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59 results for “JWST”
Data for The UNCOVER Survey: A First-Look HST+JWST Catalog of Galaxy Redshifts and Stellar Populations Properties Spanning 0.2 ≲ z ≲ 15
<p>The recent UNCOVER survey with the James Webb Space Telescope (JWST) exploits the nearby cluster Abell 2744 to create the deepest view of our universe to date by leveraging strong gravitational lensing. In this work, we perform photometric fitting of more than 50,000 robustly detected sources out to z ~ 15. We show the redshift evolution of stellar ages, star formation rates, and rest-frame colors across the full range of 0.2 < z < 15. The galaxy properties are inferred using the Prospector Bayesian inference framework using informative Prospector-beta priors on masses and star formation histories to produce joint redshift and stellar populations posteriors, and additionally lensing magnification is performed on-the-fly to ensure consistency with the scale-dependent priors. We show that this approach produces excellent photometric redshifts with NMAD ~ 0.03, of a similar quality to the established photometric redshift code EAzY. In line with the open-source scientific objective of the Treasury survey, we publicly release the stellar populations catalog with this paper, derived from the photometric catalog adapting aperture sizes based on source profiles. This release includes posterior moments, maximum-likelihood spectra, star-formation histories, and full posterior distributions, offering a rich data set to explore the processes governing galaxy formation and evolution over a parameter space now accessible by JWST.</p>
Products and Models for "Early Release Science of the Exoplanet WASP-39b with JWST NIRCam"
<p>Associated Publication: <a href="https://www.nature.com/articles/s41586-022-05590-4">https://www.nature.com/articles/s41586-022-05590-4</a><br> <br> OVERVIEW: Measuring the metallicity and carbon-to-oxygen (C/O) ratio in exoplanet atmospheres is a fundamental step towards constraining the dominant chemical processes at work and, if in equilibrium, revealing planet formation histories. Transmission spectroscopy<sup> </sup>provides the necessary means by constraining the abundances of oxygen- and carbon-bearing species; however, this requires broad wavelength coverage, moderate spectral resolution, and high precision that, together, are not achievable with previous observatories. Now that JWST has commenced science operations, we are able to observe exoplanets at previously uncharted wavelengths and spectral resolutions. Here we report time-series observations of the transiting exoplanet WASP-39b using JWST’s Near InfraRed Camera (NIRCam). The long-wavelength spectroscopic and short-wavelength photometric light curves span 2.0 – 4.0 µm, exhibit minimal systematics, and reveal well-defined molecular absorption features in the planet’s spectrum. Specifically, we detect gaseous H<sub>2</sub>O in the atmosphere and place an upper limit on the abundance of CH<sub>4</sub>. The otherwise prominent CO<sub>2</sub> feature at 2.8 µm is largely masked by H<sub>2</sub>O. The best-fit chemical equilibrium models favour an atmospheric metallicity of 1–100× solar (i.e., an enrichment of elements heavier than helium relative to the Sun) and a sub-stellar carbon-to-oxygen (C/O) ratio. The inferred high metallicity and low C/O ratio may indicate significant accretion of solid materials during planet formation<sup> </sup>or disequilibrium processes in the upper atmosphere.</p>
Synthetic JWST MIRI-MRS Observations of Mid-IR Noble Gas Emission from T Cha
<p>Synthetic detctor images for the continuum + line emission from [Ne II], [Ne III], [Ar II], [Ar III] for T Cha made with MIRISim (Klaassen et al. 2021) for the overall best fitting model with r_in = 0.1 rG (both with and without a cavity). Also provided are backgrounds for the source observation (applicable to both with and without a cavity) and models for a synthetic standard star and its background. </p> <p>The .fits files are the underlying data cubes for the [Ne II] and [Ar II] lines which were provided as inputs to the simulator. </p> <p>For a full description, see Sellek et al. (2024a).</p>
Data and model for 'JWST transmission spectroscopy of HD 209458b: a super-solar metallicity, a very low C/O, and no evidence of CH4, HCN, or C2H2'
