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304 results for “Planets”
Electron density and altitude of the main ionospheric peak of Mars as observed by Mars Express instruments. Archived data for the paper "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", submitted to JGR-Planets
<p>This repository contains archived data for the manuscript "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", published in Journal of Geophysical Research-Planets. Details about the methods to generate the data can be found in the paper.</p> <p>5 data files plus 2 readme text files are included.</p> <p>The file MEx_ionpeak.dat (described in the readme file README_ionpeak.txt) contains the peak electron densities and peak altitudes resulting from 34539 observations. Each record includes 14 columns. The content of each column is:</p> <p>Column 1: Instrument providing the observation (MARSIS or MaRS)<br> Column 2: Mars Year at which the observation was obtained (from MY27 to MY33)<br> Column 3: Solar Longitude (Ls) of the observation (unit: degrees)<br> Column 4: Latitude of the observation (unit: degrees)<br> Column 5: Longitude of the observation (unit: degrees)<br> Column 6: Solar Zenith Angle (SZA) of the observation (unit: degrees)<br> Column 7: F10.7 solar proxy index at 1 Astronomic Unit (unit: solar flux units)<br> Column 8: Peak electron density measured by the instrument (unit: cm-3)<br> Column 9: Peak electron density at the subsolar point, i.e., corrected for the SZA variation (unit: cm-3)<br> Column 10: Peak electron density at the subsolar point and at F10.7 (1AU)=100, i.e., corrected for the SZA and the solar radiation output variations (unit: cm-3)<br> Column 11: Peak electron density at the subsolar point, at F10.7 (1AU)=100 and corrected for the seasonal variation (unit: cm-3)<br> Column 12: Peak altitude measured by the instrument (unit: km)<br> Column 13: Peak altitude at the subsolar point, i.e. corrected for the SZA variation (unit: km)<br> Column 14: Peak altitude at the subsolar point and corrected for the seasonal variation (unit: km)</p> <p> </p> <p>The files eprofiles_MaRS.dat, eprofiles_MARSIS_prof1.dat, eprofiles_MARSIS_prof2.dat and eprofiles_MARSIS_prof3.dat contain 4 electron density profiles. They are described in the file README_eprofiles.txt. Each file includes 2 columns, the first one being the altitude (unit: km) and the second one the electron density (unit: cm-3).</p> <p> </p> <p>Contact: Francisco Gonzalez-Galindo, ggalindo@iaa.es<br> </p>
Planetary perturbers: Flaring star-planet interactions in Kepler and TESS
<p>This data set contains:</p> <p>a. almost 13,000 de-trended Kepler and TESS light curves used in the publication with the same title (Ilin et al. 2024). Each light curve is a fits file with the Kepler or TESS identifier, Quarter or Sector, and, if there are multiuple light curves per Quarter/Sector, the number of the light curve. The light curves can be read with any fits file handler (e.g., astropy), or with the lightkurve package. Each light curve contains arrays for the flux, detrended flux, time, and orbital phase of the innermost planet. Note that for transiting planets the orbital phase is set to zero around transit midtime, while for non-transiting planets, the phase zero is set arbitrarily. There is no particular reason for splitting the data in the zip files except for easier upload.</p> <p>b. Tables 1-4 from Ilin et al. (2024). Tables 1 and 3 are combined into one. Each table includes a description of its columns at the top.</p> <p><a href="https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.3395I/abstract"><strong>Ilin et al. (2024)</strong></a> Ilin, E., Poppenhäger, K., Chebly, J., Ilić, N., Alvarado-Gómez, J.~D.</p> <p>Planetary perturbers: flaring star-planet interactions in Kepler and TESS.</p> <p>Monthly Notices of the Royal Astronomical Society 527, 3395–3417.</p> <p>doi:10.1093/mnras/stad3398</p>
Signal-to-Noise Ratios, DYNAMITE Posteriors, and Combined Detectability Plots for 173 TESS Multi-Planet Systems
<p>Collection of figures for 173 TESS Multi-Planet Systems. Each figure (titled with the system's TOI number) has 2 rows of planets, corresponding to results from the clustered period model (upper) and period ratio model (lower) predictions for an additional planet in each system. The left-most column of the plots show the signal-to-noise ratios (SNR) of simulated transits for planets with a given radius and period in the corresponding TESS light curve. The middle column shows the dot product of the radius and period posteriors generated by DYNAMITE using TESS light curves up to and including Sector 76. The right-most column shows the detectability (SNR) modulated by the DYNAMITE posteriors, showing the location in (P, Rp) space where an additional planet in this system is most likely to be detected under each model.</p>
FIG. 1 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 1. — Number of species published by semester from the end of the expedition, with first semester: July-December 2015, and last semester: January-July 2021. The expedition was accomplished in August 2015.
