RESUMEN
We report the first observation of the hadronic transition Ï(4S)âη^{'}Ï(1S), using 496 fb^{-1} data collected at the Ï(4S) resonance with the Belle detector at the KEKB asymmetric-energy e^{+}e^{-} collider. We reconstruct the η^{'} meson through its decays to ρ^{0}γ and to π^{+}π^{-}η, with ηâγγ. We measure B(Ï(4S)âη^{'}Ï(1S))=[3.43±0.88(stat)±0.21(syst)]×10^{-5}, with a significance of 5.7σ.
RESUMEN
Using a sample of 771.6×10(6) ÏÏ(4S) decays collected by the Belle experiment at the KEKB e(+)e(-) collider, we observe, for the first time, the transition Ï(4S)âηh(b)(1P) with the branching fraction B[Ï(4S)âηh(b)(1P)]=(2.18±0.11±0.18)×10(-3) and we measure the h(b)(1P) mass M(h(b)(1P))=(9899.3±0.4±1.0) MeV/c(2), corresponding to the hyperfine (HF) splitting ΔM(HF)(1P)=(0.6±0.4±1.0) MeV/c(2). Using the transition h(b)(1P)âγη(b)(1S), we measure the η(b)(1S) mass M(η(b)(1S))=(9400.7±1.7±1.6) MeV/c(2), corresponding to ΔM(HF)(1S)=(59.6±1.7±1.6) MeV/c(2), the η(b)(1S) width Γ(η(b)(1S))=(8(-5)(+6)±5) MeV/c(2) and the branching fraction B[h(b)(1P)âγη(b)(1S)]=(56±8±4)%.
RESUMEN
We present the novel implementation of a non-differentiable metric approximation and a corresponding loss-scheduling aimed at the search for new particles of unknown mass in high energy physics experiments. We call the loss-scheduling, based on the minimisation of a figure-of-merit related function typical of particle physics, a Punzi-loss function, and the neural network that utilises this loss function a Punzi-net. We show that the Punzi-net outperforms standard multivariate analysis techniques and generalises well to mass hypotheses for which it was not trained. This is achieved by training a single classifier that provides a coherent and optimal classification of all signal hypotheses over the whole search space. Our result constitutes a complementary approach to fully differentiable analyses in particle physics. We implemented this work using PyTorch and provide users full access to a public repository containing all the codes and a training example.