Variable dimension automatic synthesis programs (VASP)

Variable dimension FORTRAN 4 version of the Automatic Synthesis Program (ASP) compensates for limitations within the program itself. Improvements are versatile programming language, convenient input/output format, new subprograms, variable dimensioning, and efficient storage

The diagonalization of quantum field Hamiltonians

We introduce a new diagonalization method called quasi-sparse eigenvector diagonalization which finds the most important basis vectors of the low energy eigenstates of a quantum Hamiltonian. It can operate using any basis, either orthogonal or non-orthogonal, and any sparse Hamiltonian, either Hermitian, non-Hermitian, finite-dimensional, or infinite-dimensional. The method is part of a new computational approach which combines both diagonalization and Monte Carlo techniques.Comment: 12 pages, 8 figures, new material adde

Supersymmetry and Localization in the Quantum Hall Effect

We study the localization transition in the integer quantum Hall effect as described by the network model of quantum percolation. Starting from a path integral representation of transport Green's functions for the network model, which employs both complex (bosonic) and Grassman (fermionic) fields, we map the problem of localization to the problem of diagonalizing a one-dimensional non-Hermitian Hamiltonian of interacting bosons and fermions. An exact solution is obtained in a restricted subspace of the Hilbert space which preserves boson-fermion supersymmetry. The physically relevant regime is investigated using the density matrix renormalization group (DMRG) method, and critical behavior is found at the plateau transition.Comment: 14 RevTex pages, 3 eps figures; This revised version contains an extended disussion of supersymmetry and improved numerical result

Investigation of the effect of hub support parameters on two-bladed rotor oscillatory loads

The results are presented of a test program and analysis to investigate the effects of inplane hub support parameters on the oscillatory chordwise loads of a two-bladed teetering rotor. The test program was conducted in two phases. The first consisted of a shake test to define the impedance of a number of test configurations as a function of frequency. The second phase was the test of these configurations in the NASA-Langley transonic dynamics tunnel. The test showed that the one-per-rev inplane bending moments could be changed by a factor of 2.0 as a function of the pylon configuration at the same aerodynamic operating condition. The higher harmonic inplane, flapwise, and torsional bending moments, and pitch link axial loads were not affected by changes in inplane hub impedance. The maximum inplane loads occurred for the pylon configuration with the minimum spring rate and maximum inertia

Community-level characteristics of high infant mortality: A tool to identify at-risk communities

Infant mortality (IM) rate is a key indicator of population health and has been gradually improving in the United States. However, it is still a public health problem among minority and low-income communities. Maternal factors explain some of the variation, but community-level factors may also be a contributor. This study examines measures to identify a set of indicators that explain variations in IM at the community-level. Data for 77 communities in a city were obtained from local health databases. We used multivariable linear regression models to examine the strength of the association between IM and maternal, population, community wealth, and social capital characteristics. Community-level IM rates ranged from 2.1 – 25.6 deaths per 1,000 live births in 2000-2002. The final model explained 75% of the variation in IM rates at the community-level (R2=0.75). The model included a high percentage of low birth weight babies, a decline in mothers who began prenatal care in the second trimester, an increase in the percentage of Hispanics, increased unemployment rates, an increase in the percentage of veterans, an increased rate of foreign-born residents, and smaller average family sizes. Social capital variables, homicide rate and vacant housing, were also significant in the final model. Identifying communities at risk for high IM rates is imperative to improve maternal and child health outcomes because of shortages in public health resources. The development of a parsimonious set of community-level indicators can assist public health practitioners in targeting their resources to prevent infant mortality in high-risk communities

Charge ordering in doped manganese oxides: lattice dynamics and magnetic structure

Based on the Hamiltonian of small polarons with the strong nearest neighbor repulsion, we have investigated the charge ordering phenomena observed in half-doped manganites R_{1/2}A_{1/2}MnO_3. We have explored possible consequences of the charge ordering phase in the half-doped manganites. First, we have studied the renormalization of the sound velocity around $T_{CO}$, considering the acoustic phonons coupled to the electrons participating in the charge ordering. Second, we have found a new antiferromagnetic phase induced by the charge ordering, and discussed its role in connection with the specific CE-type antiferromagnetic structure observed in half-doped manganites.Comment: 5 pages, 2 Postscript figures. To appear in Phys. Rev. B - Rapid Comm. (01Jun97

Sequential Symbolic Regression with Genetic Programming

This chapter describes the Sequential Symbolic Regression (SSR) method, a new strategy for function approximation in symbolic regression. The SSR method is inspired by the sequential covering strategy from machine learning, but instead of sequentially reducing the size of the problem being solved, it sequentially transforms the original problem into potentially simpler problems. This transformation is performed according to the semantic distances between the desired and obtained outputs and a geometric semantic operator. The rationale behind SSR is that, after generating a suboptimal function f via symbolic regression, the output errors can be approximated by another function in a subsequent iteration. The method was tested in eight polynomial functions, and compared with canonical genetic programming (GP) and geometric semantic genetic programming (SGP). Results showed that SSR significantly outperforms SGP and presents no statistical difference to GP. More importantly, they show the potential of the proposed strategy: an effective way of applying geometric semantic operators to combine different (partial) solutions, avoiding the exponential growth problem arising from the use of these operators