A microscopic HFB-FBD framework extracts fusion parameters self-consistently from potential energy surfaces for cold fusion reactions, reproducing the experimental evaporation-residue cross section for 48Ca+208Pb and showing an exponential drop in compound-nucleus formation probability with Z.
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XGBoost residual learning corrects ETFSI fission barrier heights to experimental values with 0.3-1.2 MeV RMSE and identifies binding energies and proton number as key drivers for inner versus outer barriers.
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New perspective on cold fusion reactions: A microscopic description
A microscopic HFB-FBD framework extracts fusion parameters self-consistently from potential energy surfaces for cold fusion reactions, reproducing the experimental evaporation-residue cross section for 48Ca+208Pb and showing an exponential drop in compound-nucleus formation probability with Z.
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Machine Learning Insights into Discrepancies Between Theoretical and Experimental Fission Barrier Heights
XGBoost residual learning corrects ETFSI fission barrier heights to experimental values with 0.3-1.2 MeV RMSE and identifies binding energies and proton number as key drivers for inner versus outer barriers.