Determining VtbV_{tb} at Electron-Positron Colliders

Verifying $V_{tb} \simeq 1$ is critical to test the three generation assumption of the Standard Model. So far our best knowledge of $V_{tb}$ is inferred either from the $3\times 3$ unitarity of CKM matrix or from single top-quark productions upon the assumption of universal weak couplings. The unitarity could be relaxed in new physics models with extra heavy quarks and the universality of weak couplings could also be broken if the $Wtb$ coupling is modified in new physics models. In this work we propose to measure $V_{tb}$ in the process of $e^+ e^- \to t\bar{t}$ without prior knowledge of the number of fermion generations or the strength of the $Wtb$ coupling. Using an effective Lagrangian approach, we perform a model-independent analysis of the interactions among electroweak gauge bosons and the third generation quarks, i.e. the $Wtb$, $Zt\bar{t}$ and $Zb\bar{b}$ couplings. The electroweak symmetry of the Standard Model specifies a pattern of deviations of the $Z$-$t_L$-$t_L$ and $W$-$t_L$-$b_L$ couplings after one imposes the known experimental constraint on the $Z$-$b_L$-$b_L$ coupling. We demonstrate that, making use of the predicted pattern and the accurate measurements of top-quark mass and width from the energy threshold scan experiments, one can determine $V_{tb}$ from the cross section and the forward-backward asymmetry of top-quark pair production at an {\it unpolarized} electron-positron collider.Comment: publish versio

Quadratic Projection Based Feature Extraction with Its Application to Biometric Recognition

This paper presents a novel quadratic projection based feature extraction framework, where a set of quadratic matrices is learned to distinguish each class from all other classes. We formulate quadratic matrix learning (QML) as a standard semidefinite programming (SDP) problem. However, the con- ventional interior-point SDP solvers do not scale well to the problem of QML for high-dimensional data. To solve the scalability of QML, we develop an efficient algorithm, termed DualQML, based on the Lagrange duality theory, to extract nonlinear features. To evaluate the feasibility and effectiveness of the proposed framework, we conduct extensive experiments on biometric recognition. Experimental results on three representative biometric recogni- tion tasks, including face, palmprint, and ear recognition, demonstrate the superiority of the DualQML-based feature extraction algorithm compared to the current state-of-the-art algorithm

Thermodynamic Magnon Recoil for Domain Wall Motion

We predict a thermodynamic magnon recoil effect for domain wall motions in the presence of temperature gradients. All current thermodynamic theories assert that a magnetic domain wall must move toward the hotter side, based on equilibrium thermodynamic arguments. Microscopic calculations on the other hand show that a domain wall can move either along or against the direction of heat currents, depending on how strong the heat currents are reflected by the domain wall. We have resolved the inconsistency between these two approaches by augmenting the theory in the presence of thermal gradients by incorporating in the free energy of domain walls by a heat current term present in nonequilibrium steady states. The condition to observe a domain wall propagation toward the colder regime is derived analytically and can be tested by future experiments.Comment: Submitted with revision