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261 results for “gamma-ray”
Supporting information for a rapid gamma-ray flux reduction paper
<p>Supporting data and information needed to reproduce the described in the paper results and conclusions.</p>
Figure data for the paper: "Spectral Observations of Optical Emissions Associated with Terrestrial Gamma-Ray Flashes"
<p>This repository contains 13 files with data which were used to produce the figures in the paper "Spectral Observations of Optical Emissions Associated with Terrestrial Gamma-Ray Flashes" by Heumesser et al. The description of the different files is included in the supporting information of the paper and additionally uploaded here, see "2020GL090700_OpticalEmissionsAssociatedwithTGFs_SupportingInformation".</p>
Dataset for neutron and gamma-ray pulse shape discrimination: radiation pulse signals and discrimination methodologies
<p>This dataset provides neutron and gamma-ray pulse signals for pulse shape discrimination experiments. Serval traditional and recently proposed pulse shape discrimination algorithms are utilized to conduct pulse shape discrimination under raw pulse signals and noise-enhanced datasets. These algorithms include zero-crossing (ZC), charge comparison (CC), falling edge percentage slope (FEPS), frequency gradient analysis (FGA), pulse-coupled neural network (PCNN), ladder gradient (LG), and heterogeneous quasi-continuous spiking cortical model (HQC-SCM). This dataset also provides the source code of all these pulse shape discrimination methods, together with the source code of schematic pulse shape discrimination performance evaluation and anti-noise performance evaluation. Detailed descriptions of this dataset can be found at: https://doi.org/10.48550/arXiv.2305.18242.</p>
Supporting Information for "First Results of Terrestrial Gamma-ray Flash observations by Insight-HXMT"
<p>The compressed file contains data for 282 HXMT Terrestrial Gamma-ray Flashes (TGFs), spanning from T0-1 second to T0+1 second. Below is a description of the data format included in the file.</p> <p>[HXMT 1K Science Data Description]</p> <p>1. The "Time" column represents the Mission Elapsed Time (MET) in seconds for HXMT, starting from 2012-01-01T00:00:00.</p> <p>2. The "Det_ID" column indicates the detector index for the 18 HXMT/HE NaI/CsI detectors, ranging from 00 to 17.</p> <p>3. The "Channel" column refers to the energy channel for HXMT/HE NaI/CsI detectors, which spans from 0 to 255. Data filtering often uses "Channel>30" to exclude lower energy events.</p> <p>4. The "Pulse_Width" column measures the pulse width of the detector signal in milliseconds. For HXMT/HE data, a Pulse Width value of N translates to N/48 ms. To filter the data, "Pulse_Width>75" is commonly used.</p> <p>5. The "ACD" column presents data from the anticoincidence detectors of the HXMT/HE Anti-Coincidence Detector (ACD). This data consists of an array of 18 boolean values, each corresponding to a specific ACD. For instance, if the first value in the array is 1, it indicates that the event was simultaneously detected by ACD-01; conversely, a 0 in the second position signifies that ACD-02 did not detect the event at the same time. Typically, events detected by any ACD are excluded from data analysis. Conversely, events are included in data analysis when all ACD values are 0.</p> <p>6. The "Event_Type" column describes the operational modes of the detector: 0 for normal-gain mode and 1 for low-gain mode.</p> <p>Details on the NaI/CsI and ACD detector installation positions and the relationship between energy and channel for both normal-gain and low-gain modes can be found in Song et al. 2022.</p>
Production of Terrestrial Gamma-ray Flashes During the Early Stages of Lightning Flashes
<p>Supporting data to the paper "Production of Terrestrial Gamma-ray Flashes During the Early Stages of Lightning Flashes", Lindanger et al., 2022, JGR</p>
Data relating to "Millisecond Pulsars from Accretion Induced Collapse as the Origin of the Galactic Centre Gamma-ray Excess Signal"
<p>Data describe the evolution of a population of millisecond pulsars (MSPs) born from Accretion Induced Collapse.</p> <p>Data entries are comma-separated.</p> <p>The formation and subsequent evolution of 9194 MSPs have been modelled with code based on the BSE Code [see Hurley, J. R., Pols, O. R. & Tout, C. A. Comprehensive analytic formulae for stellar evolution as a function of mass and metallicity. Mon. Not. Roy. Astron. Soc. 315, 543–569 (2000)].</p> <p>For each MSP, the first row describes the magnetic field B (in Gauss) and the inclination angle (i, in radians) between magnetic & rotational axes.</p> <p>These quantities (B,i) do not evolve.</p> <p>Thus, every row containing only two entries indicates the beginning of the data covering a separate MSP.<br> For subsequent rows, there are seven entries in each row.</p> <p>The first entry in each row is the (discretised) time in units of Gyr since the star formation event when the MSP is formed. 0.1 is the minimum time possible time for which an MSP can be born. Subsequent discrete time steps are 0.1 Gyr. The last row for every MSP is for a time of 15.9 Gyr. </p> <p>Subsequent entries show (as a function of time)</p> <p>period (in s)</p> <p>period derivative dP/dt (s/s)</p> <p>NS mass (in units of solar masses)</p> <p>secondary mass (in units of solar masses)</p> <p>secondary type (for an explanation of secondary type label see Hurley, J. R., Pols, O. R. & Tout, C. A. Comprehensive analytic formulae for stellar evolution as a function of mass and metallicity. Mon. Not. Roy. Astron. Soc. 315, 543–569 (2000).</p> <p>orbital separation</p>
