Find research datasets worth reusing

opencc-by-4.0May 2020View details →

Empirical relationship between calcium triplet equivalent widths and [Fe/H] using Gaia photometry

I present a new empirical relationship for red giant branch stars between the overall metallicity of the star and the sum of equivalent widths of the near-infrared calcium triplet (CaT) spectral lines. This method takes advantage of the all-sky photometry and astrometry of the Gaia mission, and the archival spectra from 2050 red giant branch stars from 18 globular clusters (-0.69>[Fe/H]>-2.44) acquired with the Anglo-Australian Telescope's AAOmega spectrograph. <ul> <li><cluster_name>.tar.gz <ul> <li>Raw and reduced spectra for 18 globular clusters (NGC104, NGC6752, NGC6809, NGC288, NGC7099, NGC362, NGC6218, NGC4590, IC4499, NGC1904, ESO452-SC06, ESO280-SC12, NGC1851, NGC6624, NGC2298, Pal 5, NGC5024, Terzan 8, NGC5053)</li> <li>Lists of likely members</li> <li>Measured equivalent widths and radial velocities</li> </ul> </li> <li>code.tar.gz <ul> <li>running.py – calculates the equivalent widths and radial velocities of the stars from the spectra</li> <li>cat_new_params.py – calculates the best fitting empirical relationship</li> </ul> </li> <li>paper.tar.gz <ul> <li>The LaTeX source for the submitted RNAAS paper.</li> </ul> </li> </ul>

opencc-by-4.0Apr 2024View details →

Reward perseveration is shaped by GABAA-mediated dopamine pauses: Fiber Photometry Data

Fiber photometry data. These data were used to generate the following figures in the paper "Reward perseveration is shaped by GABAA-mediated dopamine pauses": <ul> <li>Figure 3, all panels</li> <li>Ext. Fig 4, all panels</li> </ul> Specifics of the data: <ul> <li>FiberPho_Cohort_*.zip files contain all of the raw fiber photometry and behavior data for each mouse, grouped by cohort.</li> <li>FiberPho_Histo_Cohort_*.zip files contain the histological images and ROIs for each mouse, grouped by cohort. </li> <li>HTP_grouped_data.zip contains the grouped analysis fiber photometry and behavior MATLAB files for the experimental group.</li> <li>ddHTP_grouped_data.zip contains the grouped analysis fiber photometry and behavior MATLAB files for the control group.</li> <li>The various .csv files contain the summarized mouse, cohort, and analysis details and data.</li> </ul>

opencc-by-4.0Jun 2022View details →

Gaia Catalogue of Synthetic Photometry - White Dwarfs (GCSP-WD)

