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The IceCube 2 generation is a project to create a ten-cubic meter neutrino telescope at South Pole. In 2010, one cubic meter was called IceCube. Neutrino telescopes are another telescope that goes alongside the visible light, X-rays, infrared, ultraviolet, microwave, radio, gamma and gravity waves.
They can look deep into space sources and master the supernova and they can discover the structure inside the Earth.
There are many underwater neutrino detectors, underwater and underground detectors.
Underwater Neutral Telescopes:
Baikal Deep Underwater Neutrine Telescope (1993)
ANTARES (2006)
KM3NeT (future telescope built since 2013)
NESTOR project (developed since 1998)
Neutral Telescopes Under Ice:
AMANDA (1996–2009, replaced by IceCube)
IceCube (since 2004)
DeepCore and PINGU, the existing extension and the proposed IceCube extension
Underground Neutrine Observation Centers:
Gran Sasso National Laboratories (LNGS), Italy, Borexino, CUORE and other experiments.
Soudan Mine, Soudan 2, MINOS and CDMS home
Kamioka Observatory, Japan
Underground Neutrino Observatory, Mont Blanc, France / Italy
The next-generation KM3NeT deepwater neutrino telescope will be about five cubic kilometers, and the IceCube Gen2 detector will be ten cubic meters. These two will result in much greater sensitivity to neutrino detection. They will be three to ten times more capable than the best existing detectors. The KM3NeT detector will be built at three installation locations in the Mediterranean. The implementation of the first phase of the telescope began in 2013.
Several detectors are needed to make triangles on neutral sources in space and analyze the deep interior of the earth.
Earth Neutrine Tomography
Neutrine detectors have accurately measured the Earth's mass and density. Earth interacts with neutrinos. The differences in the distribution of neutrons passing through the Earth can be used to analyze the density and create an internal kernel and a 3D rendering model. Neutrine detectors with enhanced sensitivity and multi-year data collection will significantly improve modeling.
Brian Wang from Nextbigfuture.com
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