946 research outputs found
Accuracy of the Explicit Energy-Conserving Particle-in-Cell Method for Under-resolved Simulations of Capacitively Coupled Plasma Discharges
The traditional explicit electrostatic momentum-conserving Particle-in-cell
algorithm requires strict resolution of the electron Debye length to deliver
numerical accuracy. The explicit electrostatic energy-conserving
Particle-in-Cell algorithm alleviates this constraint with minimal modification
to the traditional algorithm, retaining its simplicity and ease of
parallelization and acceleration on modern supercomputing architectures. In
this article we apply the algorithm to model a one-dimensional radio-frequency
capacitively coupled plasma discharge relevant to industrial applications. The
energy-conserving approach closely matches the results from the
momentum-conserving algorithm and retains accuracy even for cell sizes up to 8x
the electron Debye length. For even larger cells the algorithm loses accuracy
due to poor resolution of steep gradients in the radio-frequency sheath. This
can be amended by introducing a non-uniform grid, which allows for accurate
simulations with 9.4x fewer cells than the fully resolved case, an improvement
that will be compounded in higher-dimensional simulations. We therefore
consider the explicit energy-conserving algorithm as a promising approach to
significantly reduce the computational cost of full-scale device simulations
and a pathway to delivering kinetic simulation capabilities of use to industry
Deep learning enabled laser speckle wavemeter with a high dynamic range
Funding: This work was supported by a Medical Research Scotland PhD studentship PhD 873-2015 awarded to R.K.G, and grant funding from Leverhulme Trust (RPG-2017-197) and UK Engineering and Physical Sciences Research Council (grant EP/P030017/1).The speckle pattern produced when a laser is scattered by a disordered medium has recently been shown to give a surprisingly accurate or broadband measurement of wavelength. Here it is shown that deep learning is an ideal approach to analyse wavelength variations using a speckle wavemeter due to its ability to identify trends and overcome low signal to noise ratio in complex datasets. This combination enables wavelength measurement at high precision over a broad operating range in a single step, with a remarkable capability to reject instrumental and environmental noise, which has not been possible with previous approaches. It is demonstrated that the noise rejection capabilities of deep learning provide attometre-scale wavelength precision over an operating range from 488 nm to 976 nm. This dynamic range is six orders of magnitude beyond the state of the art.Publisher PDFPeer reviewe
Fine- and hyperfine-structure effects in molecular photoionization. I. General theory and direct photoionization
We develop a model for predicting fine- and hyperfine intensities in the direct photoionization of molecules based on the separability of electron and nuclear spin states from vibrational-electronic states. Using spherical tensor algebra, we derive highly symmetrized forms of the squared photoionization dipole matrix elements from which we derive the salient selection and propensity rules for fine- and hyperfine resolved photoionizing transitions. Our theoretical results are validated by the analysis of the fine-structure resolved photoelectron spectrum of O2 reported by Palm and Merkt [Phys. Rev. Lett. 81, 1385 (1998)] and are used for predicting hyperfine populations of molecular ions produced by photoionization
Vibrationally induced inversion of photoelectron forward-backward asymmetry in chiral molecule photoionization by circularly polarized light
Electron–nuclei coupling accompanying excitation and relaxation processes is a fascinating phenomenon in molecular dynamics. A striking and unexpected example of such coupling is presented here in the context of photoelectron circular dichroism measurements on randomly oriented, chiral methyloxirane molecules, unaffected by any continuum resonance. Here, we report that the forward-backward asymmetry in the electron angular distribution, with respect to the photon axis, which is associated with photoelectron circular dichroism can surprisingly reverse direction according to the ion vibrational mode excited. This vibrational dependence represents a clear breakdown of the usual Franck–Condon assumption, ascribed to the enhanced sensitivity of photoelectron circular dichroism (compared with other observables like cross-sections or the conventional anisotropy parameter-β) to the scattering phase off the chiral molecular potential, inducing a dependence on the nuclear geometry sampled in the photoionization process. Important consequences for the interpretation of such dichroism measurements within analytical contexts are discussed
Effect of Field-Line Curvature on the Ionospheric Accessibility of Relativistic Electron Beam Experiments
Magnetosphere-ionosphere coupling is a particularly important process that regulates and controls magnetospheric dynamics such as storms and substorms. However, in order to understand magnetosphere-ionosphere coupling it is necessary to understand how regions of the magnetosphere are connected to the ionosphere. It has been proposed that this connection may be established by firing electron beams from satellites that can reach an ionospheric footpoint creating detectable emissions. This type of experiment would greatly aid in identifying the relationship between convection processes in the magnetotail and the ionosphere and how the plasma sheet current layer evolves during the growth phase preceding substorms. For practical purposes, the use of relativistic electron beams with kinetic energy on the order of 1 MeV would be ideal for detectability. However, Porazik et al. (2014) has shown that, for relativistic particles, higher order terms of the magnetic moment are necessary for consideration of the ionospheric accessibility of the