GSPC-WD catalogue  This catalogue contains objects described in detail in Gaia Collaboration, Montegriffo et al., 2022, A&A, in press. The description of the catalogue from the paper is given below. We have made the GSPC-WD synthetic photometry available as a stand-alone catalogue27, including SDSS, JKC and JPLUS XPSP and the DA classification probability. The photometry of the individual J-PAS bands, used in the random forest analysis, is not included due to their low signal-to-noise. For WDs classified in SDSS, a subset of which were used in the training/validation of the random forest algorithim, we also include the full SDSS classifications as a separate column in the GSPC-WD catalogue table. When the synthetic spectral bands are very narrow a significant number of sources will have low signal-to-noise. Furthermore, at the edges of the Gaia spectral range, away from the peak of the effective area, this is also true for some stars in the wider bands included in the catalogue. In some extreme cases, there is no significant detection of the object. The random forest algorithm is only able to classify a WD when valid flux measurements are available for every photometric band we include in the analysis. Therefore, no classification is recorded in the catalogue when data for one or more bands is "missing". In total 15,003 WDs from the total sample of 101,783 are not classified. For completeness, we have made all the flux measurements and corresponding magnitudes available for all objects in the GSPC-WD. Hence magnitude/fluxes with very large errors, up to several times the flux itself, are included. However, where fluxes are negative, the magnitudes are not defined. When using the catalogue, appropriate signal-to-noise cuts are advisable for the specific work in-hand, to ensure data quality. Total number of objects = 101,786; Format 1 object per row, 73 columns of data as listed below. Column  Description of contents 1    Gaia source_id 2    ra 3    ra_error 4    dec 5    dec_error 6    JohnsonStd_mag_U 7    JohnsonStd_mag_B 8    JohnsonStd_mag_V 9    JohnsonStd_mag_R 10    JohnsonStd_mag_I 11    JohnsonStd_flux_U 12    JohnsonStd_flux_B 13    JohnsonStd_flux_V 14    JohnsonStd_flux_R 15    JohnsonStd_flux_I 16    JohnsonStd_flux_error_U 17    JohnsonStd_flux_error_B 18    JohnsonStd_flux_error_V 19    JohnsonStd_flux_error_R 20    JohnsonStd_flux_error_I 21    SdssStd_mag_u 22    SdssStd_mag_g 23    SdssStd_mag_r 24    SdssStd_mag_i 25    SdssStd_mag_z 26    SdssStd_flux_u 27    SdssStd_flux_g 28    SdssStd_flux_r 29    SdssStd_flux_i 30    SdssStd_flux_z 31    SdssStd_flux_error_u 32    SdssStd_flux_error_g 33    SdssStd_flux_error_r 34    SdssStd_flux_error_i 35    SdssStd_flux_error_z 36    Jplus_mag_uJAVA 37    Jplus_mag_J0378 38    Jplus_mag_J0395 39    Jplus_mag_J0410 40    Jplus_mag_J0430 41    Jplus_mag_gJPLUS 42    Jplus_mag_J0515 43    Jplus_mag_rJPLUS 44    Jplus_mag_J0660 45    Jplus_mag_iJPLUS 46    Jplus_mag_J0861 47    Jplus_mag_zJPLUS 48    Jplus_flux_uJAVA 49    Jplus_flux_J0378 50    Jplus_flux_J0395 51    Jplus_flux_J0410 52    Jplus_flux_J0430 53    Jplus_flux_gJPLUS 54    Jplus_flux_J0515 55    Jplus_flux_rJPLUS 56    Jplus_flux_J0660 57    Jplus_flux_iJPLUS 58    Jplus_flux_J0861 59    Jplus_flux_zJPLUS 60    Jplus_flux_error_uJAVA 61    Jplus_flux_error_J0378 62    Jplus_flux_error_J0395 63    Jplus_flux_error_J0410 64    Jplus_flux_error_J0430 65    Jplus_flux_error_gJPLUS 66    Jplus_flux_error_J0515 67    Jplus_flux_error_rJPLUS 68    Jplus_flux_error_J0660 69    Jplus_flux_error_iJPLUS 70    Jplus_flux_error_J0861 71    Jplus_flux_error_zJPLUS 72    probability DA 73    SDSS WD type

opencc-by-4.0Apr 2023View details →

Azcorra2023 - Raw fiber photometry recordings

Raw data from fiber photometry recordings of different subtypes (Vglut2+, Calb1+, Anxa1+ and Aldh1a1+ as well as DAT+) SNc dopamine neurons labelled with GCaMP6f, as used in Azcorra et al. Nat Neuro 2023. Metadata for these recordings (recording location, mouse sex...) can be found in the pre-processed dataset (see below). The code used to pre-processed this data to get DF/F is available on GitHub (<a href="https://github.com/DombeckLab/Azcorra2023/releases/tag/Azcorra2023">https://github.com/DombeckLab/Azcorra2023/releases/tag/Azcorra2023</a>) and Zenodo (DOI: 10.5281/zenodo.7872052, <a href="https://zenodo.org/record/7872052">https://zenodo.org/record/7872052</a>). We have also made the pre-processed data available on Zenodo (DOI: 10.5281/zenodo.7871982, <a href="https://zenodo.org/record/7871982">https://zenodo.org/record/7871982</a>). The code necessary to analyze this data and generate the figures shown in the manuscript is is found in that same GitHub repository as the pre-processing code above.

opencc-by-4.0Jul 2023View details →

Tables for: The Panchromatic Hubble Andromeda Treasury XXI. The Legacy Resolved Stellar Photometry Catalog

