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365 results for “neutron”
Constraining the properties of dense neutron star cores: The case of the transient low-mass X-ray binary HETE J1900.1-2455
<p>This is a basic reproduction package for the paper "Constraining the properties of dense neutron star cores: The case of the transient low-mass X-ray binary HETE J1900.1-2455" by <a href="https://doi.org/10.1093/mnras/stab2202">N. Degenaar et al. (2021)</a>. It provides reduced data products, simulated data and scripts to allow the reproduction of the work performed in this paper. It also lists software used and data archives containing the public observational data.</p>
Constraining Neutron-Star Matter with Microscopic and Macroscopic Collisions
<p>Data release associated with the preprint "<em>Constraining Neutron-Star Matter with Microscopic and Macroscopic Collisions</em>'' (2021; <a href="https://arxiv.org/abs/2107.06229">arxiv:2107.06229[nucl-th]</a>)</p> <p>Data includes:</p> <p>EOS files:</p> <ol> <li>chiral effective field theory (CEFT) up to 1nsat and extended with speed-of-sound extension (cse)</li> <li>CEFT up to 1.5 nsat and cse</li> <li>CEFT up to 1.5 nsat and extended with piecewise-polytrope</li> <li>CEFT up to 1.0 nsat, cse and enforced a uniform distribution on a radius for 1.4 solar mass neutron star (R14)</li> <li>CEFT up to 1.5 nsat, cse and enforced a uniform distribution on R14</li> </ol> <p>Posterior probability files: details to be found in README.txt<br> <br> Data used in Fig.1 and Fig.2 are included</p>
Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter: Neutron star equation of state posterior samples
<p>Equation of state posterior samples associated with Legred et al., "Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter," Phys. Rev. D 104, 063003 (2021); doi:10.1103/PhysRevD.104.063003</p> <p> </p> <p>Three sets of 1e4 samples from the posterior distribution over equations of state are provided. These sets are drawn from the posterior conditioned on different combinations of radio pulsar observations, gravitational wave data, and NICER x-ray measurements. The data release contains the equation of state table and the corresponding table of neutron star observables for each sample. The posterior distributions one can generate from these samples approximate those plotted in Figs. 1-6 of the accompanying paper.</p> <p> </p> <p>Refer to the readme for usage information.</p>
Neutron spin echo and intramolecular FRET and DEER-EPR measurements on hGBP1 (human guanylate binding protein 1)
<p>Neutron spin echo (NSE), double electron–electron resonance (<em>DEER</em>) <em>EPR</em>, ensemble time-correlated single photon counting (eTCSPC) fluorescence, and single-molecule detection (SMD) fluorescence spectroscopy data of the human guanylate binding protein 1 (hGBP1).</p> <p>CSH prepared samples for smFRET and performed protein activity assays. TV prepared sampled for EPR measurements. TOP, CSH, and AV performed the smFRET measurements under the supervision of CAMS. TOP analyzed the smFRET measurements. JPK performed and analyzed the EPR measurements.</p>
In-situ neutron diffraction during reversible deuterium loading in Ti-rich and Mn-substituted Ti(Fe,Mn)0.90 alloys - Dataset related to publication
<p>Data type: resume of Rietveld refinement outputs and original refinements</p> <p>Date format: .zip, .opj; .xlsm, .dat, .pcr (Software FullProf package outputs), .inp (Software Topas package outputs)</p> <p>Origin of the data: neutron diffraction patterns from ILL and ISIS, and manual Sievert measurements (PCI curves from home-made Sieverts’ type apparatus from CNRS, ICMPE, Thiais, France)</p> <p>Software needed to plot the data: folders need to be unzipped, Origin, FullProf package and Topas package.</p>
NURBS Enhanced Virtual Element Methods for the Spatial Discretisation of the Multigroup Neutron Diffusion Equation on Curvilinear Polygonal Meshes
<p>This repository holds all of the raw data generated by my C++ code for a paper "NURBS Enhanced Virtual Element Methods for the Spatial Discretisation of the Multigroup Neutron Diffusion Equation on Curvilinear Polygonal Meshes".</p> <p>The C++ code solves the neutron diffusion equation using a novel spatial discretisation called the Virtual Element Method.</p> <p>Alongside the raw data (stored in VTK and HDF5 files) are post-processing python scripts which read the raw data, compute meaningful quantities of interest and generate plots/figures.</p>
Supporting data for "Quantifying the Strength of a Salt Bridge by Neutron Scattering and Molecular Dynamics"
<p>Supporting data for the following published paper: Mason, Jungwirth, Duboué-Dijon, 2019, JPhysChemLett, 10, 3254-3259</p> <p>Contains both data from neutron scattering measurements and input simulation files necessary for reproduction of the work.</p>