Supplementary material: Multi-wavelength view of the close-by GRB~190829A sheds light on gamma-ray burst physics
<p>This repository contains supplementary data regarding the article "Multi-wavelength view of the close-by GRB~190829A sheds light on gamma-ray burst physics" published by the Astrophysical Journal Letters.</p> <p>In particular, the repository contains:</p> <ul> <li>Markov Chain Monte Carlo samples for both the afterglow modelling and the circular gaussian fits to VLBI data</li> <li>clean radio images, residuals and UV coverage plots for all our VLBI epochs</li> </ul> <p>Data formats should be self-explanatory. Do not hesitate to contact us at omsharan.salafia@gmail.com for any question.</p>
Data files for "Curvature in the very-high energy gamma-ray spectrum of M87"
<h1>Summary</h1> <p>In this repository, we provide some auxiliary material in connection to our paper “Curvature in the very-high energy gamma-ray spectrum of M87" accepted for publication in the Astronomy and Astrophysics (A&A) Journal and available on Arxiv through the ID <a href="https://arxiv.org/abs/2402.13330" target="_blank" rel="noopener">arXiv:2402.13330</a>. For the full list of authors, please refer to the paper.</p> <p>In the publication, we study the very-high energy gamma-ray spectrum of a stacked high emission state of M87 using H.E.S.S. observations. We detect a curvature in the spectrum that is not related to the EBL absorption. In addition to that, we show that the gamma-gamma absorption by star light from the galaxy is weak to explain the measured curvature and that it is unlikely that different high states with similar spectral distribution could be able to explain the same curvature.</p> <h1>Data and example code</h1> <h2>ECSV tables</h2> <p>The ecsv tables provide the means to reproduce the figures found in the paper. They can be opened with `astropy.QTable` as demonstrated below.</p> <pre><code>from astropy.table import QTable table = QTable.read('Fig1_lightcurve_table.ecsv') print(table)</code></pre> <p>The following example shows how to reproduce Fig. A2 from the paper (the modules imported are needed in the loaded enviroment):</p> <pre><code>from astropy.table import QTable from scipy.stats import gmean %matplotlib inline import matplotlib.pyplot as plt import numpy as np import seaborn as sns from ebltable.ebl_from_model import EBL cmap = sns.color_palette("colorblind", as_cmap=True) colors = sns.color_palette("colorblind", 6) ebl = {} for m in ["finke2022", "kneiske", "dominguez-upper"]: ebl[m] = EBL.readmodel(m) lmu = np.logspace(-1,3.,100) z = 0.0042 nuInu = {} for m, e in ebl.items(): nuInu[m] = e.ebl_array(z,lmu) nuInu table = QTable.read('FigA2_EBL_ULs.ecsv') wavelengths = table["Wavelength"].value wavelengths = wavelengths counter = 0 for m in ["finke2022", "kneiske", "dominguez-upper"]: plt.loglog(lmu,nuInu[m], lw = 2.,label=f"{m} UL", color=colors[counter] ) ULs = table[f"{m} UL"][(wavelengths>12.4)*(wavelengths<40)].value plt.loglog(wavelengths[(wavelengths>12.4)*(wavelengths<40)],ULs, lw = 2., label = f"UL (this work)", ls='dashed', color=colors[counter]) plt.arrow(gmean(wavelengths[(wavelengths>12.4)*(wavelengths<40)]), np.median(ULs), 0, -0.2*np.median(ULs), head_width=5 ,head_length=0.1*np.median(ULs), alpha=0.5, color=colors[counter]) counter+=1 plt.gca().set_xlabel('Wavelength ($\mu$m)',size = 'x-large') plt.gca().set_ylabel(r'$\nu I_\nu (\mathrm{nW}\,\mathrm{sr}^{-1}\mathrm{m}^{-2})$',size = 'x-large') plt.legend(loc = 'lower center', ncol = 2) plt.tight_layout() plt.show()</code></pre> <h2>Text files</h2> <p>The text files provide the gammapy fit results for the various analyses in the main text of the paper. For a complete definition of the models, we refer the reader to the paper. The name of the file is given by <em>fit_stacked_M87_<strong>MODEL</strong>_flux_90perc_<strong>ENERGYRANGE</strong>_90perc.txt</em>, where <strong>MODEL</strong> is the spectral model fitted (e.g., <em>PLxEBLfinke2022</em> or <em>PLxEBLfinke2022-free</em> in case the EBL intensity alpha_norm is a free parameter) and <strong>ENERGYRANGE</strong> is the energy range of the reduced dataset (e.g., <em>0.3_31.6TeV</em>).</p> <p> </p>
Supporting information for the paper "Evidence of a new population of weak Terrestrial Gamma-ray Flashes observed from aircraft altitude" by I. Bjørge-Engeland et al.