This deposit contains the full machine-readable tables for the accepted version of the manuscript, "The Panchromatic Hubble Andromeda Treasury XXI. The Legacy Resolved Stellar Photometry Catalog", submitted and accepted to the Astrophysical Journal Supplments.  The specific files included in this deposit are the full version of Tables 1-3 in this manuscript: <ul> <li>Table 1: Simplified table of PHAT photometry for easy use;</li> <li>Table 2: Simplified table of artificial star test results for easy use;</li> <li>Table 3: Summary of artificial star statistics as a function of brightness and stellar density.</li> </ul> The *.txt files are formatted according to the machine-readable standards adopted by the AAS Journals and CDS/Vizier. Documentation of this format can be found at these links: <ul> <li><a href="https://journals.aas.org/mrt-overview/">AAS Journals MRT overview</a></li> <li><a href="http://vizier.u-strasbg.fr/doc/catstd.htx">CDS/Vizier standards</a></li> </ul> These files can be read in python using the astropy package or with the most recent version of <a href="https://www.star.bris.ac.uk/~mbt/topcat/">TOPCAT</a> (> Version 4.8). An example script for reading these files in astropy is given here: <pre><code class="language-python"> from astropy.table import Table data = Table.read("datafile3.txt", format="ascii.cds") </code></pre> In addition, a headerless, compressed TeX (&-delimited; "full_table.tex.xz") version of Table 1, and a header-only, dataless version of Table 1 ("datafile1_headeronly.txt") are provided to give users additional tools for dealing with this large dataset.  The compression routine was applied using xz <https://tukaani.org/xz/> with the encodings <ul> <li> <code>xz -z -7 -T 0 full_table.tex</code> </li> <li> <code>xz -z -9 -T 0 datafile1.txt</code> </li> </ul> The Table 1 files on Zenodo were then split into smaller chunks to upload them to Zenodo using the GNU <a href="https://www.gnu.org/software/coreutils/manual/html_node/split-invocation.html"><code>split</code></a> routine. The full files can be recovered by recombining them before decompressing them. The list of related commands and the expected md5 hexidecimal checksums are given here: <ul> <li> <code>split --bytes=512M ../full_table.tex.xz full_table.tex.xz.</code> </li> <li> <code>split --bytes=512M ../datafile1.txt.xz datafile1.txt.xz.</code> </li> <li> <code>cat full_table.tex.xz.a* > full_table.tex.xz</code> </li> <li> <code>cat datafile1.txt.xz.a* > datafile1.txt.xz</code> </li> <li> <code>MD5 (full_table.tex.xz) = 7f9195210bec61c08d04926ada4a021a</code> </li> <li> <code>MD5 (datafile1.txt.xz) = 63205fe1051e97f4e04380dd23469893</code> </li> </ul> Finally, those interested in generating their own cuts from the DOLPHOT quality parameters can access the full photometry tables, available at MAST as a High Level Science Product via <a href="https://doi.org/10.17909/T91S30">doi.org/10.17909/T91S30</a>

opencc-by-4.0Feb 2024View details →

The UltracoolSheet: Photometry, Astrometry, Spectroscopy, and Multiplicity for 4000+ Ultracool Dwarfs and Imaged Exoplanets

