Search

We present the first lattice QCD calculation of single-channel $DD$ scattering with quantum numbers $I(J^P)=1(0^+)$ and $0(1^-)$. The calculation is performed on the $2+1$ flavor Wilson-Clover ensembles with a lattice spacing $a\simeq 0.077$ fm and two different pion masses, $m_{\pi}\simeq207$ and $305$ MeV. The scattering parameters are determined using the L\"uscher's finite volume method. Our results indicate weak repulsive interaction in the $1(0^+)$ channel and slightly attractive interaction in the $0(1^-)$ channel. The $S$-wave isovector $DD$ scattering length and effective range, extrapolated to the physical pion mass, are $(-0.26\pm0.05)$ fm and $(-5.5\pm2.1)$ fm, respectively., Comment: 19 pages, 7 figures

We propose a systematic method to block-diagonalize the finite volume effective Hamiltonian for two-particle system with arbitrary spin in both the rest and moving frames. The framework is convenient and efficient for addressing the left-hand cut issue arising from the long-range potential, which are challenging in the framework of standard L\"ushcer formula. Furthermore, the method provides a foundation for further extension to the three-particle system. We first benchmark our approach by examining several toy models, demonstrating its consistency with the standard L\"ushcer formula in the absence of long-range interactions. In the presence of long-range potential, we investigate and resolve the effect of left-hand cut. As a realistic application, we calculate the finite volume spectrum of isoscalar $D\bar{D}^*$ system, where the well-known exotic state $\chi_{c1}(3872)$ is observed. The results are qualitatively consistent with the lattice QCD calculation, highlighting the reliability and potential application of our framework to the study of other exotic states in the hadron physics., Comment: 46 pages, 7 figures

Since 1959, singularities within single-loop diagrams have been studied. They are believed to significantly influence our understanding of experimental observables. In this study, we explore the singularities that arise from box diagrams in the decay process, which can be classified into two distinct categories. A comprehensive analysis of box singularities has been conducted, wherein we have derived and presented specific conditional formulae to ascertain the occurrence of singularities, along with the related physical scenarios.

We present a lattice QCD investigation of the $\rho$ resonance using nine $N_f = 2 + 1$ Wilson-Clover ensembles with three lattice spacings and various pion masses ranging from $135$ to $320$ MeV. For each ensemble, a large number of finite volume energy levels are determined and the energy dependence of the phase shift obtained from L\"uscher's finite volume method. The mass and width of the $\rho$ resonance are then extracted by assuming the Breit-Wigner form. The mass and width are extrapolated to the physical pion mass and continuum limit ($\mathcal{O}(a^2)$) using a linear function of $a^2$ and $m^2_\pi$. The extrapolated values for the mass and width in the Breit-Wigner form are $(m_\rho,\,\Gamma_\rho) = (781.6\pm10.0,\, 146.5\pm 9.9)$ MeV, which are in good agreement with experiment. An alternative method of analysis, based on Hamiltonian effective field theory, involves directly fitting the lattice energy levels and accounting for the quark mass dependence of the hadronic loop diagrams which yield the leading and next-to-leading non-analytic behaviour. This approach also yields consistent $\rho$ parameters at the physical point. This represents the most precise determination to date of the mass and width of a hadron which is unstable under strong decay, achieved through comprehensive lattice QCD calculations and methods of analysis., Comment: 17 pages, 14 figures

Molecular evolution is the process of simulating the natural evolution of molecules in chemical space to explore potential molecular structures and properties. The relationships between similar molecules are often described through transformations such as adding, deleting, and modifying atoms and chemical bonds, reflecting specific evolutionary paths. Existing molecular representation methods mainly focus on mining data, such as atomic-level structures and chemical bonds directly from the molecules, often overlooking their evolutionary history. Consequently, we aim to explore the possibility of enhancing molecular representations by simulating the evolutionary process. We extract and analyze the changes in the evolutionary pathway and explore combining it with existing molecular representations. Therefore, this paper proposes the molecular evolutionary network (MEvoN) for molecular representations. First, we construct the MEvoN using molecules with a small number of atoms and generate evolutionary paths utilizing similarity calculations. Then, by modeling the atomic-level changes, MEvoN reveals their impact on molecular properties. Experimental results show that the MEvoN-based molecular property prediction method significantly improves the performance of traditional end-to-end algorithms on several molecular datasets. The code is available at https://anonymous.4open.science/r/MEvoN-7416/., Comment: 9 pages, 6 figures, 5 tables

