Collective spin waves in arrays of Permalloy nanowires with single-side periodically modulated width

We have experimentally and numerically investigated the dispersion of collective spin waves prop-agating through arrays of longitudinally magnetized nanowires with periodically modulated width. Two nanowire arrays with single-side modulation and different periodicity of modulation were studied and compared to the nanowires with homogeneous width. The spin-wave dispersion, meas-ured up to the third Brillouin zone of the reciprocal space, revealed the presence of two dispersive modes for the width-modulated NWs, whose amplitude of magnonic band depends on the modula-tion periodicity, and a set of nondispersive modes at higher frequency. These findings are different from those observed in homogeneous width NWs where only the lowest mode exhibits sizeable dis-persion. The measured spin-wave dispersion has been satisfactorily reproduced by means of dynam-ical matrix method. Results presented in this work are important in view of the possible realization of frequency tunable magnonic device

Unified nonequilibrium dynamical theory for exchange bias and training effects

We investigate the exchange bias and training effects in the FM/AF heterostructures using a unified Monte Carlo dynamical approach. This real dynamical method has been proved reliable and effective in simulating dynamical magnetization of nanoscale magnetic systems. The magnetization of the uncompensated AF layer is still open after the first field cycling is finished. Our simulated results show obvious shift of hysteresis loops (exchange bias) and cycling dependence of exchange bias (training effect) when the temperature is below 45 K. The exchange bias fields decrease with decreasing the cooling rate or increasing the temperature and the number of the field cycling. With the simulations, we show the exchange bias can be manipulated by controlling the cooling rate, the distributive width of the anisotropy energy, or the magnetic coupling constants. Essentially, these two effects can be explained on the basis of the microscopical coexistence of both reversible and irreversible moment reversals of the AF domains. Our simulated results are useful to really understand the magnetization dynamics of such magnetic heterostructures. This unified nonequilibrium dynamical method should be applicable to other exchange bias systems.Comment: Chin. Phys. B, in pres

Manipulating Majorana Fermions in Quantum Nanowires with Broken Inversion Symmetry

We study a Majorana-carrying quantum wire, driven into a trivial phase by breaking the spatial inversion symmetry with a tilted external magnetic field. Interestingly, we predict that a supercurrent applied in the proximate superconductor is able to restore the topological phase and therefore the Majorana end-states. Using Abelian bosonization, we further confirm this result in the presence of electron-electron interactions and show a profound connection of this phenomenon to the physics of a one-dimensional doped Mott-insulator. The present results have important applications in e.g., realizing a supercurrent assisted braiding of Majorana fermions, which proves highly useful in topological quantum computation with realistic Majorana networks.Comment: 5 pages, 3 figures, Supplementary Material is adde

Entropy, Dynamics and Instantaneous Normal Modes in a Random Energy Model

It is shown that the fraction f of imaginary frequency instantaneous normal modes (INM) may be defined and calculated in a random energy model(REM) of liquids. The configurational entropy S and the averaged hopping rate among the states R are also obtained and related to f, with the results R~f and S=a+b*ln(f). The proportionality between R and f is the basis of existing INM theories of diffusion, so the REM further confirms their validity. A link to S opens new avenues for introducing INM into dynamical theories. Liquid 'states' are usually defined by assigning a configuration to the minimum to which it will drain, but the REM naturally treats saddle-barriers on the same footing as minima, which may be a better mapping of the continuum of configurations to discrete states. Requirements of a detailed REM description of liquids are discussed

The Microsoft 2016 Conversational Speech Recognition System

We describe Microsoft's conversational speech recognition system, in which we combine recent developments in neural-network-based acoustic and language modeling to advance the state of the art on the Switchboard recognition task. Inspired by machine learning ensemble techniques, the system uses a range of convolutional and recurrent neural networks. I-vector modeling and lattice-free MMI training provide significant gains for all acoustic model architectures. Language model rescoring with multiple forward and backward running RNNLMs, and word posterior-based system combination provide a 20% boost. The best single system uses a ResNet architecture acoustic model with RNNLM rescoring, and achieves a word error rate of 6.9% on the NIST 2000 Switchboard task. The combined system has an error rate of 6.2%, representing an improvement over previously reported results on this benchmark task

Nonclassical 2-photon interference with separate intrinsically narrowband fibre sources

In this paper, we demonstrate a source of photon pairs based on four-wave-mixing in photonic crystal fibres. Careful engineering of the phase matching conditions in the fibres enables us to create photon pairs at 597 nm and 860 nm in an intrinsically factorable state showing no spectral correlations. This allows for heralding one photon in a pure state and hence renders narrow band filtering obsolete. The source is narrow band, bright and achieves an overall detection efficiency of up to 21% per photon. For the first time, a Hong-Ou-Mandel interference with unfiltered photons from separate fibre sources is presented.Comment: 10 pages, 6 figure