The UltracoolSheet is a catalog of 4000+ ultracool dwarfs (spectral types M6 and later) and imaged exoplanets, including photometry, absolute astrometry, proper motions, parallaxes, multiplicity, spectroscopic classifications, memberships, and ages. The catalog lives in a Google spreadsheet at       <a href="http://bit.ly/UltracoolSheet">http://bit.ly/UltracoolSheet</a> where it will receive future updates.  The README tab in the spreadsheet contains a detailed description of the contents of the catalog. UltracoolSheet started as a catalog of all spectroscopically confirmed objects of spectral type L0 or later in the extended solar neighborhood (out to ~100 pc) that were known as of April 15, 2015.  It has subsequently been extended to include many late-M dwarfs and also augmented with more recent discoveries spanning all ultracool spectral types. The component spreadsheets of UltracoolSheet are posted here as CSV files, along with summary figures and (.dat) files containing ASCII tables to simplify figure plotting for users. The Summary Plots.pdf file shows the sky map, age distribution, publication dates, and proper motion since publication for all objects in UltracoolSheet, as well as the distribution of projected separations of companions. When using data from the UltracoolSheet, please cite the individual papers from which the data comes. Citations codes are included for all the data in the tables, and the References table translates the citation codes into ADS bibcodes, Papers citekeys, and publication titles. For research that benefits from this compilation, please cite this Zenodo post and include the following acknowledgment: "This work has benefited from The UltracoolSheet at <a href="http://bit.ly/UltracoolSheet">http://bit.ly/UltracoolSheet</a>, maintained by Will Best, Trent Dupuy, Michael Liu, Aniket Sanghi, Rob Siverd, and Zhoujian Zhang, and developed from compilations by <a href="http://adsabs.harvard.edu/abs/2012ApJS..201...19D">Dupuy & Liu (2012)</a>, <a href="http://adsabs.harvard.edu/abs/2013Sci...341.1492D">Dupuy & Kraus (2013)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2014ApJ...792..119D/abstract">Deacon et al. (2014)</a>,  <a href="http://adsabs.harvard.edu/abs/2016ApJ...833...96L">Liu et al. (2016)</a>, <a href="http://adsabs.harvard.edu/abs/2018ApJS..234....1B">Best et al. (2018)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2021AJ....161...42B/abstract">Best et al. (2021)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...959...63S">Sanghi et al. (2023)</a>, and <a href="https://ui.adsabs.harvard.edu/abs/2023AJ....166..103S">Schneider et al. (2023)</a>." The UltracoolSheet itself can be cited by this Zenodo DOI: 10.5281/zenodo.4169084   Questions, comments, suggestions, or contributions? Please send them to <a href="mailto:ultracool.sheet@gmail.com">ultracool.sheet@gmail.com</a> (especially contributions!)

opencc-by-4.0Mar 2024View details →

LRD Photometry and Physical Parameters in Blank JWST Fields (Kokorev+24)

Photometry and physical parameters of little red dots in an array of blank extragalactic fields as presented in <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240109981K/abstract">Kokorev+24.</a>

Data products from "oMEGACat II - Photometry and proper motions for 1.4 million stars in Omega Centauri and its rotation in the plane of the sky"

This repository contains the data products of the publication: <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240403722H/abstract"> Häberle et al (2024): "oMEGACat II - Photometry and proper motions for 1.4 million stars in Omega Centauri and its rotation in the plane of the sky"</a> A detailed description of the data products and their creation is given in the accompanying paper. The data products include: <ul> <li>The astrometric catalog with position and proper motion information for around 1.4 million sources within the half-light radius of Omega Centauri. We provide the catalog in both the .fits and .mrt format.</li> <li>The 7 photometric catalogs (for the 7 different used Hubble Space Telescope filters), both in .fits and .mrt format.</li> <li>The 7 deep, stacked image mosaics (one for each filter) in .fits format</li> <li>In addition, we include an IPython Notebook with basic usage examples for all these files.</li> </ul> Please cite the catalog paper <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240403722H/abstract">Häberle et al. (2024)</a> when using this work. In case of any questions, feel free to contact us using <a href="mailto:haeberle@mpia.de">haeberle@mpia.de</a>

Synthetic JWST NIRCam, Euclid NISP, and Roman WFI Near-Infrared Photometry for 800+ Ultracool Dwarfs

