Source Detection and Image Reconstruction with Position-Sensitive Gamma-Ray Detectors.

Gamma-ray detectors have important applications in security, medicine, and nuclear non-proliferation. This thesis investigates the use of regularization to improve image reconstruction and efficient methods for predicting source detection performance with position-sensitive gamma-ray detectors. Position-sensitive detectors have the ability to measure the spatial gamma emission density around the detector. An image of the spatial gamma emission density where a spatially small source is present will be sparse in the canonical basis, meaning that the emission density is zero for most directions but large for a small number of directions. This work uses regularization to enforce sparsity in the reconstructed image, and proposes a regularizer that effectively enforces sparsity in the reconstructed images. This work also proposes a method for predicting detection performance. Position-sensitive gamma-ray imaging systems are complex and difficult to model both accurately and efficiently. This work investigates the asymptotic properties of tests based on maximum likelihood (ML) estimates under model mismatch, meaning that the statistical model used for detection differs from the true distribution. We propose general expressions for the asymptotic distribution of likelihood-based test statistics when the number of measurements is Poisson. We use the general expressions to derive expressions specific to gamma-ray source detection that one can evaluate using a modest amount of data from a real system or Monte-Carlo simulation. We show empirically with simulated data that the proposed expressions yield more accurate detection performance predictions than expressions that ignore model mismatch. We also use data recorded with a 3D position-sensitive CdZnTe system with a Cs-137 source in a natural background to show that the proposed method is reasonably accurate with real data. These expressions require less data and computation than conventional empirical methods. To quantify the benefit of position-sensitivity, we state and prove a theorem affirming that, asymptotically as scan time becomes large, position-sensitivity increases the area under the receiver operating characteristic curve (AUC) when the background intensity is known, detector sensitivity is spatially uniform, and the system model is correctly specified.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91441/1/danling_1.pd

Adaptive Imaging with a Cylindrical, Time-Encoded Imaging System

Most imaging systems for terrestrial nuclear imaging are static in that the design of the system and the data acquisition protocol are defined prior to the experiment. Often, these systems are designed for general use and not optimized for any specific task. The core concept of adaptive imaging is to modify the imaging system during a measurement based on collected data. This enables scenario specific adaptation of the imaging system which leads to better performance for a given task. This dissertation presents the first adaptive, cylindrical, time-encoded imaging (c-TEI) system and evaluates its performance on tasks relevant to nuclear non-proliferation and international safeguards. We explore two methods of adaptation of a c-TEI system, adaptive detector movements and adaptive mask movements, and apply these methods to three tasks, improving angular resolution, detecting a weak source in the vicinity of a strong source, and reconstructing complex source scenes. The results indicate that adaptive imaging significantly improves performance in each case. For the MATADOR imager, we find that adaptive detector movements improve the angular resolution of a point source by 20% and improve the angular resolution of two point sources by up to 50%. For the problem of detecting a weak source in the vicinity of a strong source, we find that adaptive mask movements achieve the same detection performance as a similar, non-adaptive system in 20%-40% less time, depending on the relative position of the weak source. Additionally, we developed an adaptive detection algorithm that doubles the probability of detection of the weak source at a 5% false-alarm rate. Finally, we applied adaptive imaging concepts to reconstruct complex arrangements of special nuclear material at Idaho National Laboratory. We find that combining data from multiple detector positions improves image uniformity of extended sources by 38% and reduces the background noise by 50%. We also demonstrate 2D (azimuthal and radial) imaging in a crowded source scene. These promising experimental results highlight the potential for adaptive imaging using a c-TEI system and motivate further research toward specific, real-world applications.PHDNuclear Engineering & Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163009/1/nirpshah_1.pd

Benefits of Position-Sensitive Detectors for Radioactive Source Detection

There are many systems for counting photons such as gamma-rays emitted from radioactive sources. Many of these systems are also position-sensitive, which means that the system provides directional information about recorded events. This paper investigates whether or not the additional information provided by position-sensitive capability improves the performance of detecting a point-source in background. We analyze the asymptotic performance of the generalized likelihood ratio test (GLRT) and a test based on the maximum-likelihood (ML) estimate of the source intensity for systems with and without position-sensitive capability. When the background intensity is known and detector sensitivity is spatially uniform, we prove that position-sensitive capability increases the area under the receiver operating characteristic curve (AUC). For cases when detector sensitivity is nonuniform or background intensity is unknown, we provide numerical results to illustrate the effect of the parameters on detection performance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85967/1/Fessler6.pd

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

Gravitational waves from Sco X-1: A comparison of search methods and prospects for detection with advanced detectors

The low-mass X-ray binary Scorpius X-1 (Sco X-1) is potentially the most luminous source of continuous gravitational-wave radiation for interferometers such as LIGO and Virgo. For low-mass X-ray binaries this radiation would be sustained by active accretion of matter from its binary companion. With the Advanced Detector Era fast approaching, work is underway to develop an array of robust tools for maximizing the science and detection potential of Sco X-1. We describe the plans and progress of a project designed to compare the numerous independent search algorithms currently available. We employ a mock-data challenge in which the search pipelines are tested for their relative proficiencies in parameter estimation, computational efficiency, robust- ness, and most importantly, search sensitivity. The mock-data challenge data contains an ensemble of 50 Scorpius X-1 (Sco X-1) type signals, simulated within a frequency band of 50-1500 Hz. Simulated detector noise was generated assuming the expected best strain sensitivity of Advanced LIGO and Advanced VIRGO ($4 \times 10^{-24}$ Hz$^{-1/2}$). A distribution of signal amplitudes was then chosen so as to allow a useful comparison of search methodologies. A factor of 2 in strain separates the quietest detected signal, at $6.8 \times 10^{-26}$ strain, from the torque-balance limit at a spin frequency of 300 Hz, although this limit could range from $1.2 \times 10^{-25}$ (25 Hz) to $2.2 \times 10^{-26}$ (750 Hz) depending on the unknown frequency of Sco X-1. With future improvements to the search algorithms and using advanced detector data, our expectations for probing below the theoretical torque-balance strain limit are optimistic.Comment: 33 pages, 11 figure

Maximum-likelihood detection of sources among Poissonian noise

A maximum likelihood (ML) technique for detecting compact sources in images of the x-ray sky is examined. Such images, in the relatively low exposure regime accessible to present x-ray observatories, exhibit Poissonian noise at background flux levels. A variety of source detection methods are compared via Monte Carlo, and the ML detection method is shown to compare favourably with the optimized-linear-filter (OLF) method when applied to a single image. Where detection proceeds in parallel on several images made in different energy bands, the ML method is shown to have some practical advantages which make it superior to the OLF method. Some criticisms of ML are discussed. Finally, a practical method of estimating the sensitivity of ML detection is presented, and is shown to be also applicable to sliding-box source detection.Comment: 17 pages, 10 figures. Accepted by Astronomy & Astrophysic

Working Papers: Astronomy and Astrophysics Panel Reports

The papers of the panels appointed by the Astronomy and Astrophysics survey Committee are compiled. These papers were advisory to the survey committee and represent the opinions of the members of each panel in the context of their individual charges. The following subject areas are covered: radio astronomy, infrared astronomy, optical/IR from ground, UV-optical from space, interferometry, high energy from space, particle astrophysics, theory and laboratory astrophysics, solar astronomy, planetary astronomy, computing and data processing, policy opportunities, benefits to the nation from astronomy and astrophysics, status of the profession, and science opportunities