Shielding of absorbing objects in collisionless flowing plasma

The electrostatic shielding of a charged absorbing object (dust grain) in a flowing collisionless plasma is investigated by using the linearized kinetic equation for plasma ions with a point-sink term accounting for ion absorption on the object. The effect of absorption on the attractive part of the grain potential is investigated. For subthermal ion flows, the attractive part of the grain potential in the direction perpendicular to the ion flow can be significantly reduced or completely destroyed, depending on the absorption rate. For superthermal ion flows, however, the effect of absorption on the grain attraction in the direction perpendicular to the ion flow is shown to be exponentially weak. It is thus argued that, in the limit of superthermal ion flow, the effect of absorption on the grain shielding potential can be safely ignored for typical grain sizes relevant to complex plasmas.Comment: 25 pages, 3 figure

Dispersion and damping of potential surface waves in a degenerate plasma

Potential (electrostatic) surface waves in plasma half-space with degenerate electrons are studied using the quasi-classical mean-field kinetic model. The wave spectrum and the collisionless damping rate are obtained numerically for a wide range of wavelengths. In the limit of long wavelengths, the wave frequency $\omega$ approaches the cold-plasma limit $\omega=\omega_p/\sqrt{2}$ with $\omega_p$ being the plasma frequency, while at short wavelengths, the wave spectrum asymptotically approaches the spectrum of zero-sound mode propagating along the boundary. It is shown that the surface waves in this system remain weakly damped at all wavelengths (in contrast to strongly damped surface waves in Maxwellian electron plasmas), and the damping rate nonmonotonically depends on the wavelength, with the maximum (yet small) damping occuring for surface waves with wavelength of $\approx5\pi\lambda_{F}$, where $\lambda_{F}$ is the Thomas-Fermi length.Comment: 22 pages, 6 figure

Persistent subplasma-frequency kinetic electrostatic electron nonlinear waves

International audienceDriving a one-dimensional collisionless Maxwellian Vlasov plasma with a sufficiently strong longitudinal ponderomotive driver for a sufficiently long time results in a self-sustaining nonsinusoidal wave train with well-trapped electrons even for frequencies well below the plasma frequency, i.e., in the plasma wave spectral gap. Typical phase velocities of these waves are somewhat above the electron thermal velocity. This new nonlinear wave is being termed a kinetic electrostatic electron nonlinear KEEN wave. The drive duration must exceed the bounce period B of the trapped electrons subject to the drive, as calculated from the drive force and the linear plasma response to the drive. For a given wavenumber a wide range of KEEN wave frequencies can be readily excited. The basic KEEN structure is essentially kinetic, with the trapped electron density variation being almost completely shielded by the free electrons, leaving just enough net charge to support the wave

Laying foundations for effective machine learning in law enforcement. Majura – A labelling schema for child exploitation materials

The health impacts of repeated exposure to distressing concepts such as child exploitation materials (CEM, aka ‘child pornography’) have become a major concern to law enforcement agencies and associated entities. Existing methods for ‘flagging’ materials largely rely upon prior knowledge, whilst predictive methods are unreliable, particularly when compared with equivalent tools used for detecting ‘lawful’ pornography. In this paper we detail the design and implementation of a deep-learning based CEM classifier, leveraging existing pornography detection methods to overcome infrastructure and corpora limitations in this field. Specifically, we further existing research through direct access to numerous contemporary, real-world, annotated cases taken from Australian Federal Police holdings, demonstrating the dangers of overfitting due to the influence of individual users’ proclivities. We quantify the performance of skin tone analysis in CEM cases, showing it to be of limited use. We assess the performance of our classifier and show it to be sufficient for use in forensic triage and ‘early warning’ of CEM, but of limited efficacy for categorising against existing scales for measuring child abuse severity. We identify limitations currently faced by researchers and practitioners in this field, whose restricted access to training material is exacerbated by inconsistent and unsuitable annotation schemas. Whilst adequate for their intended use, we show existing schemas to be unsuitable for training machine learning (ML) models, and introduce a new, flexible, objective, and tested annotation schema specifically designed for cross-jurisdictional collaborative use. This work, combined with a world-first ‘illicit data airlock’ project currently under construction, has the potential to bring a ‘ground truth’ dataset and processing facilities to researchers worldwide without compromising quality, safety, ethics and legality