On the Throughput of Channels that Wear Out

This work investigates the fundamental limits of communication over a noisy discrete memoryless channel that wears out, in the sense of signal-dependent catastrophic failure. In particular, we consider a channel that starts as a memoryless binary-input channel and when the number of transmitted ones causes a sufficient amount of damage, the channel ceases to convey signals. Constant composition codes are adopted to obtain an achievability bound and the left-concave right-convex inequality is then refined to obtain a converse bound on the log-volume throughput for channels that wear out. Since infinite blocklength codes will always wear out the channel for any finite threshold of failure and therefore cannot convey information at positive rates, we analyze the performance of finite blocklength codes to determine the maximum expected transmission volume at a given level of average error probability. We show that this maximization problem has a recursive form and can be solved by dynamic programming. Numerical results demonstrate that a sequence of block codes is preferred to a single block code for streaming sources.Comment: 23 pages, 1 table, 11 figures, submitted to IEEE Transactions on Communication

Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM

We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known. To solve this semi-blind deconvolution problem, prior distributions are specified for the PSF and the 3D image. Joint image reconstruction and PSF estimation is then performed within a Bayesian framework, using a variational algorithm to estimate the posterior distribution. The image prior distribution imposes an explicit atomic measure that corresponds to image sparsity. Importantly, the proposed Bayesian deconvolution algorithm does not require hand tuning. Simulation results clearly demonstrate that the semi-blind deconvolution algorithm compares favorably with previous Markov chain Monte Carlo (MCMC) version of myopic sparse reconstruction. It significantly outperforms mismatched non-blind algorithms that rely on the assumption of the perfect knowledge of the PSF. The algorithm is illustrated on real data from magnetic resonance force microscopy (MRFM)

Testing Game Theory in the Field: Swedish LUPI Lottery Games

Game theory is usually difficult to test precisely in the field because predictions typically depend sensitively on features that are not controlled or observed. We conduct one such test using field data from the Swedish lowest unique positive integer (LUPI) game. In the LUPI game, players pick positive integers and whoever chose the lowest unique number wins a fixed prize. Theoretical equilibrium predictions are derived assuming Poisson- distributed uncertainty about the number of players, and tested using both field and laboratory data. The field and lab data show similar patterns. Despite various deviations from equilibrium, there is a surprising degree of convergence toward equilibrium. Some of the deviations from equilibrium can be rationalized by a cognitive hierarchy model

Statistics of lower tropospheric inversions over the continental United States

The basic structure parameters of lower tropospheric inversions (LTIs) have been derived from 10 years (1998–2007) of high vertical resolution (~50 m) radiosonde observations over 56 United States stations. Seasonal and longitudinal variability of these parameters are presented and the formation mechanisms of LTI are also discussed. It is found that LTI seems to be a common feature over the continental United States. The LTI occurrence rates (defined as the fraction of measurements with LTI, which is calculated from the number of LTI cases divided by the number of measurements of the whole 10 years) at these 56 stations vary from 3.7% to 14.5%; the averaged base heights of LTI have a range of 3–5 km above mean sea level (a.m.s.l.); the averaged thicknesses and temperature jump ranges from 420–465 m and 1.9–2.2 K, respectively. These parameters have an obvious seasonal variation. In winter, all the occurrence rates, thicknesses and temperature jumps of LTI have much larger values than those in summer. LTI occurrence rate shows an obvious west-east increasing trend in all 4 seasons. Detailed analyses reveal that dynamical instability induced by strong zonal wind shear is responsible for LTI in winter, spring and autumn; the frontal system tends to generate LTI in summer. Since the higher occurrence rate, larger temperature jump and larger thickness of LTI occur in winter, we believe strong zonal wind shear plays a more important role in the formation of LTI

Evaluation of ECMWF medium-range ensemble forecasts of precipitation for river basins

Providing probabilistic forecasts using Ensemble Prediction Systems has become increasingly popular in both the meteorological and hydrological communities. Compared to conventional deterministic forecasts, probabilistic forecasts may provide more reliable forecasts of a few hours to a number of days ahead, and hence are regarded as better tools for taking uncertainties into consideration and hedging against weather risks. It is essential to evaluate performance of raw ensemble forecasts and their potential values in forecasting extreme hydro-meteorological events. This study evaluates ECMWF's medium-range ensemble forecasts of precipitation over the period 1 January 2008 to 30 September 2012 on a selected midlatitude large-scale river basin, the Huai river basin (ca. 270 000 km2) in central-east China. The evaluation unit is sub-basin in order to consider forecast performance in a hydrologically relevant way. The study finds that forecast performance varies with sub-basin properties, between flooding and non-flooding seasons, and with the forecast properties of aggregated time steps and lead times. Although the study does not evaluate any hydrological applications of the ensemble precipitation forecasts, its results have direct implications in hydrological forecasts should these ensemble precipitation forecasts be employed in hydrology

Detecting Extra Dimension by Helium-like Ions

Considering that gravitational force might deviate from Newton's inverse-square law and become much stronger in small scale, we present a method to detect the possible existence of extra dimensions in the ADD model. By making use of an effective variational wave function, we obtain the nonrelativistic ground energy of a helium atom and its isoelectronic sequence. Based on these results, we calculate gravity correction of the ADD model. Our calculation may provide a rough estimation about the magnitude of the corresponding frequencies which could be measured in later experiments.Comment: 8 pages, no figures, accepted by Mod. Phys. Lett.