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Langmuir probes have been extensively studied theoretically, and used experimentally to infer plasma parameters, such as density and temperature, in laboratory and space plasma. Because of their small size and relative simplicity, these probes are used to diagnose plasma in most laboratory experiments and many space missions. Despite the apparent simplicity, however, the task of inferring accurate physical parameters with Langmuir probes remains notoriously challenging. Aside from technical aspects related for example, to calibration and surface condition, one difficulty is that the inference of plasma parameters from probe measurements requires the solution of a complex inverse problem. The direct problem in which a characteristic; that is, current as a function of bias voltage, is calculated for known plasma conditions, is now relatively easy to solve numerically, by accounting for the relevant physical processes and measurement conditions. The inverse problem however, is significantly more daunting, owing the large computation time required to carry out simulations, and the several iterations required to interpret a single characteristic. This is why the inference of plasma parameters from Langmuir probe characteristics has so far relied almost exclusively on analytic models, leading to fast and simple algorithms capable producing answers in near-real time. In order to be tractable analytically, however, theoretical interpretive models cannot account for several of the conditions under which measurements are made, and they must rely on assumptions that are seldom fully satisfied in an actual experimental setup. This in turn can lead to significant uncertainties in the inferred density or temperature. In our approach we use three-dimensional kinetic simulations to compute probe characteristics for a set of representative plasma parameters, while accounting for more realistic geometry than possible analytically. Solution libraries, or in machine learning parlance training data sets, are then constructed from which empirical analytic inversions algorithms can be derived. The physics of current collection by electric probes immersed in plasma was described in seminal articles by Mott-Smith and Langmuir (1926), and Tonks and Langmuir (1929) nearly a century ago. These papers defined the basis of the "Orbital Motion" theory for spherical and cylindrical probes, now referred to as "Orbital Motion Limited" or OML theory, which has since been used to infer plasma density and temperature in many laboratory, and more recently, in space plasma experiments. Several assumptions are made in the OML theory, in order to obtain analytic solutions, including (i) a spatially uniform plasma background, (ii) negligible collisions and magnetic field, (iii) probe radii much smaller than the Debye length, and (iv) for a cylindrical probe, a length much larger than the Debye length in order for end effects to be Abstract A novel approach is presented to infer plasma parameters from Langmuir probe measurements. Three-dimensional kinetic...

The front plates and embedded particle sensor shells that are part of the Electric Field Instrument (EFI) on the Swarm satellites have recently been used as planar Langmuir probes, as an additional diagnostic tool to infer environment parameters. The interpretation of measured currents in terms of the plasma density or incoming flow speed, however, requires a knowledge of the front plate effective cross section A ef f. Measurements made under various space plasma conditions have led to the conclusion that this cross section is generally larger than the known geometrical cross section Ageo. Interpretations of measurements have thus been made using fixed relative enhancements of Ageo ranging from 8 to 17%. In this paper results from kinetic simulations are presented, from which the effective cross section can be determined over a range of plasma parameters. These are used to shed light on the physical mechanisms responsible for this enhancement, and construct an empirical fit to the relative enhancement δ, where A ef f = Ageo(1 + δ), and in turn enable improvements in the accuracy of inferred plasma parameters.

The Compact Ion Mass Spectrometer (CIMS) is a highly compact ion mass spectrometer capable of high-mass resolution for low-energy space plasma. CIMS is capable of measuring flux, energy, and mass of ions providing unique measurements of the ionospheric outflow and cold plasma in the magnetosphere. Measurements of the ionospheric outflow and cold-magnetospheric ion population will provide the necessary initial conditions of the ion populations that drive some magnetosphere-ionosphere (MI) coupling processes along with magnetospheric ion composition and dynamics. Simultaneous measurements of the cold and hot magnetospheric ion composition in the reconnection region at the magnetotail would provide clues for the outflowing ions as they journey through the plasmasphere and magnetosphere. These data are critical to advancing our current understanding of MI coupling and are required to answer the long-standing questions regarding ionospheric outflow, the source of magnetospheric mass loading, and the subsequent impact on magnetic reconnection. The CIMS utilizes a laminated collimator to define the field-of-view, a laminated electrostatic analyzer to selectively filter ions based on energy-per-charge, a magnetic sector analyzer to separate ions by mass-per-charge, and a microchannel plate with a position sensitive cross-delay anode assembly to detect the location of the ions on the detector plane. This ion mass spectrometer is a simple, compact, and robust instrument ideal for obtaining low-energy (0.1 eV to 500 eV) ion composition measurements of ionospheric and cold magnetospheric ions. The instrument design has significant mass and volume savings when compared to current state-of-the-art ion mass spectrometers and has the additional advantage of being able to simultaneously measure multiple ion species at given energy-per-charge at 100% duty cycle, thus providing a full energy spectra for individual ion species. The concept and operation are intrinsically simple, and enable ultrafast (<0.1 s) measurement of plasma ion composition to provide an improved understanding of the physical processes that drive the complex ion dynamics in the magnetosphere.