Computational Nuclear Physics and Post Hartree-Fock Methods

We present a computational approach to infinite nuclear matter employing Hartree-Fock theory, many-body perturbation theory and coupled cluster theory. These lectures are closely linked with those of chapters 9, 10 and 11 and serve as input for the correlation functions employed in Monte Carlo calculations in chapter 9, the in-medium similarity renormalization group theory of dense fermionic systems of chapter 10 and the Green's function approach in chapter 11. We provide extensive code examples and benchmark calculations, allowing thereby an eventual reader to start writing her/his own codes. We start with an object-oriented serial code and end with discussions on strategies for porting the code to present and planned high-performance computing facilities.Comment: 82 pages, to appear in Lecture Notes in Physics (Springer), "An advanced course in computational nuclear physics: Bridging the scales from quarks to neutron stars", M. Hjorth-Jensen, M. P. Lombardo, U. van Kolck, Editor

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Colored Emission of Rare Earth Ions in a Potassium Feldspar Glass

The viability of rare earth ions as fluorescent coloring additives for dental porcelain was investigated. The data presented allow the formulation of porcelain with specific color properties under illumination by ultraviolet light. Attention is drawn to the possibility of energy transfer occurring with the result that prediction of color may not be done by application of the additive color-mixing scheme.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67486/2/10.1177_00220345770560110401.pd

Probabilistic State Estimation in Distribution Networks

State estimation is a procedure that can be used to obtain an estimate of the networkstate by processing the available set of measurements. The state of a network iscommonly defined as the voltage magnitude and angle at every bus. Other parametersin the network such as power flows and currents can be calculated fromthe network state. The information provided by the state estimation is used toassess the network security, to analyze contingencies, and to make decisions onrequired control actions. The concept of applying state estimation to power systemswas developed around 1970 [1]. Since then state estimation has become a routinetask in transmission systems. Over time a large number of redundant measurementdevices were installed throughout transmission networks, and accurate networkmodels have been developed. As a result, it is usually possible to estimate the stateof a transmission network with a high degree of accuracy