Extended Optical Model Analyses of Elastic Scattering and Fusion Cross Section Data for the 12^{12}C+208^{208}Pb System at Near-Coulomb-Barrier Energies by using a Folding Potential

Simultaneous $\chi^{2}$ analyses are performed for elastic scattering and fusion cross section data for the $^{12}$C+$^{208}$Pb system at near-Coulomb-barrier energies by using the extended optical model approach in which the polarization potential is decomposed into direct reaction (DR) and fusion parts. Use is made of the double folding potential as a bare potential. It is found that the experimental elastic scattering and fusion data are well reproduced without introducing any normalization factor for the double folding potential and also that both DR and fusion parts of the polarization potential determined from the $\chi^{2}$ analyses satisfy separately the dispersion relation. Furthermore, it is shown that the imaginary parts of both DR and fusion potentials at the strong absorption radius change very rapidly, which results in a typical threshold anomaly in the total imaginary potential as observed with tightly bound projectiles such as $\alpha$-particle and $^{16}$O.Comment: 26 pages, 7 figures, submitted to Physical Review

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

An exact effective two-qubit gate in a chain of three spins

We show that an effective two-qubit gate can be obtained from the free evolution of three spins in a chain with nearest neighbor XY coupling, without local manipulations. This gate acts on the two remote spins and leaves the mediating spin unchanged. It can be used to perfectly transfer an arbitrary quantum state from the first spin to the last spin or to simultaneously communicate one classical bit in each direction. One ebit can be generated in half of the time for state transfer. For longer spin chains, we present methods to create or transfer entanglement between the two end spins in half of the time required for quantum state transfer, given tunable coupling strength and local magnetic field. We also examine imperfect state transfer through a homogeneous XY chain.Comment: RevTeX4, 7 pages, 4 figue

Analysis of the Disorder-Induced Zero Bias Anomaly in the Anderson-Hubbard Model

Using a combination of numerical and analytical calculations, we study the disorder-induced zero bias anomaly (ZBA) in the density of states of strongly-correlated systems modeled by the two dimensional Anderson-Hubbard model. We find that the ZBA comes from the response of the nonlocal inelastic self-energy to the disorder potential, a result which has implications for theoretical approaches that retain only the local self-energy. Using an approximate analytic form for the self-energy, we derive an expression for the density of states of the two-site Anderson-Hubbard model. Our formalism reproduces the essential features of the ZBA, namely that the width is proportional to the hopping amplitude $t$ and is independent of the interaction strength and disorder potential

Application of large eddy interaction model to channel flow

A procedure utilizing an expansion of proper orthogonal functions (or modes) to predict a fully developed flow in channel is derived. To examine numerical and conceptual difficulties, preliminary computations are performed with assigned mean velocity, and turbulence is expressed with only the first mode. The nonlinear interactions of the components of the first mode are treated specifically, with the influence of higher modes neglected; this treatment required adjustment of the skewness and effective Reynolds number to assure energy equilibrium of the first mode. Computational results show that the first mode possesses the structural character similar to that of the entire flow

Visualizing urban microclimate and quantifying its impact on building energy use in San Francisco

Weather data at nearby airports are usually used in building energy simulation to estimate energy use in buildings or evaluate building design or retrofit options. However, due to urbanization and geography characteristics, local weather conditions can differ significantly from those at airports. This study presents the visualization of 10-year hourly weather data measured at 27 sites in San Francisco, aiming to provide insights into the urban microclimate and urban heat island effect in San Francisco and how they evolve during the recent decade. The 10-year weather data are used in building energy simulations to investigate its influence on energy use and electrical peak demand, which informs the city's policy making on building energy efficiency and resilience. The visualization feature is implemented in CityBES, an open web-based data and computing platform for urban building energy research

Neutron Stars with Bose-Einstein Condensation of Antikaons as MIT Bags

We investigate the properties of an antikaon in medium, regarding itas a MIT bag. We first construct the MIT bag model for a kaon with$\sigma^*$ and $\phi$ in order to describe the interaction of$s$-quarks in hyperonic matter in the framework of the modifiedquark-meson coupling model. The coupling constant $g'^{B_K}_\sigma$in the density-dependent bag constant $B(\sigma)$ is treated as afree parameter to reproduce the optical potential of a kaon in asymmetric matter and all other couplings are determined by usingSU(6) symmetry and the quark counting rule. With various values ofthe kaon potential, we calculate the effective mass of a kaon inmedium to compare it with that of a point-like kaon. We thencalculate the population of octet baryons, leptons and $K^-$ and theequation of state for neutron star matter. The results show thatkaon condensation in hyperonic matter is sensitive to the $s$-quarkinteraction and also to the way of treating the kaon. The mass andthe radius of a neutron star are obtained by solving theTolmann-Oppenheimer-Volkoff equation.Comment: 14 figure