Unquenched complex Dirac spectra at nonzero chemical potential: Two-colour QCD lattice data versus matrix model

We compare analytic predictions of non-Hermitian chiral random matrix theory with the complex Dirac operator eigenvalue spectrum of two-color lattice gauge theory with dynamical fermions at nonzero chemical potential. The Dirac eigenvalues come in complex conjugate pairs, making the action of this theory real and positive for our choice of two staggered flavors. This enables us to use standard Monte Carlo simulations in testing the influence of the chemical potential and quark mass on complex eigenvalues close to the origin. We find excellent agreement between the analytic predictions and our data for two different volumes over a range of chemical potentials below the chiral phase transition. In particular, we detect the effect of unquenching when going to very small quark masses

Soccer: is scoring goals a predictable Poissonian process?

The non-scientific event of a soccer match is analysed on a strictly scientific level. The analysis is based on the recently introduced concept of a team fitness (Eur. Phys. J. B 67, 445, 2009) and requires the use of finite-size scaling. A uniquely defined function is derived which quantitatively predicts the expected average outcome of a soccer match in terms of the fitness of both teams. It is checked whether temporary fitness fluctuations of a team hamper the predictability of a soccer match. To a very good approximation scoring goals during a match can be characterized as independent Poissonian processes with pre-determined expectation values. Minor correlations give rise to an increase of the number of draws. The non-Poissonian overall goal distribution is just a consequence of the fitness distribution among different teams. The limits of predictability of soccer matches are quantified. Our model-free classification of the underlying ingredients determining the outcome of soccer matches can be generalized to different types of sports events

Field To Flight: A Techno-Economic Analysis of Stover to Aviation Biofuels Supply Chain

Greenhouse gas emissions have been a growing concern. The transportation sector contributes to one-third of GHG emissions in the United States from fossil fuel burning. The Renewable Fuel Standard set a requirement for 16 billion gallons (ethanol equivalent) of cellulosic biofuels to be used in the market. Aviation biofuels can help to meet both of these problems as well as improve U.S. energy security. Investment in the biofuel industry carries a lot of risk. The biofuel industry is run by the private sector, but can be incentivized by government. Cellulosic biofuels carry even more risk than first generation biofuels, because conversion technology is more expensive. As a result, incentives are needed to reduce the risk for private investors. Government can implement policies to reduce the risk in investment in aviation biofuels. The issue is choosing which policy will provide the most reduction in risk, while providing a lowest cost to the government. This analysis focuses on aviation biofuel production using fast pyrolysis from corn stover. Cost benefit analysis is used to calculate the net present value, internal rate of return, and benefit-cost ratio for a plant. We look at deterministic and stochastic cases. For the stochastic cases, this study uses @Risk, a Palisades Corporation software to determine the risk of investment in aviation biofuels. Uncertainty is added to fuel price and four technical variables: capital cost, final fuel yield, hydrogen cost, and feedstock cost. The fuel price can be steady or increasing at DOE projections. We look at the impact of three policies: reverse auction, competitive capital subsidy, and carbon tax. For the reverse auction and capital subsidy, we used contract lengths of 5, 10, and 15 years to see the impact a longer contract could have on probability of loss. All three policies reduced risk in investment of aviation biofuels. A reverse auction reduced risk of investment the most. As the contract length increased, the probability of loss and coefficient of variation in net present value were reduced substantially. When fuel price increased stochastically and a contract length of 15 years was used, probability of loss was reduced to 9.9 percent

Lattice Models of Quantum Gravity

Standard Regge Calculus provides an interesting method to explore quantum gravity in a non-perturbative fashion but turns out to be a CPU-time demanding enterprise. One therefore seeks for suitable approximations which retain most of its universal features. The $Z_2$-Regge model could be such a desired simplification. Here the quadratic edge lengths $q$ of the simplicial complexes are restricted to only two possible values $q=1+\epsilon\sigma$, with $\sigma=\pm 1$, in close analogy to the ancestor of all lattice theories, the Ising model. To test whether this simpler model still contains the essential qualities of the standard Regge Calculus, we study both models in two dimensions and determine several observables on the same lattice size. In order to compare expectation values, e.g. of the average curvature or the Liouville field susceptibility, we employ in both models the same functional integration measure. The phase structure is under current investigation using mean field theory and numerical simulation.Comment: 4 pages, 1 figure

A Simple Non-Markovian Computational Model of the Statistics of Soccer Leagues: Emergence and Scaling effects

We propose a novel algorithm that outputs the final standings of a soccer league, based on a simple dynamics that mimics a soccer tournament. In our model, a team is created with a defined potential(ability) which is updated during the tournament according to the results of previous games. The updated potential modifies a teams' future winning/losing probabilities. We show that this evolutionary game is able to reproduce the statistical properties of final standings of actual editions of the Brazilian tournament (Brasileir\~{a}o). However, other leagues such as the Italian and the Spanish tournaments have notoriously non-Gaussian traces and cannot be straightforwardly reproduced by this evolutionary non-Markovian model. A complete understanding of these phenomena deserves much more attention, but we suggest a simple explanation based on data collected in Brazil: Here several teams were crowned champion in previous editions corroborating that the champion typically emerges from random fluctuations that partly preserves the gaussian traces during the tournament. On the other hand, in the Italian and Spanish leagues only a few teams in recent history have won their league tournaments. These leagues are based on more robust and hierarchical structures established even before the beginning of the tournament. For the sake of completeness, we also elaborate a totally Gaussian model (which equalizes the winning, drawing, and losing probabilities) and we show that the scores of the "Brasileir\~{a}o" cannot be reproduced. Such aspects stress that evolutionary aspects are not superfluous in our modeling. Finally, we analyse the distortions of our model in situations where a large number of teams is considered, showing the existence of a transition from a single to a double peaked histogram of the final classification scores. An interesting scaling is presented for different sized tournaments.Comment: 18 pages, 9 figure

Make life simple: unleash the full power of the parallel tempering algorithm

We introduce a new update scheme to systematically improve the efficiency of parallel tempering simulations. We show that by adapting the number of sweeps between replica exchanges to the canonical autocorrelation time, the average round-trip time of a replica in temperature space can be significantly decreased. The temperatures are not dynamically adjusted as in previous attempts but chosen to yield a 50% exchange rate of adjacent replicas. We illustrate the new algorithm with results for the Ising model in two and the Edwards-Anderson Ising spin glass in three dimensionsComment: 4 pages, 5 figure