Spin-glass behavior, spin-fluctuations and superconductivity in Sr2Y(Ru1-uCuu)O6

[[abstract]]Muon spin rotation measurements of Sr2Y(Ru1-uCuu)O6 (for u=0.1) reveal two distinct muon sites: one located in a SrO layer (which is superconducting at low temperatures) and the other in a Y(Ru1-uCuu)O4 layer (which is magnetically ordered at low temperatures). A precursor spin-glass state due to the Ru moments is detected in high fields (≈3.3 kOe) in Y(Ru1-uCuu)O4 layers, with a spin-glass temperature of TG=29.25K. The Y(Ru1-uCuu)O4 layers order ferromagnetically in the a-b planes at the Néel temperature, TN≈23K. This in-plane ferromagnetism alternates direction between adjacent Y(Ru1-uCuu)O4 planes, resulting in a net antiferromagnetic structure. Although the onset of superconductivity is observed both by electron spin resonance and by dc susceptibility to occur for temperatures up to about Tc,onset≈49K, this superconductivity is adversely affected by the Ru moments that fluctuate for T>TN producing magnetic fields that break pairs in the SrO layers. The muons, as well as other probes, sense the more-robust static superconductivity for TTN are frozen in-plane. Hence strictly speaking, the superconducting transition temperature is the same as TN, which is far below Tc,onset. Below TN there are no pair breaking fluctuating magnetic fields in the SrO layers where the hole condensate resides.[[incitationindex]]SCI[[booktype]]紙

A tensor analysis improved genetic algorithm for online bin packing

Mutation in a Genetic Algorithm is the key variation operator adjusting the genetic diversity in a population throughout the evolutionary process. Often, a fixed mutation probability is used to perturb the value of a gene. In this study, we describe a novel data science approach to adaptively generate the mutation probability for each locus. The trail of high quality candidate solutions obtained during the search process is represented as a 3rd order tensor. Factorizing that tensor captures the common pattern between those solutions, identifying the degree of mutation which is likely to yield improvement at each locus. An online bin packing problem is used as an initial case study to investigate the proposed approach for generating locus dependent mutation probabilities. The empirical results show that the tensor approach improves the performance of a standard Genetic Algorithm on almost all classes of instances, significantly

A Solvable Model for Decoupling of Interacting Clusters

We consider M clusters of interacting particles, whose in-group interactions are arbitrary, and inter-group interactions are approximated by oscillator potentials. We show that there are masses and frequencies that decouple the in-group and inter-group degrees of freedom, which reduces the initial problem to M independent problems that describe each of the relative in-group systems. The dynamics of the M center-of-mass coordinates is described by the analytically solvable problem of M coupled harmonic oscillators. This paper derives and discusses these decoupling conditions. Furthermore, to illustrate our findings, we consider a charged impurity interacting with a ring of ions. We argue that the impurity can be used to probe the center-of-mass dynamics of the ions.Comment: Version accepted for publication in EP