Review of SIS Experimental Results on Strangeness

>A review of meson emission in heavy ion collisions at incident energies around 1 -- 2 $A\cdot$GeV is presented. It is shown how the shape of the spectra and the various particle yields vary with system size, with centrality and with incident energy. A statistical model assuming thermal and chemical equilibrium and exact strangeness conservation (i.e. strangeness conservation per collision) explains most of the observed features. Emphasis is put onto the study of $K^+$ and $K^-$ emission. In the framework of this statistical model it is shown that the experimentally observed equality of $K^+$ and $K^-$ rates at threshold corrected energies $\sqrt{s} - \sqrt{s_{th}}$ is due to a crossing of two excitation functions. Furthermore, the independence of the $K^+$ to $K^-$ ratio on the number of participating nucleons observed between 1 and 10 $A\cdot$GeV is consistent with this model. The observed flow effects are beyond the scope of this model.Comment: 10 pages, 9 figures, Strangeness 2000, V International Conference on Strangeness in Quark Matter, July, 2000, Berkeley, Californi

Survey of experimental data

>A review of meson emission in heavy ion collisions at incident energies from SIS up to collider energies is presented. A statistical model assuming chemical equilibrium and local strangeness conservation (i.e. strangeness conservation per collision) explains most of the observed features. Emphasis is put onto the study of $K^+$ and $K^-$ emission at low incident energies. In the framework of this statistical model it is shown that the experimentally observed equality of $K^+$ and $K^-$ rates at ``threshold-corrected'' energies $\sqrt{s} - \sqrt{s_{th}}$ is due to a crossing of two excitation functions. Furthermore, the independence of the $K^+/K^-$ ratio on the number of participating nucleons observed between SIS and RHIC is consistent with this model. It is demonstrated that the $K^-$ production at SIS energies occurs predominantly via strangeness exchange and that this channel is approaching chemical equilibrium. The observed maximum in the $K^+/\pi^+$ excitation function is also seen in the ratio of strange to non-strange particle production. The appearance of this maximum around 30 $A\cdot$GeV is due to the energy dependence of the chemical freeze-out parameters $T$ and $\mu_B$.Comment: 13 pages, 14 figures, SQM2001 in Frankfurt, Sept. 2001, submitted to IO

Strange Particle Production from SIS to LHC

>1A review of meson emission in heavy ion collisions at incident energies from SIS up to collider energies is presented. A statistical model assuming chemical equilibrium and local strangeness conservation (i.e. strangeness conservation per collision) explains most of the observed features. Emphasis is put onto the study of $K^+$ and $K^-$ emission at low incident energies. In the framework of this statistical model it is shown that the experimentally observed equality of $K^+$ and $K^-$ rates at ``threshold-corrected'' energies $\sqrt{s} - \sqrt{s_{th}}$ is due to a crossing of two excitation functions. Furthermore, the independence of the $K^+$ to $K^-$ ratio on the number of participating nucleons observed between SIS and RHIC is consistent with this model. It is demonstrated that the $K^-$ production at SIS energies occurs predominantly via strangeness exchange and this channel is approaching chemical equilibrium. The observed maximum in the $K^+/\pi^+$ excitation function is also seen in the ratio of strange to non-strange particle production. The appearance of this maximum around 30 $A\cdot$GeV is due to the energy dependence of the chemical freeze-out parameters $T$ and $\mu_B$.Comment: Presented at the International Workshop "On the Physics of the Quark-Gluon Plasma", Palaiseau, France, September 2001. 10 pages, 8 figure

Nonparametric estimation of extremal dependence

There is an increasing interest to understand the dependence structure of a random vector not only in the center of its distribution but also in the tails. Extreme-value theory tackles the problem of modelling the joint tail of a multivariate distribution by modelling the marginal distributions and the dependence structure separately. For estimating dependence at high levels, the stable tail dependence function and the spectral measure are particularly convenient. These objects also lie at the basis of nonparametric techniques for modelling the dependence among extremes in the max-domain of attraction setting. In case of asymptotic independence, this setting is inadequate, and more refined tail dependence coefficients exist, serving, among others, to discriminate between asymptotic dependence and independence. Throughout, the methods are illustrated on financial data.Comment: 22 pages, 9 figure

Exchangeable Variable Models

A sequence of random variables is exchangeable if its joint distribution is invariant under variable permutations. We introduce exchangeable variable models (EVMs) as a novel class of probabilistic models whose basic building blocks are partially exchangeable sequences, a generalization of exchangeable sequences. We prove that a family of tractable EVMs is optimal under zero-one loss for a large class of functions, including parity and threshold functions, and strictly subsumes existing tractable independence-based model families. Extensive experiments show that EVMs outperform state of the art classifiers such as SVMs and probabilistic models which are solely based on independence assumptions.Comment: ICML 201

Quotient correlation: A sample based alternative to Pearson's correlation

The quotient correlation is defined here as an alternative to Pearson's correlation that is more intuitive and flexible in cases where the tail behavior of data is important. It measures nonlinear dependence where the regular correlation coefficient is generally not applicable. One of its most useful features is a test statistic that has high power when testing nonlinear dependence in cases where the Fisher's $Z$-transformation test may fail to reach a right conclusion. Unlike most asymptotic test statistics, which are either normal or $\chi^2$, this test statistic has a limiting gamma distribution (henceforth, the gamma test statistic). More than the common usages of correlation, the quotient correlation can easily and intuitively be adjusted to values at tails. This adjustment generates two new concepts--the tail quotient correlation and the tail independence test statistics, which are also gamma statistics. Due to the fact that there is no analogue of the correlation coefficient in extreme value theory, and there does not exist an efficient tail independence test statistic, these two new concepts may open up a new field of study. In addition, an alternative to Spearman's rank correlation, a rank based quotient correlation, is also defined. The advantages of using these new concepts are illustrated with simulated data and a real data analysis of internet traffic.Comment: Published in at http://dx.doi.org/10.1214/009053607000000866 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org