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1,206 results for “gamma”
IODP Expedition 366 Natural gamma radiation
<p>Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.</p>
7 years of Fermi-LAT Gamma-ray data
<p>This is binned data for all Source-class photons from the first 7 years of Fermi-LAT. It is a special compact format used by the poiintlke application. It contains 447 M photons, in 14 M bins. Energy bins are 4/decade from 10 MeV to 1 TeV. Angular bins use HEALPix, with nside varying according to the PSF for the energy and event type (front or back).</p> <p>For details see</p> <p>https://github.com/tburnett/Fermi-LAT/blob/master/pointlike_document/Data%20Format.ipynb.</p>
Gamma Ray Bursts X-ray afterglow spectra from Swift/XRT
<p>Swift/XRT X-ray spectra of Gamma Ray Bursts. These are taken from swift.ac.uk, but time intervals from the light curves have been selected to remove flares and prompt emission. These spectra therefore show Gamma Ray Burst afterglow only.</p> <p> </p> <p>Reference: http://adsabs.harvard.edu/abs/2016arXiv161009379B</p> <p>Please cite Evans et al (2009, 2010) and Buchner et al (2016a).</p> <p> </p>
Data package for paper "DeepGlow: an efficient neural-network emulator of physical afterglow models for gamma-ray bursts and gravitational-wave events
<p>This is a data package accompanying the paper "DeepGlow: an efficient neural-network emulator of physical afterglow models for gamma-ray bursts and gravitational-wave events".</p>
Assessment of the Axial Resolution of a Compact Gamma Camera With Coded Aperture Collimator
<p>The dataset contains 21 images of a point-like gamma source, taken with a compact gamma camera that was equipped with a coded aperture collimator. The pixel intensity represents the accumulated energy deposited by the captured gamma photons. This dataset was acquired as part of the following paper, to which the reader is referred for an in-depth explanation.</p> <p>Note: Although the TIFF files may appear as all black or all transparent images, they will be displayed correctly when opened with an image processing tool such as ImageJ or a Python script.</p> <p><strong>Assessment of the Axial Resolution of a Compact Gamma Camera With Coded Aperture Collimator<br></strong></p> <p><strong>Purpose:</strong> Handheld gamma cameras with coded aperture collimators are under investigation for intraoperative imaging in nuclear medicine. Coded apertures are a promising collimation technique for applications such as lymph node localization due to their high sensitivity and the possibility of 3D imaging. We evaluated the axial resolution and computational performance of two reconstruction methods.<br><strong>Methods:</strong> An experimental gamma camera was set up consisting of the pixelated semiconductor detector Timepix3 and MURA mask of rank 31 with round holes of 0.08mm in diameter in a 0.11mm thick Tungsten sheet. A set of measurements was taken where a point-like gamma source was placed centrally at 21 different positions within the range of 12 to 100mm. For each source position, the detector image was reconstructed in 0.5mm steps around the true source position, resulting in an image stack. The axial resolution was assessed by the full width at half maximum (FWHM) of the contrast-to-noise ratio (CNR) profile along the z-axis of the stack. <br>Two reconstruction methods were compared: MURA Decoding and a 3D maximum likelihood expectation maximization algorithm (3D-MLEM). <br><strong>Results: </strong>While taking 4,400 times longer in computation, 3D-MLEM yielded a smaller axial FWHM and a higher CNR. The axial resolution degraded from 5.3mm and 1.8mm at 12mm to 42.2mm and 13.5mm at 100mm for MURA Decoding and 3D-MLEM respectively. <br><strong>Conclusion:</strong> Our results show that the coded aperture enables the depth estimation of single point-like sources in the near field. Here, 3D-MLEM offered a better axial resolution but was computationally much slower than MURA Decoding, whose reconstruction time is compatible with real-time imaging.</p>
Gamma cascades in 77Ge after neutron capture
<p>After neutron capture on 76Ge the gamma cascades and spectra in 77Ge are presented. This is supplementary material to the publication. </p>
A Study of Primordial Very Massive Star Evolution II: Stellar Rotation and Gamma-Ray Burst Progenitors
<p>Wind ejecta tables of rotating very massive stars from the paper:</p> <p><a href="https://iopscience.iop.org/article/10.3847/1538-4357/ad1185">A Study of Primordial Very Massive Star Evolution II: Stellar Rotation and Gamma-Ray Burst Progenitors</a></p>
Probabilistic classification of Fermi LAT gamma-ray sources (effect of covariate shift)
