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587 results for “Asteroid”
Using neural networks to model Main Belt Asteroid albedos as a function of their proper orbital elements
<p>This repository contains a copy of the following repository https://github.com/r-zachary-murray/Asteroid-Albedos. It contains weights for an ensemble of neural nets trained on the Asteroid Family Portal proper elements and NEOWISE albedos. These weights can be used to predict albedos of asteroids based of their proper elements. Example.ipynb contains an ipython notebook that shows how these predictions can be made.</p>
Numerical Modeling of Asteroid Impact in 2D Cylindrical Coordinates
<p>Additional material and code for the Bachelor Thesis "Numerical Modeling of Asteroid Impact in 2D Cylindrical Coordinates" </p>
The boulder population of asteroid 4 Vesta
<p>These are data described in the paper "The boulder population of asteroid 4 Vesta: Size-frequency distribution and survival time" by Schröder et al., submitted to Earth & Space Science (Wiley). The data concern boulder counts for craters on the asteroid Vesta.</p> <p>Boulder counts for all 69 craters in Table 1 of the paper are provided as text files with 3 columns: (1) longitude and (2) latitude, both in degrees, and (3) boulder diameter in meters. Generally, boulder identifications are only reliable above 3 image pixels (60 m), but the data files contain all boulders that we (tentatively) identified, including those smaller than 60 m.</p> <p>We also provide figures in PDF format, one for each crater, of the spatial boulder distribution. The figures have the format of Fig. 6 in the paper: Green, small dots represent boulders with a size between 3 and 4 pixels (60 m < d < 80 m). Red, large dots represent boulders larger than 4 pixels (d > 80 m). Boulders smaller than 60 m are not shown.</p>
Movies associated with "Direct N-body simulations of satellite formation around small asteroids: insights from DART's encounter with the Didymos system"
<pre>All movies are titled based on the figure in the paper they correspond to and the ID number of the simulation. All movies, except for movie_fig1_fig2_spinup.mp4 are rendered in a rotating, primary-centered frame with a period of 10 hours. This is done to make it easier to watch the satellite accumulate. movie_fig1_fig2_spinup.mp4 is rendered in an inertial frame. The movies are quite long, so we recommend fast-forwarding some of the boring parts :)</pre>
Data from: Disequilibrium oxygen isotope distribution among aqueously altered minerals in Ryugu asteroid returned samples
<p>Oxygen 3-isotope ratios of magnetite and carbonates in aqueously altered carbonaceous chondrites provide important clues to understanding the evolution of the fluid in the asteroidal parent bodies. We conducted oxygen 3-isotope analyses of magnetite, dolomite, and breunnerite in two sections of asteroid Ryugu returned samples, A0058 and C0002, using a secondary ion mass spectrometer (SIMS). Magnetite was analyzed by using a lower primary ion energy that reduced instrumental biases due to the crystal orientation effect. We found two groups of magnetite data identified from the SIMS pit morphologies: (1) higher δ<sup>18</sup>O (from 3‰ to 7‰) and ∆<sup>17</sup>O (~2‰) with porous SIMS pits mostly from spherulitic magnetite, and (2) lower δ<sup>18</sup>O (~ –3‰) and variable ∆<sup>17</sup>O (0-2‰) mostly from euhedral magnetite. Dolomite and breunnerite analyses were conducted using multi-collection Faraday cup detectors with precisions ≤0.3‰. The dependence of instrumental biases on carbonate compositions was corrected using two methods, using Fe and (Fe+Mn) contents, because Ryugu dolomite contains higher amounts of Mn than the terrestrial standard. Results of dolomite and breunnerite analyses show a narrow range of ∆<sup>17</sup>O; 0.0–0.3‰ for dolomite in A0058 and 0.2–0.8‰ for dolomite and breunnerite in C0002. The majority of breunnerite, including large ≥100 µm grains, show systematically lower δ<sup>18</sup>O (~21‰) than dolomite (25–30‰ and 23–27‰ depending on the instrumental bias corrections). The equilibrium temperatures between magnetite and dolomite from the coarse-grained lithology in A0058 are calculated to be 51±11˚C and 78±14˚C, depending on the instrumental bias correction scheme for dolomite; a reliable temperature estimate would require a Mn-bearing dolomite standard to evaluate the instrumental bias corrections, which is not currently available. These results indicate that oxygen isotope ratios of aqueous fluids in the Ryugu parent asteroid were isotopically heterogeneous, either spatially or temporally. Initial water ice accreted to the Ryugu parent body might have ∆<sup>17</sup>O >2‰ that was melted and interacted with anhydrous solids with the initial ∆<sup>17</sup>O <0‰. In the early stage of aqueous alteration, spherulitic magnetite and calcite formed from aqueous fluid with ∆<sup>17</sup>O ~2‰ that was produced by isotope exchange between water (∆<sup>17</sup>O >2‰) and anhydrous solids (∆<sup>17</sup>O <0‰). Dolomite and breunnerite along with some magnetite formed at a later stage of aqueous alteration under higher water-to-rock ratios and the oxygen isotope ratios were nearly at equilibrium between fluid and solid phases. Including literature data, δ<sup>18</sup>O of carbonates decreases in the order of calcite, dolomite, and breunnerite, suggesting that the temperature of alteration might have increased with the degree of aqueous alteration.</p>
Time optimal low-thrust rendezvous from an asteroid belt
<p>This dataset allows to train regression models representing the optimal time of flight of a constant acceleration low-thrust trajectory aimed at a randezvous with a target orbiting station (placed at 1.3 Astronomical Units).</p><p>The version 2 of the dataset should be used, correcting a data bias towards simpler transfers present in the previous version.</p><p>The attributes, X, represent the modified equinoctial parameters (p,f,g,h,k,sin(L), cos(L)) of the spacecraft (SI units) at the start of the transfer. L is the true longitude. Different representations of the initial state are likely key to improving any model.</p><p>The time of flight, Y, is given in units of TIME=5022642.890912783s</p><p>The dataset was used for <strong>value function learning</strong> in our paper:</p><p>Izzo, D. and Origer, S.: "Neural representation of a time optimal, constant acceleration rendezvous" - https://arxiv.org/abs/2203.15490</p><p>where we were more interested on the effects/use of the data augmentation technique called "Backward Generation of Optimal Examples" than on the accuracy of the resulting neural model. A MAE of ~25 days is obtained on the test set, when training from the augmented dataset (vs. ~34.08 days from the non augmented one). Both these numbers can likely be improved considerably, constituting a nice challenge for the community.</p><p>The python pickles can be opened as:</p><blockquote><p>with open("filename.pk", "rb") as f:<br> X, Y = pkl.load(f)</p></blockquote><p>else , we also provide the corresponding csv files.</p><p>* <strong>training</strong>: contains 3000 items</p><p>* <strong>test</strong>: contains ~1000 items</p><p>* <strong>training_augmented_32_0.0001</strong>: contains 96000 items (augmented from the 3000 of training)</p>
Data for: The rock-forming minerals and macroscale mechanical properties of asteroid rocks
<p>HaH 346 meteorite samples are tested using the nanoindentation experiment with Berkovich indenter. The data includes the Young’s modulus of different rock-forming minerals in HaH 346 meteorites measured by nanoindentation test.</p>
Insight into the distribution of high-pressure shock metamorphism in rubble-pile asteroids
