A new way to unravel the ¹²C(α,γ)¹⁶O cross section components using neural networks

The ¹²C(α,γ)¹⁶O reaction rate plays a crucial role in determining the ¹²C to ¹⁶O abundance ratio in various stellar nucleosynthesis scenarios. Measuring the cross section for this reaction at stellar energies is challenging because of its extremely small size, estimated to be about 10⁻¹⁷ b at E_c.m. = 300 keV. To overcome this limitation, R-matrix calculations are used to extrapolate the data to lower energies. These calculations rely on a comprehensive understanding of each contribution to the cross section. The dominant contributions to the cross section at stellar energies arise from the electric dipole (E1) and electric quadrupole (E2) transitions to the ground state of ¹⁶O, accompanied by a non-negligible cascade contribution. Traditionally, these contributions have been separated using the γ-ray angular distribution. In this work, we propose a novel technique that uses the energy distribution of the ¹⁶O recoils at the focal plane. The analysis utilizes a neural network trained on a detailed Monte Carlo simulation of the transport of the recoils through the recoils mass separator ERNA. This approach will enable us to simultaneously determine all three contributions achieving systematic uncertainties better than 10% for the ground state contributions and better than 14% for the cascade contribution in the energy region from E_c.m. = 1 to 2.2 MeV. By employing this new technique, we aim to improve the accuracy in determining the cross section of the ¹²C(α,γ)¹⁶O reaction at astrophysical energies.