Directionality and head-tail recognition in the keV-range with the MIMAC detector by deconvolution of the ionic signal
Cyprien Beaufort, Olivier Guillaudin, Jean-Fran\c{c}ois Muraz, Nadine, Sauzet, Daniel Santos, Richard Babut

TL;DR
This paper introduces a deconvolution method for ionic signals in a Micromegas detector, enabling head-tail recognition and improved directionality of low-energy nuclear recoils for dark matter detection.
Contribution
It presents an analytical deconvolution formula validated experimentally, enhancing head-tail recognition and directional detection capabilities at keV energies.
Findings
Deconvolution accurately reveals primary electron cloud structure.
Achieved head-tail recognition in the keV-range.
Reconstructed neutron spectra with angular resolution better than 15°.
Abstract
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…
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Taxonomy
TopicsDark Matter and Cosmic Phenomena · Particle Detector Development and Performance · Neutrino Physics Research