FIG. 4 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 4. —Density map of the shared data from the GBIF portal (https://www.gbif.org) for insects at the scale of the Guiana Shield. Only data with a high occurrence resolution (<1 km) are included.
FIG. 2 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 2. — Number of new (non-marine) animal species of French Guiana's fauna described since 2000. New species collected during the Mitaraka survey are indicated in colour.
FIG. 5 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 5. — Number of holotypes collected according to the different techniques used. Abbreviations: BS, beating sheet; HC, hand collecting; PVB, cross flight intercept trap with a blue LED; PVP, idem, with pink LED; PGL, idem, with GemLight; BPT, blue pan trap; SLAM, sea and land air malaise trap; SW & NS, sweeping & net sweeping; WPT, white pan trap; YPT, yellow pan trap (for a more detailed description of the techniques, see Touroult et al. 2018).
FIG. 6 in The "Our Planet Reviewed" Mitaraka 2015 expedition: a full account of its research outputs after six years and recommendations for future surveys
FIG. 6. — Level of compliance with recommendations for citation of expedition, ABS authorization and deposit of specimens according to two discriminating variables (n = 90 articles).
Kinematic catalog of 2,174 planet host stars from Planet across space and time (PAST). I
<p>We present a catalog of kinematic properties (i.e., Galactic positions, velocities, and the relative membership probabilities among the thin disk, thick disk, Hercules stream, and the halo) as well as other basic stellar parameters (e.g., effective temperature, metallicity) for 2174 host stars of 2872 planets by combining data from Gaia DR2, LAMOST DR4, APOGEE DR16, RAVE DR5, and the NASA exoplanet archive by applying the revised kinematic methods from Planet across space and time (PAST). I.</p> <p>we will continue to update our catalogue with the release of new data in the future.</p> <p> </p>
Datasets for Dynamical Habitability of an Earthlike Planet with Two Giant Companions
<p>Two tables are included in this dataset:</p> <ul> <li>"Stability Results" table has the predicted stability outcomes for 80 Earthlike planets for a grid of parameters associated with two giant companions.</li> <li>"Relative Habitablity" has the calculated relative habitability for each configuration of giant planets. The relative habitability quantifies the predicted habitability for an Earthlike planet in a system with two giant planets compared to a system where the Earthlike planet is the only planet.</li> </ul> <p>See the accompanying readme files for more details on the columns of each table and the paper Bailey & Fabrycky 2022 for more information on how these datasets were created.</p>
Data for research article "CCS investment – fiddling while the planet burns"
<p>This data set contains electricity systems and technology data for the UK, Poland, Texas, Wyoming, South Korea, and Indonesia. This data was used for modeling and analysis for the research article titled 'CCS investment – fiddling while the planet burns', authored by Yoga Wienda Pratama and Niall Mac Dowell from Imperial College London.</p> <p>In this work, we modeled and optimised the systems using Electricity Systems Optimisation framework (DOI: 10.5281/zenodo.1048943) that was developed General Algebraic Modeling System (GAMS). Data for this study is therefore provided in .gdx format that is suitable for GAMS.</p> <p>Procedure to reproduce this study is discussed in the article. Further questions can be addressed to Yoga Wienda Pratama (y.pratama18@imperial.ac.uk) or Niall Mac Dowell (niall@imperial.ac.uk).</p>
An Aligned Orbit for the Young Planet V1298 Tau b
<p>Code, data, and MCMC chains associated with the article "An Aligned Orbit for the Young Planet V1298 Tau b," by Johnson et al. 2022 (accepted to The Astronomical Journal). Pre-print available at <a href="https://arxiv.org/abs/2110.10707">arXiv</a>.</p> <p> </p>
Protostars and Planets VII -- Figures and Table for "The Origin and Evolution of Multiple Star Systems"
<p>Figures 1-9 and Table 1 for "The Origin and Evolution of Multiple Star Systems" chapter to appear in Protostars and Planet VII.</p>
Neutron and LIBS data behind figures in Gabriel et al. (2022). On an extensive late hydrologic event in Gale crater as indicated by water-rich fracture halos. JGR-Planets.