JWST NIRCam, Euclid NISP, and Roman WFI photometry (apparent magnitudes) for 800+ ultracool dwarfs synthesized using near-IR SpeX prism spectra. This is a supplementary data product to <a href="https://iopscience.iop.org/article/10.3847/2515-5172/acf864">Sanghi et al. 2023 (RNAAS, 7, 194)</a> and <a href="https://ui.adsabs.harvard.edu/abs/2024RNAAS...8..137S/abstract">Sanghi et al. 2024 (RNAAS, 8, 137)</a>. JWST photometry is presented in the Vega magnitude system and Euclid and Roman photometry are presented in the AB magnitude system. For research that benefits from this compilation, please cite <a href="https://iopscience.iop.org/article/10.3847/2515-5172/acf864">Sanghi et al. 2023 (RNAAS, 7, 194)</a> for JWST photometry, <a href="https://ui.adsabs.harvard.edu/abs/2024RNAAS...8..137S/abstract">Sanghi et al. 2024 (RNAAS, 8, 137)</a> for Euclid and Roman photometry, and include the following acknowledgment: "This work has benefitted from The UltracoolSheet, maintained by Will Best, Trent Dupuy, Michael Liu, Aniket Sanghi, Rob Siverd, and Zhoujian Zhang, and developed from compilations by <a href="https://ui.adsabs.harvard.edu/abs/2012ApJS..201...19D/abstract">Dupuy & Liu (2012, ApJS, 201, 19)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2013Sci...341.1492D/abstract">Dupuy & Kraus (2013, Science, 341, 1492)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2016ApJ...833...96L/abstract">Liu et al. (2016, ApJ, 833, 96)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2018ApJS..234....1B/abstract">Best et al. (2018, ApJS, 234, 1</a>), <a href="https://ui.adsabs.harvard.edu/abs/2021AJ....161...42B">Best et al. (2021, AJ, 161, 42)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...959...63S/abstract">Sanghi et al. (2023, ApJ, 959, 63)</a>, and <a href="https://ui.adsabs.harvard.edu/abs/2023AJ....166..103S/abstract">Schneider et al. (2023, AJ, 166, 103)</a>." Contact <a href="mailto:asanghi@caltech.edu">asanghi@caltech.edu</a> regarding questions.

Euclid Early Release Observations of Abell 2390 & 2764: NISP-selected photometry and photometric redshift catalogue

Euclid Early Release Observations 'Magnifying Lens' (PI: Atek) Elementary Photometric Catalogues and Photometric Redshifts Version 1.0.0 Authors: J. Weaver (UMass), S. Taamoli (UCR), and H. Atek (IAP) Contact: john.weaver.astro@gmail.com If you use this work, please cite: Survey Paper: Atek et al. 2024 Processing Paper: Cuillandre et al. 2024 Demonstration Paper: Weaver et al. 2024 While photometric redshfits are provided, we caution that they are derived from only four optical-NIR bands and are designed for high-z dropout galaxies. Users may encounter issues at lower redshifts. These files are provided 'as is'. We the authors retain the right to modify the files at any time. Please see the dedicated README file for details.

Data for "Spectro-photometry of Phobos simulants: I. Detectability of hydrated minerals and organic bands"

Data underlying the paper: "Spectro-photometry of Phobos simulants: I. Detectability of hydrated minerals and organic bands". The dataset contains visible, near-infrared, and mid-infrared spectra of various samples, including phyllosilicates, coals, and Phobos simulants. Measurements at different observation geometries are available for the Phobos simulants in the visible and near-infrared.

opencc-by-4.0Jun 2018View details →

Gaia data, Pan-STARRS photometry, and stream selection masks for the region around the GD-1 stream

This file contains: <ul> <li>relevant columns from Gaia DR2</li> <li>Pan-STARRS (PS1) photometry (grizy)</li> <li>de-reddened PS1 photometry (g0, r0, etc.)</li> <li>binary masks to apply to select out stars that pass our proper motion and color-magnitude diagram selection (pm_mask, gi_cmd_mask)</li> <li>a binary mask to apply to select out stars in the stream track defined in <a href="https://arxiv.org/abs/1805.00425">Price-Whelan & Bonaca (2018) </a>(stream_track_mask)</li> <li>GD-1 positional coordinates (phi1, phi2)</li> <li>Proper motions in the GD-1 coordinate system (pm_phi1_cosphi2, pm_phi2)</li> <li>Proper motions in the GD-1 coordinate system, corrected for solar reflex motion (pm_phi1_cosphi2_no_reflex, pm_phi2_no_reflex)</li> </ul> To select out probable members of the GD-1 stream in, e.g., Python, use: <pre><code class="language-python">from astropy.table import Table tbl = Table.read('gd1-with-masks.fits') tbl = tbl[tbl['pm_mask'] & tbl['gi_cmd_mask']]</code></pre> To select out only stars within the stream track identified in <a href="https://arxiv.org/abs/1805.00425">Price-Whelan & Bonaca (2018)</a>, do: <pre><code class="language-python">from astropy.table import Table tbl = Table.read('gd1-with-masks.fits') tbl = tbl[tbl['pm_mask'] & tbl['gi_cmd_mask'] & tbl['stream_track_mask']</code></pre> <pre>  </pre>

opencc-by-4.0Jul 2021View details →

Sonora Bobcat: cloud-free, substellar atmosphere models, spectra, photometry, evolution, and chemistry