<p>Supplementary materials for https://arxiv.org/abs/2310.03245 </p> <p>include:</p> <p>1. <strong>spectra_final.csv: </strong>transmission spectrum reduced by Eureka! and SPARTA (Figure 6), the best-fit model presented in Figure 1(a).</p> <p>2. <strong>Opacities </strong>used in the retrieval that are compatible with PLATON described in section 3.</p> <p>All opacity numpy pickle files are generated by <code>Python 3.9.7</code> and <code>Numpy 1.24.2</code>.</p> <p> </p> <p>**Bestfit in spectra_final.csv and all opacities are updated on Jan 23, 2024</p> <p>For any additional data requests or questions, please contact: qiaox@uchicago.edu</p>
The data for "Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant"
<p>Data used for "Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant" by Siyang Li, Adam G. Riess, Stefano Casertano, Gagandeep S. Anand, Daniel M. Scolnic, Wenlong Yuan, Louise Breuval, and Caroline D. Huang. Magnitudes provided are after correcting for foreground extinction and crowding bias.</p>
JWST NIRISS/SOSS analysis of HAT-P-18 b with a photospheric model and TACHELES
<ul> <li><strong>photosphere.csv and TACHELES.csv: </strong>Best-fit parameters for the photospheric (Mandel-Agol) and TACHELES fits of the unbinned light curves.</li> <li><strong>*_results.txt and *_spectrum_retrieved.txt: </strong>POSEIDON output files and best-fit spectra for photospheric and TACHELES models for each of the three stellar heterogeneity setups (no spot, single spot, two heterogeneities)</li> <li><strong>*.pdf: </strong>Corner plots for all POSEIDON fits</li> <li><strong>chromspec.csv: </strong>Chromospheric spectrum</li> </ul>
Images and catalogs of HST and JWST images in the SMACS-0723 field
<p>This repository is a first-pass reduction of the HST and JWST images of the SMACS-0723 lensing cluster field. </p> <p>All images have been processed with the <a href="https://github.com/gbrammer/grizli">grizli</a> software pipeline. Further documentation will be provided by Brammer et al. (in prep).</p>
The chemical enrichment in the early Universe as probed by JWST via direct metallicity measurements at z~8
<p>Reduced and flux calibrated JWST/NIRSpec 1D spectra for the three sources (ID_4590 at z=8.4953, ID_6355 at z=7.6643 and ID_10612 at z=7.6592) analysed in Curti et al., 2022, "The chemical enrichment in the early Universe as probed by JWST via direct metallicity measurements at 𝑧~8" (published on MNRAS, Volume 518, Issue 1, pp.425-438)</p> <p>For more details on the data processing we refer to the Section 2.1 of the paper.</p> <p> </p> <p> </p>
Supplementary Material: Knobs and dials of retrieving JWST transmission spectra. I. The importance of p-T profile complexity
<p>This is supplementary material to <a title="Schleich et al. (2024)" href="https://www.aanda.org/articles/aa/abs/2024/10/aa51845-24/aa51845-24.html" target="_blank" rel="noopener">Schleich et al. (2024)</a>. The content of the provided data repository (also described in the file "content.txt") is as follows:</p> <p> </p> <h2>ADDITIONAL ANALYSIS</h2> <p>This folder contains a collection of ancillary data products for the evaluation of the retrievals performed in this work.</p> <ul> <li>'bayes-factor' contains the data tables for evaluating the Bayes' factor for each separate collection of models(*)</li> <li>'corner-plots' contains a collection of all corner plots associated with the individual input cases</li> <li>'fit-residuals' contains all fit residuals for the individual atmospheric retrievals performed in this work (used to make Fig. C.1)</li> <li>'resampled-pt-profiles' contains resampled p-T profiles to generate Figs. 6 and F.1</li> <li>'retrieval-accuracy' contains additional plots related to the accuracy of each retrieval (used to make Fig. 5, as well as Figs. E.1 - E.5)</li> </ul> <p><br>(*) SIDE NOTE:<br>Table headers in the "bayes-factor" data tables reference evidence reported from MultiNest (variable "Z"), and calculated Bayes factor (variable R). The case with log(R) = 0 is necessarily the reference case, and outliers are marked in a binary table with 1 (|log(R)| > 5) or 0 (|log(R)| < 5). In all cases, "log" refers to the natural logarithm.</p> <ul> <li>If someone actually reads this, I'm sorry. I also spent way too much time trying to track down if the values reported in MultiNest are natural or base-10 logarithm. I have now been convinced that it is worth it, always, to either specify "ln" for the base-e logarithm, or give the base of your logarithm if your write it down (i.e. log_10(X)) -Simon.