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Search Results: 1 - 10 of 144494 matches for " F. Mayet "
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Performance Results of the AMS-01 Aerogel Threshold Cherenkov
F. Mayet
Physics , 2000,
Abstract: The Alpha Magnetic Spectrometer (AMS) was flown in june 1998 on board of the space shuttle Discovery (flight STS-91) at an altitude ranging between 320 and 390 km. This preliminary version of AMS included an Aerogel Threshold Cherenkov detector (ATC) to separate antiprotons from electron background, for momenta less than 3.5 GeV/c. In this paper, the design and physical principles of ATC will be discussed briefly, then the performance results of the ATC will be presented.
A review on the discovery reach of Dark Matter directional detection
F. Mayet,J. Billard
Physics , 2013, DOI: 10.1088/1742-6596/469/1/012013
Abstract: Directional detection of galactic Dark Matter offers a unique opportunity to identify Weakly Interacting Massive Particle (WIMP) events as such. Depending on the unknown WIMP-nucleon cross section, directional detection may be used to : exclude Dark Matter, discover galactic Dark Matter with a high significance or constrain WIMP and halo properties. We review the discovery reach of Dark Matter directional detection.
Low energy electron/recoil discrimination for directional Dark Matter detection
J. Billard,F. Mayet,D. Santos
Physics , 2012, DOI: 10.1088/1475-7516/2012/07/020
Abstract: Directional detection is a promising Dark Matter search strategy. Even though it could accommodate to a sizeable background contamination, electron/recoil discrimination remains a key and challenging issue as for direction-insensitive detectors. The measurement of the 3D track may be used to discriminate electrons from nuclear recoils. While a high rejection power is expected above 20 keV ionization, a dedicated data analysis is needed at low energy. After identifying discriminant observables, a multivariate analysis, namely a Boosted Decision Tree, is proposed, enabling an efficient event tagging for Dark Matter search. We show that it allows us to optimize rejection while keeping a rather high efficiency which is compulsory for rare event search.With respect to a sequential analysis, the rejection is about 20 times higher with a multivariate analysis, for the same Dark Matter exclusion limit.
Exclusion limits from data of directional Dark Matter detectors
J. Billard,F. Mayet,D. Santos
Physics , 2010, DOI: 10.1103/PhysRevD.82.055011
Abstract: Directional detection is a promising search strategy to discover galactic Dark Matter. Taking advantage on the rotation of the Solar system around the Galactic center through the Dark Matter halo, it allows to show a direction dependence of WIMP events. Even though the goal of directional search is to identify a WIMP positive detection, exclusion limits are still needed for very low exposure with a rather large background contamination, such as the one obtained with prototype experiments. Data of directional detectors are composed of energy and 3D track of recoiling nuclei. However, to set robust exclusion limits, we focus on the angular part of the event distribution, arguing that the energy part of the WIMP distribution is featureless and may even be mimic by the background one. Then, as the angular distributions of both background and WIMP events are known, a Bayesian approach to set exclusion limits is possible. In this paper, a statistical method based on an extended likelihood is proposed, compared to existing ones and is shown to be optimal. Eventually, a comprehensive study of the effect of detector configuration on exclusion limits is presented. It includes the effect of having or not sense recognition, a finite angular resolution, taking into account energy threshold as well as some astrophysical uncertainties.
Identification of Dark Matter with directional detection
J. Billard,F. Mayet,D. Santos
Physics , 2010,
Abstract: Directional detection is a promising search strategy to discover galactic Dark Matter. Taking advantage on the rotation of the Solar system around the Galactic center through the Dark Matter halo, it allows to show a direction dependence of WIMP events. Data of directional detectors are composed of energy and a 3D track for each recoiling nuclei. Here, we present a Bayesian analysis method dedicated to data from upcoming directional detectors. However, we focus only on the angular part of the event distribution, arguing that the energy part of the background distribution is unknown. Two different cases are considered: a positive or a null detection of Dark Matter. In the first scenario, we will present a map-based likelihood method allowing to recover the main incoming direction of the signal and its significance, thus proving its Galactic origin. In the second scenario, a new statistical method is proposed. It is based on an extended likelihood in order to set robust and competitive exclusion limits. This method has been compared to two other methods and has been shown to be optimal in any detector configurations. Eventually, prospects for the MIMAC project are presented in the case of a 10 kg CF4 detector with an exposition time of 3 years.
