University of Rennes

About: University of Rennes is a education organization based out in Rennes, France. It is known for research contribution in the topics: Population & Crystal structure. The organization has 18404 authors who have published 40374 publications receiving 995327 citations.

GW170817: Implications for the Stochastic Gravitational-Wave Background from Compact Binary Coalescences

Abstract: The LIGO Scientific and Virgo Collaborations have announced the event GW170817, the first detection of gravitational waves from the coalescence of two neutron stars. The merger rate of binary neutron stars estimated from this event suggests that distant, unresolvable binary neutron stars create a significant astrophysical stochastic gravitational-wave background. The binary neutron star component will add to the contribution from binary black holes, increasing the amplitude of the total astrophysical background relative to previous expectations. In the Advanced LIGO-Virgo frequency band most sensitive to stochastic backgrounds (near 25 Hz), we predict a total astrophysical background with amplitude ΩGW(f=25 Hz)=1.8 +2.7 −1.3×10−9 with 90% confidence, compared with ΩGW(f=25 Hz)=1.1 +1.2 −0.7×10−9 from binary black holes alone. Assuming the most probable rate for compact binary mergers, we find that the total background may be detectable with a signal-to-noise-ratio of 3 after 40 months of total observation time, based on the expected timeline for Advanced LIGO and Virgo to reach their design sensitivity.

Quantitative evaluation of indentation-induced densification in glass

Abstract: To estimate the ratio of densification to Vickers indentation volume, three-dimensional images of Vickers indentations on several glasses, including silicate glasses and bulk metallic glass (BMG), were obtained before and after annealing using an atomic force microscope. Large volume recovery of Vickers indentation by annealing was observed for all glasses but BMG. Following previous studies, this recovered volume almost corresponded to the densified volume under a Vickers indenter, and the compositional dependence of densification was discussed. The ratios of densification to the total indentation volume for silica and soda-lime glasses were 92% and 61%, respectively. It was concluded that densification was a general property for silicate glasses and that the ratios of densification to the total indentation volume for all the glasses correlated well with Poisson’s ratios of the glasses.

Estimating the Contribution of Dynamical Ejecta in the Kilonova Associated with GW170817

Abstract: The source of the gravitational-wave (GW) signal GW170817, very likely a binary neutron star merger, was also observed electromagnetically, providing the first multi-messenger observations of this type. The two-week-long electromagnetic (EM) counterpart had a signature indicative of an r-process-induced optical transient known as a kilonova. This Letter examines how the mass of the dynamical ejecta can be estimated without a direct electromagnetic observation of the kilonova, using GW measurements and a phenomenological model calibrated to numerical simulations of mergers with dynamical ejecta. Specifically, we apply the model to the binary masses inferred from the GW measurements, and use the resulting mass of the dynamical ejecta to estimate its contribution (without the effects of wind ejecta) to the corresponding kilonova light curves from various models. The distributions of dynamical ejecta mass range between = - - - M M ej 10 10  3 2 for various equations of state, assuming that the neutron stars are rotating slowly. In addition, we use our estimates of the dynamical ejecta mass and the neutron star merger rates inferred from GW170817 to constrain the contribution of events like this to the r-process element abundance in the Galaxy when ejecta mass from post-merger winds is neglected. We find that if 10% of the matter dynamically ejected from binary neutron star (BNS) mergers is converted to r-process elements, GW170817-like BNS mergers could fully account for the amount of r-process material observed in the Milky Way.

Ica: a potential tool for bci systems

Abstract: Several studies dealing with independent component analysis (ICA)-based brain-computer interface (BCI) systems have been reported. Most of them have only explored a limited number of ICA methods, mainly FastICA and INFOMAX. The aim of this article is to help the BCI community researchers, especially those who are not familiar with ICA techniques, to choose an appropriate ICA method. For this purpose, the concept of ICA is reviewed and different measures of statistical independence are reported. Then, the application of these measures is illustrated through a brief description of the widely used algorithms in the ICA community, namely SOBI, COM2, JADE, ICAR, FastICA, and INFOMAX. The implementation of these techniques in the BCI field is also explained. Finally, a comparative study of these algorithms, conducted on simulated electroencephalography (EEG) data, shows that an appropriate selection of an ICA algorithm may significantly improve the capabilities of BCI systems.