PAN AIR: A computer program for predicting subsonic or supersonic linear potential flows about arbitrary configurations using a higher order panel method. Volume 2: User's manual (version 3.0)

A comprehensive description of user problem definition for the PAN AIR (Panel Aerodynamics) system is given. PAN AIR solves the 3-D linear integral equations of subsonic and supersonic flow. Influence coefficient methods are used which employ source and doublet panels as boundary surfaces. Both analysis and design boundary conditions can be used. This User's Manual describes the information needed to use the PAN AIR system. The structure and organization of PAN AIR are described, including the job control and module execution control languages for execution of the program system. The engineering input data are described, including the mathematical and physical modeling requirements. Version 3.0 strictly applies only to PAN AIR version 3.0. The major revisions include: (1) inputs and guidelines for the new FDP module (which calculates streamlines and offbody points); (2) nine new class 1 and class 2 boundary conditions to cover commonly used modeling practices, in particular the vorticity matching Kutta condition; (3) use of the CRAY solid state Storage Device (SSD); and (4) incorporation of errata and typo's together with additional explanation and guidelines

Putting the Lid on Lobbying: Tariff Structure and Long-Term Growth when Protection is for Sale

It has long been recognized that a country's tariffs are the endogenous outcome of a rent-seeking game whose equilibrium reflects national institutions. Thus, the structure of tariffs across industries provides insights into how institutions, as reflected in tariff policies, affect long-term growth. We start with the commonplace perception among politicians that protection of skill-intensive industries generates a growth-enhancing externality. Modifying the Grossman-Helpman protection for sale model to allow for this, we make two predictions. First, a country with good institutions will tolerate high average tariffs provided tariffs are biased towards skill-intensive industries. Second, there need not be any relationship between average tariffs and good institutions. Using data for 17 manufacturing industries in 59 countries over approximately 25 years, we find that average tariffs are uncorrelated with output growth and that the skill-bias of tariff structure is positively correlated with output growth. We interpret this to mean that countries grow faster if they are able and willing to put a lid on the rent-seeking behaviour of special interest lobby groups. We show that our results are not compatible with explanations that appeal to (1) externalities per se, (2) initial industrial structure that is skewed towards skill-intensive industries, or (3) the effects of broader institutions such as rule of law and control of corruption.

Supporting Abstraction when Model Checking ASM

Model checking as a method for automatic tool support for verification highly stimulates industry's interests. It is limited, however, with respect to the size of the systems' state space. In earlier work, we developed an interface between the ASM Workbench and the SMV model checker that allows model checking of finite ASM models. In this work, we add a means for abstraction in case the model to be checked is infinite and therefore not feasible for the model checking approach. We facilitate the ASM specification language (ASM-SL) with a notion for abstract types and introduce an interface between ASM-SL and Multiway Decision Graphs (MDGs). MDGs are capable of representing transition systems with abstract types and functions and provide the functionality necessary for symbolic model checking. Our interface maps abstract ASM models into MDGs in a semantic preserving way. It provides a very simple means for generating abstract models that are infinite but can be checked by a model checker based on MDGs

Mean-field theory for confinement transitions and magnetization plateaux in spin ice

We study phase transitions in classical spin ice at nonzero magnetization, by introducing a mean-field theory designed to capture the interplay between confinement and topological constraints. The method is applied to a model of spin ice in an applied magnetic field along the [1 0 0] crystallographic direction and yields a phase diagram containing the Coulomb phase as well as a set of magnetization plateaux. We argue that the lobe structure of the phase diagram, strongly reminiscent of the Bose–Hubbard model, is generic to Coulomb spin liquids

Quantum canonical tensor model and an exact wave function

Tensor models in various forms are being studied as models of quantum gravity. Among them the canonical tensor model has a canonical pair of rank-three tensors as dynamical variables, and is a pure constraint system with first-class constraints. The Poisson algebra of the first-class constraints has structure functions, and provides an algebraically consistent way of discretizing the Dirac first-class constraint algebra for general relativity. This paper successfully formulates the Wheeler-DeWitt scheme of quantization of the canonical tensor model; the ordering of operators in the constraints is determined without ambiguity by imposing Hermiticity and covariance on the constraints, and the commutation algebra of constraints takes essentially the same from as the classical Poisson algebra, i.e. is first-class. Thus one could consistently obtain, at least locally in the configuration space, wave functions of "universe" by solving the partial differential equations representing the constraints, i.e. the Wheeler-DeWitt equations for the quantum canonical tensor model. The unique wave function for the simplest non-trivial case is exactly and globally obtained. Although this case is far from being realistic, the wave function has a few physically interesting features; it shows that locality is favored, and that there exists a locus of configurations with features of beginning of universe.Comment: 17 pages. Section 2 expanded to include fuzzy-space interpretation, and other minor change

International price discovery in the presence of microstructure noise

This paper addresses and resolves the issue of microstructure noise when measuring the relative importance of home and U.S. market in the price discovery process of Canadian interlisted stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, due to the considerable amount of microstructure noise inherent in return data at very high frequencies, these estimators are distorted. We offer a modified approach that identifies unique information shares based on distributional assumptions and thereby enables us to control for microstructure noise. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been underestimated so far. Moreover, we suggest that rather than stock specific factors, market characteristics determine information shares

Phase diagram of self-assembled rigid rods on two-dimensional lattices: Theory and Monte Carlo simulations

Monte Carlo simulations and finite-size scaling analysis have been carried out to study the critical behavior in a two-dimensional system of particles with two bonding sites that, by decreasing temperature or increasing density, polymerize reversibly into chains with discrete orientational degrees of freedom and, at the same time, undergo a continuous isotropic-nematic (IN) transition. A complete phase diagram was obtained as a function of temperature and density. The numerical results were compared with mean field (MF) and real space renormalization group (RSRG) analytical predictions about the IN transformation. While the RSRG approach supports the continuous nature of the transition, the MF solution predicts a first-order transition line and a tricritical point, at variance with the simulation results.Comment: 12 pages, 10 figures, supplementary informatio

Self-Organizing Time Map: An Abstraction of Temporal Multivariate Patterns

This paper adopts and adapts Kohonen's standard Self-Organizing Map (SOM) for exploratory temporal structure analysis. The Self-Organizing Time Map (SOTM) implements SOM-type learning to one-dimensional arrays for individual time units, preserves the orientation with short-term memory and arranges the arrays in an ascending order of time. The two-dimensional representation of the SOTM attempts thus twofold topology preservation, where the horizontal direction preserves time topology and the vertical direction data topology. This enables discovering the occurrence and exploring the properties of temporal structural changes in data. For representing qualities and properties of SOTMs, we adapt measures and visualizations from the standard SOM paradigm, as well as introduce a measure of temporal structural changes. The functioning of the SOTM, and its visualizations and quality and property measures, are illustrated on artificial toy data. The usefulness of the SOTM in a real-world setting is shown on poverty, welfare and development indicators