Astrophysical constraints on neutron star f -modes with a nonparametric equation of state representation
<p>Data release for Mohanty et al. "<em>Astrophysical constraints on neutron star f-modes with a nonparametric equation of state representation"</em></p> <p>The data release consists of three files: </p> <ol> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR.h5</a> </li> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR+GW.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR+GW.h5</a> </li> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR+GW+NICER.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR+GW+NICER.h5</a> </li> </ol> <p>Each file contains 9,835 samples of EOS draws. The equation of state id's matches those of Legred et. al. 2022</p> <p>The data structure follows Legred, I. (2022) “<em>Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter: Neutron star equation of state posterior samples</em>”. Zenodo. doi: 10.5281/zenodo.6502467.</p> <p>Samples were generated using stanspy, a general relativistic neutron star code written by Sailesh Ranjan Mohanty. </p> <p>Please see the readme (adapted from Legred et. al. 2022 Zenodo. doi: 10.5281/zenodo.6502467) </p>
Reproduction package for: 'Exploring Waveform Variations among Neutron Star Ray-tracing Codes for Complex Emission Geometries'
<p>Data files, python scripts and notebooks to reproduce the code output comparisons performed in "Exploring Waveform Variations among Neutron Star Ray-tracing Codes for Complex Emission Geometries" by Choudhury et al. (2024; <a href="https://doi.org/10.3847/1538-4357/ad7255" target="_blank" rel="noopener"><em>ApJ</em> <strong>975</strong> 202</a>, <a href="https://doi.org/10.48550/arXiv.2406.07285" target="_blank" rel="noopener">arXiv.2406.07285</a>).</p> <p>Please refer to the README for detailed information.</p> <p>N.B. The neutral hydrogen column density (${\rm N}_{\rm H}$) value is mentioned in the paper to be $0.2 \times 10^{20} {\rm cm}^{-2}$, whereas all the analyses in the paper, as reflected in this Zenodo package, actually uses ${\rm N}_{\rm H} = 2 \times 10^{20} {\rm cm}^{-2}$.</p>
Constraining scalar-tensor theories by neutron star-balck hole gravitational wave events
<p>This data release corresponds to the paper "Constraining scalar-tensor theories by neutron star-balck hole gravitational wave events" (<a href="https://arxiv.org/abs/2105.13644">arXiv:2105.13644</a>). In this paper, we consider three specific models of scalar-tensor theories, including the Brans-Dicke theory (BD), the theory with scalarization phenomena proposed by Damour and Esposito-Far\`{e}se (DEF), and Screened Modified Gravity (SMG). From all 4 possible NSBH events so far, we use two of them to place the constraints. The other two are excluded in this work due to the possible unphysical deviations. Four equations of state (EoSs), <em>sly</em>, <em>alf2</em>, <em>H4</em> and <em>mpa1</em>, are used to derive the scalar charges of neutron stars for BD and DEF. The constraints are obtained by performing the full Bayesian inference with the help of the open source software <a href="https://git.ligo.org/lscsoft/bilby">Bilby</a>.</p> <p>This dataset contains all posterior samples of the runs discussed in the paper. The models and EoSs can be read form the filenames for the runs of BD and DEF. The files of "<em>*_half_dipole.json</em>" correspond to the runs for constraining the dipole radiation without considering specific model parameters. All files are JSON format which is the default output format of <a href="https://git.ligo.org/lscsoft/bilby">Bilby</a>. They are human readable and also can be processed or visualized by <a href="https://git.ligo.org/lscsoft/bilby">Bilby</a> or <a href="https://git.ligo.org/lscsoft/pesummary">PESummary</a> conveniently.</p>
Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter : Weighted Monte Carlo samples for neutron star observables
<p>This data release contains weighted Monte Carlo samples associated with</p> <p>Legred, Chatziioannou, Essick, Han, and Landry, 2021</p> <p>"Impact of PSR J0740+6620 radius constraint on the properties of high-density matter"</p> <p>Phys. Rev. D 104, 063003;</p> <p>doi:10.1103/PhysRevD.104.063003</p> <p> </p> <p> </p> <p> </p> <p> </p>
Soil Moisture taken with a neutron probe 1969-1974 from 11 sites: Weekly
These original basic fertilization experiments were started to give preliminary information for designing future experiments and to study basic long term fertilization responses in a range of age classes for the dominant forest types of interior Alaska. In addition, the instrumentation of the control plots provide long term information on various environmental parameters. No fertilization or growth measurements were done in the black spruce stands.
