DOI: 10.5281/zenodo.6928501
title: Resampled Opacity Database for PICASO

description: Wavelength range of the opacities go from 0.3-15 microns. Opacities are resampled to R=60,000 from an original R=1e6 line by line calculation performed by Richard Freedman, Ehsan Gharib-Nezhad, and Roxana Lupu. <strong>This does not mean that these opacities are suitable for data at R=60k!!!! </strong>Instead, resampled opacities have to be convolved to data that are at a resolution of to 100x less than the original data. This tutorial shows the effects of under-sampling opacities. <br> <br> 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. <strong>File sizes too big? </strong>Please download version 1: https://zenodo.org/record/3759675#.YuN4E-zMLvU <strong>"But my data is less then R=3000, is it possible to get a lower sampling?"</strong><br> Yes! <pre><code class="language-python">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 -&gt; R=30000) </code></pre> <strong>Using PICASO to Query the data</strong> A full tutorial on querying the database is available in the PICASO read the docs. Below is a brief example: <pre><code class="language-python">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. <em><strong>NOTE:</strong> A full table of references and citations is currently being compiled for publication with the Sonora Grid (Marley+2020). </em> <strong>PICASO<em> </em>Citation Tools</strong> PICASO can help you get out individual citations. If you do not want to look at code: you can find bibid's here for each molecule corresponding PICASO bib file here If you do want to look at code you can check out this tutorial. (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>
description: {"references": ["Marley M.~S., Saumon D., Visscher C., Lupu R., Freedman R., Morley C., Fortney J.~J., et al., 2021, ApJ, 920, 85. doi:10.3847/1538-4357/ac141d"]}