Recent Progress on the GAPS Time of Flight System

Quinn, S.

doi:10.22323/1.358.0128

Cited by 5 publications

(7 citation statements)

References 6 publications

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“…The inner ToF is a cube that surround the tracker system on top, bottom and lateral sides. All scintillators are 6.35 mm thick and 16 cm wide, with a variable lenght between 1.51 and 1.8 m. Each paddle system provides the measurement of energy deposit, time and longitudinal position along its largest dimension [10]. The tracker systems is made of 1440 Si(Li) detectors arranged in 10 evenly spaced planes [11][12][13][14].…”

Section: The Gaps Experimentsmentioning

confidence: 99%

Reconstruction of antinucleus-annihilation events in the GAPS experiment

Tiberio¹,

Aramaki²,

Bird³

et al. 2021

Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)

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Section: The Gaps Experimentsmentioning

confidence: 99%

Reconstruction of antinucleus-annihilation events in the GAPS experiment

Tiberio¹,

Aramaki²,

Bird³

et al. 2021

Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)

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“…The ToF system consists of ∼ 160 plastic scintillator paddles [10] and is arranged in an outer Tof system and an inner Tof system (see Fig. 1 right).…”

Section: The Gaps Detectormentioning

confidence: 99%

Neural Networks approach to event reconstruction for the GAPS experiment

Marcelli¹

2021

Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)

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The General Antiparticle Spectrometer (GAPS) is a balloon-borne experiment, scheduled for a first flight in the austral summer 2022. It is designed to measure low energy (< 0.25 GeV/ ) cosmic antinuclei. A particular focus is on antideuterons, which are predicted to have an ultra-low astrophysical background as compared to signals from dark matter annihilation or decay in the Galactic halo. GAPS uses a novel technique for particle identification based on the formation and decay of exotic atoms. To achieve sufficient rejection power for particle identification, an accurate determination of several fundamental quantities is needed. The precise reconstruction of the energy deposition pattern on the primary track is a particularly intricate problem and we developed a strategy devised to solve this using modern machine learning techniques. In the future, this approach can also be used for particle identification. Here, we present preliminary results of these efforts obtained from simulations.

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“…The ToF system consists by ∼ 160 plastic scintillator paddles [12] and is arranged in and outer ToF system and an inner ToF system (see Figure 1).…”

Section: The Gaps Detectormentioning

confidence: 99%

“…In addition, this last trigger scheme requires that the TOF energy depositions are in the range of slow-moving |Z| = 1 or |Z| = 2 to reject minimally ionizing (high-velocity) and high-charge particles. This second configuration was optimal for selecting the annihilating antinuclei with an efficiency higher than 60% in the β range of scientific interest for the GAPS experiment, ∼ 0.2 to ∼ 0.6, while reducing the trigger rate down to less than 1 kHz from the expected MHz rate with the minimum bias trigger [12].…”

Section: Instrument Simulationmentioning

confidence: 99%

The antinucleus annihilation reconstruction algorithm of the GAPS experiment

Munini,

Vannuccini,

Boezio

et al. 2021

Preprint

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The General AntiParticle Spectrometer (GAPS) is an Antarctic balloon-borne detector designed to measure low-energy cosmic antinuclei (< 0.25 GeV/n), with a specific focus on antideuterons, as a distinctive signal from dark matter annihilation or decay in the Galactic halo. The instrument consists of a tracker, made up of ten planes of lithium-drifted Silicon Si(Li) detectors, surrounded by a plastic scintillator Time-of-Flight system. GAPS uses a novel particle identification method based on exotic atom capture and decay with the emission of pions, protons, and atomic X-rays from a common annihilation vertex.

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Recent Progress on the GAPS Time of Flight System

Cited by 5 publications

References 6 publications

Reconstruction of antinucleus-annihilation events in the GAPS experiment

Reconstruction of antinucleus-annihilation events in the GAPS experiment

Neural Networks approach to event reconstruction for the GAPS experiment

The antinucleus annihilation reconstruction algorithm of the GAPS experiment

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