Soil volumetric water content calculated from neutron hydroprobe data along the LTER-I transects (control and fertilized) at the Jornada Basin LTER, 1986-ongoing
This data package contains volumetric water content (VWC) measurements calculated from soil neutron hydroprobe data collected on the permanent LTER-I transects located at Chihuahuan Desert Rangeland Research Center (CDRRC) in the Jornada Basin of southern New Mexico, USA. The control and treatment transects are parallel to each other and are 2.7 km in length extending from the middle of the College Playa to the foot of Mt. Summerford. The treatment transect was treated annually with ammonium nitrate fertilizer (NH4NO3 at 10g N/m2/yr) until 1987. Measurement stations are located at 30 meter intervals along each transect, and there are neutron probe access tubes located every station on the control transect (n=89) and at every fifth station at the treatment transect (n=19). Measurements were taken at 5 depths using a neutron probe (CPN Model 503DR Hydroprobe) and were then converted to VWC at 30 cm, 60 cm, 90 cm, 110 cm, and 130 cm depths. Neutron probe VWC readings taken in 3 non-weighing mini-lysimeters along each transect are also included. This dataset consists of the calculated water content (cm3 water/cm3 soil) obtained by applying site-specific calibration equations to data derived from the thermalized neutron counts found in EDI packageID knb-lter-jrn.210001001. Measurements were taken at 2 week intervals from April 1982 to 1987 and monthly thereafter. Data collection for this study is ongoing.
Soil volumetric water content calculated from neutron hydroprobe data at 15 NPP study sites at the Jornada Basin LTER, 1989-2011 (Deprecated)
This data package contains soil water content data calculated from monthly neutron hydroprobe count measurements made at 15 net primary production (NPP) study locations on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Once a month, neutron probe measurements are made at 10 depths (where possible) at each of 10 access tubes at each of the 15 NPP sites using a neutron probe (CPN Model 503DR Hydroprobe). The raw dataset, also on EDI (knb-lter-jrn.210013001), consists of the count of thermalized neutrons at 30 cm depth intervals to a maximum depth of 300 cm. In this data package, the raw neutron counts have been converted to volumetric water content (VWC) to a maximum depth of 270 cm using calibration equations (deepest probe depths are excluded from VWC calculations). The NPP sites these measurements are made at represent the 5 dominant vegetation types of the Jornada Basin, which consist of 3 shrub (creosotebush, mesquite dune, and tarbush) and 2 grass (upland grassland and playa) types. Three NPP sites are located in each of the types. This data collection is ongoing with new data collected monthly. NOTE: This data package is deprecated and will not be updated in the future. These VWC values were calculated using a now-outdated calibration method. Values of VWC calculated with the improved and fully documented calibration method are available in another EDI data package (knb-lter-jrn.210013003).
Data Accompanying "Dynamics of Water Absorption in Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography"
<p>These are the datasets analysed in the publication "Dynamics of Water Absorption in<br> Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography" by Stavropoulou <em>et al.</em> in 2020 in Frontiers in Earth Science, DOI: <a href="https://doi.org/10.3389/feart.2020.00006">https://doi.org/10.3389/feart.2020.00006</a></p> <ol> <li>File 1 contains the 3D reconstructed x-ray and neutron tomography volumes analysed in the paper. State 002 is taken as a reference and the greylevels of all images in the times series for both x-ray and neutrons are rescaled using two characteristic image features (top-cap and air in the case of x-rays) linearly to align with 002. Neutron volumes are rescaled to the same pixel size as 2-bin x-ray volumes, and a mean registration is applied to align neutrons with x-rays.<br> Furthermore, a bilateral filter is applied to the neutron tomographies (domain sigma = 1, range sigma=3000).<br> Full scale images are available at <a href="https://doi.ill.fr/10.5291/ILL-DATA.UGA-42">https://doi.ill.fr/10.5291/ILL-DATA.UGA-42</a><br> </li> <li>File 2 contains the joint histograms for registered pairs of images, as visible in Figure 4 and Figure 5.<br> </li> <li>File 3 contains the results of the digital volume correlation performed with the <a href="https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html">spam</a> tookit.<br> The overall "registration" is used to create Figure 6<br> The global correlations available in "gdic" are used to create Figures 7, 8 and 9.</li> </ol>
