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5,462 results for “binary”
Binary black-hole simulation SXS:BBH:1655
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:1901
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:1681
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:1723
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:1947
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:2051
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:0710
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:1387
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Simulations from: Formation of the first three gravitational-wave observations through isolated binary evolution
<p>The results of all simulations shown and discussed in "<a href="https://www.nature.com/articles/ncomms14906">Formation of the first three gravitational-wave observations through isolated binary evolution</a>", published in Nature Communications, 8, 14906 (<a href="https://arxiv.org/abs/1704.01352">arXiv</a>).</p> <p>Contents:</p> <p>README<br> Z0_002_LVT151012_1475624202.dat<br> Z0_001_GW150914_1394278271.dat<br> Z0_002_allMergers.dat<br> Z0_001_GW151226_294773844.dat<br> Z0_002_alphalambda0_01_allMergers.dat<br> Z0_001_LVT151012_784739229.dat<br> Z0_002_fLBV_10_allMergers.dat<br> Z0_001_allMergers.dat<br> Z0_005_GW151226_1432529107.dat<br> Z0_001_alphalambda0_01_allMergers.dat<br> Z0_005_LVT151012_1051180640.dat<br> Z0_001_fLBV_10_allMergers.dat<br> Z0_005_allMergers.dat<br> Z0_002_GW151226_997696601.dat</p> <p>All simulations made using <a href="http://compas.science/">COMPAS</a></p>
Age determination of galactic B-type stars in double-lined eclipsing binaries
<p>We present the results of age determination for galactic B-type main sequence stars which are components of double-lined eclipsing binaries. Only detached systems are considered. We analyze 38 binary systems that meet such criteria. The analysis is based on evolutionary computations and we consider that the age is determined if there is a common value from the radius−age diagrams and the agreement in the position of both components in the Hertzsprung-Russell diagram. In some cases, to meet these two conditions, it was necessary to adjust the value of the metallicity, Z or/and the parameter of overshooting from the convective core, αov. We determine the consistent age for 33 binaries out of 38. Besides, we made an extensive computations and for each system we give the range of αov and Z, for which the consistent solutions exist. The age of the studied B-type main sequence stars ranges, as counted from the Zero Age Main Sequence, from about 2.5 Myr to about 200 Myr.</p>
wide binaries from Gaia DR2
<p>This is a catalog of 378,488 wide binary candidates selected using data from Gaia DR2. The catalog construction procedure is similar to that outlined in <a href="https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.4884E/abstract">this</a> paper, but the search is extended to larger distances (d < 1 kpc), lower astrometric SNR (parallax_over_error > 10), and wider separations (s < 1 pc). </p> <p>The included pdf shows the separation distribution, and the red dashed line shows an estimate of the contamination rate from chance alignments. For the full catalog, contamination is negligible at s < 50,000 AU, but it becomes dominant at wider separations, such that it completely overwhelms the real binaries at s ~ 1 pc. It is, however, possible to construct subsamples that are pure out to wider separations by selecting binaries with (a) larger parallaxes, (b) higher astrometric SNR, or (c) larger plane-of-the-sky velocities with respect to the Sun. </p> <p>If you use this catalog for your research, please cite this dataset and the paper linked above. For questions or comments, contact Kareem El-Badry. </p>
Ultra-luminous X-ray sources and neutron-star-black-hole mergers from very massive close binaries at low metallicity