</li> </ul> <h1> </h1> <h2>RETRIEVAL RESULTS</h2> <p>This folder contains the data products associated with the retrieval runs for each synthetic spectrum. The sub-directories are aranged by the following keys:</p> <ul> <li>'drs' and 'pandexo' refere to the two noise cases considered</li> <li>'inv-t' and 'norm-t' refere to the two underlying p-T profiles used to make the synthetic spectra</li> <li>'hpc', 'mpc', and 'lpc' refere two the three cloud-top pressure cases considerd</li> </ul> <p>Each individual folder contains (1) the TauREx parameter files for running retrievals using the selection of p-T profiles, (2) a folder called 'results', which containts the associated data products, and (3) a folder called 'chains', which stores the ancillary data products associated with the MultiNest sampling runs of each retrieval.</p> <p> We note that for the "drs_inv-t_mpc" case, the chains for the isothermal, 2-point, and 4-point runs have been lost</p> <p> </p> <h2>SYNTHETIC SPECTRA</h2> <p>This folder contains data products associated with the sample of synthetic transmission spectra.</p> <ul> <li>'pt-profile_*.csv' are csv-files containing the p-T points used to make Figure 1 , and to generate the synthetic transmissions spectra</li> <li>'forward-models' contains TauREx parameter files and forward models for the sample of synthetic transmission spectra. Each of the sub-directories also contains a faux-spectrum representing the wavelength-map of NIRSpec PRISM <ul> <li>'no-clouds' contains contains the above for generating Figure 3.</li> <li>'inv-t' contains forward models using the "inverse" p-T profile</li> <li>'norm-t' contains forwrad models using the "monotonic" p-T profile</li> </ul> </li> </ul>
Data for: JWST COMPASS: A NIRSpec/G395H Transmission Spectrum of the Sub-Neptune TOI-836c
<p>Data and models presented in "JWST COMPASS: A NIRSpec/G395H Transmission Spectrum of the Sub-Neptune TOI-836c"</p> <ul> <li>Transmission spectra from all three reductions presented</li> <li>Fitted white light curves from all three reductions</li> <li>Fitted spectroscopic light curves from the main Eureka! reduction</li> <li>PICASO models presented in Figure 11</li> </ul> <p>Manuscript: <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240401264W/abstract">Wallack et al. 2024</a> (DOI: 10.3847/1538-3881/ad3917)</p>
JWST convolutions for a modular set of synthetic SEDs for young stellar objects (Robitaille, 2017)
<p>This is a companion to the models released alongside the publication:</p> <p><em>A modular set of synthetic spectral energy distributions for young stellar objects</em>, Robitaille (2017)</p> <p>The models are convolved with JWST filters taken from the SVO’s filter profile service. Some models with rotationally flattened envelopes (i.e. geometries with<strong> u</strong>)<strong> </strong>not present in the original model grid have since been completed; their convolved SEDs are included here.</p> <p>Files unzip to {geometry}/convolved/JWST/{SVO_filtername}.fits.</p> <p>This is a subset of the information included in https://doi.org/10.5281/zenodo.8114592.</p>
An Ice Age JWST inventory of dense molecular cloud ices
<p>This dataset is the first observational data release for the JWST Early Release Science Ice Age program (#1309). More information about this program can be found at our team website (<a href="http://jwst-iceage.org/">http://jwst-iceage.org/</a>) and the STScI website (<a href="https://www.stsci.edu/jwst/science-execution/approved-programs/dd-ers/program-1309">https://www.stsci.edu/jwst/science-execution/approved-programs/dd-ers/program-1309</a>). The data is analyzed in the article by McClure et al. (2023), to be published on January 24th, 2023 by Nature Astronomy.</p> <p>The dataset consists of 5 files, each containing a spectrum of one of two background stars analyzed in that publication. The spectra are given as wavelength in microns (column 1), flux in milli-Janskys (column 2), and uncertainty in the flux (column 3). Some basic information about the JWST pipeline version is given in the header of each text file, but users should refer to the Methods section of McClure et al. (2023) for the full description of how the data were processed and extracted, as it extends beyond the basic pipelines. Information about how the data were observed is given in the APT file, accessible through a query in STScI's APT application (search by PID 1309) or here at STScI (<a href="https://www.stsci.edu/jwst/science-execution/program-information.html?id=1309">https://www.stsci.edu/jwst/science-execution/program-information.html?id=1309</a>).