Exploring Nuclear Structure with Machine Learning and Quantum Mechanics
Delve into the world of ab initio nuclear structure through the lens of machine learning and quantum mechanics. Discover the power of neural networks in approximating functions, live neural network training, symmetries in physical properties, and the role of group theory in understanding atomic nucl
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Advanced Studies on Nuclear Matter Using Green's Functions Approach
Francesco Marino presents research on the Green's functions approach for homogeneous nuclear matter at the 10th International Conference on Quarks and Nuclear Physics. The ab initio approach in nuclear theory, self-consistent Green's functions, and algebraic diagrammatic construction are explored. P
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Understanding Electron-Phonon Interactions in Iron-Based Superconductors
This discussion explores the effects of electron-phonon interactions on orbital fluctuations in iron-based superconductors. Topics covered include ab initio downfolding for electron-phonon coupled systems, evaluation methods such as Constrained Random Phase Approximation (cRPA), Constrained Density-
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