Chimera-like states in an ensemble of globally coupled oscillators

We demonstrate emergence of a complex state in a homogeneous ensemble of globally coupled identical oscillators, reminiscent of chimera states in locally coupled oscillator lattices. In this regime some part of the ensemble forms a regularly evolving cluster, while all other units irregularly oscillate and remain asynchronous. We argue that chimera emerges because of effective bistability which dynamically appears in the originally monostable system due to internal delayed feedback in individual units. Additionally, we present two examples of chimeras in bistable systems with frequency-dependent phase shift in the global coupling

Null-test signal for T-invariance violation in pdpd scattering

The integrated proton-deuteron cross section $\widetilde\sigma$ for the case of the incident proton vector polarization $p_y^p$ and tensor polarization $P_{xz}$ of the deuteron target provides a null test signal for time-reversal invariance violating but P-parity conserving (TVPC) effects. We study the null-test observable $\widetilde\sigma$ within the Glauber theory of the double-polarized $pd$ scattering. Full spin dependence of the ordinary strong $pN$ scattering amplitudes and different types of the hypothetical TVPC pN-amplitudes are taken into account. We show that the contribution from the exchange of the lowest-mass meson allowed in the TVPC interaction, i.e. the $\rho$-meson, to the null-test observable $\widetilde\sigma$ is zero. The axial $h_1$ meson exchange makes a non-zero contribution. We find that inclusion of the Coulomb interaction does not lead to divergence of the cross section $\widetilde\sigma$ and calculate its energy dependence at the proton beam energy 100-1000 MeV.Comment: 12 pages, 3 figures, to appear in Phys.Rev.

Statistical Morphological Disambiguation for Kazakh Language

This paper presents the results of developing a statistical model for morphological disambiguation of Kazakh text. Starting with basic assumptions we tried to cope with the complex morphology of Kazakh language by breaking up lexical forms across their derivational boundaries into inflectional groups and modeling their behavior with statistical methods. We also provide maximum likelihood estimates for the parameters and an effective way to perform disambiguation with the Viterbi algorithm