</p> <p>Three of the files correspond to the background star NIR38. These represent spectra of this star taken separately by JWST with the NIRCam WFSS, NIRSpec FS, and MIRI LRS FS instrument modes on JWST. The other two files correspond to the background star J110621 and are spectra taken separately by JWST using the NIRSpec FS and MIRI LRS FS instrument modes.</p> <p>It is necessary to cite the McClure et al. (2023) Nature Astronomy publication when making use of these data, to fully describe the data processing, as well as this Zenodo DOI.</p>
Products and Models for "Detection of carbon monoxide's 4.6 micron fundamental band structure in WASP-39b's atmosphere with JWST NIRSpec G395H"
<p>Overview:</p> <p>Carbon monoxide (CO) is predicted to be the dominant carbon-bearing molecule in giant planet atmospheres, and, along with water, is important for discerning the oxygen and therefore carbon-to-oxygen ratio of these planets. The fundamental absorption mode of CO has a broad double-branched structure composed of many individual absorption lines from 4.3 to 5.1 µm, which can now be spectroscopically measured with JWST. Here we present a technique for detecting the rotational sub-band structure of CO at medium resolution with the NIRSpec G395H instrument. We use a single transit observation of the hot Jupiter WASP-39b from the JWST Transiting Exoplanet Community Early Release Science (JTEC ERS) program at the native resolution of the instrument (R ~ 2700) to resolve the CO absorption structure. We robustly detect absorption by CO, with an increase in transit depth of 264 <span>\(\pm\)</span> 68 ppm, in agreement with the predicted CO contribution from the best-fit model at low resolution. This detection confirms our theoretical expectations that CO is the dominant carbon-bearing molecule in WASP-39b's atmosphere, and further supports the conclusions of low C/O and super-solar metallicities presented in the JTEC ERS papers for WASP-39b. </p>
A JWST inventory of protoplanetary disk ices. The edge-on protoplanetary disk HH 48 NE, seen with the Ice Age ERS program
<p>JWST NIRSpec G395H spectrum for HH 48 NE edge-on disk, as analyzed in Sturm et al. (2023). DOI: 10.1051/0004-6361/202347512</p>
JWST spectrum of galaxy COSMOS-11142 from the Blue Jay survey.
<p>Spectroscopic and photometric data for galaxy COSMOS-11142, studied in Belli et al. (2024).</p> <ul> <li>The JWST/NIRSpec spectroscopy is stored as a FITS table which includes wavelength (in angstrom), calibrated flux, uncertainty, and best-fit model (in erg/(s cm2 A)).</li> <li>The JWST and HST photometry is stored as a FITS table which includes the name of each filter, the effective wavelength (in angstrom), the observed flux and its uncertainty (in microJy).</li> </ul>
LRD Photometry and Physical Parameters in Blank JWST Fields (Kokorev+24)
<p>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></p>
Supplementary Information: Investigating the detectability of hydrocarbons in exoplanet atmospheres with JWST
<p>Supplementary information containing additional figures of the journal article 'Investigating the detectability of hydrocarbons in exoplanet atmospheres with JWST' by D. Gasman, M. Min, and K. L. Chubb, published in Astronomy & Astrophysics (2022).</p>
PICASO 3.0 Atmospheric Models of WASP-39 b for the JWST Transiting Exoplanet Community Early Release Science Program
<p><strong>OVERVIEW</strong></p> <p>The exoplanetary atmospheric models used in the recent <a href="https://www.nature.com/articles/s41586-022-05269-w">discovery of CO<sub>2 </sub>in WASP- 39 b's atmosphere</a> by the JWST transiting exoplanet community early release science program are presented here. These models are also being used to analyze multiple observations of WASP 39-b obtained using various JWST instruments and observational modes by the transiting exoplanet ERS team. The 1D Radiative-Convective-Thermochemical Equilibrium (RCTE) atmospheric models were computed using the open-source 1D climate model <a href="https://natashabatalha.github.io/picaso/">PICASO 3.0</a> (<a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>). These atmospheric models were then post-processed with condensation clouds using the open-source cloud model <a href="https://natashabatalha.github.io/virga/">VIRGA</a> (<a href="https://ui.adsabs.harvard.edu/abs/2022ApJ...925...33R/abstract">Rooney et al. (2022)</a>). The atmospheric models were also post-processed with the 1D photochemical network code <a href="https://github.com/exoclime/VULCAN">VULCAN</a> (<a href="https://arxiv.org/abs/2108.01790">Tsai et al. (2021)</a>) to explore photochemistry in WASP-39 b's atmosphere.