<p>Version 1:</p> <p>These are data products connected to <a href="https://arxiv.org/abs/2307.09584">https://arxiv.org/abs/2307.09584</a>, where an analysis of the effect of covariate shift on the probabilistic classification of the Fermi LAT gamma-ray sources from the 4FGL-DR3 catalog is performed.</p> <p>The files </p> <p>4FGL-DR3_6class_GMM_nmin100_prob_cat.csv<br>4FGL-DR3_6class_GMM_nmin100_weighted_prob_cat.csv</p> <p>contain probabilistic classification into 6 classes (determined in <a href="https://arxiv.org/abs/2307.09584">https://arxiv.org/abs/2301.07412</a>) with random forest and neural networks methods. The catalog in "4FGL-DR3_6class_GMM_nmin100_weighted_prob_cat.csv" is constructed including weights for associated sources used in training in order to account for the difference in the distribution of associated (training dataset) and unassociated (target dataset) sources. The catalog in "4FGL-DR3_6class_GMM_nmin100_prob_cat.csv" is constructed with unweighted training samples.</p> <p>The files</p> <p>4FGL-DR3_6class_GMM_nmin100_summary.csv<br>4FGL-DR3_6class_GMM_nmin100_weighted_summary.csv</p> <p>contain the corresponding summaries of the definition of classes and predicted numbers of sources for the RF and NN algorithms for associated sources (averaged over cases when the sources are in the testing samples) and unassociated sources.</p> <p>Detailed description of the construction of the catalogs can be found in <a href="https://arxiv.org/abs/2307.09584">https://arxiv.org/abs/2307.09584</a>.</p> <p>Version 2: update for the Fermi LAT 4FGL-DR4 catalog.</p> <p>The filenames slightly change.<br>Probabilistic catalogs with unweighted and weighted training respectively:<br>4FGL-DR4_6classes_GMM_prob_cat.csv<br>4FGL-DR4_6classes_GMM_weighted_prob_cat.csv<br><br>The corresponding summary files:<br>4FGL-DR4_6classes_GMM_summary.csv<br>4FGL-DR4_6classes_GMM_weighted_summary.csv</p> <p>Version 3: catalogs corresponding to the published version of the paper. The filenames and the format are the same as in Version 2.</p>
Fig. 1 in Evidence of Stress Recovery in Free-Living Ciliate Colpoda cucullus: The Repair Capability of Resting Cysts to Damage Caused by Gamma Irradiation
Fig. 1. Excystment assay of Colpoda wet cysts (A) and dry cysts (B). 'Non-irradiated' indicates non-irradiated cysts; 'irradiated' indicates cysts irradiated at 4000 Gy, and 'irradiated-incubated' indicates cysts irradiated at 4000 Gy and incubated for 12 hours before the induction of excystment. Time indicates the number of hours after the induction of excystment. Columns and attached bars correspond to the means and standard errors, respectively, of six measurements. Asterisks and double asterisks represent significant differences at p <0.05 and p <0.01 (Mann-Whitney U test), respectively.
Search for merger ejecta emission in Short Gamma Ray Bursts from very late time radio observations
<p>Coalescence of inspiral binary neutron stars (BNS) system, giving rise to short Gamma Ray Bursts (GRBs), are one of the most probable candidates for Gravitational Waves (GWs). If the resultant product of the merger is a millisecond magnetar, a significant proportion of the rotational energy deposited to emerging ejecta that produce late time radio brightening from the interaction with the surrounding ambient medium. Detection of this late-time radio emission from short GRBs can have profound implications for understanding the physics of the progenitor. This study presents the deepest and an extensive search for radio emission at late times following a short GRB to date incorporating proper frequency regime, wider observation span and relativistic correction. Five short GRBs were observed with the Giant Meter Wave Radio Telescope (GMRT) at 1250, 610, and 325 MHz band $\sim$ 2 - 11 years since the burst to search for radio emission from the merger ejecta. The estimated upper limits at the burst location are used to constrain the parameters of the burst and its surrounding environment. The magnetar model, with appropriate modifications, constrains the number density of the ambient medium for these bursts to be between $10^{-4}$ - $10^{-2}$ $cm^{-3}$. Our analysis rules out a stable magnetar with an energy of $10^{53}$ erg for four out of the five GRBs in our sample.</p>
Novel polarimetric technique to constrain the magnetic field structure and strength of Gamma-ray burst jets
<p>Gamma-ray bursts (GRBs) are extremely energetic events of cosmological origin. Observed GRBs have high luminosity and rapid variability that requires ultra-relativistic motion in the production mechanism which drive the synchrotron radiation associated with the relativistic jets and their shocked interactions with the local ambient medium. They are broadly divided into two types based on the gamma-ray duration; long GRBs (>2 seconds), and short GRBs (<2 seconds). Long GRBs are thought to be originated from explosions of very massive stars and short GRBs are thought to be produced by the merger of compact binaries. Several key open questions about our understanding of GRB physics remain: What is the driving mechanism of GRB jets? What is the origin and role of magnetic fields in driving the explosion? Since these events happen at cosmological distances, they can not be resolved using traditional astronomical techniques. However, polarimetric observations of GRBs have allowed us to start the exploration of the structure and magnetic field configurations of their relativistic jets. Generally, polarization is measured via the ratio of fluxes by taking consecutive exposures, however for rapidly varying objects such as GRBs, it is not an effective way to observe polarization. Liverpool Telescope (LT) has utilized rapidly rotating polaroids to overcome this problem and created a series of polarimeters that have successfully detected early-time optical polarimetry of various GRBs. I will present photometric and polarimetric results of various GRBs observed by RINGO3. 