Structural transitions in vertically and horizontally coupled parabolic channels of Wigner crystals

Structural phase transitions in two vertically or horizontally coupled channels of strongly interacting particles are investigated. The particles are free to move in the $x$-direction but are confined by a parabolic potential in the $y$-direction. They interact with each other through a screened power-law potential ($r^{-n}e^{-r/\lambda}$). In vertically coupled systems the channels are stacked above each other in the direction perpendicular to the $(x,y)$-plane, while in horizontally coupled systems both channels are aligned in the confinement direction. Using Monte Carlo (MC) simulations we obtain the ground state configurations and the structural transitions as a function of the linear particle density and the separation between the channels. At zero temperature the vertically coupled system exhibits a rich phase diagram with continuous and discontinuous transitions. On the other hand the vertically coupled system exhibits only a very limited number of phase transitions due to its symmetry. Further we calculated the normal modes for the Wigner crystals in both cases. From MC simulations we found that in the case of vertically coupled systems the zigzag transition is only possible for low densities. A Ginzburg-Landau theory for the zigzag transition is presented, which predicts correctly the behavior of this transition from which we interpret the structural phase transition of the Wigner crystal through the reduction of the Brillouin zone.Comment: 9 pages, 13 figure

Diversity of chemistry and excitation conditions in the high-mass star forming complex W33

The object W33 is a giant molecular cloud that contains star forming regions at various evolutionary stages from quiescent clumps to developed H II regions. Since its star forming regions are located at the same distance and the primary material of the birth clouds is probably similar, we conducted a comparative chemical study to trace the chemical footprint of the different phases of evolution. We observed six clumps in W33 with the Atacama Pathfinder Experiment (APEX) telescope at 280 GHz and the Submillimeter Array (SMA) at 230 GHz. We detected 27 transitions of 10 different molecules in the APEX data and 52 transitions of 16 different molecules in the SMA data. The chemistry on scales larger than $\sim$0.2 pc, which are traced by the APEX data, becomes more complex and diverse the more evolved the star forming region is. On smaller scales traced by the SMA data, the chemical complexity and diversity increase up to the hot core stage. In the H II region phase, the SMA spectra resemble the spectra of the protostellar phase. Either these more complex molecules are destroyed or their emission is not compact enough to be detected with the SMA. Synthetic spectra modelling of the H$_{2}$CO transitions, as detected with the APEX telescope, shows that both a warm and a cold component are needed to obtain a good fit to the emission for all sources except for W33 Main1. The temperatures and column densities of the two components increase during the evolution of the star forming regions. The integrated intensity ratios N$_{2}$H$^{+}$(3$-$2)/CS(6$-$5) and N$_{2}$H$^{+}$(3$-$2)/H$_{2}$CO(4$_{2,2}$$-$3$_{2,1}$) show clear trends as a function of evolutionary stage, luminosity, luminosity-to-mass ratio, and H$_{2}$ peak column density of the clumps and might be usable as chemical clocks.Comment: 66 pages, 28 figures, 8 tables, accepted for publication at A&

Simplifying the mosaic description of DNA sequences

By using the Jensen-Shannon divergence, genomic DNA can be divided into compositionally distinct domains through a standard recursive segmentation procedure. Each domain, while significantly different from its neighbours, may however share compositional similarity with one or more distant (non--neighbouring) domains. We thus obtain a coarse--grained description of the given DNA string in terms of a smaller set of distinct domain labels. This yields a minimal domain description of a given DNA sequence, significantly reducing its organizational complexity. This procedure gives a new means of evaluating genomic complexity as one examines organisms ranging from bacteria to human. The mosaic organization of DNA sequences could have originated from the insertion of fragments of one genome (the parasite) inside another (the host), and we present numerical experiments that are suggestive of this scenario.Comment: 16 pages, 1 figure, Accepted for publication in Phys. Rev.

Finite-sample frequency distributions originating from an equiprobability distribution

Given an equidistribution for probabilities p(i)=1/N, i=1..N. What is the expected corresponding rank ordered frequency distribution f(i), i=1..N, if an ensemble of M events is drawn?Comment: 4 pages, 4 figure

Ginzburg-Landau theory of the zig-zag transition in quasi-one-dimensional classical Wigner crystals

We present a mean-field description of the zig-zag phase transition of a quasi-one-dimensional system of strongly interacting particles, with interaction potential $r^{-n}e^{-r/\lambda}$, that are confined by a power-law potential ($y^{\alpha}$). The parameters of the resulting one-dimensional Ginzburg-Landau theory are determined analytically for different values of $\alpha$ and $n$. Close to the transition point for the zig-zag phase transition, the scaling behavior of the order parameter is determined. For $\alpha=2$ the zig-zag transition from a single to a double chain is of second order, while for $\alpha>2$ the one chain configuration is always unstable and for $\alpha<2$ the one chain ordered state becomes unstable at a certain critical density resulting in jumps of single particles out of the chain.Comment: 12 pages, 11 figure

