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Register a new userA study of the solar neutrino survival probability
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We present a study of recent solar neutrino data using a Bayesian method. Assuming that only $ u_e$ are observed in the Super-Kamiokande experiment our results show a marked supression of the survival probability at about 1 MeV, in good agreement with $chi ^2$-based analyses. When the detection of $ u_{mu}$ by Super-Kamiokande is taken into account, assuming $ u_e$ to $ u_{mu}$ oscillations, we find the largest suppression in survival probability at about 8.5 MeV.
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With SNO data on electron-neutrino flux from the sun, it is possible to derive the $ u_e$ survival probability $P_{ee}(E)$ from existing experimental data of Super-Kamiokande, gallium experiments and Homestake. The combined data of SNO and Super-Kamiokande provide boron $ u_e$ flux and the total flux of all active boron neutrinos, giving thus $P_{ee}(E)$ for boron neutrinos. The Homestake detector, after subtraction of the signal from boron neutrinos, gives the flux of Be+CNO neutrinos, and $P_{ee}$ for the corresponding energy interval, if the produced flux is taken from the Standard Solar Model (SSM). Gallium detectors, GALLEX, SAGE and GNO, detect additionally pp-neutrinos. The pp-flux can be calculated subtracting from the gallium signal the rate due to boron, beryllium and CNO neutrinos. The ratio of the measured $pp$-neutrino flux to that predicted by the SSM gives the survival probability for $pp$-neutrinos. Comparison with theoretical survival probabilities shows that the best (among known models) fit is given by LMA and LOW solutions.
First passage models, where corporate assets undergo correlated random walks and a company defaults if its assets fall below a threshold provide an attractive framework for modeling the default process. Typical one year default correlations are small, i.e., of order a few percent, but nonetheless including correlations is very important, for managing portfolio credit risk and pricing some credit derivatives (e.g. first to default baskets). In first passage models the exact dependence of the joint survival probability of more than two firms on their asset correlations is not known. We derive an expression for the dependence of the joint survival probability of $n$ firms on their asset correlations using first order perturbation theory in the correlations. It includes all terms that are linear in the correlations but neglects effects of quadratic and higher order. For constant time independent correlations we compare the first passage model expression for the joint survival probability with what a multivariate normal Copula function gives. As a practical application of our results we calculate the dependence of the five year joint survival probability for five basic industrials on their asset correlations.
Consider a discrete-time one-dimensional supercritical branching random walk. We study the probability that there exists an infinite ray in the branching random walk that always lies above the line of slope $gamma-epsilon$, where $gamma$ denotes the asymptotic speed of the right-most position in the branching random walk. Under mild general assumptions upon the distribution of the branching random walk, we prove that when $epsilonto 0$, the probability in question decays like $exp{- {beta + o(1)over epsilon^{1/2}}}$, where $beta$ is a positive constant depending on the distribution of the branching random walk. In the special case of i.i.d. Bernoulli$(p)$ random variables (with $0<p<{1over 2}$) assigned on a rooted binary tree, this answers an open question of Robin Pemantle.
We discuss recent calculations of the survival probability of the large rapidity gaps in exclusive processes of the type pp --> p+A+p at high energies. Absorptive or screening effects are important, and one consequence is that the total cross section at the LHC is predicted to be only about 90 mb.
We consider branching Brownian motion on the real line with absorption at zero, in which particles move according to independent Brownian motions with the critical drift of $-sqrt{2}$. Kesten (1978) showed that almost surely this process eventually dies out. Here we obtain upper and lower bounds on the probability that the process survives until some large time $t$. These bounds improve upon results of Kesten (1978), and partially confirm nonrigorous predictions of Derrida and Simon (2007).
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