Abstract

Wave particle interactions, an essential aspect of laboratory, terrestrial, and astrophysical plasmas, have been studied for decades by transmitting high power HF radio waves into Earth’s weakly ionized space plasma, to use it as a laboratory without walls. Application to HF electron acceleration remains an active area of research (Gurevich in Usp Fizicheskikh Nauk 177(11):1145–1177, 2007) today. HF electron acceleration studies began when plasma line observations proved (Carlson et al. in J Atmos Terr Phys 44:1089–1100, 1982) that high power HF radio wave-excited processes accelerated electrons not to ~eV, but instead to −100 times thermal energy (10 s of eV), as a consequence of inelastic collision effects on electron transport. Gurevich et al (J Atmos Terr Phys 47:1057–1070, 1985) quantified the theory of this transport effect. Merging experiment with theory in plasma physics and aeronomy, enabled prediction (Carlson in Adv Space Res 13:1015–1024, 1993) of creating artificial ionospheres once ~GW HF effective radiated power could be achieved. Eventual confirmation of this prediction (Pedersen et al. in Geophys Res Lett 36:L18107, 2009; Pedersen et al. in Geophys Res Lett 37:L02106, 2010; Blagoveshchenskaya et al. in Ann Geophys 27:131–145, 2009) sparked renewed interest in optical inversion to estimate electron spectra in terrestrial (Hysell et al. in J Geophys Res Space Phys 119:2038–2045, 2014) and planetary (Simon et al. in Ann Geophys 29:187–195, 2011) atmospheres. Here we present our unpublished optical data, which combined with our modeling, lead to conclusions that should meaningfully improve future estimates of the spectrum of HF accelerated electron fluxes. Photometric imaging data can significantly improve detection of emissions near ionization threshold, and confirm depth of penetration of accelerated electrons many km below the excitation altitude. Comparing observed to modeled emission altitude shows future experiments need electron density profiles to derive more accurate HF electron flux spectra.

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