Multi-Frequency Magnonic Logic Circuits for Parallel Data Processing

We describe and analyze magnonic logic circuits enabling parallel data processing on multiple frequencies. The circuits combine bi-stable (digital) input/output elements and an analog core. The data transmission and processing within the analog part is accomplished by the spin waves, where logic 0 and 1 are encoded into the phase of the propagating wave. The latter makes it possible to utilize a number of bit carrying frequencies as independent information channels. The operation of the magnonic logic circuits is illustrated by numerical modeling. We also present the estimates on the potential functional throughput enhancement and compare it with scaled CMOS. The described multi-frequency approach offers a fundamental advantage over the transistor-based circuitry and may provide an extra dimension for the Moor's law continuation. The shortcoming and potentials issues are also discussed

Electron-Positron colliders

An electron-positron linear collider in the energy range between 500 and 1000 GeV is of crucial importance to precisely test the Standard Model and to explore the physics beyond it. The physics program is complementary to that of the Large Hadron Collider. Some of the main physics goals and the expected accuracies of the anticipated measurements at such a linear collider are discussed. A short review of the different collider designs presently under study is given including possible upgrade paths to the multi-TeV region. Finally a framework is presented within which the realisation of such a project could be achieved as a global international project.Comment: 14 pages, 16 figures, Proceedings of the XX International Symposium on Lepton and Photon Interactions at High Energies, Rome, Italy, 23-28 July, 200

Two-dimensional manifold with point-like defects

We study a class of two-dimensional compact extra spaces isomorphic to the sphere $S^2$ in the framework of multidimensional gravitation. We show that there exists a family of stationary metrics that depend on the initial (boundary) conditions. All these geometries have a singular point. We also discuss the possibility for these deformed extra spaces to be considered as dark matter candidates.Comment: 4 pages, 2 figures; Proceedings of the Conference of Fundamental Research and Particle Physics, 18-20 February 2015, Moscow, Russian Federatio

Characterizing correlations with full counting statistics: classical Ising and quantum XY spin chains

We propose to describe correlations in classical and quantum systems in terms of full counting statistics of a suitably chosen discrete observable. The method is illustrated with two exactly solvable examples: the classical one-dimensional Ising model and the quantum spin-1/2 XY chain. For the one-dimensional Ising model, our method results in a phase diagram with two phases distinguishable by the long-distance behavior of the Jordan-Wigner strings. For the quantum XY chain, the method reproduces the previously known phase diagram.Comment: 6 pages, section on Lee-Yang zeros added, published versio

Spin-Forster transfer in optically excited quantum dots

The mechanisms of energy and spin transfer in quantum dot pairs coupled via the Coulomb interaction are studied. Exciton transfer can be resonant or phonon-assisted. In both cases, the transfer rates strongly depend on the resonance conditions. The spin selection rules in the transfer process come from the exchange and spin-orbit interactions. The character of energy dissipation in spin transfer is different than that in the traditional spin currents. The spin-dependent photon cross-correlation functions reflect the exciton transfer process. In addition, a mathematical method to calculate F\"orster transfer in crystalline nanostructures beyond the dipole-dipole approximation is described.Comment: 22 pages, 10 figures, Phys. Rev. B, in pres

PrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex

Much of the human cortex seems to be organized into topographic cortical maps. Yet few quantitative methods exist for characterizing these maps. To address this issue we developed a modeling framework that can reveal group-level cortical maps based on neuroimaging data. PrAGMATiC, a probabilistic and generative model of areas tiling the cortex, is a hierarchical Bayesian generative model of cortical maps. This model assumes that the cortical map in each individual subject is a sample from a single underlying probability distribution. Learning the parameters of this distribution reveals the properties of a cortical map that are common across a group of subjects while avoiding the potentially lossy step of co-registering each subject into a group anatomical space. In this report we give a mathematical description of PrAGMATiC, describe approximations that make it practical to use, show preliminary results from its application to a real dataset, and describe a number of possible future extensions