Dark photon effects with the kinetic and mass mixing in Z→τ−τ+Z\to \tau^-\tau^+

Motivated by the most recent measurement of tau polarization in $Z\to \tau^-\tau^-$ by CMS, we have introduced a new $U(1)_X$ gauge boson field X, which can have renormalizable kinetic mixing with the standard model $U(1)_Y$ gauge boson field Y. In addition to the kinetic mixing of the dark photon, denoted as $\sigma$, there may also be mass mixing introduced by the additional Higgs doublet with a vacuum expectation value (vev) participating in $U(1)_X$ and electroweak symmetry breaking simultaneously. The interaction of the Z boson with the SM tau lepton is modified by the introduction of the mixing ratio parameter $\epsilon$, which quantifies the magnitude of both the mass and kinetic mixing of the dark photon. We investigate the Z boson phenomenology of the dark photon model with both kinetic and mass mixing. The allowed parameter region is obtained by analyzing these constraints from the vector and axial-vector couplings $g_{V,A}^\tau$, the decay branching ratio $Br(Z\to \tau^- \tau^+)$ and tau lepton polarization in $Z\to \tau^-\tau^+$. We found that the mixing ratio plays important role in the Z boson features by choosing different $\epsilon$ values. Furthermore, we attempt to identify common regions that satisfy the aforementioned four constraints for both $m_X>m_Z$ and $m_X<m_Z$. However, the regions allowed by $g_A^\tau$ and $Br(Z\to \tau^-\tau^-)$ tend to point in opposite directions, making it impossible to find viable parameter spaces within $2\sigma$ errors. The problem can be resolved within a $3\sigma$ error margin.Comment: 8 pages,3 figure

Track-before-detect Algorithm based on Cost-reference Particle Filter Bank for Weak Target Detection

Detecting weak target is an important and challenging problem in many applications such as radar, sonar etc. However, conventional detection methods are often ineffective in this case because of low signal-to-noise ratio (SNR). This paper presents a track-before-detect (TBD) algorithm based on an improved particle filter, i.e. cost-reference particle filter bank (CRPFB), which turns the problem of target detection to the problem of two-layer hypothesis testing. The first layer is implemented by CRPFB for state estimation of possible target. CRPFB has entirely parallel structure, consisting amounts of cost-reference particle filters with different hypothesized prior information. The second layer is to compare a test metric with a given threshold, which is constructed from the output of the first layer and fits GEV distribution. The performance of our proposed TBD algorithm and the existed TBD algorithms are compared according to the experiments on nonlinear frequency modulated (NLFM) signal detection and tracking. Simulation results show that the proposed TBD algorithm has better performance than the state-of-the-arts in detection, tracking, and time efficiency

Novel models for fatigue life prediction under wideband random loads based on machine learning

Machine learning as a data-driven solution has been widely applied in the field of fatigue lifetime prediction. In this paper, three models for wideband fatigue life prediction are built based on three machine learning models, i.e. support vector machine (SVM), Gaussian process regression (GPR) and artificial neural network (ANN). The generalization ability of the models is enhanced by employing numerous power spectra samples with different bandwidth parameters and a variety of material properties related to fatigue life. Sufficient Monte Carlo numerical simulations demonstrate that the newly developed machine learning models are superior to the traditional frequency-domain models in terms of life prediction accuracy and the ANN model has the best overall performance among the three developed machine learning models

Light baryon in three quark picture light front approach and its application: hyperon weak radiative decays

Motivated by recent experimental data on $\Sigma^+\to p\gamma$ at BESIII, we investigate a class of hyperon weak radiative decays. To estimate these processes, in our research, we employ a new type of light-front quark model with a three-quark picture for octet baryons. In the three-quark picture, with the use of $SU(3)_f$ and spin symmetries, we present a general form of the light front wave function for each octet baryon. By including contributions from the penguin diagram and W exchange diagram, we perform a complete calculation on the branching ratios ($Br$) and the asymmetry parameter ($\alpha$) for hyperon weak radiative decay processes. Our results are helpful for discovering additional hyperon weak radiative decay processes in experimental facilities, and our research will promote the theoretical study of baryons.Comment: 15 pages, 2 figures, 5 table

