no code implementations • 1 Nov 2023 • Edoardo Cignoni, Divya Suman, Jigyasa Nigam, Lorenzo Cupellini, Benedetta Mennucci, Michele Ceriotti
Data-driven techniques are increasingly used to replace electronic-structure calculations of matter.
no code implementations • 28 Feb 2023 • Jigyasa Nigam, Sergey N. Pozdnyakov, Kevin K. Huguenin-Dumittan, Michele Ceriotti
In this paper, we address the challenge of obtaining a comprehensive and symmetric representation of point particle groups, such as atoms in a molecule, which is crucial in physics and theoretical chemistry.
no code implementations • 3 Feb 2022 • Jigyasa Nigam, Sergey Pozdnyakov, Guillaume Fraux, Michele Ceriotti
Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents.
no code implementations • 24 Sep 2021 • Jigyasa Nigam, Michael Willatt, Michele Ceriotti
Symmetry considerations are at the core of the major frameworks used to provide an effective mathematical representation of atomic configurations that is then used in machine-learning models to predict the properties associated with each structure.
no code implementations • 27 Aug 2020 • Andrea Grisafi, Jigyasa Nigam, Michele Ceriotti
Electronic nearsightedness is one of the fundamental principles governing the behavior of condensed matter and supporting its description in terms of local entities such as chemical bonds.
no code implementations • 7 Jul 2020 • Jigyasa Nigam, Sergey Pozdnyakov, Michele Ceriotti
While it has become clear that low-order density correlations do not provide a complete representation of an atomic environment, the exponential increase in the number of possible $N$-body invariants makes it difficult to design a concise and effective representation.
Chemical Physics