<p>This archive contains files with research data related to a publication "Insight into the distribution of high-pressure shock metamorphism in rubble-pile asteroids" by Güldemeister et al. <em>et al</em> 2022 <em>Planet. Sci. J.</em> 3 198 <a href="https://deref-gmx.net/mail/client/tUH7sPVsuLI/dereferrer/?redirectUrl=https%3A%2F%2Fdoi.org%2F">https://doi.org/</a> 10.3847/PSJ/ac83c0</p> <p> </p> <p>To use these files, you will need:<br> - authorized access to the iSALE shock physics code (iSALE-Dellen version) re-compiled with our modifications, with reference<br> to the manual in your work<br> - access to the pySALEPlot tool for iSALE users made by T. Davison acknowledged in your work<br> - running the iSALE models to generate the different jdata.dat files <br> - python<br> - Ubuntu or macOS</p> <p>You will find more content information in the README.txt file.</p>
Mapping Phyllosilicates on the Asteroid Bennu Using Thermal Emission Spectra and Machine Learning Model Applications Datasets
<p>We provide laboratory spectra of pure minerals and mineral mixtures and the corresponding metadata. Derived from the laboratory data, we include the PLS model through coefficients. Through the application of the model, we provide the prediction values in volume% for Mg-rich serpentine, cronstedtite, and saponite for the BBD1, EQ3, and TAG datasets.</p>
Mapping Phyllosilicates on the Asteroid Bennu Using Thermal Emission Spectra and Machine Learning Model Applications
<p>We provide the laboratory spectra and metadata that was used to construct the PLS model coefficients. Through the application of the model, we provide the prediction values in volume% for Mg-rich serpentine, cronstedtite, and saponite for the BBD1, EQ3, and TAG datasets.</p>
Optimal low thrust transfers among asteroid belt asteroids.
<p>This dataset contains > 3,000,000 optimal low-thrust transfers between asteroids in the belt. It was created from the asteroids data released during the 12th edition of the Global Trajectory optimization competitions (see the <a href="https://sophia.estec.esa.int/gtoc_portal/">official GTOC portal</a>) and considering a spacecraft having an initial mass <strong>ms</strong> in the range [700, 8000] kg, a maximum thrust <strong>TM</strong> = 0.6 N with a specific impule <strong>Isp</strong> = 4000 s, resulting in possible initial acceleration levels in the range [7.5 1e-5, 8.6 1e-4] m/s^2.</p> <p>The dataset was developed in the context of our contribution to the International Symposium on Space Flight Dynamics 2024 (ISSFD).</p> <p>Starting from a sampled asteroid couple <strong>(As</strong> <strong>Af)</strong>, and an initial mass <strong>ms:</strong></p> <ul> <li>The minimum time transfer <strong>tof_min </strong>is found solving the corresponding optimal control problem (in a Keplerian dynamics) and the resulting transfer recorded in a first dataset.</li> <li>In some cases, for several fixed <strong>tof</strong> > <strong>tof_min</strong> the maximum final mass transfer is found solving the corresponding optimal control problem and the resulting transfer recorded in a second dataset.</li> </ul> <p>Each line in the csv dataset correspond to a specific optimal transfer (randevouz) and contains the following information:</p> <p>[<strong>xs</strong>, <strong>ys</strong>, <strong>zs</strong>, <strong>vxs</strong>, <strong>vys</strong>, <strong>vzs</strong>, <strong>xf</strong>, <strong>yf</strong>, <strong>zf</strong>, <strong>vxf</strong>, <strong>vyf</strong>, <strong>vzf</strong>, <strong>ms</strong>, <strong>tof</strong>, <strong>mf</strong>, <strong>MIMA</strong>, <strong>MIMA2</strong>, <strong>MIMA3</strong>, <strong>mfms_approx</strong>]</p> <p>, i.e. the starting (<strong>s</strong>) spacecarft state, the final (<strong>f</strong>) spacecraft state, the starting spacecraft mass <strong>ms</strong>, the time of flight <strong>tof </strong>and the final mass <strong>mf</strong>. Several analytical approximations are also reported: <strong>MIMA</strong>, <strong>MIMA2,</strong> <strong>MIMA3, mfms_approx.</strong></p> <p>The analytical approximation <strong>MIMA</strong> is derived and published in:</p> <ul> <li>Hennes, D., Izzo, D., & Landau, D. (2016, December). Fast approximators for optimal low-thrust hops between main belt asteroids. In <em>2016 IEEE Symposium Series on Computational Intelligence (SSCI)</em> (pp. 1-7). IEEE.