beams. These higher order terms are related to gradients and curvature in the magnetic field and are typically unimportant unless the beam is injected along the magnetic field direction, such that the zero order magnetic moment is small. In this article, we address two important consequences related to these higher order terms. First, we investigate the consequences for satellites positioned in regions subject to magnetotail stretching and demonstrate systematically how curvature affects accessibility. We find that curvature can reduce accessibility for beams injected from the current sheet, but can increase accessibility for beams injected just above the current sheet. Second, we investigate how detectability of ionospheric precipitation of variable energy field-aligned electron beams could be used as a constraint on field-line curvature, which would be valuable for field-line reconstruction and/or stability analysis
Method for Approximating Field-Line Curves Using Ionospheric Observations of Energy-Variable Electron Beams Launched From Satellites
Using electron beam accelerators attached to satellites in Earth orbit, it may be possible to measure arc length and curvature of field-lines in the inner magnetosphere if the accelerator is designed with the capability to vary the beam energy. In combination with additional information, these measurements would be very useful in modeling the magnetic field of the inner magnetosphere. For this purpose, a three step data assimilation modeling approach is discussed. The first step in the procedure would be to use prior information to obtain an initial forecast of the inner magnetosphere. Then, a family of curves would be defined that satisfies the observed geometric attributes measured by the experiments, and the prior forecast would then be used to optimize the curve with respect to the allowed degrees of freedom. Finally, this approximation of the field-line would be used to improve the initial forecast of the inner magnetosphere, resulting in a description of the system that is optimally consistent with both the prior information and the measured curvature and arc length. This article details the method by which a family of possible approximations of the field-line may be defined via a numerical procedure, which is central to the three step approach. This method serves effectively as a pre-conditioner for parameter estimation problems using field-line curvature and arc length measurements in combination with other measurements
Direct Implicit and Explicit Energy-Conserving Particle-in-Cell Methods for Modeling of Capacitively-Coupled Plasma Devices
Achieving entire large scale kinetic modelling is a crucial task for the
development and optimization of modern plasma devices. With the trend of
decreasing pressure in applications such as plasma etching, kinetic simulations
are necessary to self-consistently capture the particle dynamics. The standard,
explicit, electrostatic, momentum-conserving Particle-In-Cell method suffers
from tight stability constraints to resolve the electron plasma length (i.e.
Debye length) and time scales (i.e. plasma period). This results in very high
computational cost, making this technique generally prohibitive for the large
volume entire device modeling (EDM). We explore the Direct Implicit algorithm
and the explicit Energy Conserving algorithm as alternatives to the standard
approach, which can reduce computational cost with minimal (or controllable)
impact on results. These algorithms are implemented into the well-tested
EDIPIC-2D and LTP-PIC codes, and their performance is evaluated by testing on a
2D capacitively coupled plasma discharge scenario. The investigation revels
that both approaches enable the utilization of cell sizes larger than the Debye
length, resulting in reduced runtime, while incurring only a minor compromise
in accuracy. The methods also allow for time steps larger than the electron
plasma period, however this can lead to numerical heating or cooling. The study
further demonstrates that by appropriately adjusting the ratio of cell size to
time step, it is possible to mitigate this effect to acceptable level
Numerical thermalization in 2D PIC simulations: Practical estimates for low temperature plasma simulations
The process of numerical thermalization in particle-in-cell (PIC) simulations
has been studied extensively. It is analogous to Coulomb collisions in real
plasmas, causing particle velocity distributions (VDFs) to evolve towards a
Maxwellian as macroparticles experience polarization drag and resonantly
interact with the fluctuation spectrum. This paper presents a practical
tutorial on the effects of numerical thermalization in 2D PIC applications.
Scenarios of interest include simulations which must be run for many thousands
of plasma periods and contain a population of cold electrons that leave the
simulation space very slowly. This is particularly relevant to many low
temperature plasma discharges and materials processing applications. We present
numerical drag and diffusion coefficients and their associated timescales for a
variety of grid resolutions, discussing the circumstances under which the
electron VDF is modified by numerical thermalization. Though the effects
described here have been known for many decades, direct comparison of
analytically derived, velocity-dependent numerical relaxation timescales to
those of other relevant processes has not often been applied in practice due to
complications that arise in calculating thermalization rates in 1D simulations.
Using these comparisons, we estimate the impact of numerical thermalization in
several example low temperature plasma applications including capacitively
coupled plasma (CCP) discharges, inductively coupled plasma (ICP) discharges,
beam plasmas, and hollow cathode discharges. Finally, we discuss possible
strategies for mitigating numerical relaxation effects in 2D PIC simulations
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