On the Single-Photon-Counting (SPC) modes of imaging using an XFEL source

The requirements to achieve high detection efficiency (above 50\%) and gigahertz (GHz) frame rate for the proposed 42-keV X-ray free-electron laser (XFEL) at Los Alamos are summarized. Direct detection scenarios using C (diamond), Si, Ge and GaAs semiconductor sensors are analyzed. Single-photon counting (SPC) mode and weak SPC mode using Si can potentially meet the efficiency and frame rate requirements and be useful to both photoelectric absorption and Compton physics as the photon energy increases. Multilayer three-dimensional (3D) detector architecture, as a possible means to realize SPC modes, is compared with the widely used two-dimensional (2D) hybrid planar electrode structure and 3D deeply entrenched electrode architecture. Demonstration of thin film cameras less than 100-$\mu$m thick with onboard thin ASICs could be an initial step to realize multilayer 3D detectors and SPC modes for XFELs.Comment: 11 pages, 3 figures, 17th IWoRID workshop, Jun. 28 to July 2, 2015, Hamburg, German

Tracking fast neutrons

Based on elastic collisions, the linear momentum of a fast neutron can be measured from as few as two consecutive recoil ion tracks plus the vertex position of the third collision, or `two and half' ion tracks. If the time delay between the first two consecutive ion tracks is also measured, the number of ion tracks can be reduced to one and a half. The angular and magnitude resolutions are limited by ion range straggling to about ten percent. Multi-wire proportional chambers and light-field imaging are discussed for fast neutron tracking. Single-charge or single-photon detection sensitivity is required in either approach. Light-field imaging is free of charge-diffusion-induced image blur, but the limited number of photons available can be a challenge. $^1$H,$^2$H and $^3$He could be used for the initial development of fast neutron trackers based on light-field imaging.Comment: 13 pages, 14 figure

Noise classification of ICF images using a convolutional neural network (CNN)

In this paper, noise classification of ICF images is performed. One hundred thousand synthetic ICF images are generated to classify different kinds of noise. The noise of ICF images is neither additive nor does it follow any typical distributions. So, a deep neural network model, CNN, is designed to classify ten different noise distributions. Synthetic images are used as input to the model. With two hidden layers and an Adam optimizer, 91% accuracy is obtained. Experimental images are tested with the saved model, and the result is shown in this paper. Further study is needed to improve the accuracy of the model

A double-helix neutron detector using micron-size B-10 powder

A double-helix electrode configuration is combined with a $^{10}$B powder coating technique to build large-area (9 in $\times$ 36 in) neutron detectors. The neutron detection efficiency for each of the four prototypes is comparable to a single 2-bar $^3$He drift tube of the same length (36 in). One unit has been operational continuously for 18 months and the change of efficiency is less than 1%. An analytic model for pulse heigh spectra is described and the predicted mean film thickness agrees with the experiment to within 30%. Further detector optimization is possible through film texture, power size, moderator box and gas. The estimated production cost per unit is less than 3k US\$ and the technology is thus suitable for deployment in large numbers