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Institution

Indian Institute of Technology Bombay

EducationMumbai, India
About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Population & Thin film. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.


Papers
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Journal ArticleDOI
01 Feb 2002-Geology
TL;DR: This paper used SHRIMP (sensitive, high-resolution ion microprobe) U-Pb zircon geochronology to date silicified tuffs bounding the Chorhat Sandstone.
Abstract: Bedding-plane markings in the Chorhat Sandstone (lower Vindhyan), central India, were recently interpreted as burrows produced by triploblastic animals. Because the rocks were thought to be older than 1000 Ma, these structures were regarded as the oldest fossil evidence for metazoan life. However, the biological origin of the markings has been questioned, as has their age. Current age estimates are based on K-Ar, Rb-Sr, and fission- track dates, though some contentious evidence suggests that the rocks may be only 540 Ma. Here we provide the first robust age data for the lower Vindhyan by using SHRIMP (sensitive, high-resolution ion microprobe) U-Pb zircon geochronology to date silicified tuffs bounding the Chorhat Sandstone. Our results show that the sediments were deposited between 1628 ± 8 Ma and 1599 ± 8 Ma. If the Chorhat markings are burrows left by worm-like animals, then our data suggest that complex metazoans had evolved before 1600 Ma, 1 b.y. before the “Cambrian explosion” when animals rapidly diversified and became ecologically dominant. However, given the doubts expressed about the origin of the bedding-plane structures, as well as the surprisingly “old” age of the host rocks, further studies are urgently required to provide supportive evidence.

218 citations

Journal ArticleDOI
B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2, Fausto Acernese3  +1141 moreInstitutions (126)
TL;DR: 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.
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.

218 citations

Journal ArticleDOI
B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2, Fausto Acernese3  +1141 moreInstitutions (125)
TL;DR: In this paper, 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 ejecteda.
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.

217 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a review of all the important results obtained in this family, particularly in the last few years, by means of a variety of techniques/measurements such as X-ray diffraction, neutron diffraction and NQR.

216 citations

Journal ArticleDOI
TL;DR: In this article, an experimental and numerical study of the steady state convective losses occurring from a downward facing cylindrical cavity receiver of length 0.5m, internal diameter of 0.3m and a wind skirt diameter of0.5mm is carried out.

216 citations


Authors

Showing all 17055 results

NameH-indexPapersCitations
Jovan Milosevic1521433106802
C. N. R. Rao133164686718
Robert R. Edelman11960549475
Claude Andre Pruneau11461045500
Sanjeev Kumar113132554386
Basanta Kumar Nandi11257243331
Shaji Kumar111126553237
Josep M. Guerrero110119760890
R. Varma10949741970
Vijay P. Singh106169955831
Vinayak P. Dravid10381743612
Swagata Mukherjee101104846234
Anil Kumar99212464825
Dhiman Chakraborty9652944459
Michael D. Ward9582336892
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023175
2022433
20213,013
20203,093
20192,760
20182,549