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      Dark matter search using charge amplification in liquid xenon


      Science Impact, Ltd.

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          XMASS is a multipurpose physics experiment being conducted at the Kamioka Observatory of the Institute for Cosmic Research, at the University of Tokyo. One of the outcomes of this project was the development of a simple liquid xenon scintillation detector that was based on the design of Super-Kamiokande, a neutrino observatory located under Mount Ikenoyama in central Japan. The XMASS detector was designed to detect very low energy solar neutrinos, however, it was found that this resulted in a detector with good sensitivity to electron-scattering events, making it a useful tool for discovering dark matter candidates such as axion and super-bosonic weakly-interacting massive particles (WIMPs). However, existing two-phase detectors offer a greater sensitivity to heavy super-symmetric particles that are considered to be some of the leading dark matter candidates at this stage. The XMASS detector also offers scalability benefits over gas-liquid two-phase xenon detectors as the charge amplification factor changes within these unless the liquid level at the phase boundary is kept constant at all times. This problem is exacerbated as the size of the detector increases, making it difficult to scale up these detectors to useful sizes. Furthermore, the necessity for the presence of a liquid/gas boundary restricts the possible shape formats of these detectors. The XMASS detector has a spherical shape, making it easy to scale up. However, this too offers a challenge due to its tendency to mis-reconstruct the location of scattering events, especially when these occur on the surface of the detector. Professor Hiroyuki Sekiya and his team from the Kamioka Observatory have discovered that the solution for this drawback is to use charge amplification in the liquid. This not only overcomes these obstacles, but also improves sensitivity to dark matter.

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          Science Impact, Ltd.
          December 12 2018
          December 12 2018
          : 2018
          : 9
          : 82-84
          © 2018

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Earth & Environmental sciences, Medicine, Computer science, Agriculture, Engineering


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