The chloride channel cystic fibrosis transmembrane conductance regulator (CFTR) controls cellular quiescence by hyperpolarizing the cell membrane during diapause in the crustacean Artemia

Cellular quiescence, a reversible state in which growth, proliferation, and other cellular activities are arrested, is important for self-renewal, differentiation, development, regeneration, and stress resistance. However, the physiological mechanisms underlying cellular quiescence remain largely unknown. In the present study, we used embryos of the crustacean Artemia in the diapause stage, in which these embryos remain quiescent for prolonged periods, as a model to explore the relationship between cell-membrane potential (V-mem) and quiescence. We found that V-mem is hyperpolarized and that the intracellular chloride concentration is high in diapause embryos, whereas V-mem is depolarized and intracellular chloride concentration is reduced in postdiapause embryos and during further embryonic development. We identified and characterized the chloride ion channel protein cystic fibrosis transmembrane conductance regulator (CFTR) of Artemia (Ar-CFTR) and found that its expression is silenced in quiescent cells of Artemia diapause embryos but remains constant in all other embryonic stages. Ar-CFTR knockdown and GlyH-101-mediated chemical inhibition of Ar-CFTR produced diapause embryos having a high V-mem and intracellular chloride concentration, whereas control Artemia embryos released free-swimming nauplius larvae. Transcriptome analysis of embryos at different developmental stages revealed that proliferation, differentiation, and metabolism are suppressed in diapause embryos and restored in postdiapause embryos. Combined with RNA sequencing (RNA-Seq) of GlyH-101-treated MCF-7 breast cancer cells, these analyses revealed that CFTR inhibition down-regulates the Wnt and Aurora Kinase A (AURKA) signaling pathways and up-regulates the p53 signaling pathway. Our findings provide insight into CFTR-mediated regulation of cellular quiescence and V-mem in the Artemia model

Dark photon kinetic mixing effects for the CDF W-mass measurement

A new $U(1)_X$ gauge boson $X$ primarily interacting with a dark sector can have renormalizable kinetic mixing with the standard model (SM) $U(1)_Y$ gauge boson $Y$. This mixing besides introduces interactions of dark photon and dark sector with SM particles, it also modifies interactions among SM particles. The modified interactions can be casted into the oblique $S$, $T$ and $U$ parameters. We find that with the dark photon mass larger than the $Z$ boson mass, the kinetic mixing effects can reduce the tension of the W mass excess problem reported recently by CDF from $7\sigma$ deviation to within $3 \sigma$ compared with theory prediction. If there is non-abelian kinetic mixing between $U(1)_X$ and $SU(2)_L$ gauge bosons, in simple renormalizable models of this type a triplet Higgs is required to generate the mixing. We find that this triplet with a vacuum expectation value of order 5 GeV can naturally explain the W mass excess.Comment: 10 pages, add new ref and no change for conclusio

Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs

Most text-driven human motion generation methods employ sequential modeling approaches, e.g., transformer, to extract sentence-level text representations automatically and implicitly for human motion synthesis. However, these compact text representations may overemphasize the action names at the expense of other important properties and lack fine-grained details to guide the synthesis of subtly distinct motion. In this paper, we propose hierarchical semantic graphs for fine-grained control over motion generation. Specifically, we disentangle motion descriptions into hierarchical semantic graphs including three levels of motions, actions, and specifics. Such global-to-local structures facilitate a comprehensive understanding of motion description and fine-grained control of motion generation. Correspondingly, to leverage the coarse-to-fine topology of hierarchical semantic graphs, we decompose the text-to-motion diffusion process into three semantic levels, which correspond to capturing the overall motion, local actions, and action specifics. Extensive experiments on two benchmark human motion datasets, including HumanML3D and KIT, with superior performances, justify the efficacy of our method. More encouragingly, by modifying the edge weights of hierarchical semantic graphs, our method can continuously refine the generated motion, which may have a far-reaching impact on the community. Code and pre-training weights are available at https://github.com/jpthu17/GraphMotion.Comment: Accepted by NeurIPS 202