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We report on an updated sensitivity for proton decay via $p \rightarrow\bar{\nu} K^+ $ at large, dual phase liquid argon time projection chambers (LArTPCs). Our work builds on a previous study in which several nucleon decaychannels have been simulated and analyzed [arXiv:hep-ph/0701101]. At the timeseveral assumptions were needed to be made on the detector and the backgrounds.Since then, the community has made progress in defining these, and thecomputing power available enables us to fully simulate and reconstruct largesamples in order to perform a better estimate of the sensitivity to protondecay. In this work, we examine the benchmark channel $p\rightarrow \bar{\nu}K^{+}$, which was previously found to be one of the cleanest channels. Using animproved neutrino event generator and a fully simulated LAr TPC detectorresponse combined with a dedicated neural network for kaon identification, wedemonstrate that a lifetime sensitivity of $ \tau / \text{Br} \left( p\rightarrow \bar{\nu} K^+ \right) > 7 \times 10^{34} \, \text{years}$ at $90 \,\%$ confidence level can be reached at an exposure of $1 \, \text{megaton}\cdot \text{year}$ in quasi-background-free conditions, confirming thesuperiority of the LAr TPC over other technologies to address the challengingproton decay modes.

Neural-network-driven proton decay sensitivity in the $p\rightarrow \bar{\nu} K^{+}$ channel using large liquid argon time projection chambers