OVERVIEW Presented here are models for non-irradiated, substellar mass objects belonging to the Sonora model series, described in Marley et al. (2021). The files presented here are model temperature-pressure structures ("structure"), emergent spectra from the top of the atmosphere ("spectra"), thermal evolution and photometry ("evolution_and_photometry"), and rainout chemical equilibrium tables used to compute the models ("chemistry").  Atmospheric structure and spectra .tar file names specify metallicity [M/H] and carbon-to-oxygen ratio (C/O) relative to solar. For example, "structures+0.0_co1.5<a href="../api/files/2e9ce76a-67fc-4fd6-ae5c-f88f16c610ea/structures%2B0.0_co1.5.tar.gz">.</a>tar.gz" contains the set of radiative-convective equilibrium atmospheric structures for solar metallicity ("+0.0") with C/O=1.5 times the solar abundance. The _co*.* is omitted for solar C/O, or co_1.0. The individual file naming convention is described below. All stated abundances and ratios are relative to Lodders (2010) abundances, see Marley et al. (2021) for details and use caution when referring to other abundance tabulations. This particular set of model atmosphere structures and associated spectra, photometry, and evolution, which we name Sonora Bobcat, are for cloudless objects with 3.25 ≤ log g (cgs) ≤ 5.5 and 200 ≤ Teff ≤ 2400K. Steps in Teff vary from 25K to 1000K and steps in log g are 0.25 or 0.5. Some combinations of model grid parameters include additional values of the gravity.  Models are provided for [M/H] = -0.5, 0.0, and +0.5 and "rainout" chemical equilibrium. A limited set of models with carbon-to-oxygen ratio of 0.5 and 1.5 times solar abundance are also included. For the convenience of having a rectangular table in (Teff, gravity) space, models are calculated in regimes that are not reached by the evolution, such as very high gravity and very low Teff. Refer to the companion evolution tables to identify combinations of Teff and log g outside the bounds covered by the evolution. ATMOSPHERIC STRUCTURE Atmospheric structure and spectra filenames specify Teff and gravity (in mks units) along with [M/H] and (C/O) relative to solar. "co1.5" in version and spectra header nomenclature refers to 1.5 times the solar C/O ratio. _co*.* is generally omitted for 1.0, the solar value. For example, the file t1000g316nc_m-0.5.dat contains the structure of a model with  Teff=1000K, g=316m/s2 (the exact value of the gravity is given in the first line of the file, see below) , [Fe/H]=-0.5, and C/O=1.0 times the solar value.  Temperature structure and spectra files have a one line header giving "Teff, grav(MKS), Y, f_sed, kz_min, [Fe/H], C/O, f_hole". Teff and grav are the effective temperature (K) and gravity (MKS), Y is the He mass fraction. f_sed is a cloud parameterization which is not relevant for these cloudless models and is arbitrarily given as 0.0. Likewise kz_min relates to the atmospheric eddy diffusion coefficient, which is also not relevant for these chemical equilibrium models and is arbitrarily set equal to a placeholder value that is not used in these models. [Fe/H] and C/O are the metallicity and C/O ratios as described above. [Fe/H] is identical to [M/H]. f_hole is another cloud parameter for cloudy models, not relevant to these cloudless models. Columns