Dimensionality reduction (DR) of data is a crucial issue for many machine learning tasks, such as pattern recognition and classification. In this paper, we present quantum algorithm circuit to efficiently perform linear discriminant analysis (LDA) dimensionality reduction. Firstly, the presented improves existing LDA avoid error caused by irreversibility between-class scatter matrix $S_B$ in or...

In this paper, we present a data-driven analysis of the $\gamma\gamma\to D^+D^-$ and D^0\bar{D}^0$ reactions from threshold up to 4.0 GeV in $D\bar{D}$ invariant mass. For $S$-wave contribution, adopt partial-wave dispersive representation, which is solved using $N/D$ ansatz. The left-hand cuts are accounted for model-independent conformal expansion. $D$-wave $\chi_{c2}(3930)$ state described a...

Using recent results on higher order cumulants of conserved charge fluctuations from lattice QCD, we construct mean, variance, skewness, kurtosis, hyper-skewness and hyper-kurtosis net-baryon number distributions for small baryon chemical potentials $\mu_B$. For the strangeness neutral case ($\mu_S=0$) at fixed ratio electric to density ($\frac{n_Q}{n_B}=0.4$), which is appropriate a comparison...

Avispa is now a commonly used verification tool for cryptographic protocols. The main advantage of this tool is the ability to use different verification techniques on the same protocol specification. In this paper, we present a protocol animator designed to help protocol developers in writing AVISPA specifications. This is the result of an ongoing joint experiment with Thomson R&D to use AVISP...