Predicting Neutron Production from Cosmic-ray Muons

Fast neutrons from cosmic-ray muons are an important background to underground low energy experiments. The estimate of such background is often hampered by the difficulty of measuring and calculating neutron production with sufficient accuracy. Indeed substantial disagreement exists between the different analytical calculations performed so far, while data reported by different experiments is not always consistent. We discuss a new unified approach to estimate the neutron yield, the energy spectrum, the multiplicity and the angular distribution from cosmic muons using the Monte Carlo simulation package FLUKA and show that it gives a good description of most of the existing measurements once the appropriate corrections have been applied.Comment: 8 pages, 7 figure

In pursuit of visual attention: SSVEP frequency-tagging moving targets.

Previous research has shown that visual attention does not always exactly follow gaze direction, leading to the concepts of overt and covert attention. However, it is not yet clear how such covert shifts of visual attention to peripheral regions impact the processing of the targets we directly foveate as they move in our visual field. The current study utilised the co-registration of eye-position and EEG recordings while participants tracked moving targets that were embedded with a 30 Hz frequency tag in a Steady State Visually Evoked Potentials (SSVEP) paradigm. When the task required attention to be divided between the moving target (overt attention) and a peripheral region where a second target might appear (covert attention), the SSVEPs elicited by the tracked target at the 30 Hz frequency band were significantly, but transiently, lower than when participants did not have to covertly monitor for a second target. Our findings suggest that neural responses of overt attention are only briefly reduced when attention is divided between covert and overt areas. This neural evidence is in line with theoretical accounts describing attention as a pool of finite resources, such as the perceptual load theory. Altogether, these results have practical implications for many real-world situations where covert shifts of attention may discretely reduce visual processing of objects even when they are directly being tracked with the eyes