Measurement of the singly Cabibbo-suppressed decay $\hat{I}{›}_c^{+}\to p\hat{I}{\cdot }^{\prime }$ with Deep Learning

Abstract

Using $4.5$ fb${}^{-1}$ of $e^{+}{e}^{-}$ collision data collected with the BESIII detector at center-of-mass energies from 4.600 to 4.699 GeV, we report a measurement of the singly Cabibbo-suppressed decay $\hat{I}{›}_c^{+}\to p\hat{I}{\cdot }^{\prime }$ with the single-tag method. To effectively distinguish the signal from the large backgrounds, we exploit a deep-learning classifier built on a Transformer-based neural network. Extensive validation and uncertainty quantification are carried out. The $\hat{I}{›}_c^{+}\to p\hat{I}{\cdot }^{\prime }$ signal is observed with a statistical significance of $3.4\ddot{I}ƒ$. The ratio of branching fractions of $\mathcal{B}\hat{I}{›}_c^{+}\to p\hat{I}{\cdot }^{\prime }/\mathcal{B}\hat{I}{›}_c^{+}\to p\ddot{I}‰$= $0.55\pm 0.22_{stat.}\pm 0.05_{syst.}$ is obtained, where the first uncertainty is statistical and the second systematic.