Is the Yb2Ti2O7 pyrochlore a quantum spin ice?

We use numerical linked cluster (NLC) expansions to compute the specific heat, C(T), and entropy, S(T), of a quantum spin ice model of Yb2Ti2O7 using anisotropic exchange interactions recently determined from inelastic neutron scattering measurements and find good agreement with experimental calorimetric data. In the perturbative weak quantum regime, this model has a ferrimagnetic ordered ground state, with two peaks in C(T): a Schottky anomaly signalling the paramagnetic to spin ice crossover followed at lower temperature by a sharp peak accompanying a first order phase transition to the ferrimagnetic state. We suggest that the two C(T) features observed in Yb2Ti2O7 are associated with the same physics. Spin excitations in this regime consist of weakly confined spinon-antispinon pairs. We suggest that conventional ground state with exotic quantum dynamics will prove a prevalent characteristic of many real quantum spin ice materials.Comment: 8 pages (two-column), 9 figure

Effectiveness Of Alternative Heuristic Algorithms For Identifying Indicative Minimum Requirements For Conservation Reserves

We compared the results of 30 heuristic reserve selection algorithms on the same large data set. Twelve of the algorithms were for presence-absence representation goals, designed to find a set of sites to represent all the land types in the study region at least once. Eighteen algorithms were intended to represent a minimum percentage of the total area of each land type. We varied the rules of the algorithms systematically to find the influence of individual rules or sequences of rules on efficiency of representation. Rankings of the algorithms according to relative numbers or areas of selected sites needed to achieve a specified representation target varied between the full data set and a subset and so appear to be data-dependent. We also ran optimizing algorithms to indicate the degree of suboptimality of the heuristics. For the presence-absence problems, the optimizing algorithms had the advantage of guaranteeing an optimal solution but had much longer running times than the heuristics. They showed that the solutions from good heuristics were 5-10% larger than optimal. The optimizing algorithms failed to solve the proportional area problems, although heuristics solved them quickly. Both heuristics and optimizing algorithms have important roles to play in conservation planning. The choice of method will depend on the size of data sets, the representation goal, the required time for analysis, and the importance of a guaranteed optimal solution

Age and size at maturity: sex, environmental variability and developmental thresholds

In most organisms, transitions between different life-history stages occur later and at smaller sizes as growth conditions deteriorate. Day and Rowe recently proposed that this pattern could be explained by the existence of developmental thresholds (minimum sizes or levels of condition below which transitions are unable to proceed). The developmental-threshold model predicts that the reaction norm of age and size at maturity will rotate in an anticlockwise manner from positive to a shallow negative slope if: (i) initial body size or condition is reduced; and/or (ii) some individuals encounter poor growth conditions at increasingly early developmental stages. We tested these predictions by rearing replicated populations of soil mites Sancassania berlesei (Michael) under different growth conditions. High-food environments produced a vertical relationship between age and size at maturity. The slope became increasingly shallow as food was reduced. By contrast, high food in the maternal environment reduced the slope of the reaction norm of age and size at maturity, whereas low food increased it. Overall, the reaction norm of age and size at maturity in S. berlesei was significantly nonlinear and differed for males and females. We describe how growth conditions, mother's environment and sex determine age and size at maturity in S. berlesei

Position and energy-resolved particle detection using phonon-mediated microwave kinetic inductance detectors

We demonstrate position and energy-resolved phonon-mediated detection of particle interactions in a silicon substrate instrumented with an array of microwave kinetic inductance detectors (MKIDs). The relative magnitude and delay of the signal received in each sensor allow the location of the interaction to be determined with ≲ 1mm resolution at 30 keV. Using this position information, variations in the detector response with position can be removed, and an energy resolution of σ_E = 0.55 keV at 30 keV was measured. Since MKIDs can be fabricated from a single deposited film and are naturally multiplexed in the frequency domain, this technology can be extended to provide highly pixelized athermal phonon sensors for ∼1 kg scale detector elements. Such high-resolution, massive particle detectors would be applicable to rare-event searches such as the direct detection of dark matter, neutrinoless double-beta decay, or coherent neutrino-nucleus scattering

Superscaling in inclusive electron-nucleus scattering

We investigate the degree to which the scaling functions $F(\psi')$ derived from cross sections for inclusive electron-nucleus quasi-elastic scattering define the same function for different nuclei. In the region where the scaling variable $\psi'< 0$, we find that this superscaling is experimentally realized to a high degree.Comment: Corrected previously mislabeled figures and cross references; 9 pages, 4 color figures, using BoxedEPS and REVTeX; email correspondence to [email protected]

Generalized Geometric Cluster Algorithm for Fluid Simulation

We present a detailed description of the generalized geometric cluster algorithm for the efficient simulation of continuum fluids. The connection with well-known cluster algorithms for lattice spin models is discussed, and an explicit full cluster decomposition is derived for a particle configuration in a fluid. We investigate a number of basic properties of the geometric cluster algorithm, including the dependence of the cluster-size distribution on density and temperature. Practical aspects of its implementation and possible extensions are discussed. The capabilities and efficiency of our approach are illustrated by means of two example studies.Comment: Accepted for publication in Phys. Rev. E. Follow-up to cond-mat/041274