Three-dimensional track reconstruction for directional Dark Matter detection
J. Billard,F. Mayet,D. Santos
Physics , 2012, DOI: 10.1088/1475-7516/2012/04/006
Abstract: Directional detection of Dark Matter is a promising search strategy. However, to perform such detection, a given set of parameters has to be retrieved from the recoiling tracks : direction, sense and position in the detector volume. In order to optimize the track reconstruction and to fully exploit the data of forthcoming directional detectors, we present a likelihood method dedicated to 3D track reconstruction. This new analysis method is applied to the MIMAC detector. It requires a full simulation of track measurements in order to compare real tracks to simulated ones. We conclude that a good spatial resolution can be achieved, i.e. sub-mm in the anode plane and cm along the drift axis. This opens the possibility to perform a fiducialization of directional detectors. The angular resolution is shown to range between 20$^\circ$ to 80$^\circ$, depending on the recoil energy, which is however enough to achieve a high significance discovery of Dark Matter. On the contrary, we show that sense recognition capability of directional detectors depends strongly on the recoil energy and the drift distance, with small efficiency values (50%-70%). We suggest not to consider this information either for exclusion or discovery of Dark Matter for recoils below 100 keV and then to focus on axial directional data.
Directional Detection of Dark Matter with MIMAC
J. Billard,F. Mayet,D. Santos
Physics , 2011, DOI: 10.1088/1742-6596/375/1/012008
Abstract: Directional detection is a promising search strategy to discover galactic Dark Matter. We present a Bayesian analysis framework dedicated to Dark Matter phenomenology using directional detection. The interest of directional detection as a powerful tool to set exclusion limits, to authentify a Dark Matter detection or to constrain the Dark Matter properties, both from particle physics and galactic halo physics, will be demonstrated. However, such results need highly accurate track reconstruction which should be reachable by the MIMAC detector using a dedicated readout combined with a likelihood analysis of recoiling nuclei.
Track reconstruction with MIMAC
J. Billard,F. Mayet,D. Santos
Physics , 2011, DOI: 10.1051/eas/1253017
Abstract: Directional detection of Dark Matter is a promising search strategy. However, to perform such kind of detection, the recoiling tracks have to be accurately reconstructed: direction, sense and position in the detector volume. In order to optimize the track reconstruction and to fully exploit the data from the MIMAC detector, we developed a likelihood method dedicated to the track reconstruction. This likelihood approach requires a full simulation of track measurements with MIMAC in order to compare real tracks to simulated ones. Finally, we found that the MIMAC detector should have the required performance to perform a competitive directional detection of Dark Matter.
Markov Chain Monte Carlo analysis to constrain Dark Matter properties with directional detection
J. Billard,F. Mayet,D. Santos
Physics , 2010, DOI: 10.1103/PhysRevD.83.075002
Abstract: Directional detection is a promising dark matter search strategy. Indeed, weakly interacting massive particle (WIMP)-induced recoils would present a direction dependence toward the Cygnus constellation, while background-induced recoils exhibit an isotropic distribution in the Galactic rest frame. Taking advantage of these characteristic features and even in the presence of a sizeable background, it has recently been shown that data from forthcoming directional detectors could lead either to a competitive exclusion or to a conclusive discovery, depending on the value of the WIMP-nucleon cross section. However, it is possible to further exploit these upcoming data by using the strong dependence of the WIMP signal with : the WIMP mass and the local WIMP velocity distribution. Using a Markov chain Monte Carlo analysis of recoil events, we show for the first time the possibility to constrain the unknown WIMP parameters, both from particle physics (mass and cross section) and Galactic halo (velocity dispersion along the three axis), leading to an identification of non-baryonic dark matter.
Exclusion, Discovery and Identification of Dark Matter with Directional Detection
J. Billard,F. Mayet,D. Santos
Physics , 2011, DOI: 10.1051/eas/1253009
Abstract: Directional detection is a promising search strategy to discover galactic Dark Matter. We present a Bayesian analysis framework dedicated to data from upcoming directional detectors. The interest of directional detection as a powerful tool to set exclusion limits, to authentify a Dark Matter detection or to constrain the Dark Matter properties, both from particle physics and galactic halo physics, will be demonstrated.
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