Time-of-flight neutron tomography
<p>This dataset contains the wavelength-resolved neutron tomography of a contrast sample imaged with the time-of-flight (TOF) transmission imaging method at the IMAT beamline at the ISIS pulsed neutron source. The sample is made of several polycrystalline materials: nickel, iron, titanium, lead, copper and aluminium</p> <p>The data are pre-processed for the detector event overlap correction, binned in the TOF axis and cropped. The datasets can be used for replicating the tomographic reconstruction as described in (Carminati et al 2020, https://doi.org/10.1107/S1600576720000151), or for further analysis.</p>
Neutron powder diffraction data from solid nitrogen in the range 6K-70K
<p>Neutron powder diffraction patterns from nitrogen solidified in-situ. This data accompanies a submitted paper.</p>
Datasets for "Hall cascade with fractional magnetic helicity in neutron star crusts"
<pre>The run directories contain time series and spectra as text files and other secondary data as idl save files. They can be read directly with the corresponding idl routines that are in the directory run_directories/run_idl. The run directories can be used to rerun the cases with the Pencil Code (https://github.com/pencil-code).</pre>
r-process abundances in neutron-rich merger ejecta given different theoretical nuclear physics inputs
<p>This data release contains nucleosynthesis predictions for the r-process abundances presented in Côté, Eichler, Yagüe, Vassh et al. (2021) for compact object merger ejecta based on the publicly available simulation trajectories of Rosswog et al. (2013). All ejecta for the merger scenarios considered here are very neutron-rich (Ye ~ 0.016-0.11). Calculations were performed with the PRISM code (Mumpower et al. 2018) which accounts for nuclear reheating (here with a reheating efficiency of 50%). Results are reported for several different theoretical nuclear physics inputs but all calculations make use of the GEF fission yield prescription (see Vassh et al. 2019). All abundances are given at 1 Myr (10^6 years) post-merger. Please see the README file for more details and references.</p> <p>When using these nucleosynthesis yields, please cite this Zenodo data release (Vassh et al. 2021), and refer to Vassh et al. (2019) and Côté, Eichler, Yagüe, Vassh et al. (2021) for further details on the nuclear data applied as well as Rosswog et al. (2013), Piran et al. (2013), and Korobkin et al. (2012) for further details on the merger ejecta trajectories.</p>
How loud are neutron star mergers?
<p>We release neutron star merger waveforms computed using fully general relativistic simulations of equal and unequal-mass binaries drawn from the galactic population. The simulations employ finite-temperature microphysical equations of state (LS220, DD2, and SFHo) and neutrino cooling. Please, see</p> <p>http://arxiv.org/abs/1512.06397</p> <p>for details.</p> <p> </p> <p>Each tarball refers to a simulation and contains</p> <ul> <li>Curvature multipolar waveform <span class="math-tex">\(\psi^{(4)}_{\ell m}\)</span></li> <li>Metric multipolar waveform <span class="math-tex">\(h_{\ell m}\)</span></li> <li>Radiated energy and angular momentum</li> </ul> <p>Files:</p> <ul> <li><em>waveforms/Psi4_l?_m?_r200.txt </em> <ul> <li>Columns: <span class="math-tex">\(t,\ \Re{(\psi^{(4)}_{\ell m})},\ \Im{(\psi^{(4)}_{\ell m})} \)</span></li> </ul> </li> <li><em>waveforms/Rh_l?_m?_r200.txt</em> <ul> <li>Columns: <span class="math-tex">\(u/M,\ \Re{(h_{\ell m})}/M,\ \Im{(h_{\ell m})}/M,\ \Re{(\dot{h}_{\ell m})},\ \Im{(\dot{h}_{\ell m}}),\ M\omega_{\ell m},\ A_{\ell m}/M,\ \phi_{\ell m},\ t \)</span></li> </ul> </li> <li><em>waveforms/Ej_r200.txt</em> <ul> <li>Columns: <span class="math-tex">\(E_b,\ j,\ E_\text{rad},\ J_\text{rad},\ t \)</span></li> </ul> </li> </ul> <p>where</p> <ul> <li><span class="math-tex">\(t\)</span> simulation time</li> <li><span class="math-tex">\(u\)</span> retarded time</li> <li><span class="math-tex">\(M\)</span> binary mass</li> <li><span class="math-tex">\(\omega_{\ell m}\)</span> wave frequency</li> <li><span class="math-tex">\(A_{\ell m}\)</span> wave amplitude</li> <li><span class="math-tex">\(\phi_{\ell m}\)</span> wave phase</li> <li><span class="math-tex">\(E_\text{GW}\)</span> radiated energy</li> <li><span class="math-tex">\(J_\text{GW}\)</span> radiated angular momentum</li> <li><span class="math-tex">\(E_b\)</span> binary energy</li> <li><span class="math-tex">\(j\)</span> binary specific angular momentum</li> </ul> <p>Please refer to the paper and references therein for the definition of the different quantities.</p> <p>Units <span class="math-tex">\(c=G=M_\text{Sun}=1\)</span></p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.