in the atmosphere structure files describe the atmosphere at discrete levels. Columns give: level index, P(bar), T(K), internally used check parameter, adiabatic temperature gradient (d ln T / d ln P), local temperature gradient (d ln T / d ln P), atmospheric density (g / cm3). EVOLUTION AND PHOTOMETRY Evolution and Photometry tables are described in detail in a README file included in that tar file. Evolution files connect mass, effective temperature, radius, age, gravity, and moment of inertia for these model sets. Each set of model spectra is complemented with tables of fluxes and of absolute magnitudes in a number of photometric systems commonly used in brown dwarf and exoplanet research (MKO, Keck, 2MASS, SDSS, WISE, Spitzer IRAC, etc).  Fluxes and magnitudes for the full set of JWST filters is also included in separate tables.  Magnitudes are computed on the Vega system (using the Vega spectrum of Bohlin & Gilliland 2004) or on the AB system (e.g. for SDSS). SPECTRA The model spectra each contain close to 362000 wavelength points. The resolving power varies with wavelength and ranges from R=6000 to 200000 but is otherwise the same for all spectra. The first line gives the model parameters in the same format as the structure files described above. This is followed by the spectrum Column 1: wavelength in µm Column 2:  Radiation flux Fν = \(4\pi\) x Eddington flux Hν, in erg/cm2/s/Hz (always exercise caution with factors of \(4\pi\) when comparing to the radiation and Eddington flux, e.g., see Section 3.3 of Hubeny & Mihalas, "Theory of Stellar Atmospheres") The spectral fluxes are given at the top of the atmosphere and are strictly monochromatic. The model spectrum provides no information in the wavelength range between two tabulated points. Unless a spectral line or feature is well resolved, interpolation in wavelength is not advised.  For comparison with data, the model spectra need to be convolved and binned to the instrumental resolution and sampling. In our experience, a minimum of 10 wavelength points is necessary to obtain a reasonable average flux over a wavelength interval. This is a rule of thumb and caution is advised, especially when comparing with high resolution data. The flux received at Earth is that given in the table scaled by (R/D)2  where R is the radius of the object (given in the companion evolution tables) and D its distance.  The solar spectra and photometry are the same as those archived at https://zenodo.org/record/1309035#.YOyz4S1h2X0, which did not provide the T(P) profiles available here. CHEMISTRY We also separately include rainout chemical equilibrium tables for these same atmospheric bulk abundances. These chemistry files are described in detail by their own README file. Additional chemistry tables, beyond those used for the models presented here, are also included for completeness. Users interested in the chemical abundances of the structure models must interpolate within the matching chemistry file for the atmospheric species of interest. CREDITS If you use these tables in your research, please cite Marley et al. (2021, Astrophysical Journal, Volume 920, Issue 2, id.85.) 16 Feb 2024: Error corrected in Column 2 heading. Column 2 is the Radiation flux, not the Eddington flux as previously stated. Citation updated.

