Machine Learning Techniques for Solving Quantum Many-Body Problems (QuanticLearn)

Contributions to international conferences

• "The R-matrix formalism for two-particle scattering problems", D.V. Anghel, A.T. Preda, G.A.Nemnes, IC-MSQUARE 2021
• "Mapping energy spectra of Coulomb interacting bi-particle systems using multi-target regression methods", G.A. Nemnes, T.L. Mitran, A.T. Preda, D.V. Anghel, I. Ghiu, V. Baran, M. Marciu, A. Manolescu, IC-MSQUARE 2021
• "Machine learning techniques applied to many-particle states in quantum dot systems", A.T. Preda et al., IBWAP 2022.
• "Emulating superconducting pairing correlations in finite systems", V.V. Baran et al., IC-MSQUARE 2022
• "Tuning electronic band structure properties in Lieb-like lattices", A.T. Preda et al., Northern Lights Conference 2022
• "Predicting the topology of charge density maps in 2D nanostructures with machine learning techniques", A.T. Preda, C.A. Pantis-Simut, N. Filipoiu, L. Ion, A. Manolescu, G.A. Nemnes, DPG Spring Meeting 28-30 Martie 2023
• "The design of a probabilistic quantum sorter in the R-matrix formalism", A.T. Preda, C.A. Pantis-Simut, I. Ghiu, G.A. Nemnes, IBWAP 11-14 Iulie 2023