The SS- and PP-wave fully charmed tetraquark states and their radial excitations

Inspired by recent progresses in observations of the fully charmed tetraquark states by LHCb, CMS, and ATLAS Collaborations, we perform a systematic study of the ground states and the first radial excitations of the $S$- and $P$-wave $\mathrm{cc}\bar{\mathrm{c}}\bar{\mathrm{c}}$ system. Their mass spectra, root mean square(r.m.s.) radii and radial density distributions are studied with the relativized quark model. The calculations show that there is no stable bound states for the full-charmed tetraquark states, and the r.m.s. radii of these tetraquark states are smaller than 1 fm. Our results support assigning X(6600) structure, $M_{X(6600)}=6552\pm10\pm12$ MeV, as one of the $0^{++}$(1$S$) and $2^{++}$(1$S$) states or their mixtures. Another structure also named as X(6600) by CMS Collaboration, $M_{X(6600)}=6.62\pm0.03^{+0.02}_{-0.01}$ GeV, may arise from the lowest 1$P$ states with $J^{PC}$=$0^{-+}$, $1^{-+}$, and $2^{-+}$. The possible assignments for X(6900) include the $0^{++}$(2$S$), $2^{++}$(2$S$) states, and the highest 1$P$ state with $J^{PC}=0^{-+}$. As for X(7200), it can be interpreted as one of the highest 2$P$ states with $J^{PC}=0^{-+}$, $1^{-+}$, and $2^{-+}$, and the 3$S$ states can not be completely excluded from the candidates.Comment: to be published in European Physical Journal

Strong decay properties of single heavy baryons ΛQ\Lambda_{Q}, ΣQ\Sigma_{Q} and ΩQ\Omega_{Q}

Motivated by recent progresses in experiments in searching for the $\Omega_{c}$ baryons, we systematically analyze the strong decay behaviors of single heavy baryons $\Lambda_{Q}$, $\Sigma_{Q}$ and $\Omega_{Q}$. The two-body strong decay properties of $S$-wave, $P$-wave and some $D$-wave states are studied with the $^{3}P_{0}$ model. The results support assigning the recently observed $\Omega_{c}(3185)$ and $\Omega_{c}(3327)$ as the 2S($\frac{3}{2}^{+}$) and 1D($\frac{3}{2}^{+}$) states, respectively. In addition, the quantum numbers of many other experimentally observed baryons are also suggested according to their strong decays. Finally, some baryons which have good potentials to be observed in experiments are predicted and the possible decay channels for searching for these predicted states are also suggested.Comment: arXiv admin note: substantial text overlap with arXiv:2206.0812

Systematic analysis of doubly charmed baryons Ξcc\Xi_{cc} and Ωcc\Omega_{cc}

In this work, we perform a systematic study of the mass spectra, the root mean square(r.m.s.) radii and the radial density distributions of the doubly charmed baryons $\Xi_{cc}$ and $\Omega_{cc}$. The calculations are carried out in the frame work of Godfrey-Isgur (GI) relativized quark model, where the baryon is regarded as a real three-body system of quarks. Our results show that the excited energy of doubly charmed baryon with $\rho$-mode is lower than those of the $\lambda$-mode and $\lambda$-$\rho$ mixing mode, which indicates that the lowest state is dominated by the $\rho$-mode. According to this conclusion, we systematically investigate the mass spectra, the r.m.s. radii of the ground and excited states($1S\sim4S$, $1P\sim4P$, $1D\sim4D$, $1F\sim4F$ and $1G\sim4G$) with $\rho$-mode. Using the wave functions obtained from quark model, we also study the radial density distributions. Finally, with the predicated mass spectra, the Regge trajectories of $\Xi_{cc}$ and $\Omega_{cc}$ in the ($J$,$M^{2}$) plane are constructed, and the slopes, intercepts are determined by linear fitting. It is found that model predicted masses fit nicely to the constructed Regge trajectories.Comment: arXiv admin note: text overlap with arXiv:2206.0812

QCD θ\theta-vacuum energy and axion properties

At low energies, the strong interaction is governed by the Goldstone bosons associated with the spontaneous chiral symmetry breaking, which can be systematically described by chiral perturbation theory. In this paper, we apply this theory to study the $\theta$-vacuum energy density and hence the QCD axion potential up to next-to-leading order with $N$ non-degenerate quark masses. By setting $N=3$, we then derive the axion mass, self-coupling, topological susceptibility and the normalized fourth cumulant both analytically and numerically, taking the strong isospin breaking effects into account. In addition, the model-independent part of the axion-photon coupling, which is important for axion search experiments, is also extracted from the chiral Lagrangian supplemented with the anomalous terms up to $\mathcal{O}(p^6)$.Comment: 22 pages, 1 figure, 2 tables; Version to appear in JHE

A fair evaluation of the potential of machine learning in maritime transportation

Machine learning (ML) techniques are extensively applied to practical maritime transportation issues. Due to the difficulty and high cost of collecting large volumes of data in the maritime industry, in many maritime studies, ML models are trained with small training datasets. The relative predictive performances of these trained ML models are then compared with each other and with the conventional model using the same test set. The ML model that performs the best out of the ML models and better than the conventional model on the test set is regarded as the most effective in terms of this prediction task. However, in scenarios with small datasets, this common process may lead to an unfair comparison between the ML and the conventional model. Therefore, we propose a novel process to fairly compare multiple ML models and the conventional model. We first select the best ML model in terms of predictive performance for the validation set. Then, we combine the training and the validation sets to retrain the best ML model and compare it with the conventional model on the same test set. Based on historical port state control (PSC) inspection data, we examine both the common process and the novel process in terms of their ability to fairly compare ML models and the conventional model. The results show that the novel process is more effective at fairly comparing the ML models with the conventional model on different test sets. Therefore, the novel process enables a fair assessment of ML models' ability to predict key performance indicators in the context of limited data availability in the maritime industry, such as predicting the ship fuel consumption and port traffic volume, thereby enhancing their reliability for real-world applications