<p>MESA inlists, run_star_extras, and data associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017A&A...604A..55M">Marchant et al. (2017)</a>. MESA version 8118.</p> <p>Publication DOI: <a href="https://doi.org/10.1051/0004-6361/201630188">10.1051/0004-6361/201630188</a></p> <p>Files are also available in a gihub repository <a href="https://github.com/orlox/mesa_input_data/tree/master/2016_ULX">here</a></p> <p>Upload includes post-processed simulation output in the files Z-XX.tar.xz, where XX represents the metallicity (Z-25.tar.gz is for a metallicity of log10(Z)=-2.5). Each folder inside the archive corresponds to a single MESA simulation, with the name indicating the value of log10(M_1), q=M2/M1 and the orbital period in days. For example, the directory 1.600_0.500_0.900 corresponds to the simulation with log10(M1/Msun)=1.6, M2/M1=0.5 and Porb=0.9 days. Each folder is also a MESA template folder, containing all input files neccesary to reproduce that individual simulation.</p> <p>The file summary_tables.tar.gz contains summarized information for each simulation in ascii format.</p>
Animations for "Remnants of Subdwarf Helium Donor Stars Ejected from Close Binaries with Thermonuclear Supernovae"
<p>Movies showing time evolution of the density in the z=0 plane for each of the seven Athena++ models in the paper. Each movie file corresponds to one model, labeled according to donor model number and the kinetic energy of the explosion in units of 10<sup>51</sup> ergs.</p>
VPS: Excavating High-Level C++ Constructs from Low-Level Binaries to Protect Dynamic Dispatching - (Evaluation Data)
<p>Evaluation data of the published paper: "VPS: Excavating High-Level C++ Constructs from Low-Level Binaries to Protect Dynamic Dispatching". The paper was published at the Annual Computer Security Applications Conference (ACSAC) 2019.</p> <p>The paper is available at: https://www.syssec.ruhr-uni-bochum.de/research/publications/VPS/</p> <p> </p> <p>Ab­stract</p> <p>Po­ly­mor­phism and in­heri­t­an­ce make C++ sui­ta­ble for wri­ting com­plex soft­ware, but si­gni­fi­cant­ly in­crea­se the at­tack sur­face be­cau­se the im­ple­men­ta­ti­on re­li­es on vir­tu­al func­tion ta­bles (vta­bles). These vta­bles con­tain func­tion poin­ters that at­ta­ckers can po­ten­ti­al­ly hi­jack and in prac­tice, vta­ble hi­ja­cking is one of the most im­portant at­tack vec­tor for C++ bi­na­ries. In this paper, we pre­sent VTa­ble Poin­ter Se­pa­ra­ti­on (VPS), a prac­tical bi­na­ry-le­vel de­fen­se against vta­ble hi­ja­cking in C++ ap­p­li­ca­ti­ons. Un­li­ke pre­vious bi­na­ry-le­vel de­fen­ses, which rely on un­sound sta­tic ana­ly­ses to match clas­ses to vir­tu­al call­si­tes, VPS achie­ves a more ac­cu­ra­te pro­tec­tion by re­stric­ting vir­tu­al call­si­tes to va­lidly crea­ted ob­jects. More spe­ci­fi­cal­ly, VPS en­su­res that vir­tu­al call­si­tes can only use ob­jects crea­ted at valid ob­ject con­struc­tion sites, and only if those ob­jects can reach the call­si­te. Mo­re­over, VPS ex­pli­cit­ly prevents false po­si­ti­ves (fal­se­ly iden­ti­fied vir­tu­al call­si­tes) from brea­king the bi­na­ry, an issue exis­ting work does not hand­le cor­rect­ly or at all. We eva­lua­te the pro­to­ty­pe im­ple­men­ta­ti­on of VPS on a di­ver­se set of com­plex, re­al-world ap­p­li­ca­ti­ons (Mon­goDB, MySQL ser­ver, Node.js, SPEC CPU2017/CPU2006), show­ing that our ap­proach pro­tects on aver­a­ge 97.8% of all vir­tu­al call­si­tes in SPEC CPU2006 and 97.4% in SPEC CPU2017 (all C++ bench­marks), with a mo­de­ra­te per­for­mance over­head of 11% and 9% geo­me­an, re­spec­tive­ly. Fur­ther­mo­re, our eva­lua­ti­on re­veals 86 false ne­ga­ti­ves in VTV, a po­pu­lar sour­ce-ba­sed de­fen­se which is part of GCC.</p>
Binary black-hole simulation SXS:BBH:0233
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:0290
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:0245
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:0279
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:0252
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
Binary black-hole simulation SXS:BBH:0260
Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.
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.