论文标题
旨在发现新颖的$ b_c $状态:辐射和望子型过渡
Towards the discovery of novel $B_c$ states: radiative and hadronic transitions
论文作者
论文摘要
$ b_c $ -Meson家族($ C \ b $)的特性仍未在实验上确定,因为形成和衰减的特定机制仍然很熟悉。与重型Quarkonia不同,即Charmonium($ C \ bar c $)和PostoneNium($ b \ b \ b $)的隐藏重型夸克式式扇区,$ b_c $ -mesons不能ni灭gluonate,因此它们是更稳定的。激动的$ b_c $状态位于最低的强度$ bd $阈值以下,只能通过辐射衰减和辐射过渡到$ b_c $地面状态,然后衰减较弱。因此,出现了$ bd $阈值以下的丰富狭窄激发态,其总宽度比charmon和底部的激发水平的数量级小两个数量级。在另一篇文章中,我们使用非偏好的夸克模型确定了底部粘液质量,该模型已应用于广泛的强子物理可观察物,因此模型参数得到了完全限制。在此,我们继续研究$ b_c $行业,我们计算了相关的辐射衰减宽度和辐射过渡速率,而$ c \ bar b $ nate(低于$ bd $ bd $ threshold)。这将提供最有前途的信号,以发现低于最低的$ decay $ bd $ threshold的激发$ b_c $状态。最后,我们的结果与其他模型进行了比较,以衡量预测的可靠性并指出差异。
The properties of the $B_c$-meson family ($c\bar b$) are still not well determined experimentally because the specific mechanisms of formation and decay remain poorly understood. Unlike heavy quarkonia, i.e. the hidden heavy quark-antiquark sectors of charmonium ($c\bar c$) and bottomonium ($b\bar b$), the $B_c$-mesons cannot annihilate into gluons and they are, consequently, more stable. The excited $B_c$ states, lying below the lowest strong-decay $BD$-threshold, can only undergo through radiative decays and hadronic transitions to the $B_c$ ground state, which then decays weakly. As a result of this, a rich spectrum of narrow excited states below the $BD$-threshold appear, whose total widths are two orders of magnitude smaller than those of the excited levels of charmonium and bottomonium. In a different article, we determined bottom-charmed meson masses using a non-relativistic constituent quark model which has been applied to a wide range of hadron physical observables, and thus the model parameters are completely constrained. Herein, continuing to our study of the $B_c$ sector, we calculate the relevant radiative decay widths and hadronic transition rates between $c\bar b$ states which are below $BD$-threshold. This shall provide the most promising signals for discovering excited $B_c$ states that are below the lowest strong-decay $BD$-threshold. Finally, our results are compared with other models to measure the reliability of the predictions and point out differences.