The effects of the pre-pulse on capillary discharge extreme ultraviolet laser

In the past few years collisionally pumped extreme ultraviolet (XUV) lasers utilizing a capillary discharge were demonstrated. An intense current pulse is applied to a gas filled capillary, inducing magnetic collapse (Z-pinch) and formation of a highly ionized plasma column. Usually, a small current pulse (pre-pulse) is applied to the gas in order to pre-ionize it prior to the onset of the main current pulse. In this paper we investigate the effects of the pre-pulse on a capillary discharge Ne-like Ar XUV laser (46.9nm). The importance of the pre-pulse in achieving suitable initial conditions of the gas column and preventing instabilities during the collapse is demonstrated. Furthermore, measurements of the amplified spontaneous emission (ASE) properties (intensity, duration) in different pre-pulse currents revealed unexpected sensitivity. Increasing the pre-pulse current by a factor of two caused the ASE intensity to decrease by an order of magnitude - and to nearly disappear. This effect is accompanied by a slight increase in the lasing duration. We attribute this effect to axial flow in the gas during the pre-pulse.Comment: 4 pages, 4 figure

The Buckland Park air shower array

The new Buckland Park Air Shower Array has been producing analyzed shower data since July 1984. The array is described and some preliminary performance figures are presented

Beta lives - some statistical perspectives on the capital asset pricing model

This note summarizes some technical issues relevant to the use of the idea of excess return in empirical modelling. We cover the case where the aim is to construct a measure of expected return on an asset and a model of the CAPM type is used. We review some of the problems and show examples where the basic CAPM may be used to develop other results which relate the expected returns on assets both to the expected return on the market and other factors

Random Matrix Theory Analysis of Cross Correlations in Financial Markets

We confirm universal behaviors such as eigenvalue distribution and spacings predicted by Random Matrix Theory (RMT) for the cross correlation matrix of the daily stock prices of Tokyo Stock Exchange from 1993 to 2001, which have been reported for New York Stock Exchange in previous studies. It is shown that the random part of the eigenvalue distribution of the cross correlation matrix is stable even when deterministic correlations are present. Some deviations in the small eigenvalue statistics outside the bounds of the universality class of RMT are not completely explained with the deterministic correlations as proposed in previous studies. We study the effect of randomness on deterministic correlations and find that randomness causes a repulsion between deterministic eigenvalues and the random eigenvalues. This is interpreted as a reminiscent of ``level repulsion'' in RMT and explains some deviations from the previous studies observed in the market data. We also study correlated groups of issues in these markets and propose a refined method to identify correlated groups based on RMT. Some characteristic differences between properties of Tokyo Stock Exchange and New York Stock Exchange are found.Comment: RevTex, 17 pages, 8 figure

Calibration of optimal execution of financial transactions in the presence of transient market impact

Trading large volumes of a financial asset in order driven markets requires the use of algorithmic execution dividing the volume in many transactions in order to minimize costs due to market impact. A proper design of an optimal execution strategy strongly depends on a careful modeling of market impact, i.e. how the price reacts to trades. In this paper we consider a recently introduced market impact model (Bouchaud et al., 2004), which has the property of describing both the volume and the temporal dependence of price change due to trading. We show how this model can be used to describe price impact also in aggregated trade time or in real time. We then solve analytically and calibrate with real data the optimal execution problem both for risk neutral and for risk averse investors and we derive an efficient frontier of optimal execution. When we include spread costs the problem must be solved numerically and we show that the introduction of such costs regularizes the solution.Comment: 31 pages, 8 figure

Data clustering and noise undressing for correlation matrices

We discuss a new approach to data clustering. We find that maximum likelihood leads naturally to an Hamiltonian of Potts variables which depends on the correlation matrix and whose low temperature behavior describes the correlation structure of the data. For random, uncorrelated data sets no correlation structure emerges. On the other hand for data sets with a built-in cluster structure, the method is able to detect and recover efficiently that structure. Finally we apply the method to financial time series, where the low temperature behavior reveals a non trivial clustering.Comment: 8 pages, 5 figures, completely rewritten and enlarged version of cond-mat/0003241. Submitted to Phys. Rev.