</li> </ul> <p>A second improved version (<strong>MIMA2</strong>) is derived and published in:</p> <ul> <li>Izzo, D., Märtens, M., L. Beauregard ..., G. Acciarini et al. "Asteroid Mining: ACT&Friends’ Results for the GTOC 12 Problem." <em>to appear in Astrodynamics (Springer).</em></li> </ul> <p>and the final one, <strong>MIMA3,</strong> is derived and published in:</p> <ul> <li>G. Acciarini, Beauregard L. and Izzo, D., Computing low-thrust transfers in the asteroid belt, a comparison between astrodynamical manipulations and a machine learning approach. <em>ISSFD conference, Darmstadt, 2024</em>.</li> </ul> <p>The MIMAs approximate the maximum initial mass a spacecarft can have to perform a given fixed time transfer (that also is, in the optimal time of flight transfer dataset <strong>ms</strong>). For these transfers no coast arc exists. In all other cases, a related analytical approach can be used to approximate <strong>mf</strong>. The result, when available is added to the dataset as <strong>mfms_approx </strong>(approximating the ratio <strong>mf/ms</strong>, an approximation for the final mass can be retreived multiplying by <strong>ms</strong>)</p> <p> </p> <p>NOTE: the <strong>MIMAs</strong> and <strong>mfms_approx </strong>sometimes fail numerically or conceptually in which case a nan is reported or a 'nonsensical' number (e.g. lower than the actual starting mass).</p> <p>NOTE: The second version of the dataset corrects some trajectories in the time-optimal dataset that were not time optimal since during the optimization they hit a lower bound on the mass (500kg). They have now been removed. Thanks to Hongxin Shen for testing and reporting the issue.</p> <p> </p>
Data for Estimate of water and hydroxyl abundance on asteroid (16) Psyche from JWST data
<p>The data as ASCII files used to produce the figures in the manuscript, " Estimate of water and hydroxyl abundance on asteroid (16) Psyche from JWST data". Almost all the files are ECSV files created from astropy Table. These files have complete metadata headers. Otherwise, the data, where appropriate, include s3d fits IFU data cubes used to produce 1D spectra, the solar spectra output by the Planetary Spectrum Generator, a thermophysical model output, asteroid reflectance measurements, and chondrite reflectance measurements all of which are described in further detail below. </p> <p>The Figures folder contains data behind the figures where data were used.</p> <p>For Figure 2 this corresponds to the NIRSpec and MIRI flux observations with a column for wavelength (in microns), flux (in Jansky), and error (in Jansky). </p> <p>For Figure 3 this corresponds to the normalized reflectance for the NIRSpec observations. The first column in each dataset corresponds to the wavelength in microns, the second column to the normalized reflectance (unitless), the third column to the error (unitless), and in the case of the .txt files the fourth column corresponds to the gaussian fit to the normalized reflectance. </p> <p>For Figure 4 these are the normalized reflectance divided by the continuum of the groups of data along wavelength ranges described in the manuscript for Figure 4. The first column corresponds to the wavelength in microns, the second column to the reflectance, the third column to the continuum fit to the data, the fourth column is the normalized reflectance divided by the continuum, and the error. </p> <p>For Figure 5 these are the data used to produce the 3-micron feature plot with the gaussian fit for each NIRSpec observation. The first column corresponds to the wavelength in microns, second column to the normalized reflectance divided by the continuum (unitless) and subtracted from the mean of the continuum between 3.6 and 3.7 microns such that the average of the continuum would be 0, the fourth column the error (unitless), and the fifth column the gaussian fit to the data. </p> <p>For Figure 6 the only additional data needed to produce this plot beyond what is provided for Figure 5 is the IRTF data which is provided as a text file. The first column corresponds to the wavelength in microns, the second column to the normalized