The bottomonium spectrum is systematically studied within an unquenched quark model. Based on a good description of both the masses and widths for the well-established states, we further give predictions for the higher $S$-, $P$-, and $D$-wave bottomonium states up to a mass region of $\sim 11.3$ GeV. For the vector states, the $S$-$D$ mixing and dielectron decays are studied. Additionally, to understand the role of the higher vector resonances in the $e^{+}e^{-}$ annihilation reaction, we evaluate the cross section by combining our quark model predictions for the mass, dielectron and strong decay properties. It is found that (i) The mass shifts of the high $b\bar{b}$ states due to the coupled-channel effects are the order of a few tens MeV, most of the high-lying resonances contain significant non-$b\bar{b}$ components. (ii) The $\Upsilon_1(3D,5D,6D)$ states significantly mix with $\Upsilon(4S,6S,7S)$, respectively, which is mainly induced by the intermediate hadronic loops. (iii) The non-$b\bar{b}$ components will lead a significant suppression for the dielectron decay widths of some vector resonances.(iv) The threshold effects of open-bottom meson pairs can cause rich bump structures in the cross section of $e^{+}e^{-}\to b\bar{b}$. Our model shows that the $\Upsilon(10753)$ may arise from threshold effects due to the strong coupling between $\Upsilon(4S)$ and $\bar{B}^*B^*$.

Responsible Artificial Intelligence (RAI) has emerged as a crucial framework for addressing ethical concerns in the development and deployment of Artificial Intelligence (AI) systems. A significant body of literature exists, primarily focusing on either RAI guidelines and principles or the technical aspects of RAI, largely within the realm of traditional AI. However, a notable gap persists in bridging theoretical frameworks with practical implementations in real-world settings, as well as transitioning from RAI to Responsible Generative AI (Gen AI). To bridge this gap, we present this article, which examines the challenges and opportunities in implementing ethical, transparent, and accountable AI systems in the post-ChatGPT era, an era significantly shaped by Gen AI. Our analysis includes governance and technical frameworks, the exploration of explainable AI as the backbone to achieve RAI, key performance indicators in RAI, alignment of Gen AI benchmarks with governance frameworks, reviews of AI-ready test beds, and RAI applications across multiple sectors. Additionally, we discuss challenges in RAI implementation and provide a philosophical perspective on the future of RAI. This comprehensive article aims to offer an overview of RAI, providing valuable insights for researchers, policymakers, users, and industry practitioners to develop and deploy AI systems that benefit individuals and society while minimizing potential risks and societal impacts. A curated list of resources and datasets covered in this survey is available on GitHub {https://github.com/anas-zafar/Responsible-AI}., Comment: under review

Superpixel segmentation is a foundation for many higher-level computer vision tasks, such as image segmentation, object recognition, and scene understanding. Existing graph-based superpixel segmentation methods typically concentrate on the relationships between a given pixel and its directly adjacent pixels while overlooking the influence of non-adjacent pixels. These approaches do not fully leverage the global information in the graph, leading to suboptimal segmentation quality. To address this limitation, we present SIT-HSS, a hierarchical superpixel segmentation method based on structural information theory. Specifically, we first design a novel graph construction strategy that incrementally explores the pixel neighborhood to add edges based on 1-dimensional structural entropy (1D SE). This strategy maximizes the retention of graph information while avoiding an overly complex graph structure. Then, we design a new 2D SE-guided hierarchical graph partitioning method, which iteratively merges pixel clusters layer by layer to reduce the graph's 2D SE until a predefined segmentation scale is achieved. Experimental results on three benchmark datasets demonstrate that the SIT-HSS performs better than state-of-the-art unsupervised superpixel segmentation algorithms. The source code is available at \url{https://github.com/SELGroup/SIT-HSS}., Comment: Accepted by SDM 2025