Magnetic interference patterns in long disordered Josephson junctions

We study a diffusive superconductor - normal metal - superconductor (SNS) junction in an external magnetic field. In the limit of a long junction, we find that the form of the dependence of the Josephson current on the field and on the length of the junction depends on the ratio between the junction width and the length associated with the magnetic field. A certain critical ratio between these two length scales separates two different regimes. In narrow junctions, the critical current exhibits a pure decay as a function of the junction length or of the magnetic field. In wide junctions, the critical current exhibits damped oscillations as a function of the same parameters. This damped oscillating behavior differs from the Fraunhofer pattern typical for short or tunnel junctions. In wide and long junctions, superconducting pair correlations and supercurrent are localized along the edges of the junction.Comment: 9 pages, 4 figures, minor modifications corresponding to the published versio

Oscillations of the superconducting critical current in Nb-Cu-Ni-Cu-Nb junctions

We report on experimental studies of superconductor-ferromagnet layered structures. Strong oscillations of the critical supercurrent were observed with the thickness variation of the ferromagnet. Using known microscopic parameters of Ni, we found reasonable agreement between the period of oscillations and the decay of the measured critical current, and theoretical calculations.Comment: 5 page

Shot noise in superconducting junctions with weak link formed by Anderson impurity

A theory is developed to study shot noise in superconducting (SAS) and hybrid (SAN) junctions with singly occupied Anderson impurity (A) as a weak link. The zero-frequency DC component of the shot noise spectral density is calculated at zero temperature as a function of the bias at different Coulomb repulsion strengths U, and show a remarkable structure resulting from combination of electron-electron interaction and Andreev reflections.Comment: 4 two column pages including 4 .eps figure

Conformal Higher Spin Currents in Any Dimension and AdS/CFT Correspondence

The full list of conserved conformal higher spin currents built from massless scalar and spinor fields is presented. It is shown that, analogously to the relationship between usual conformal and AdS symmetries, the set of the conformal higher spin symmetry parameters associated with the conformal conserved currents in d dimensions is in the one-to-one correspondence with the result of the dimensional reduction of the usual (i.e., non-conformal) higher spin symmetry parameters in d+1 dimensions.Comment: 10 pages, Late

Numerical study of pi-junction using spin filtering barriers

We numerically investigate the Josephson transport through ferromagnetic insulators (FIs) by taking into account its band structure. By use of the recursive Green's function method, we found the formation of the pi junction in the case of the fully spin-polarized FI (FPFI), e.g., La$_2$BaCuO$_5$. Moreover, the 0-pi transition is induced by increasing the thickness of FPFI. On the other hand, Josephson current through the Eu chalcogenides shows the pi junction behavior in the case of the strong d-f hybridization between the conduction d and the localized f electrons of Eu. Such FI-based Josephson junctions may become a element in the architecture of future quantum information devices.Comment: 9 pages, 5 figure

Comparison of machine learning methods for analysis of ulcerative colitis proteomic data

Ulcerative colitis is a chronic inflammatory disease of the gastrointestinal system, affecting adults and children. Its cause is unknown, and the knowledge of reliable biomarkers is limited, especially for children. That makes the search for new biomarkers and pushing forth the analysis of the available data particularly challenging. We investigate proteomic data from children patients as a promising source, and tackle the problem implementing the recently developed parenclitic network approach to machine learning algorithms that solve classification task for proteomic data from healthy and diseased. We expect our approach to be applicable to other gastrointestinal diseases

Entrainment of randomly coupled oscillator networks by a pacemaker

Entrainment by a pacemaker, representing an element with a higher frequency, is numerically investigated for several classes of random networks which consist of identical phase oscillators. We find that the entrainment frequency window of a network decreases exponentially with its depth, defined as the mean forward distance of the elements from the pacemaker. Effectively, only shallow networks can thus exhibit frequency-locking to the pacemaker. The exponential dependence is also derived analytically as an approximation for large random asymmetric networks.Comment: 4 pages, 3 figures, revtex 4, submitted to Phys. Rev. Let

Heat transport in proximity structures

We study heat and charge transport through a normal diffusive wire coupled with a superconducting wire over the region smaller than the coherence length. Due to partial Andreev reflection of quasiparticles from the interface, the subgap thermal flow is essentially suppressed and approaches zero along with energy, which is specific for diffusive structures. Whereas the electric conductance shows conventional reentrance effect, the thermal conductance rapidly decreases with temperature which qualitatively explains the results of recent experiments. In the Andreev interferometer geometry, the thermal conductance experiences full-scale oscillations with the order parameter phase difference.Comment: 4 pages, 4 figures, minor revision, to be published in Phys. Rev. Let

Variations in the Intragene Methylation Profiles Hallmark Induced Pluripotency

We demonstrate the potential of differentiating embryonic and induced pluripotent stem cells by the regularized linear and decision tree machine learning classification algorithms, based on a number of intragene methylation measures. The resulting average accuracy of classification has been proven to be above 95%, which overcomes the earlier achievements. We propose a constructive and transparent method of feature selection based on classifier accuracy. Enrichment analysis reveals statistically meaningful presence of stemness group and cancer discriminating genes among the selected best classifying features. These findings stimulate the further research on the functional consequences of these differences in methylation patterns. The presented approach can be broadly used to discriminate the cells of different phenotype or in different state by their methylation profiles, identify groups of genes constituting multifeature classifiers, and assess enrichment of these groups by the sets of genes with a functionality of interest