10 GRBs were bright enough to perform analysis and we were able to perform polarimetric analysis for 7 GRBs. I will discuss how polarimetric detection for a long GRB 191016A along with photometric data constraint the energy injection mechanism for the central engine. In addition, I will present how polarization depends on various properties of GRBs such as photometric decay index, isotropic energy of GRBs, redshift etc.</p>
Supporting information for the paper: Terrestrial Gamma-ray Flashes with Accompanying Elves Detected by ASIM
<p>Supporting data to the paper "Terrestrial Gamma-ray Flashes with Accompanying Elves Detected by ASIM"</p>
IODP Expedition 372A Natural gamma radiation
<p>Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.</p>
IODP Expedition 374 Natural gamma radiation
<p>Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.</p>
Fermi-GBM Data Release Related to Searches for Neutrinos from Gamma-Ray Bursts using the IceCube Neutrino Observatory
<p>This data release includes Fermi Gamma-ray Burst Monitor (GBM) localizations used in searches for neutrinos from gamma-ray bursts (GRB) by the IceCube Neutrino Observatory. These localizations are provided publicly to the community since they are generally useful for any analysis that needs the Fermi-GBM localization for a GRB.</p> <p><strong>Full Details:</strong></p> <p>The files contained herein are HEALPix representations of GRB localizations from the Fermi-GBM stored as FITS files and produced according to the automated method described in [1]. Each file represents the probability density (statistical + systematic) for the true source location. By definition, this excludes the Earth occulted region of the sky, which is set to 0 due to the fact that real sources are not visible through the Earth. These files cover a time range spanning the first detection of GRBs by GBM in July 2008 through July 2019 and should be considered preliminary. The files are preliminary in the sense that they contain some key differences to the official files hosted at HEASARC FTP server through the Fermi Science Support Center (FSSC; <a href="https://fermi.gsfc.nasa.gov/ssc/data/access/gbm/">https://fermi.gsfc.nasa.gov/ssc/data/access/gbm/</a>). We list the key differences here:</p> <ul> <li>Fermi began production HEALPix FITS files in early 2018, and files prior to that have not been officially provided. The files in this archive are currently the only version of HEALPix files pre-2018.<br> </li> <li>These files were not produced via the standard GBM operational pipeline; however they were produced with the same functional code that is used to make the files. The result of this is that the standard quality checks on the FITS headers by uploading to the FSSC were skipped. The primary header is most affected, with some null values, but these null values do not affect the HEALPix data.<br> </li> <li>These localizations may have centroids that are slightly different than reported in the online catalog. This is because an automated algorithm for localization (RoboBA) was used to localize the GRBs and produce these files as opposed to the manual Human-in-the-Loop localization performed for every GRB prior to 2016, and ~15% of GRBs thereafter [1].<br> </li> <li>These localizations contain an updated and improved systematic uncertainty model compared to the pre-July 2019 localizations at the FSSC. The new systematic uncertainty model is explained in [1], while the older localizations at the FSSC contain a systematic uncertainty model from [2].<br> </li> <li> In general, the official localizations hosted at the FSSC currently do not remove localization probability that overlaps the Earth, but these files do remove the probability that overlaps the Earth and renormalizes the remaining PDF. This encodes the assertion that the localization is indeed of an astrophysical nature.</li> </ul> <p>The FITS files are organized with two HDUs:</p> <ul> <li> PRIMARY HDU with some basic metadata about the mission from which the data originated<br> </li> <li> HEALPIX HDU containing header information about the GBM detector pointings, as well as the Sun and Geocenter localizations with respect to Fermi. There are two data fields contained in the extension: <ul> <li> PROBABILITY: the differential localization probability per pixel (NSIDE=128)</li> <li> SIGNIFICANCE: integrated probability for estimating confidence intervals (NSIDE=128)</li> </ul> </li> </ul> <p>Furthermore, we provide images of each localization. The images are a Mollweide projection of the sky, with the 50% and 90% localization confidence regions marked in shaded purple. The location of the Earth from Fermi's perspective is marked in shaded blue.</p> <p>The GBM trigger number associated with each FITS file and image is listed in the filename.</p> <p><strong>References:</strong></p> <p><a href="https://iopscience.iop.org/article/10.3847/1538-4357/ab8bdb">[1] Goldstein, A. et al. 2020, ApJ, 895, 40</a><br> <a href="https://iopscience.iop.org/article/10.1088/0067-0049/216/2/32/meta">[2] Connaughton, V. et al. 2015, ApJS, 216, 32</a></p>
