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相关论文: Exploring fully-heavy tetraquarks through the CGAN…

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We suppose that there exist three vector hidden-charm tetraquark states with the $J^{PC}=1^{--}$ at the energy about $4.5\,\rm{GeV}$, and investigate the two-body strong decays systematically. We obtain thirty QCD sum rules for the hadronic…

高能物理 - 唯象学 · 物理学 2024-06-13 Zhi-Gang Wang

This paper focuses on tetraquarks containing one heavy quark and one heavy antiquark in the formal limit where the heavy quark masses go to infinity. It extends the theoretical framework developed for tetraquark containing two heavy quarks…

高能物理 - 唯象学 · 物理学 2020-09-02 Yiming Cai , Thomas Cohen

Within the framework of the quark model and the variational method, the bound states of four heavy quarks (tetraquarks) are investigated. The basis variational wave functions are chosen in the Gaussian form. The matrix elements of the…

高能物理 - 唯象学 · 物理学 2025-08-19 A. V. Eskin , A. P. Martynenko , F. A. Martynenko

Generative Adversarial Networks (GANs) have demonstrated immense potential in synthesizing diverse and high-fidelity images. However, critical questions remain unanswered regarding how quantum principles might best enhance their…

Assuming X(3872) is a $qc \bar q \bar c$ tetraquark and using its mass as input, we perform a schematic study of the masses of possible heavy tetraquarks using the color-magnetic interaction with the flavor symmetry breaking corrections.

高能物理 - 唯象学 · 物理学 2008-11-26 Ying Cui , Xiao-Lin Chen , Wei-Zhen Deng , Shi-Lin Zhu

Inspired by the recent discovery of a doubly charmed tetraquark state $T_{cc}^+$ by the LHCb Collaboration, we employ the effective Lagrangian approach to investigate the decay width of $T_{cc}^{+}\to D^{+} D^{0}\pi^{0}/D^{0} D^{0}\pi^{+}$…

高能物理 - 唯象学 · 物理学 2022-01-19 Xi-Zhe Ling , Ming-Zhu Liu , Li-Sheng Geng , En Wang , Ju-Jun Xie

It is known that the inconsistent distribution and representation of different modalities, such as image and text, cause the heterogeneity gap that makes it challenging to correlate such heterogeneous data. Generative adversarial networks…

多媒体 · 计算机科学 2018-04-27 Yuxin Peng , Jinwei Qi , Yuxin Yuan

Baryons containing two heavy quarks are important and interesting systems to study the quark-diquark structure of baryons and to understand the dynamics of QCD at hadronic scale. The Selex Collaboration has recently reported the discovery…

高能物理 - 唯象学 · 物理学 2008-09-30 Ajay Majethiya , Bhavin Patel , Ajay Kumar Rai , P C Vinodkumar

In this paper, we have systematically explored the mass spectrum of fully strange tetraquark candidates within the framework of QCD sum rules, focusing on states with quantum numbers $J^{PC}=0^{++}$, $0^{-+}$, $0^{--}$, $1^{--}$, $1^{+-}$,…

高能物理 - 唯象学 · 物理学 2026-05-05 Bing-Dong Wan , Ji-Chong Yang

Recent observations by Belle and BESIII of charged quarkonium-like resonances give new stimulus for theoretical investigation of exotic hadrons in general and heavy tetraquarks in particular. We use QED_2, a confining theory, as a model for…

高能物理 - 唯象学 · 物理学 2015-06-16 Yitzhak Frishman , Marek Karliner

In present work, spectrum of the $S$-wave fully-heavy tetraquark states $QQ\bar{Q}\bar{Q}$ ($Q=c,b$), i.e., $cc\bar{c}\bar{c}$, $bb\bar{b}\bar{b}$, $cc\bar{b}\bar{b}$/$bb\bar{c}\bar{c}$, $bc\bar{c}\bar{c}$/ $cc\bar{b}\bar{c}$,…

高能物理 - 唯象学 · 物理学 2022-12-28 Jie Zhang , Jin-Bao Wang , Gang Li , Chun-Sheng An , Cheng-Rong Deng , Ju-Jun Xie

I review some selected aspects of the phenomenology of multiquark states discovered in high energy experiments. They have four valence quarks (called tetraquarks) and two of them are found to have five valence quarks (called pentaquarks),…

高能物理 - 唯象学 · 物理学 2016-05-23 Ahmed Ali

Conditional Generative Adversarial Networks (cGANs) are generative models that can produce data samples ($x$) conditioned on both latent variables ($z$) and known auxiliary information ($c$). We propose the Bidirectional cGAN (BiCoGAN),…

机器学习 · 计算机科学 2018-11-06 Ayush Jaiswal , Wael AbdAlmageed , Yue Wu , Premkumar Natarajan

Inspired by the observation of the $X(6900)$ by LHCb and the $X(6600)$ (with mass $6552\pm 10$ $\pm 12$ MeV) recently by CMS and ATLAS experiments of the LHC in the di-$J/\Psi $ invariant mass spectrum, we systemically study masses of all…

高能物理 - 唯象学 · 物理学 2023-09-14 Ting-Qi Yan , Wen-Xuan Zhang , Duojie Jia

The low-lying $S$-wave $QQ\bar{s}\bar{s}$ ($Q=c, b$) tetraquark states with $IJ^P=00^+$, $01^+$ and $02^+$ are systematically investigated in the framework of complex scaling range of chiral quark model. Every structure including…

高能物理 - 唯象学 · 物理学 2020-09-30 Gang Yang , Jialun Ping , Jorge Segovia

Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing 3D GANs are either compute-intensive or make approximations…

The discovery of four-quark states attracted a lot of attention from the theoretical as well as the experimental side. To study their properties from QCD we use a functional framework which combines (truncated) Dyson-Schwinger and…

高能物理 - 唯象学 · 物理学 2023-01-27 Joshua Hoffer , Christian S. Fischer

Traditionally, incorporating additional physics into existing cosmological simulations requires re-running the cosmological simulation code, which can be computationally expensive. We show that conditional Generative Adversarial Networks…

宇宙学与河外天体物理 · 物理学 2019-11-01 Florian List , Ishaan Bhat , Geraint F. Lewis

Conditional generative adversarial networks (cGANs) have been widely researched to generate class conditional images using a single generator. However, in the conventional cGANs techniques, it is still challenging for the generator to learn…

计算机视觉与模式识别 · 计算机科学 2020-04-09 Min-Cheol Sagong , Yong-Goo Shin , Yoon-Jae Yeo , Seung Park , Sung-Jea Ko

Accurate surface roughness prediction in ultra-precision machining (UPM) is critical for real-time quality control, but small datasets hinder model performance. We propose HAS-CGAN, a Hybrid Adversarial Spectral Loss CGAN, for effective UPM…

机器学习 · 计算机科学 2025-07-08 Suiyan Shang , Chi Fai Cheung , Pai Zheng