Dr Peter Hatfield

Abstract:

We present measurements of the H-like potassium (K xix) X-ray spectrum and its He-like (K xviii) satellite lines, which are situated in the wavelength region between 3.34 and 3.39 Å, which has been of interest for the detection of dark matter. The measurements were taken with a high-resolution X-ray spectrometer from targets irradiated by a long-pulse (2 ns) beam from the Orion laser facility. We obtain experimental wavelength values of dielectronic recombination satellite lines and show that the ratio of the Lyα lines and their dielectronic satellite lines can be used to estimate the electron temperature, which in our case was about 1.5 ± 0.3 keV.

Abstract:

The design of inertial confinement fusion (ICF) experiments, alongside improving the development of energy density physics theory and experimental methods, is one of the key challenges in the quest for nuclear fusion as a viable energy source [O. A. Hurricane, J. Phys.: Conf. Ser. 717, 012005 (2016)]. Recent challenges in achieving a high-yield implosion at the National Ignition Facility (NIF) have led to new interest in considering a much wider design parameter space than normally studied [J. L. Peterson et al., Phys. Plasmas 24, 032702 (2017)]. Here, we report an algorithmic approach that can produce reasonable ICF designs with minimal assumptions. In particular, we use the genetic algorithm metaheuristic, in which “populations” of implosions are simulated, the design of the capsule is described by a “genome,” natural selection removes poor designs, high quality designs are “mated” with each other based on their yield, and designs undergo “mutations” to introduce new ideas. We show that it takes ∼5 × 104 simulations for the algorithm to find an original NIF design. We also link this method to other parts of the design process and look toward a completely automated ICF experiment design process—changing ICF from an experiment design problem to an algorithm design problem.

Abstract:

The Langton Ultimate Cosmic ray Intensity Detector (LUCID) is a payload onboard the satellite TechDemoSat-1, used to study the radiation environment in Low Earth Orbit (635 km). LUCID operated from 2014 to 2017, collecting over 2.1 million frames of radiation data from its five Timepix detectors on board. LUCID is one of the first uses of the Timepix detector technology in open space, with the data providing useful insight into the performance of this technology in new environments. It provides high-sensitivity imaging measurements of the mixed radiation field, with a wide dynamic range in terms of spectral response, particle type and direction. The data has been analysed using computing resources provided by GridPP, with a new machine learning algorithm that uses the Tensorflow framework. This algorithm provides a new approach to processing Medipix data, using a training set of human labelled tracks, providing greater particle classification accuracy than other algorithms. For managing the LUCID data, we have developed an online platform called Timepix Analysis Platform at School (TAPAS). This provides a swift and simple way for users to analyse data that they collect using Timepix detectors from both LUCID and other experiments. We also present some possible future uses of the LUCID data and Medipix detectors in space.