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We report a precision measurement of the parity-violating asymmetry APV in the elastic scattering of longitudinally polarized electrons from 208Pb. We measure APV=550±16(stat)±8(syst) parts per billion, leading to an extraction of the neutral weak form factor FW(Q2=0.00616  GeV2)=0.368±0.013. Combined with our previous measurement, the extracted neutron skin thickness is Rn−Rp=0.283±0.071  fm. The result also yields the first significant direct measurement of the interior weak density of 208Pb: ρ0W=−0.0796±0.0036(exp)±0.0013(theo)  fm−3 leading to the interior baryon density ρ0b=0.1480±0.0036(exp)±0.0013(theo)  fm−3. The measurement accurately constrains the density dependence of the symmetry energy of nuclear matter near saturation density, with implications for the size and composition of neutron stars. 

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.