</p> <p><strong>1D RCTE CLOUD-FREE MODELS</strong></p> <p>The base 1D RCTE grid includes atmospheric metallicity points at 0.1, 0.3, 1.0, 3.0, 10.0, 30.0, 50.0, and 100.0x solar values. The Carbon-to-Oxygen (C/O) ratio value is varied between four values - 0.23, 0.46, 0.69, and 0.92. The intrinsic temperature of the planet has been varied across 100, 200, and 300 K, whereas two values of the heat redistribution factor - 0.4 and 0.5 are included. A heat redistribution factor of 0.5 corresponds to the case of full heat redistribution. With these grid points, the grid includes a total of 8x4x3x2= 192 different models.</p> <p>These models are in the "RCTE_cloud_free.zip" folder. The naming scheme of these files is "profile_eq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_.nc" where [T_int] represents the intrinsic temperature of the planet, [MH] is the log<sub>10 </sub>of the atmospheric metallicity relative to solar, [CtoO] is the C/O ratio relative to solar, and [rfacv] is the heat-redistribution factor. So, a metallicity value of 0.3xsolar will have a [MH] value of -0.5, and a C/O 0.46 is considered 1xsolar and will correspond to [CtoO]=1. [T_int] and [rfacv] can assume values described in the previous paragraph.</p> <p><strong>1D RCTE CLOUDY MODELS</strong></p> <p>The base 1D RCTE cloud-free models were post-processed to include condensation cloud species Na<sub>2</sub>S, MnS, and MgSiO<sub>3</sub>. The cloud structure and optical property calculations were performed using the VIRGA model where the sedimentation efficiency <em>f<sub>sed </sub></em>and the vertical eddy diffusion coefficient (<em>K<sub>zz</sub></em>) are free parameters. For the cloudy models, 5 <em>f<sub>sed </sub></em> values - 0.6, 1, 3, 6, and 10 were used along with 3 different values of log<sub>10</sub><em>K<sub>zz </sub></em>- 5, 7, 9, and 11, where <em>K<sub>zz </sub></em>is in cm<sup>2</sup>/s. These models are included in the "RCTE_cloudy.zip" folder following the naming structure "profile_eq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_kzz_1e[log10Kzz]_fsed_[fsed].cld.nc" where two other variables are added in the name - [log10Kzz] and [fsed]. Both of these variables can take values listed here.</p> <p><strong>PHOTOCHEMICAL CLOUD-FREE MODELS</strong></p> <p>A much smaller subset of the base 1D RCTE models were post-processed with the 1D photochemical network code VULCAN to simulate the effects of vertical mixing and photochemistry in WASP-39 b's atmosphere. log<sub>10</sub><em>K<sub>zz </sub></em>was varied again between the 5, 7, 9, and 11 for this purpose. These files are named as "profile_diseq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_kzz_1e[log10Kzz].nc" and can be found in the "photochem_cloud_free.zip" folder.<br> <br> <strong>PHOTOCHEMICAL CLOUDY MODELS</strong></p> <p>The photochemical models were post-processed with clouds to simulate a cloudy atmosphere with disequilibrium chemistry. The <em>f<sub>sed </sub></em> and log<sub>10</sub><em>K<sub>zz </sub></em> grid system for the RCTE cloudy models has been used again for these models as well. These files are in the "photochem_cloudy.zip" folder and are named according to the format "profile_diseq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_kzz_1e[log10Kzz]_fsed_[fsed].cld.nc".</p> <p><strong>FILE FORMATTING AND USAGE</strong></p> <p>All the files are released in the <a href="https://docs.xarray.dev/en/stable/">xarray</a> format. Each model has one single xarray file containing all metadata of that model. This metadata includes the input parameters used to compute the model, for example, the metallicity, C/O ratio, and intrinsic temperature. The temperature-pressure (<em>T(P)</em>) profile and the volume mixing ratio profiles of all the different gases in each model is also included in the metadata. The computed transmission spectrum of the model planet from 0.3-6 microns is included in the same file as well. The spectrum is calculated with resampled opacities at a spectral resolution of 60,000, but they should be re-binned at a spectral resolution of 3000 or less for comparison with observed data. For cloudy models, the wavelength dependant optical depth, asymmetry parameter, and single scattering albedo for each atmospheric layer are included in these xarray files.