We investigate the feasibility of constructing a data-driven distance metric for use in null-hypothesis testing in the context of arms-control treaty verification. The distance metric is used in testing the hypothesis that the available data are representative of a certain object or otherwise, as opposed to binary-classification tasks studied previously. The metric, being of strictly quadratic form, is essentially computed using projections of the data onto a set of optimal vectors. These projections can be accumulated in list mode. The relatively low number of projections hampers the possible reconstruction of the object and subsequently the access to sensitive information. The projection vectors that channelize the data are optimal in capturing the Mahalanobis squared distance of the data associated with a given object under varying nuisance parameters. The vectors are also chosen such that the resulting metric is insensitive to the difference between the trusted object and another object that is deemed to contain sensitive information. Data used in this study were generated using the GEANT4 toolkit to model gamma transport using a Monte Carlo method. For numerical illustration, the methodology is applied to synthetic data obtained using custom models for plutonium inspection objects. The resulting metric based on a relatively low number of channels shows moderate agreement with the Mahalanobis distance metric for the trusted object but enabling a capability to obscure sensitive information.
Linear mathematical models were applied to binary-discrimination tasks relevant to arms control verification measurements in which a host party wishes to convince a monitoring party that an item is or is not treaty accountable. These models process data in list-mode format and can compensate for the presence of variability in the source, such as uncertain object orientation and location. The Hotelling observer applies an optimal set of weights to binned detector data, yielding a test statistic that is thresholded to make a decision. The channelized Hotelling observer applies a channelizing matrix to the vectorized data, resulting in a lower dimensional vector available to the monitor to make decisions. We demonstrate how incorporating additional terms in this channelizing-matrix optimization offers benefits for treaty verification. We present two methods to increase shared information and trust between the host and monitor. The first method penalizes individual channel performance in order to maximize the information available to the monitor while maintaining optimal performance. Second, we present a method that penalizes predefined sensitive information while maintaining the capability to discriminate between binary choices. Data used in this study was generated using Monte Carlo simulations for fission neutrons, accomplished with the GEANT4 toolkit. Custom models for plutonium inspection objects were measured in simulation by a radiation imaging system. Model performance was evaluated and presented using the area under the receiver operating characteristic curve.
Observer models were developed to process data in list-mode format in order to perform binary discrimination tasks for use in an arms-control-treaty context. Data used in this study was generated using GEANT4 Monte Carlo simulations for photons using custom models of plutonium inspection objects and a radiation imaging system. Observer model performance was evaluated and presented using the area under the receiver operating characteristic curve. The ideal observer was studied under both signal-known-exactly conditions and in the presence of unknowns such as object orientation and absolute count-rate variability; when these additional sources of randomness were present, their incorporation into the observer yielded superior performance.
This report summarizes the discussion and conclusions reached during a table top exercise held at Sandia National Laboratories, Albuquerque on September 3, 2014 regarding a recently described approach for nuclear warhead verification based on the cryptographic concept of a zero-knowledge protocol (ZKP) presented in a recent paper authored by Glaser, Barak, and Goldston. A panel of Sandia National Laboratories researchers, whose expertise includes radiation instrumentation design and development, cryptography, and arms control verification implementation, jointly reviewed the paper and identified specific challenges to implementing the approach as well as some opportunities. It was noted that ZKP as used in cryptography is a useful model for the arms control verification problem, but the direct analogy to arms control breaks down quickly. The ZKP methodology for warhead verification fits within the general class of template-based verification techniques, where a reference measurement is used to confirm that a given object is like another object that has already been accepted as a warhead by some other means. This can be a powerful verification approach, but requires independent means to trust the authenticity of the reference warhead - a standard that may be difficult to achieve, which the ZKP authors do not directly address. Despite some technical challenges, the concept of last-minute selection of the pre-loads and equipment could be a valuable component of a verification regime.
This report provides a short overview of the DNN R&D funded project SL12-Optlmg-PD2Nc, Optimal Imaging for Treaty Verification. The project began in FY12 and in FY15 is merging with a PNNL project to form the PL14-V-InfoBarrierimg-PD2Nc venture. The Project Description below provides the overall motivation and objectives for the project as well as a summary of programmatic direction. The most recent comprehensive technical report is referenced.
FY2014 technical report of our project funded by DNN R&D that leverages advanced inference methods developed for medical and adaptive imaging to address arms control applications. We seek a method to acquire and analyze imaging data of declared treaty-accountable items without creating an image of those objects or otherwise storing or revealing any classified information. Such a method would avoid the use of classified-information barriers. We present our progress on FY2014 tasks defined in our life-cycle plan. We also describe some future work that is part of the continuation of this project in FY2015 and beyond as part of a venture that joins ours with a related PNNL project.
Because of their penetrating power, energetic neutrons and gamma rays ({approx}1 MeV) offer the best possibility of detecting highly shielded or distant special nuclear material (SNM). Of these, fast neutrons offer the greatest advantage due to their very low and well understood natural background. We are investigating a new approach to fast-neutron imaging- a coded aperture neutron imaging system (CANIS). Coded aperture neutron imaging should offer a highly efficient solution for improved detection speed, range, and sensitivity. We have demonstrated fast neutron and gamma ray imaging with several different configurations of coded masks patterns and detectors including an 'active' mask that is composed of neutron detectors. Here we describe our prototype detector and present some initial results from laboratory tests and demonstrations.
The primary function of the Gamma Detector Response and Analysis Software (GADRAS) is the solution of inverse radiation transport problems, by which the con-figuration of an unknown radiation source is inferred from one or more measured radia-tion signatures. GADRAS was originally developed for the analysis of gamma spec-trometry measurements. During fiscal years 2007 and 2008, GADRAS was augmented to implement the simultaneous analysis of neutron multiplicity measurements. This report describes the radiation transport methods developed to implement this new capability. This work was performed at the direction of the National Nuclear Security Administration's Office of Nonproliferation Research and Development. It was executed as an element of the Proliferation Detection Program's Simulation, Algorithm, and Modeling element. Acronyms BNL Brookhaven National Laboratory CSD Continuous Slowing-Down DU depleted uranium ENSDF Evaluated Nuclear Structure Data Files GADRAS Gamma Detector Response and Analysis Software HEU highly enriched uranium LANL Los Alamos National Laboratory LLNL Lawrence Livermore National Laboratory NA-22 Office of Nonproliferation Research and Development NNDC National Nuclear Data Center NNSA National Nuclear Security Administration ODE ordinary differential equation ONEDANT One-dimensional diffusion accelerated neutral particle transport ORNL Oak Ridge National Laboratory PARTISN Parallel time-dependent SN PDP Proliferation Detection Program RADSAT Radiation Scenario Analysis Toolkit RSICC Radiation Safety Information Computational Center SAM Simulation, Algorithms, and Modeling SNL Sandia National Laboratories SNM special nuclear material ToRI Table of Radioactive Isotopes URI uniform resource identifier XML Extensible Markup Language