WWLLN Datasets for "A Terrestrial Gamma-ray Flash from the 2022 Hunga Tonga–Hunga Ha'apai Volcanic Eruption"
<p>These data files contain data used in the paper "A Terrestrial Gamma-ray Flash from the 2022 Hunga Tonga–Hunga Ha’apai Volcanic Eruption", M. S. Briggs, S. Lesage, C. Schultz, B. Mailyan, R. H. Holzworth, Geophysical Research Letters, 2022.</p> <p>The authors wish to thank the World Wide Lightning Location Network (WWLLN), a collaboration among over 50 universities and institutions, for providing the lightning location data used in these datasets and in the paper. Additional WWLLN data are available at nominal cost from http://wwlln.net.</p> <p>The file named Fig_1.txt contains the data used to generate Figure 1 in the paper.</p> <p>The first two columns list the time ranges for each histogram bin, in UTC on 2022 January 15, while the final column lists the lightning detection rate, in counts per minute, for all WWLLN sferics located within a 400 km radius of the Hunga Tonga–Hunga Ha’apai volcano.</p> <p>The times when Fermi passed within 1000 km of the volcano, shown as grey bars in Figure 1, are:<br> 03:47:58.5 to 03:52:56.2 UTC<br> 05:29:25.1 to 05:33:59.7 UTC<br> 07:11:04.0 to 07:15:18.3 UTC<br> 08:52:04.8 to 08:57:05.1 UTC<br> 10:33:48.1 to 10:37:32.7 UTC</p> <p>The time of the Fermi TGF detection, shown as a red line in Figure 1, is:<br> 08:52:40.011500 UTC</p> <p><br> The file named Fig_2.txt contains the WWLLN sferic data used to generate Figure 2 in the aforementioned paper.</p> <p>This file has the same format as the text files for the WWLLN maps provided in the Fermi GBM TGF catalog, https://fermi.gsfc.nasa.gov/ssc/data/access/gbm/tgf/.</p> <p>Line 1 is the network_name<br> Line 2 is TGF_name<br> Line 3 is the coordinates of Fermi at the time of the TGF (2022-01-15 08:52:40.011500 UTC).<br> Line 4 is the coordinates of the center of the map<br> The second number on line 5 is the number of sferics in a +/- 1 minute interval about the TGF.<br> The remaining 104 lines list the properties of each sferic in columns containing the following information:<br> sequence_number, longitude, latitude, time_separation_between_sferic_and_TGF_corrected_for_light-travel-time</p> <p>The two GLM lightning flashes, shown as magenta dots in Figure 2, have longitude and latitude values:<br> -175.27394, -20.9348<br> -175.29301, -20.8466</p> <p>All of the aforementioned longitudes are East longitudes.<br> </p>
Supporting information for the paper: The temporal relationship between Terrestrial Gamma-ray flashes and associated optical pulses from lightning
<p>Supporting information for the paper: The temporal relationship between Terrestrial Gamma-ray flashes and associated optical pulses from lightning, consisting of 2 data files and 221 presentations of TGF-Optical emission events observed by ASIM between end of March 2019 and November 2020.</p> <p>See 0_READ_ME for information about the individual files and variables.</p>
IODP Expedition 352 Natural gamma radiation
<p>Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.</p>
IODP Expedition 351 Natural gamma radiation
<p>Natural gamma radiation (NGR) data in the ~0.1 to 3.0 MeV range were measured using eight custom-designed sodium iodide (thallium) [NaI(Tl)] detectors arranged along the core measurement axis at 20 cm intervals. The NGR system uses layers of passive shielding (lead) and active shielding (plastic scintillators and coincidence electronics) to reduce the cosmic-ray signal for low-count analysis of sediment core sections and to obtain the maximum signal-to-noise ratio. Data are reported on a total counts per second basis and the raw spectral files are available as compressed files for later analysis.</p>
Data release associated with ``Search for Coincident Gravitational Wave and Long Gamma-Ray Bursts from 4-OGC and the Fermi-GBM/Swift-BAT Catalog"
<p>This is associated data release for the paper https://arxiv.org/abs/2208.03279. It contains the skymaps from potential gravitational-wave candidates from binary neutron star or neutron star-black hole merger. The notebook showcases how to use it. More information can be found in the github repository: https://github.com/gwastro/gw-longgrb</p> <pre> </pre> <pre> </pre>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
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