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Electrons in earth's magnetotail are energized significantly both in the form of heating and in the form of acceleration to non-thermal energies. While magnetic reconnection is considered to play an important role in this energization, it still remains unclear how electrons are energized and how energy is partitioned between thermal and non-thermal components. Here, we show, based on in situ observations by NASA's magnetospheric multiscale mission combined with multi-component spectral fitting methods, that the average electron energy [Formula: see text] (or equivalently temperature) is substantially higher when the locally averaged electric field magnitude [Formula: see text] is also higher. While this result is consistent with the classification of “plasma-sheet” and “tail-lobe” reconnection during which reconnection is considered to occur on closed and open magnetic field lines, respectively, it further suggests that a stochastic Fermi acceleration in 3D, reconnection-driven turbulence is essential for the production and confinement of energetic electrons in the reconnection region. The puzzle is that the non-thermal power-law component can be quite small even when the electric field is large and the bulk population is significantly heated. The fraction of non-thermal electron energies varies from sample to sample between ∼20% and ∼60%, regardless of the electric field magnitude. Interestingly, these values of non-thermal fractions are similar to those obtained for the above-the-looptop hard x-ray coronal sources for solar flares. 

This Letter reports the first measurement of the oscillation amplitude and frequency of reactor antineutrinos at Daya Bay via neutron capture on hydrogen using 1958 days of data. With over 3.6 million signal candidates, an optimized candidate selection, improved treatment of backgrounds and efficiencies, refined energy calibration, and an energy response model for the capture-on-hydrogen sensitive region, the relative ${\overline{\nu }}_e$rates and energy spectra variation among the near and far detectors gives ${\sin }^{2}2{\theta }_{13}=0.0759_{-0.0049}^{+0.0050}$and $\mathrm{\Delta }{m}_{32}^2=\left(2.72_{-0.15}^{+0.14}\right)\times {10}^{-3}{\mathrm{eV}}^2$assuming the normal neutrino mass ordering, and $\mathrm{\Delta }{m}_{32}^2=(-2.83_{-0.14}^{+0.15})\times {10}^{-3}{\mathrm{eV}}^2$for the inverted neutrino mass ordering. This estimate of ${\sin }^{2}2{\theta }_{13}$is consistent with and essentially independent from the one obtained using the capture-on-gadolinium sample at Daya Bay. The combination of these two results yields ${\sin }^{2}2{\theta }_{13}=0.0833\pm 0.0022$, which represents an 8% relative improvement in precision regarding the Daya Bay full 3158-day capture-on-gadolinium result. Published by the American Physical Society2024 

Abstract The prediction of reactor antineutrino spectra will play a crucial role as reactor experiments enter the precision era. The positron energy spectrum of 3.5 million antineutrino inverse beta decay reactions observed by the Daya Bay experiment, in combination with the fission rates of fissile isotopes in the reactor, is used to extract the positron energy spectra resulting from the fission of specific isotopes. This information can be used to produce a precise, data-based prediction of the antineutrino energy spectrum in other reactor antineutrino experiments with different fission fractions than Daya Bay. The positron energy spectra are unfolded to obtain the antineutrino energy spectra by removing the contribution from detector response with the Wiener-SVD unfolding method. Consistent results are obtained with other unfolding methods. A technique to construct a data-based prediction of the reactor antineutrino energy spectrum is proposed and investigated. Given the reactor fission fractions, the technique can predict the energy spectrum to a 2% precision. In addition, we illustrate how to perform a rigorous comparison between the unfolded antineutrino spectrum and a theoretical model prediction that avoids the input model bias of the unfolding method.