reflectance divided by the continuum (unitless), and the third column to the error (unitless). </p> <p>For Figure 7 the additional data used to produce this plot beyond what is provided for Figure 5 includes laboratory reflectance measurements of various chondrites. The .scl files are the original laboratory measurements where the first column corresponds to the wavelength in microns, the second column to the normalized reflectance (unitless) and the third column to the error to 1 significant digit (unitless). The scaled_lab_reflectance.txt file has all the laboratory reflectance data used to produce the Figure 7 plot that includes the wavelength in microns, the normalized scaled reflectance for the CM chondrite, the normalized scaled reflectance for the CH/CBb chondrite, and the normalized scaled reflectance for the CY chondrite. </p> <p>For Figure 8 the additional data include original normalized reflectance data for asteroids interamnia, themis, bamberga, and europa as .trim files. The columns for these files correspond to wavelength in microns, normalized reflectance (unitless), and the error (unitless). The 'continuumremoved' .txt files correspond to the wavelength in microns and the normalized reflectance divided by the continuum (unitless). </p> <p>For Figure 9 these are the MIRI emissivity data for the two sets of observations. The first column corresponds to the wavelength in microns, the second column to the normalized emission by taking the flux subtracting the solar flux and dividing by a thermophysical model (unitless), the error (unitless), and the gaussian fit to the normalized emission. </p> <p>For the supplemental figures these are the additional fit absorption features that are located in the appendix of the manuscript. For the 1.25 - 4.8 micron text files the columns correspond to the wavelength in microns, the continuum divided normalized reflectance (unitless), the error (unitless), and the gaussian fit. For the 5.74 - 5.98 micron text files the columns correspond to wavelength in microns, normalized emission divided by a linear fit to a region outside any potential features (unitless), the error (unitless), and the gaussian fit to the feature. </p> <p>The MIRI 1D spectra folder contains the ASCII files corresponding to the 1 arcsec aperture summed spectra from the MIRI observations. The columns correspond to wavelength in microns, flux in Jansky, and error in Jansky. </p> <p>The NIRSpec 1D spectra folder contains the ASCII files corresponding to the 1 arcsec aperture summed spectra from the NIRSpec observations. The columns correspond to wavelength in microns, flux in Jansky, and error in Jansky. </p> <p>The Solar Spectra folder contains the solar spectra flux used to reduce the data to produce the reflectance and emission spectra. The lbl text files are equivalent to the files with the same name without the lbl but also include the column information. The first column corresponds to the wavelength in microns, the second column to the total spectral irradiance in Jansky, the third column to the flux from the object in Jansky, the fourth column to the reflected sunlight in Jansky, and the fifth column to the thermal contribution in Jansky. The only column used for the solar reflectance used in the analysis corresponds to the fourth column. </p> <p>The ThermalModel folder contains the ASCII files with the data corresponding to the thermophysical model used to produce the reflectance (by subtracting the thermal contribution) and the emission (by dividing by the thermal contribution). The first column corresponds to the wavelength in microns, the second to the thermal flux in Jansky, the third to the smoothed thermal flux in Jansky, and the fourth column to the normalized thermal flux. Only column two corresponding to the thermal flux in Jansky was used in the analysis associated with the manuscript. </p>
MACADAMIA Sloan Digital Sky Survey Asteroid Photometry, Measurements, and Images