<p>Supporting data for the paper "Evidence of a new population of weak Terrestrial Gamma-ray Flashes observed from aircraft altitude" by I. Bjørge-Engeland et al. </p>
Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes
<p>The data supports the manuscript entitled “Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes<br> ” that is under review in GRL. These files can be opened by MATLAB. The data can be used freely for scientific purposes with appropriate citation.</p>
Data for "Source Altitude of Energetic In-cloud Pulses Inside Thunderstorms and Implication for the Intrinsic Brightness of Terrestrial Gamma-Ray Flashes"
<p>The spreadsheet contains detailed information for the EIP events analyzed in this work, including the time, location, peak current, distance to sensors, estimated source height, height error, etc. </p> <p>The compressed file in this dataset contains the low-frequency waveforms of EIPs measured by Duke and FIT sensors. The modeled skywaves are shown in the figures. The cross-correlation coefficient between the measured skywaves and the modeled waveforms of each event are also presented. </p> <p> </p>
Inlists for "Rethinking Thorne-Żytkow Object Formation: The Fate of X-ray Binary LMC X-4 and Implications for Ultra-long Gamma-ray Bursts"
<div> <div> <div> <p>We use the MESA Isochrones and Stellar Tracks (MIST) package (Dotter 2016; Choi et al. 2016) with MESA v7503 (Paxton et al. 2011, 2013, 2015) and mesasdk x86_64-linux-20141212 revision 245. </p> </div> </div> </div>
Energetic Compact Strokes as the Major Source of Downward Terrestrial Gamma-ray Flashes in Winter Thunderstorms
<p>ECS-TGF_10km.csv contains a list of ECSs in Figure 1. Raw FALMA waveforms of these ECSs are in FALMA_wave.zip. For each ECS, waveforms of one or two seconds recorded at one FALMA site are provided. Some waveform data contain a PPS pulse. See PPS_pulse.txt in FALMA_wave.zip for more details. The format of waveform data is described at https://tingwu.info/pylab/lab05.html.</p> <p>ECS_100km.csv contains a list of ECSs in Figure 5.</p>
Radio and gamma-ray timing of TRAPUM L-band Fermi pulsar survey discoveries - Supplementary material
<p>Timing ephemerides for the redback pulsar J1803-6707 (published in <em>"Radio and gamma-ray timing of TRAPUM L-band \textit{Fermi} pulsar survey discoveries"</em>, Burgay et al 2024, A&A) covering 15 years of Fermi data. The ephemeris are provided both in "ORBIFUNC" (to be used with timing software <a href="https://bitbucket.org/psrsoft/tempo2/src/master/" target="_blank" rel="noopener">tempo2</a>) and "ORBWAVES" (with <a href="https://github.com/nanograv/PINT" target="_blank" rel="noopener">PINT</a>) formats. The ORBIFUNC parameters are a time-domain interpolating function describing the orbital phase variations over time, while the ORBWAVES parameters are the Fourier-domain representation of the same function.</p>
Ground Gamma-ray Spectrometry Data of the Cerro do Jarau Impact Structure
<p>This is gamma-ray dataset that was collected during two field campaings in the Cerro do Jarau impact structure in Brazil. The Cerro do Jarau structure is a ~13.5 km diameter impact structure located in southern Brazil and formed on Cretaceous continental flood basalts of the Serra Geral Formation and underlying sedimentary strata. The available file provides the raw dataset in counts per unit of time; concentration values of K, U along with their respective histograms; and calibration crossplots for each channel.</p>
Mountaintop gamma ray observations of three terrestrial gamma-ray flashes at the Säntis Tower, Switzerland with coincident radio waveforms
<p>We report on the mountain top observation of three terrestrial gamma-ray flashes (TGFs) that occurred during the summer storm season of 2021. To our knowledge, these are the first TGFs observed in a mountaintop environment and the first published European TGFs observed from the ground. A gamma-ray sensitive detector was located at the base of the Säntis Tower in Switzerland and observed three unique TGF events with coincident radio sferic data characteristic of TGFs seen from space. We will show an example of a 'slow pulse' radio signature, an -EIP, and a double peak TGF associated with an extraordinarily powerful and complicated positive-polarity sferic, where each TGF peak is possibly preceded by a short burst of stepped leader emission. </p>
Mountaintop gamma ray observations of three terrestrial gamma-ray flashes at the Säntis Tower, Switzerland with coincident radio waveforms
Open the record for dataset details and reuse information.
Determining a lower limit of luminosity for the first satellite observation of a reverse beam terrestrial gamma-ray flash associated with a cloud to ground lightning leader
Open the record for dataset details and reuse information.
Data used in the publication "The emission of terrestrial gamma-ray flashes associated to streamer coronae of the final leader step"
<p>Simulation data used to create Fig. 2 of "The emission of terrestrial gamma-ray flashes associated to streamer coronae of the final leader step"</p>
Fermi/LAT detection of extraordinary variability in the gamma-ray emission of the blazar PKS 1510-089
Data set of the published paper. There are lightcurves in the gamma-ray energy band in QDP format (*.qdp; *.pco) and the corresponding PS figure. See the paper for details.
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.