The cold neutron imaging and diffraction instrument IMAT at the second target station of the pulsed neutron source ISIS is currently being commissioned and prepared for user operation. IMAT will enable white-beam neutron radiography and tomography. One of the benefits of operating on a pulsed source is to determine the neutron energy via a time of flight measurement, thus enabling energy-selective and energy-dispersive neutron imaging, for maximizing image contrasts between given materials and for mapping structure and microstructure properties. We survey the hardware and software components for data collection and image analysis on IMAT, and provide a step-by-step procedure for operating the instrument for energy-dispersive imaging using a two-phase metal test object as an example.

We present the dimensioning of a photon-photon collider based on Compton gamma sources for the observation of Breit-Wheeler pair production and QED γγ events. Two symmetric electron beams, generated by photocathodes and accelerated in linacs, produce two gamma ray beams through Compton back scattering with two J-class lasers. Tuning the system energy above the Breit-Wheeler cross section threshold, a flux of electron-positron pairs is generated out of light-light interaction. The process is analyzed by start-to-end simulations. Realistic numbers of the secondary particle yield, referring to existing state-of-the-art set-ups and a discussion of the feasibility of the experiment taking into account the background signal are presented

We present the design of a photon-photon collider based on conventional Compton gamma sources for the observation of elastic γγ scattering. Two symmetric electron beams, generated by photocathodes and accelerated in linacs, produce two primary gamma rays through Compton backscattering with two high energy lasers. The elastic photon-photon scattering is analyzed by start-to-end simulations from the photocathodes to the detector. A new Monte Carlo code has been developed ad hoc for the counting of the QED events. Realistic numbers of the secondary gamma yield, obtained by using the parameters of existing or approved Compton devices, a discussion of the feasibility of the experiment and of the nature of the background are presented

This work presents the first neutron characterization of artefacts from the grave-goods of Kha and Merit, a unique cultural treasure of mankind and preserved at the Museo Egizio in Turin. This magnificent collection, discovered in the early years of the last century, includes an impressive amount of artefacts such as coffins, textiles, metallic and ceramic pottery, and alabaster containers. The present study investigates two sealed potteries, using enhanced Neutron Tomography, Radiography, and Prompt Gamma Activation Analysis techniques. The neutron probe provides access to the morphological reconstructions of the inner parts of the vases and to map, with unprecedented details, the elemental composition of the surfaces and bulk areas of the potteries. The present work extends the knowledge to hitherto unknown contents of the sealed vases unlocking their secrets

Neutron Tomography (NT) is a non-destructive technique to investigate the inner structure of a wide range of objects and, in some cases, provides valuable results in comparison to the more common X-ray imaging techniques. However, NT is time consuming and scanning a set of similar objects during a beamtime leads to data redundancy and long acquisition times. Nowadays NT is unfeasible for quality checking study of large quantities of similar objects. One way to decrease the total scan time is to reduce the number of projections. Analytical reconstruction methods are very fast but under this condition generate streaking artifacts in the reconstructed images. Iterative algorithms generally provide better reconstruction for limited data problems, but at the expense of longer reconstruction time. In this study, we propose the recently introduced Neural Network Filtered Back-Projection (NN-FBP) method to optimize the time usage in NT experiments. Simulated and real neutron data were used to assess the performance of the NN-FBP method as a function of the number of projections. For the first time a machine learning based algorithm is applied and tested for NT image reconstruction problem. We demonstrate that the NN-FBP method can reliably reduce acquisition and reconstruction times and it outperforms conventional reconstruction methods used in NT, providing high image quality for limited datasets.