Abstract
The ALPHA experiment at CERN is designed to produce and trap antihydrogen to the purpose of making a precise comparison with hydrogen. The basic technique consists of driving an antihydrogen resonance which will cause the antiatom to leave the trap and annihilate. The main background to antihydrogen detection is due to cosmic rays. When an experimental cycle extends for several minutes, while the number of trapped antihydrogen remains fixed, background rejection can become challenging. Machine learning methods have been employed in ALPHA for several years, leading to a dramatic reduction of the background contamination. This allowed ALPHA to perform the first laser spectroscopy experiment on antihydrogen.
Highlights
Antihydrogen is a tool to explore the fundamental symmetries [1] that lie at foundation of the Standard Model, i.e., the CPT invariance, and of the General Relativity, i.e., the Equivalence Principle
The ALPHA collaboration observed for the first time a transition between Zeeman levels of the antihydrogen ground state [2], placed the most stringent upper limit to the antihydrogen electric charge [3], performed the first laser spectroscopy experiment [4] and, more recently, measured the hyperfine splitting of the ground state [5]
ALPHA relies upon annihilation position reconstruction for antihydrogen detection
Summary
Antihydrogen is a tool to explore the fundamental symmetries [1] that lie at foundation of the Standard Model, i.e., the CPT invariance, and of the General Relativity, i.e., the Equivalence Principle. This allowed ALPHA to perform the first laser spectroscopy experiment on antihydrogen. During the mixing phase all the events recorded with the silicon detector are due to the annihilation of “hot” antihydrogen (i.e., antiatoms with too much kinetic energy to be confined) with a negligible background contamination.
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