<p>This dataset contains data from the Multi-Archive Catalog of Asteroid Detections And Measurements for Interactive Access (MACADAMIA), specifically of numbered asteroids observed serendipitously by the Sloan Digital Sky Survey (SDSS).</p> <p>photometry_archive_20201027.db is a SQLite database containing data corresponding to a search of the SDSS image archive conducted on 2020 May 1 of all numbered asteroids known at the time, which yielded 2.84 million search results, 1.98 million detections that were determined to actually be within the field of view of the identified image, and 993,777 successfully measured detections. Preview images of all detections and non-detections where the object was determined to be within the field of view of an identified image are collected in the detection_previews_*tar.gz files in this dataset, indexed by detection_id in the photometry database and listed under preview_image_file in the detection_data table.</p> <p>photometry_archive_20210927.db contains an update to the SDSS search, containing data corresponding to a search of the SDSS image archive conducted on 2021 July 2 of all numbered asteroids known at the time, which yielded 2.96 million search results, 2.06 million detections that were determined to actually be within the field of view of the identified image, and 1.02 million successfully measured detections. Previews of additional detections identified in this updated search may not be available due to data loss in a system failure in August 2023.</p> <p> </p>
Lunar ejecta origin of near-Earth asteroid Kamo`oalewa is compatible with rare orbital pathways
<p>Outcomes of numerical simulations for orbital elements and collisional states of test particles launched from the surface of the Moon as described by:</p> <p>Castro-Cisneros, Malhotra, Rosengren (2023). Lunar ejecta origin of near-Earth asteroid Kamo`oalewa is compatible with rare orbital<br> pathways. Accepted for publication in Communications Earth & Environment.</p> <p> </p> <p> </p>
Assess Safety and Efficacy of Vilaprisan in Subjects With Uterine Fibroids (ASTEROID 3)
ClinicalTrials.gov study NCT03400943. IPD Sharing: NO. Countries: 9. Publications: 1.
Data from: Disequilibrium oxygen isotope distribution among aqueously altered minerals in Ryugu asteroid returned samples
Open the record for dataset details and reuse information.
FIGURE 1. A, B in The fossil record of the asteroid (Echinodermata) family Chaetasteridae Sladen 1889 and subfamily Hyalothricinae Fisher, 1911
FIGURE 1. A, B, Arthraster dixoni Forbes, 1848. Holotype specimen NHMUK 47000, "Lower Chalk", probably Middle Turonian, Balcombe, Sussex, UK. A, actinal surface, B, enlargement of abactinal surface and base of arms. C–F, Chaetaster longipes (Bruzelius, 1805). C, enlargement of actinal arm. D, enlargement of abactinal disc. E, actinal view of specimen. F, abactinal view of specimen. Recent, Mediterranean.
FIGURE 2. A, B in The fossil record of the asteroid (Echinodermata) family Chaetasteridae Sladen 1889 and subfamily Hyalothricinae Fisher, 1911
FIGURE 2. A, B, Arthraster dixoni Forbes, 1848, small individual, in abactinal (A) and actinal (B) views; Middle Turonian, Dieppe, France; Collection of Nicolas Cottard, Offranville, Normany, France. C–I, Chaetasterina gracilis Hess, 1970. Holotype (NMB Hess A 94), Upper Hauterivian, Neuchâtel, Switzerland, original of Hess (1970: figs 9–14, pl. 3: fig. 5); C, abactinal view; D, actinal view; E–G enlargement of abactinal ossicles; H, I, enlargement of adambulacrals (ad) and inferomarginal (im). J–M, Hyalinothrix sp., Recent, Philippines, AS Gale coll. J, actinal view; K, abactinal view; L, enlargement of ossicles of denuded ambulacral groove; M, enlargement of denuded abactinal surface.
Supplementary Data for "Synchronous asteroid breakup paused the Great Ordovician Biodiversification Event"
<p>Supplementary Data includes a detailed comparison of the YW2 borehole with the well-studied Puxi River section, the U-Pb isotopic data of the bentonite, and coupled carbon isotope data of the YW2 borehole. </p>
Datafiles for Hydrogen in magnetite from asteroid Ryugu
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.