How Does Wind Project Performance Change with Age in the United States?

Wind-plant performance declines with age, and the rate of decline varies between regions. The rate of performance decline is important when determining wind-plant financial viability and expected lifetime generation. We determine the rate of age-related performance decline in the United States wind fleet by evaluating generation records from 917 plants. We find the rate of performance decline to be 0.53%/year for older vintages of plants and 0.17%/year for newer vintages of plants on an energy basis for the first 10 years of operation, which is on the lower end of prior estimates in Europe. Unique to the United States, we find a significant drop in performance by 3.6% after 10 years, as plants lose eligibility for the production tax credit. Certain plant characteristics, such as the ratio of blade length to nameplate capacity, influence the rate of performance decline. These results indicate that the performance decline rate can be partially managed and influenced by policy

Production of superpositions of coherent states in traveling optical fields with inefficient photon detection

We develop an all-optical scheme to generate superpositions of macroscopically distinguishable coherent states in traveling optical fields. It non-deterministically distills coherent state superpositions (CSSs) with large amplitudes out of CSSs with small amplitudes using inefficient photon detection. The small CSSs required to produce CSSs with larger amplitudes are extremely well approximated by squeezed single photons. We discuss some remarkable features of this scheme: it effectively purifies mixed initial states emitted from inefficient single photon sources and boosts negativity of Wigner functions of quantum states.Comment: 13 pages, 9 figures, to be published in Phys. Rev.

Friction force microscopy : a simple technique for identifying graphene on rough substrates and mapping the orientation of graphene grains on copper

At a single atom thick, it is challenging to distinguish graphene from its substrate using conventional techniques. In this paper we show that friction force microscopy (FFM) is a simple and quick technique for identifying graphene on a range of samples, from growth substrates to rough insulators. We show that FFM is particularly effective for characterizing graphene grown on copper where it can correlate the graphene growth to the three-dimensional surface topography. Atomic lattice stick–slip friction is readily resolved and enables the crystallographic orientation of the graphene to be mapped nondestructively, reproducibly and at high resolution. We expect FFM to be similarly effective for studying graphene growth on other metal/locally crystalline substrates, including SiC, and for studying growth of other two-dimensional materials such as molybdenum disulfide and hexagonal boron nitride

Growing Perfect Decagonal Quasicrystals by Local Rules

A local growth algorithm for a decagonal quasicrystal is presented. We show that a perfect Penrose tiling (PPT) layer can be grown on a decapod tiling layer by a three dimensional (3D) local rule growth. Once a PPT layer begins to form on the upper layer, successive 2D PPT layers can be added on top resulting in a perfect decagonal quasicrystalline structure in bulk with a point defect only on the bottom surface layer. Our growth rule shows that an ideal quasicrystal structure can be constructed by a local growth algorithm in 3D, contrary to the necessity of non-local information for a 2D PPT growth.Comment: 4pages, 2figure

Construction of equilibrium networks with an energy function

We construct equilibrium networks by introducing an energy function depending on the degree of each node as well as the product of neighboring degrees. With this topological energy function, networks constitute a canonical ensemble, which follows the Boltzmann distribution for given temperature. It is observed that the system undergoes a topological phase transition from a random network to a star or a fully-connected network as the temperature is lowered. Both mean-field analysis and numerical simulations reveal strong first-order phase transitions at temperatures which decrease logarithmically with the system size. Quantitative discrepancies of the simulation results from the mean-field prediction are discussed in view of the strong first-order nature.Comment: To appear in J. Phys.