A three-level common-mode voltage eliminated inverter with single dc supply using flying capacitor inverter and cascaded H-bridge

A three-level common-mode voltage eliminated in- verter with single dc supply using flying capacitor inverter and cascaded H-bridge has been proposed in this paper. The three phase space vector polygon formed by this configuration and the polygon formed by the common-mode eliminated states have been discussed. The entire system is simulated in Simulink and the re- sults are experimentally verified. This system has an advantage that if one of devices in the H-bridge fails, the system can still be oper- ated as a normal three-level inverter at full power. This inverter has many other advantages like use of single dc supply, making it pos- sible for a back-to-back grid-tied converter application, improved reliability, etc

Effect of extreme data loss on long-range correlated and anti-correlated signals quantified by detrended fluctuation analysis

We investigate how extreme loss of data affects the scaling behavior of long-range power-law correlated and anti-correlated signals applying the DFA method. We introduce a segmentation approach to generate surrogate signals by randomly removing data segments from stationary signals with different types of correlations. These surrogate signals are characterized by: (i) the DFA scaling exponent $\alpha$ of the original correlated signal, (ii) the percentage $p$ of the data removed, (iii) the average length $\mu$ of the removed (or remaining) data segments, and (iv) the functional form of the distribution of the length of the removed (or remaining) data segments. We find that the {\it global} scaling exponent of positively correlated signals remains practically unchanged even for extreme data loss of up to 90%. In contrast, the global scaling of anti-correlated signals changes to uncorrelated behavior even when a very small fraction of the data is lost. These observations are confirmed on the examples of human gait and commodity price fluctuations. We systematically study the {\it local} scaling behavior of signals with missing data to reveal deviations across scales. We find that for anti-correlated signals even 10% of data loss leads to deviations in the local scaling at large scales from the original anti-correlated towards uncorrelated behavior. In contrast, positively correlated signals show no observable changes in the local scaling for up to 65% of data loss, while for larger percentage, the local scaling shows overestimated regions (with higher local exponent) at small scales, followed by underestimated regions (with lower local exponent) at large scales. Finally, we investigate how the scaling is affected by the statistics of the remaining data segments in comparison to the removed segments

New stopping criteria for segmenting DNA sequences

We propose a solution on the stopping criterion in segmenting inhomogeneous DNA sequences with complex statistical patterns. This new stopping criterion is based on Bayesian Information Criterion (BIC) in the model selection framework. When this stopping criterion is applied to a left telomere sequence of yeast Saccharomyces cerevisiae and the complete genome sequence of bacterium Escherichia coli, borders of biologically meaningful units were identified (e.g. subtelomeric units, replication origin, and replication terminus), and a more reasonable number of domains was obtained. We also introduce a measure called segmentation strength which can be used to control the delineation of large domains. The relationship between the average domain size and the threshold of segmentation strength is determined for several genome sequences.Comment: 4 pages, 4 figures, Physical Review Letters, to appea

Precision measurement of the neutron β-decay asymmetry

A new measurement of the neutron β-decay asymmetry A_0 has been carried out by the UCNA Collaboration using polarized ultracold neutrons (UCNs) from the solid deuterium UCN source at the Los Alamos Neutron Science Center. Improvements in the experiment have led to reductions in both statistical and systematic uncertainties leading to A_0=−0.11954(55)_(stat)(98)_(syst), corresponding to the ratio of axial-vector to vector coupling λ ≡ g_A/g_V = −1.2756(30)

Heuristic Segmentation of a Nonstationary Time Series

Many phenomena, both natural and human-influenced, give rise to signals whose statistical properties change under time translation, i.e., are nonstationary. For some practical purposes, a nonstationary time series can be seen as a concatenation of stationary segments. Using a segmentation algorithm, it has been reported that for heart beat data and Internet traffic fluctuations--the distribution of durations of these stationary segments decays with a power law tail. A potential technical difficulty that has not been thoroughly investigated is that a nonstationary time series with a (scale-free) power law distribution of stationary segments is harder to segment than other nonstationary time series because of the wider range of possible segment sizes. Here, we investigate the validity of a heuristic segmentation algorithm recently proposed by Bernaola-Galvan et al. by systematically analyzing surrogate time series with different statistical properties. We find that if a given nonstationary time series has stationary periods whose size is distributed as a power law, the algorithm can split the time series into a set of stationary segments with the correct statistical properties. We also find that the estimated power law exponent of the distribution of stationary-segment sizes is affected by (i) the minimum segment size, and (ii) the ratio of the standard deviation of the mean values of the segments, and the standard deviation of the fluctuations within a segment. Furthermore, we determine that the performance of the algorithm is generally not affected by uncorrelated noise spikes or by weak long-range temporal correlations of the fluctuations within segments.Comment: 23 pages, 14 figure