Holographic Shell Model: Stack Data Structure inside Black Holes

We suggest that bits of information inhabit, universally and holographically, the entire black hole interior, a bit per a light sheet unit interval of order Planck area difference. The number of distinguishable (tagged by a binary code) configurations, counted within the context of a discrete holographic shell model, is given by the Catalan series. The area entropy formula is recovered, including the universal logarithmic correction, and the equipartition of mass per degree of freedom is proven. The black hole information storage resembles a stack data structure.Comment: 4 pages, 3 figure

The Top Priority: Precision Electroweak Physics from Low to High Energy

Overall, the Standard Model describes electroweak precision data rather well. There are however a few areas of tension (charged current universality, NuTeV, (g-2)_\mu, b quark asymmetries), which I review emphasizing recent theoretical and experimental progress. I also discuss what precision data tell us about the Higgs boson and new physics scenarios. In this context, the role of a precise measurement of the top mass is crucial.Comment: 12 pages; invited talk at 21st International Symposium on Lepton and Photon Interactions at High Energies (LP 03), Batavia, Illinois, 11-16 Aug 200

A compact spectroradiometer for solar simulator measurements

Compact spectral irradiance probe has been designed and built which uses wedge filter in conjunction with silicon cell and operational amplifier. Probe is used to monitor spectral energy distribution of solar simulators and other high intensity sources

The Power of Bootstrap and Asymptotic Tests

We introduce the concept of the bootstrap discrepancy, which measures the difference in rejection probabilities between a bootstrap test based on a given test statistic and that of a (usually infeasible) test based on the true distribution of the statistic. We show that the bootstrap discrepancy is of the same order of magnitude under the null hypothesis and under non-null processes described by a Pitman drift. However, complications arise in the measurement of power. If the test statistic is not an exact pivot, critical values depend on which data-generating process (DGP) is used to determine the distribution under the null hypothesis. We propose as the proper choice the DGP which minimizes the bootstrap discrepancy. We also show that, under an asymptotic independence condition, the power of both bootstrap and asymptotic tests can be estimated cheaply by simulation. The theory of the paper and the proposed simulation method are illustrated by Monte Carlo experiments using the logit model.bootstrap test, bootstrap discrepancy, Pitman drift, drifting DGP, Monte Carlo, test power, power, asymptotic test

Regression-Based Methods for Using Control and Antithetic Variates in Monte Carlo Experiments

Methods based on linear regression provide a very easy way to use the information in control and antithetic variates to improve the efficiency with which certain features of the distributions of estimators and test statistics are estimated in Monte Carlo experiments. We propose a new technique that allows these methods to be used when the quantities of interest are quantiles. Ways to obtain approximately optimal control variates in many cases of interest are also proposed. These methods seem to work well in practice, and can greatly reduce the number of replications required to obtain a given level of accuracy.