Josephson junction ratchet: effects of finite capacitances

We study transport in an asymmetric SQUID which is composed of a loop with three capacitively and resistively shunted Josephson junctions: two in series in one arm and the remaining one in the other arm. The loop is threaded by an external magnetic flux and the system is subjected to both a time-periodic and a constant current. We formulate the deterministic and, as well, the stochastic dynamics of the SQUID in terms of the Stewart-McCumber model and derive an equation for the phase difference across one arm, in which an effective periodic potential is of the ratchet type, i.e. its reflection symmetry is broken. In doing so, we extend and generalize earlier study by Zapata et al. [Phys. Rev. Lett. 77, 2292 (1996)] and analyze directed transport in wide parameter regimes: covering the over-damped to moderate damping regime up to its fully under-damped regime. As a result we detect the intriguing features of a negative (differential) conductance, repeated voltage reversals, noise induced voltage reversals and solely thermal noise-induced ratchet currents. We identify a set of parameters for which the ratchet effect is most pronounced and show how the direction of transport can be controlled by tailoring the external magnetic flux.Comment: accepted for publication in Phys. Rev.

Tunable mass separation via negative mobility

A prerequisite for isolating diseased cells requires a mechanism for effective mass-based separation. This objective, however, is generally rather challenging because typically no valid correlation exists between the size of the particles and their mass value. We consider an inertial Brownian particle moving in a symmetric periodic potential and subjected to an externally applied unbiased harmonic driving in combination with a constant applied bias. In doing so we identify a most efficient separation scheme which is based on the anomalous transport feature of negative mobility, meaning that the immersed particles move in the direction opposite to the acting bias. This work is first of its kind in demonstrating a tunable separation mechanism in which the particle mass targeted for isolation is effectively controlled over a regime of nearly two orders of mass-magnitude upon changing solely the frequency of the external harmonic driving. This approach may provide mass selectivity required in present and future separation of a diversity of nano and micro-sized particles of either biological or synthetic origin.Comment: in press in Physical Review Letter

Chimera states and the interplay between initial conditions and non-local coupling

This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Chaos 27, 033110 (2017) and may be found at https://doi.org/10.1063/1.4977866.Chimera states are complex spatio-temporal patterns that consist of coexisting domains of coherent and incoherent dynamics. We study chimera states in a network of non-locally coupled Stuart-Landau oscillators. We investigate the impact of initial conditions in combination with non-local coupling. Based on an analytical argument, we show how the coupling phase and the coupling strength are linked to the occurrence of chimera states, flipped profiles of the mean phase velocity, and the transition from a phase- to an amplitude-mediated chimera state. Chimera states are an example of intriguing partial synchronization patterns appearing in networks of identical oscillators with symmetric coupling scheme. They exhibit a hybrid structure combining coexisting spatial domains of coherent (synchronized) and incoherent (desynchronized) dynamics and were first reported for the model of phase oscillators. Recent studies have demonstrated the emergence of chimera states in a variety of topologies and for different types of individual dynamics. In this paper, the interplay between initial conditions and non-local coupling is studied. We show that, based on an analytical argument incorporating the initial conditions and the range of non-local coupling, the occurrence of phase chimeras can be seen as caused by a phase lag in the coupling. Considering the dynamics of chimera states, our argument shows how “flipped” profiles of the mean phase velocities can be explained by a change of sign of the coupling phase. By this, one can either choose a concave (“upside”) profile of the mean phase velocities or a “flipped” one. Extending our reasoning, we show that this argument intuitively explains the transition from a phase- to an amplitude-mediated chimera state as a result of increasing coupling strength.DFG, 163436311, SFB 910: Kontrolle selbstorganisierender nichtlinearer Systeme: Theoretische Methoden und Anwendungskonzept

MBT: A Memory-Based Part of Speech Tagger-Generator

We introduce a memory-based approach to part of speech tagging. Memory-based learning is a form of supervised learning based on similarity-based reasoning. The part of speech tag of a word in a particular context is extrapolated from the most similar cases held in memory. Supervised learning approaches are useful when a tagged corpus is available as an example of the desired output of the tagger. Based on such a corpus, the tagger-generator automatically builds a tagger which is able to tag new text the same way, diminishing development time for the construction of a tagger considerably. Memory-based tagging shares this advantage with other statistical or machine learning approaches. Additional advantages specific to a memory-based approach include (i) the relatively small tagged corpus size sufficient for training, (ii) incremental learning, (iii) explanation capabilities, (iv) flexible integration of information in case representations, (v) its non-parametric nature, (vi) reasonably good results on unknown words without morphological analysis, and (vii) fast learning and tagging. In this paper we show that a large-scale application of the memory-based approach is feasible: we obtain a tagging accuracy that is on a par with that of known statistical approaches, and with attractive space and time complexity properties when using {\em IGTree}, a tree-based formalism for indexing and searching huge case bases.} The use of IGTree has as additional advantage that optimal context size for disambiguation is dynamically computed.Comment: 14 pages, 2 Postscript figure

Will the true labor share stand up?

We document the consequences of ambiguity in the empirical definition of the macroeconomic labor share. Depending on its definition, the properties of short-run fluctuations, medium-run swings, and long-run stochastic trends of the labor share may vary substantially. Based on a range of historical US time series, we carry out a systematic exploration of discrepancies between the alternative labor share definitions in terms of the observed stochastic trends, shares of short-, medium- and long-run variation in total volatility of the series, degree of persistence, mean-reversion properties, and susceptibility to structural breaks. We conclude that while short-run properties of the labor shares (represented by cyclical variation below 8 years) are relatively consistent across all definitions, their medium-run swings (8-50 years) and long-run trends ( 50 years) diverge substantially. As important applications, we document the implications of our findings for growth accounting, the identification of short-run responses of the labor share to technology shocks and for estimating inflation

On the Spectral Lags and Peak-Counts of the Gamma-Ray Bursts Detected by the RHESSI Satellite

A sample of 427 gamma-ray bursts from a database (February 2002 - April 2008) of the RHESSI satellite is analyzed statistically. The spectral lags and peak-count rates, which have been calculated for the first time in this paper, are studied completing an earlier analysis of durations and hardness ratios. The analysis of the RHESSI database has already inferred the existence of a third group with intermediate duration, apart from the so-called short and long groups. First aim of this article is to discuss the properties of these intermediate-duration bursts in terms of peak-count rates and spectral lags. Second aim is to discuss the number of GRB groups using another statistical method and by employing the peak-count rates and spectral lags as well. The standard parametric (model-based clustering) and non-parametric (K-means clustering) statistical tests together with the Kolmogorov-Smirnov and Anderson-Darling tests are used. Two new results are obtained: A. The intermediate-duration group has similar properties to the group of short bursts. Intermediate and long groups appear to be different. B. The intermediate-duration GRBs in the RHESSI and Swift databases seem to be represented by different phenomena.Comment: 41 pages, 10 figures, 9 tables, accepted to be published in The Astrophysical Journa

Endogenous labor share cycles: theory and evidence

Based on long US time series we document a range of empirical properties of the labor’s share of GDP, including its substantial medium-run swings. We explore the extent to which these empirical regularities can be explained by a calibrated micro-founded long-run economic growth model with normalized CES technology and endogenous labor- and capital-augmenting technical change driven by purposeful directed R&D investments. It is found that dynamic macroeconomic trade-offs created by arrivals of both types of new technologies may lead to prolonged swings in the labor share due to oscillatory convergence to the balanced growth path as well as stable limit cycles via Hopf bifurcations. Both predictions are broadly in line with the empirical evidence