Track Reconstruction and Performance of DRIFT Directional Dark Matter Detectors using Alpha Particles

First results are presented from an analysis of data from the DRIFT-IIa and DRIFT-IIb directional dark matter detectors at Boulby Mine in which alpha particle tracks were reconstructed and used to characterise detector performance--an important step towards optimising directional technology. The drift velocity in DRIFT-IIa was [59.3 +/- 0.2 (stat) +/- 7.5 (sys)] m/s based on an analysis of naturally-occurring alpha-emitting background. The drift velocity in DRIFT-IIb was [57 +/- 1 (stat) +/- 3 (sys)] m/s determined by the analysis of alpha particle tracks from a Po-210 source. 3D range reconstruction and energy spectra were used to identify alpha particles from the decay of Rn-222, Po-218, Rn-220 and Po-216. This study found that (22 +/- 2)% of Po-218 progeny (from Rn-222 decay) are produced with no net charge in 40 Torr CS2. For Po-216 progeny (from Rn-220 decay) the uncharged fraction is (100 +0 -35)%.Comment: 27 pages, 12 figures, 5 tables. Submitted to Nuclear Instruments and Methods in Physics Research, Section A. Subj-class: Instrumentation and Detector

It's Okay to Call Genetic Drift a “Force”

One hotly debated philosophical question in the analysis of evolutionary theory concerns whether or not evolution and the various factors which constitute it (selection, drift, mutation, and so on) may profitably be considered to be “forces” in the traditional, Newtonian sense. Several compelling arguments assert that the force picture is incoherent, due to the peculiar nature of genetic drift. I consider two of those arguments here – that drift lacks a predictable direction, and that drift is constitutive of evolutionary systems – and show that they both fail to demonstrate that a view of genetic drift as a force is untenable

Notes on drift theory

It is shown that there is a simpler way to derive the average guiding center drift of a distribution of particles than via the so-called single particle analysis. Based on this derivation it is shown that the entire drift formalism can be considerably simplified, and that results for low order anisotropies are more generally valid than is usually appreciated. This drift analysis leads to a natural alternative derivation of the drift velocity along a neutral sheet

Renormalization of Drift and Diffusivity in Random Gradient Flows

We investigate the relationship between the effective diffusivity and effective drift of a particle moving in a random medium. The velocity of the particle combines a white noise diffusion process with a local drift term that depends linearly on the gradient of a gaussian random field with homogeneous statistics. The theoretical analysis is confirmed by numerical simulation. For the purely isotropic case the simulation, which measures the effective drift directly in a constant gradient background field, confirms the result previously obtained theoretically, that the effective diffusivity and effective drift are renormalized by the same factor from their local values. For this isotropic case we provide an intuitive explanation, based on a {\it spatial} average of local drift, for the renormalization of the effective drift parameter relative to its local value. We also investigate situations in which the isotropy is broken by the tensorial relationship of the local drift to the gradient of the random field. We find that the numerical simulation confirms a relatively simple renormalization group calculation for the effective diffusivity and drift tensors.Comment: Latex 16 pages, 5 figures ep

Impact of rheology on probabilistic forecasts of sea ice trajectories: application for search and rescue operations in the Arctic

We present a sensitivity analysis and discuss the probabilistic forecast capabilities of the novel sea ice model neXtSIM used in hindcast mode. The study pertains to the response of the model to the uncertainty on winds using probabilistic forecasts of ice trajectories. neXtSIM is a continuous Lagrangian numerical model that uses an elasto-brittle rheology to simulate the ice response to external forces. The sensitivity analysis is based on a Monte Carlo sampling of 12 members. The response of the model to the uncertainties is evaluated in terms of simulated ice drift distances from their initial positions, and from the mean position of the ensemble, over the mid-term forecast horizon of 10 days. The simulated ice drift is decomposed into advective and diffusive parts that are characterised separately both spatially and temporally and compared to what is obtained with a free-drift model, that is, when the ice rheology does not play any role in the modelled physics of the ice. The seasonal variability of the model sensitivity is presented and shows the role of the ice compactness and rheology in the ice drift response at both local and regional scales in the Arctic. Indeed, the ice drift simulated by neXtSIM in summer is close to the one obtained with the free-drift model, while the more compact and solid ice pack shows a significantly different mechanical and drift behaviour in winter. For the winter period analysed in this study, we also show that, in contrast to the free-drift model, neXtSIM reproduces the sea ice Lagrangian diffusion regimes as found from observed trajectories. The forecast capability of neXtSIM is also evaluated using a large set of real buoy's trajectories and compared to the capability of the free-drift model. We found that neXtSIM performs significantly better in simulating sea ice drift, both in terms of forecast error and as a tool to assist search and rescue operations, although the sources of uncertainties assumed for the present experiment are not sufficient for complete coverage of the observed IABP positions