</p> <p>We refer to this <a href="https://natashabatalha.github.io/picaso/notebooks/codehelp/data_uniformity_tutorial.html#Reading/interpreting-an-xarray-file">PICASO tutorial</a> for reading/writing these xarray files. The spectrum from these xarray files can be easily extracted using the following code.</p> <pre><code class="language-python">import xarray as xr path = "path/to/files" ds_sm = xr.open_dataset(path+"profile_eq_planet_300_grav_4.5_mh_+2.0_CO_2.0_sm_0.0486_v_0.5_.nc") # for spectrum wavelength = ds_sm['wavelength'].values transit_depth = ds_sm['transit_depth'].values # for T(P) profile temperature = ds_sm['temperature'].values pressure = ds_sm['pressure'].values</code></pre> <p><a href="https://github.com/natashabatalha/picaso/blob/master/docs/notebooks/fitdata/GridSearch.ipynb">This tutorial</a> shows how to use these models to analyze the NIRSpec Prism observations of WASP-39 b, which led to <a href="http://www.nature.com/articles/s41586-022-05269-w">CO<sub>2 </sub>detection</a>. Please note that the folders must be unzipped before using them with this notebook.</p> <p><strong>CREDITS</strong></p> <p>If you use these modeling products in your work, please cite this zenodo repository along with the following papers depending on the part of the grid being used:</p> <p>1) RCTE_cloud_free.zip</p> <p> <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a> </p> <p>2) RCTE_cloudy.zip</p> <p><a href="https://ui.adsabs.harvard.edu/abs/2022ApJ...925...33R/abstract">Rooney et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a> </p> <p>3) photochem_cloud_free.zip</p> <p> <a href="https://arxiv.org/abs/2108.01790">Tsai et al. (2021)</a> , <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a> </p> <p>4) photochem_cloudy.zip</p> <p> <a href="https://arxiv.org/abs/2108.01790">Tsai et al. (2021)</a> , <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2022ApJ...925...33R/abstract">Rooney et al. (2022)</a></p> <p> </p>
Synthetic JWST NIRCam, Euclid NISP, and Roman WFI Near-Infrared Photometry for 800+ Ultracool Dwarfs
<p>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.</p> <p>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:</p> <p>"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>."</p> <p>Contact <a href="mailto:asanghi@caltech.edu">asanghi@caltech.edu</a> regarding questions.</p>
Products and Models for "A benchmark JWST near-infrared spectrum for the exoplanet WASP-39 b"
<p>Publication Here: https://www.nature.com/articles/s41550-024-02292-x<br><br>Observing exoplanets through transmission spectroscopy supplies detailed information on their atmospheric composition, physics, and chemistry. Prior to <em>JWST,</em> these observations were limited to a narrow wavelength range across the near-ultraviolet to near-infrared, alongside broadband photometry at longer wavelengths. To understand more complex properties of exoplanet atmospheres, improved wavelength coverage and resolution are necessary to robustly quantify the influence of a broader range of absorbing molecular species. Here we show a combined analysis of <em>JWST</em> transmission spectroscopy across four different instrumental modes spanning 0.5–5.2 micron using Early Release Science observations of the Saturn-mass exoplanet WASP-39b. Our uniform analysis constrains the orbital and stellar parameters within sub-percent precision, including matching the precision obtained by the most precise asteroseismology measurements of stellar density to-date. Leveraging the advantages of a uniform light curve analysis, we improve the agreement between the transmission spectra of all modes, except for the NIRSpec PRISM, which is affected by partial saturation of the detector. Together, these collected data constitute the most comprehensive transmission spectrum of an exoplanet to date, providing unparalleled access to atmospheric absorbers including Na, K, H2O, CO, CO2, and SO2.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.