Sc2Ga2CuO7: A possible quantum spin liquid near the percolation threshold

Sc2Ga2CuO7 (SGCO) crystallizes in a hexagonal structure (space group: P63/mmc), which can be seen as an alternating stacking of single and double triangular layers. Combining neutron, x-ray, and resonant x-ray diffraction we establish that the single triangular layers are mainly populated by non-magnetic Ga3+ ions (85% Ga and 15% Cu), while the bi-layers have comparable population of Cu2+ and Ga3+ ions (43% Cu and 57% Ga). Our susceptibility measurements in the temperature range 1.8 - 400 K give no indication of any spin-freezing or magnetic long-range order (LRO).We infer an effective paramagnetic moment μeff = 1.79±0.09 μB and a Curie-Weiss temperature �CW of about −44 K, suggesting antiferromagnetic interactions between the Cu2+(S = 1/2) ions. Low-temperature neutron powder diffraction data showed no evidence for LRO down to 1.5 K. In our specific heat data as well, no anomalies were found down to 0.35 K, in the field range 0-140 kOe. The magnetic specific heat, Cm, exhibits a broad maximum at around 2.5 K followed by a nearly power law Cm/ T� behavior at lower temperatures, with � increasing from 0.3 to 1.9 as a function of field for fields upto 90 kOe and then remaining at 1.9 for fields upto 140 kOe. Our results point to a disordered ground state in SGCO

Evolving networks with disadvantaged long-range connections

We consider a growing network, whose growth algorithm is based on the preferential attachment typical for scale-free constructions, but where the long-range bonds are disadvantaged. Thus, the probability to get connected to a site at distance $d$ is proportional to $d^{-\alpha}$, where $\alpha$ is a tunable parameter of the model. We show that the properties of the networks grown with $\alpha <1$ are close to those of the genuine scale-free construction, while for $\alpha >1$ the structure of the network is vastly different. Thus, in this regime, the node degree distribution is no more a power law, and it is well-represented by a stretched exponential. On the other hand, the small-world property of the growing networks is preserved at all values of $\alpha$.Comment: REVTeX, 6 pages, 5 figure

Quadrature domains and kernel function zipping

It is proved that quadrature domains are ubiquitous in a very strong sense in the realm of smoothly bounded multiply connected domains in the plane. In fact, they are so dense that one might as well assume that any given smooth domain one is dealing with is a quadrature domain, and this allows access to a host of strong conditions on the classical kernel functions associated to the domain. Following this string of ideas leads to the discovery that the Bergman kernel can be zipped down to a strikingly small data set. It is also proved that the kernel functions associated to a quadrature domain must be algebraic.Comment: 13 pages, to appear in Arkiv for matemati

Lattice dynamics and correlated atomic motion from the atomic pair distribution function

The mean-square relative displacements (MSRD) of atomic pair motions in crystals are studied as a function of pair distance and temperature using the atomic pair distribution function (PDF). The effects of the lattice vibrations on the PDF peak widths are modelled using both a multi-parameter Born von-Karman (BvK) force model and a single-parameter Debye model. These results are compared to experimentally determined PDFs. We find that the near-neighbor atomic motions are strongly correlated, and that the extent of this correlation depends both on the interatomic interactions and crystal structure. These results suggest that proper account of the lattice vibrational effects on the PDF peak width is important in extracting information on static disorder in a disordered system such as an alloy. Good agreement is obtained between the BvK model calculations of PDF peak widths and the experimentally determined peak widths. The Debye model successfully explains the average, though not detailed, natures of the MSRD of atomic pair motion with just one parameter. Also the temperature dependence of the Debye model largely agrees with the BvK model predictions. Therefore, the Debye model provides a simple description of the effects of lattice vibrations on the PDF peak widths.Comment: 9 pages, 11 figure

Growing Scale-Free Networks with Small World Behavior

In the context of growing networks, we introduce a simple dynamical model that unifies the generic features of real networks: scale-free distribution of degree and the small world effect. While the average shortest path length increases logartihmically as in random networks, the clustering coefficient assumes a large value independent of system size. We derive expressions for the clustering coefficient in two limiting cases: random (C ~ (ln N)^2 / N) and highly clustered (C = 5/6) scale-free networks.Comment: 4 pages, 4 figure