton (2005): https://ui.adsabs.harvard.edu/#abs/2005MNRAS.362L…1S

opencc-by-4.0Oct 2024View details →

Radiative Opacities for (Exo)Planet Atmospheres

Radiative opacity data used to explore the existence of stable radiative layers in the molecular hydrogen envelope of Jupiter and Saturn. The opacity data ranges from 1e-1 - 1e5 bar and 100 - 5000K.

opencc-by-4.0May 2022View details →

High resolution opacities for H2/He atmospheres

This set of molecular and atomic opacities has been built based on the same opacity sources used for calculating the correlated-k coefficients in the following repositories: 10.5281/zenodo.5590997 (11 windows) 10.5281/zenodo.5590995 (30 windows) 10.5281/zenodo.5590986 (180 windows) 10.5281/zenodo.5590989 (196 windows) These opacities can be used to generate high resolution spectra for the atmospheric structures computed with the correlated-k coefficients above. The set includes C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The opacities are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list. Each *.zip file contains one opacity file for each pressure-temperature layer, with the species’ name, the pressure, and the temperature given in the filename. The opacity is given in units of cm^2/molecule. For completeness, each *.zip file also contains a file named wavelengths.txt, listing the wavelengths corresponding to each opacity point, in units of microns. All the opacities are calculated on the same wavelength grid.  The references for the line lists used in these opacity calculations can be found in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper.  Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.