Gamma-ray spectroscopy at TRIUMF-ISAC

The 8π spectrometer at TRIUMF-ISAC consists of 20 Compton-suppressed germanium detectors and various auxiliary devices. The Ge array, once used for studies of nuclei at high angular momentum, has been transformed into the world's most powerful device dedicated to radioactive-decay studies. Many improvements in the spectrometer have been made, including a high-throughput data acquisition system, installation of a moving tape collector, incorporation of an array of 20 plastic scintillators for β-particle tagging, 5 Si(Li) detectors for conversion electrons, and 10 BaF2 detectors for fast-lifetime measurements. Experiments can be performed where data from all detectors are collected simultaneously, resulting in a very detailed view of the nucleus through radioactive decay. A number of experimental programmes have been launched that take advantage of the versatility of the spectrometer, and the intense beams available at TRIUMF-ISAC. © 2006 American Institute of Physics.

High-resolution γ-ray spectroscopy: A versatile tool for nuclear β-decay studies at TRIUMF-ISAC

High-resolution γ-ray spectroscopy is essential to fully exploit the unique, high-quality beams available at the next generation of radioactive ion beam facilities such as the TRIUMF isotope separator and accelerator (ISAC). The 8π spectrometer, which consists of 20 Compton-suppressed HPGe detectors, has recently been reconfigured for a vigorous research programme in weak interaction and nuclear structure physics. With the addition of a variety of ancillary detectors it has become the world's most powerful device dedicated to β-decay studies. This paper provides a brief overview of the apparatus and highlights from recent experiments. © 2005 IOP Publishing Ltd.

Discovery of a new 2.3 s isomer in neutron-rich 174Tm

A new program of K-isomer research has been initiated with the 8π spectrometer sited at the ISAC facility of TRIUMF. We discuss in this paper the identification of a new 2.3 s isomer in 174Tm and its implications. © Società Italiana di Fisica / Springer-Verlag 2005.

Random function priors for exchangeable arrays with applications to graphs and relational data

A fundamental problem in the analysis of structured relational data like graphs, networks, databases, and matrices is to extract a summary of the common structure underlying relations between individual entities. Relational data are typically encoded in the form of arrays; invariance to the ordering of rows and columns corresponds to exchangeable arrays. Results in probability theory due to Aldous, Hoover and Kallenberg show that exchangeable arrays can be represented in terms of a random measurable function which constitutes the natural model parameter in a Bayesian model. We obtain a flexible yet simple Bayesian nonparametric model by placing a Gaussian process prior on the parameter function. Efficient inference utilises elliptical slice sampling combined with a random sparse approximation to the Gaussian process. We demonstrate applications of the model to network data and clarify its relation to models in the literature, several of which emerge as special cases.