Abstract

Hypertriton is the lightest hypernucleus and a benchmark in hypernuclear physics. However, it has recently been suggested that its lifetime and binding energy values may differ from the established values. To solve this puzzle, it is necessary to measure both values with a higher precision. For the precise measurement of the binding energy, we are aiming at developing a novel technique to measure the hypertriton binding energy with unprecedented accuracy by combining nuclear emulsion data and machine learning techniques. The analysis will be based on the J-PARC E07 nuclear emulsion data. Furthermore, a machine-learning model is being developed to identify other single and double-strangeness hypernuclei.

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