<p>This repository contains datasets that allow for the reproduction of certain figures and analysis by Gabriel et al. (2022), a peer-reviewed journal article accepted in the Journal of Geophysical Research: Planets. Below are brief descriptions of the datasets.</p> <p> </p> <p>File: TGabriel_JGR-P_DAN_Passive_NoMobility_Raw_Data_sol350-400_FigureS10.txt</p> <p>Description: These are raw neutron counts from the thermal and epithermal neutron detectors as part of the Dynamic Albedo of Neutrons instrument. Only data from rover stops for sols 350 to 400 are included. Data from rover stops allows them to be readily colocated rover localization data, which includes 'site' and 'drive' numbers that are specific to each stop.</p> <p><br> File: TGabriel_JGR-P_DAN_Passive_NoMobility_Raw_Data_sol900-1500_Figure5.txt</p> <p>Description: This is similar data to the product above, however for the sol range 900 to 1500.</p> <p> </p> <p>File: TGabriel_JGR-P_DAN_Passive_withMobility_Raw_Data_sol350-420_FigureS13.txt</p> <p>Description: This is similar data to the products above, however the dataset includes passive neutron count rates acquired while the rover was traversing, smoothed over 3 meters of lateral distance traveled. This dataset allows for the analysis of environments that may be present between rover stops, and thus not detected in 'no mobility' datasets.</p> <p> </p> <p>TGabriel_JGR-P_Kukri_CCAM_MajorOxideComposition_FigureS19TableS1.xlsx</p> <p>Description: This is the result of the Major Oxide Quantification pipeline developed by the ChemCam instrument team (sPDL Tool v2.0, 25 July 2015) as run by William Rapin. Additional H quantification in Figure S19 of Gabriel et al. (2022) is not included in this dataset, but is provided in the manuscript.</p>
MarsQuakeNet: A More Complete Marsquake Catalogue Obtained by Deep Learning Techniques (Supporting Material, JGR Planets)
<p>Supporting Material (JGR Planets, 2022JE007503) - contains:</p> <ul> <li>Extended marsquake catalogue</li> <li>List of all detections</li> <li>Sol-wise predictions</li> <li>Snapshot of MarsQuakeNet code</li> </ul> <p>MarsQuakeNet code (dynamic version) also available from: https://github.com/niko-d/MarsQuakeNet.git</p>
leighfletcher/hydrogendimers: Hydrogen dimers in giant-planet infrared spectra
<p>Repository for hydrogen-hydrogen absorption spectra, including free-to-free, free-to-bound, bound-to-free and bound-to-bound components as published in Fletcher, Gustafsson and Orton (2017), ApJ Supplement.</p>
Dataset: Planet Image International Limited (YIBO) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Data associated with "The Role of Magma Oceans in Maintaining Surface Water on Rocky Planets Orbiting M-Dwarfs"
<p>The data included here involves all simulations outlined in the manuscript "The Role of Magma Oceans in Maintaining Surface Water on Rocky Planets Orbiting M-Dwarfs", submitted to MNRAS. Files are divided between models with and without a basal magma ocean, as well as different host stars, different magma ocean saturation limits, and different fringe/sensitivity analysis checks. Files are further sub-divided based on our studied parameter space: each is for a single orbital distance within the habitable zone, and a single initial water inventory. "MO_only" files correspond to the concurrent surface magma ocean/runaway greenhouse phase, while "combined_MO_cycling" files correspond to the deep-water cycling period.</p>
Simulations of Circumbinary Planets
<p>Tar archive of simulations of circumbinary planets orbiting a range of host binary stars. Each file in the archive has the assumed mass ratio, mu, and binary eccentricity, e_bin, in the file name as a tuple (mu,e_bin). Tools in python to manipulate and plot the data are provided through a GitHub repository, https://github.com/saturnaxis/CBP_stability. Inside each file contains a comma delimited text file, where the columns are the initial semimajor axis ratio, the initial phase of the planet, the maximum planetary eccentricity attained over 10^5 yr, the minimum planetary eccentricity attained over 10^5 yr, and the collision/escape time. Collisions are defined as crossing the binary orbit, where the escape is when the radial distance of the planet exceeds 10 AU.</p>
Coarse-grained outputs from near-global aqua-planet control run with QOBS SST
<p>This is the coarse-grained CTRL NG-Aqua data described in the following two papers:</p> <p>Narenpitak, P., Bretherton, C. S. & Khairoutdinov, M. F. Cloud and circulation<br> feedbacks in a near-global aquaplanet cloud-resolving model: Cloud Feedbacks in<br> a Near-Global CRM. J. Adv. Model. Earth Syst. 9, 1069–1090 (2017).</p> <p>Bretherton, C. S. & Khairoutdinov, M. F. Convective self-aggregation feedbacks<br> in near-global cloud-resolving simulations of an aquaplanet. Journal of<br> Advances in Modeling Earth Systems 7, 1765–1787 (2015).</p> <p><br> The data are generated using the System for Atmospheric Modeling, and then<br> selected fields are averaged onto (160 km)^2 grid boxes for machine learning<br> purposes.</p>
ScienceDex guides
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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.