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physics.chem-ph2026
A strategic roadmap for an atomistic machine-learning ecosystem
Jörg Behler, Michele Ceriotti, Cecilia Clementi +47
Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of matter is particularly widespre…
physics.chem-ph2026
Variational low-energy subspaces for chemically accurate excited states
Clemens Giuliani, Rocco Martinazzo, Giuseppe Carleo +1
Accurate electronic excited states are essential for photochemistry, spectroscopy and non-adiabatic molecular dynamics, but high-level calculations often scale steeply and require…