opencc-by-4.0Jul 2021View details →

Theoretical Models of Ultra-Cool Objects (Brown Dwarfs and Free-Floating Planets) Including Water Latent Heat Effect: Thermal Structure, Spectra, and Photometry

OVERVIEW Data presented here are from the work of Tang et al. (2021), which present a one-dimensional (vertical) atmospheric structure model for ultra-cool objects that includes moist adiabatic convection (water latent heat release effect). Model grids across a range of effective temperatures (350, 300, 250, 200 K), metallicities ([M/H] of 0.0, 0.5, 0.7, 1.5), and gravities (logg of 4.0, 4.5, 4.7, 5.0) that mimic the atmosphere condition of Y-class brown dwarf and Free-Floating Planets. ATMOSPHERIC THERMAL STRUCTURE The pressure-temperature profile are saved under the ./pT_profiles/, which have two folders: <ol> <li>pT_profile_dry_adiabat: for dry adiabatic treatment.</li> <li>pT_profile_moist_adiabat: for moist adiabatic treatment.</li> </ol> File name of each compressed files gives the effective temperature (Teff, in Kelvin), gravity (in MKS), and metallicity (in [M/H]) information as for example: t200g100nc_m0.0.cmp.gz --> Teff of 200K, gravity as 100 m/s2, and [M/H]=0.0. The table formate of the pressure-temperature profile, i.e., the .cmp files, is made to work with the [<a href="https://natashabatalha.github.io/picaso/">PICASO software</a>](https://natashabatalha.github.io/picaso/). Each .cmp file contains <ul> <li>Column 01   (x)                   : atmosphere pressure level</li> <li>Column 02   (pressure)       : atmosphere pressure in bar</li> <li>Column 03   (DEN)              : atmosphere density in cm^{-3}</li> <li>Column 04   (temperature) : atmosphere temperature in kelvin</li> <li>Column 05-14                    : molecule mixing ratios for H2, He, CH4, H2O, NH3, CO, PH3, H2S, N2, CO2</li> <li>Column 15   (MU)               : mean molecular weight in grams/mole</li> </ul> SPECTRA Model spectra are saved under the ./spectra/ with wavelength ranging from 1 to 30 micron. File name of each compressed file gives the effective temperature (Teff, in Kelvin), gravity (in MKS), metallicity (in [M/H]), adiabatic treatment, and the resolving power information as for example: sp_t200_g100_m0.0_dry_R3000.csv.gz --> Teff of 200K, gravity as 100 m/s2, [M/H]=0.0, with dry adiabatic treatment, and R=3000. Each spetrum .cv file contains two columns: <ul> <li>Column 01 wavelength [micron]</li> <li>Column 02 Flux            [W/m2/micron], the spectral fluxes are given at the top of the atmosphere, taken to be 1 Jupiter radius.</li> </ul> PHOTOMETRY Photometry data derived from the spectra at the top of the atmosphere (assuming one Jupiter radius) are given in the syn_photometry.csv. Photometry filters are from the Mauna Kea Observatory (MKO) photometry system, the Wide-field Infrared Survey Explorer (WISE), and the Spitzer Space Telescope. Filter profiles and Vega magnitude zero points are from the [<a href="http://svo2.cab.inta-csic.es/theory/fps/">SVO Filter Profile Service</a>](http://svo2.cab.inta-csic.es/theory/fps/) <ul> <li>Column 01 (gravity)  , gravity in MKS</li> <li>Column 02 (teff)       , effective temperature in Kelvin</li> <li>Column 03 ([M/H])    , metallicity</li> <li>Column 04-12           , photometry magnitude for IRAC36, IRAC45, W1, W2, GiminiM, MKO_J, MKO_H, MKO_K, MKO_Lp all in Vega system.</li> <li>Column 13 (adiabatic), adiabatic treatment; D: dry adiabatic, M: moist adiabatic</li> </ul> CREDITS Please cite Tang et al. (2021, Astrophysical Journal, in press.) [<a href="https://ui.adsabs.harvard.edu/abs/2021arXiv210507000T/abstract">ADS link</a>](https://ui.adsabs.harvard.edu/abs/2021arXiv210507000T/abstract) if you used data here in your research.

opencc-by-4.0Sep 2021View details →

MOBSTER: Identifying Candidate Magnetic O Stars through Rotational Modulation of TESS Photometry

O-type stars display rotational modulation of their photometric brightness due to surface features induced by fossil magnetic fields, and possibly through dynamos driven by subsurface convection. These features introduce wind perturbations that may drive large-scale structures and flows, including magnetospheres and corotating interaction regions. Until recently there has been a lack of high-precision, high-cadence photometry of O stars capable of detecting this variability. The wealth of new observations provided by the Transiting Exoplanet Survey Satellite (TESS) offers an unparalleled opportunity to conduct comprehensive studies of O-star variability at the sub-mmag level. Using the Galactic O-Stars Catalogue (GOSC) we have identified a sample of confirmed Galactic O stars observed by TESS with existing high-resolution spectroscopy from the IACOB and OWN surveys. Frequency analysis of the photometry is preceded by a careful examination of potential blending sources. Existing spectroscopy of each candidate is employed to test the rotational modulation hypothesis. In this presentation we describe the preliminary results of our study and outline plans for future analysis.

opencc-by-4.0Nov 2022View details →

Simultaneous dynamic glucose-enhanced (DGE) MRI and fiber photometry measurements of glucose in the healthy mouse brain

This dataset was acquired for the DGE and fiber photometry study published in NeuroImage ( <a href="https://doi.org/10.1016/j.neuroimage.2022.119762">https://doi.org/10.1016/j.neuroimage.2022.119762</a>). Comprises of three datasets: DGE MRI, fiber photometry and two-photon microscopy.