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Directionality and head-tail recognition in the keV-range with the MIMAC detector by deconvolution of the ionic signal
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Directionality and head-tail recognition in the keV-range with the MIMAC detector by deconvolution of the ionic signal
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Paper
Directionality and head-tail recognition in the keV-range with the MIMAC detector by deconvolution of the ionic signal
2022
Overview
Directional detection is the only strategy for the unambiguous identification of galactic Dark Matter (DM) even in the presence of an irreducible background such as beyond the neutrino floor. This approach requires measuring the direction of a DM-induced nuclear recoil in the keV-range. To probe such low energies, directional detectors must operate at high gain where 3D track reconstruction can be distorted by the influence of the numerous ions produced in the avalanches. The article describes the interplay between electrons and ions during signal formation in a Micromegas. It introduces SimuMimac, a simulation tool dedicated to high gain detection that agrees with MIMAC measurements. This work proposes an analytical formula to deconvolve the ionic signal induced on the grid from any measurements, with no need for prior nor ad hoc parameter. This deconvolution is experimentally tested and validated, revealing the fine structure of the primary electrons cloud and consequently leading to head-tail recognition in the keV-range. Finally, the article presents how this deconvolution can be used for directionality by reconstructing the spectra of mono-energetic \\(27~\\mathrm{keV}\\) and \\(8~\\mathrm{keV}\\) neutrons with an angular resolution better than \\(15^\\circ\\). This novel approach for directionality appears as complementary to the standard one from 3D tracks reconstruction and offers redundancy for improving directional performances at high gain in the keV region.
Publisher
Cornell University Library, arXiv.org
Subject
