Kernel Truncated Regression Representation for Robust Subspace Clustering

Subspace clustering aims to group data points into multiple clusters of which each corresponds to one subspace. Most existing subspace clustering approaches assume that input data lie on linear subspaces. In practice, however, this assumption usually does not hold. To achieve nonlinear subspace clustering, we propose a novel method, called kernel truncated regression representation. Our method consists of the following four steps: 1) projecting the input data into a hidden space, where each data point can be linearly represented by other data points; 2) calculating the linear representation coefficients of the data representations in the hidden space; 3) truncating the trivial coefficients to achieve robustness and block-diagonality; and 4) executing the graph cutting operation on the coefficient matrix by solving a graph Laplacian problem. Our method has the advantages of a closed-form solution and the capacity of clustering data points that lie on nonlinear subspaces. The first advantage makes our method efficient in handling large-scale datasets, and the second one enables the proposed method to conquer the nonlinear subspace clustering challenge. Extensive experiments on six benchmarks demonstrate the effectiveness and the efficiency of the proposed method in comparison with current state-of-the-art approaches.Comment: 14 page

Thermodynamics of pairing transition in hot nuclei

The pairing correlations in hot nuclei $^{162}$Dy are investigated in terms of the thermodynamical properties by covariant density functional theory. The heat capacities $C_V$ are evaluated in the canonical ensemble theory and the paring correlations are treated by a shell-model-like approach, in which the particle number is conserved exactly. A S-shaped heat capacity curve, which agrees qualitatively with the experimental data, has been obtained and analyzed in details. It is found that the one-pair-broken states play crucial roles in the appearance of the S shape of the heat capacity curve. Moreover, due to the effect of the particle-number conservation, the pairing gap varies smoothly with the temperature, which indicates a gradual transition from the superfluid to the normal state.Comment: 13 pages, 4 figure

Weak Decays of Doubly Heavy Baryons: the 1/2→1/21/2\to 1/2 case

Very recently, the LHCb collaboration has observed in the final state $\Lambda_c^+ K^-\pi^+\pi^+$ a resonant structure that is identified as the doubly-charmed baryon $\Xi_{cc}^{++}$. Inspired by this observation, we investigate the weak decays of doubly heavy baryons $\Xi_{cc}^{++}$, $\Xi_{cc}^{+}$, $\Omega_{cc}^{+}$, $\Xi_{bc}^{(\prime)+}$, $\Xi_{bc}^{(\prime)0}$, $\Omega_{bc}^{(\prime)0}$, $\Xi_{bb}^{0}$, $\Xi_{bb}^{-}$ and $\Omega_{bb}^{-}$ and focus on the decays into spin $1/2$ baryons in this paper. At the quark level these decay processes are induced by the $c\to d/s$ or $b\to u/c$ transitions, and the two spectator quarks can be viewed as a scalar or axial vector diquark. We first derive the hadronic form factors for these transitions in the light-front approach and then apply them to predict the partial widths for the semi-leptonic and non-leptonic decays of doubly heavy baryons. We find that a number of decay channels are sizable and can be examined in future measurements at experimental facilities like LHC, Belle II and CEPC.Comment: 40 pages, 4 figures, to appear in EPJ

Modular Design of an Educational Robotics Platform

The goal of this thesis is to design a modular educational robotics platform to improve the limitation of current educational robotics platforms, such as limited pins, single programming language, and single programming device. This platform uses an SPI bus for modularity and to solve the problem of limited pins on current educational robot platforms. A Raspberry Pi, which runs a 32bit Embedded Linux System, has been used to build the central control for this educational robotics platform to enable it to use different programming languages and to be programmed by different devices. The modules and libraries for stepper motors and IR sensors have been built for this robot, and the example projects, basic control, obstacle avoidance, and wall following, show that this educational robotics platform can be used as a platform for basic artificial intelligence design. This thesis also shows how to design a custom module, which enables users to design their own modules and put them into their robot projects