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Abstract A workshop on The Next Generation Gamma-Ray Source sponsored by the Office of Nuclear Physics at the Department of Energy, was held November 17-19, 2016 in Bethesda, Maryland. The goals of the workshop were to identify basic and applied research opportunities at the frontiers of nuclear physics that would be made possible by the beam capabilities of an advanced laser Compton beam facility. To anchor the scientific vision to realistically achievable beam specifications using proven technologies, the workshop brought together experts in the fields of electron accelerators, lasers, and optics to examine the technical options for achieving the beam specifications required by the most compelling parts of the proposed research programs. An international assembly of participants included current and prospective γ -ray beam users, accelerator and light-source physicists, and federal agency program managers. Sessions were organized to foster interactions between the beam users and facility developers, allowing for information sharing and mutual feedback between the two groups. The workshop findings and recommendations are summarized in this whitepaper. 

A bstract We report on a measurement of the $$ {\Lambda}_c^{+} $$ Λ c + to D 0 production ratio in peripheral PbPb collisions at $$ \sqrt{s_{\textrm{NN}}} $$ s NN = 5 . 02 TeV with the LHCb detector in the forward rapidity region 2 < y < 4 . 5. The $$ {\Lambda}_c^{+} $$ Λ c + ( D 0 ) hadrons are reconstructed via the decay channel $$ {\Lambda}_c^{+} $$ Λ c + → pK − π + ( D 0 → K − π + ) for 2 < p T < 8 GeV/ c and in the centrality range of about 65–90%. The results show no significant dependence on p T , y or the mean number of participating nucleons. They are also consistent with similar measurements obtained by the LHCb collaboration in pPb and Pbp collisions at $$ \sqrt{s_{\textrm{NN}}} $$ s NN = 5 . 02 TeV. The data agree well with predictions from PYTHIA in pp collisions at $$ \sqrt{s} $$ s = 5 TeV but are in tension with predictions of the Statistical Hadronization model.