30 citations · 77 across the 12 of their papers we have counts for
13 papers
Overcoming the limitations of body-ordered potentials for atomistic machine learning
Filippo Bigi, Michelangelo Domina, Maximilian Lloyd Ach +5
Machine-learning interatomic potentials have become indispensable tools in atomistic simulations. The most popular models rely heavily on physical priors, such as locality, smoothn…
Using large language models to probe the limits of atom-centered structural descriptors
Michelangelo Domina, Michele Ceriotti
Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modeling. A powerful and widely-used…
How unconstrained machine-learning models learn physical symmetries
Michelangelo Domina, Joseph William Abbott, Paolo Pegolo +2
The requirement of generating predictions that exactly fulfill the fundamental symmetry of the corresponding physical quantities has profoundly shaped the development of machine-le…
Resolving the Body-Order Paradox of Machine Learning Interatomic Potentials
Sanggyu Chong, Tong Jiang, Michelangelo Domina +4
In many cases, the predictions of machine learning interatomic potentials (MLIPs) can be interpreted as a sum of body-ordered contributions, which is explicit when the model is dir…
Representing spherical tensors with scalar-based machine-learning models
Michelangelo Domina, Filippo Bigi, Paolo Pegolo +1
Rotational symmetry plays a central role in physics, providing an elegant framework to describe how the properties of 3D objects -- from atoms to the macroscopic scale -- transform…
A general formalism for machine-learning models based on multipolar-spherical harmonics
Michelangelo Domina, Stefano Sanvito
The formulation of descriptors of the local chemical environment, enabling the construction of machine-learning models, is usually obtained by studying the properties of the expans…
Covariant Jacobi-Legendre expansion for total energy calculations within the projector-augmented-wave formalism
Bruno Focassio, Michelangelo Domina, Urvesh Patil +2
Machine-learning models can be trained to predict the converged electron charge density of a density functional theory (DFT) calculation. In general, the value of the density at a…
Linear Jacobi-Legendre expansion of the charge density for machine learning-accelerated electronic structure calculations
Bruno Focassio, Michelangelo Domina, Urvesh Patil +2
Kohn-Sham density functional theory (KS-DFT) is a powerful method to obtain key materials' properties, but the iterative solution of the KS equations is a numerically intensive tas…
Cluster expansion constructed over Jacobi-Legendre polynomials for accurate force fields
Michelangelo Domina, Urvesh Patil, Matteo Cobelli +1
We introduce a compact cluster expansion method, constructed over Jacobi and Legendre polynomials, to generate highly accurate and flexible machine-learning force fields. The const…
A spectral-neighbour representation for vector fields: machine-learning potentials including spin
Michelangelo Domina, Matteo Cobelli, Stefano Sanvito
We introduce a translational and rotational invariant local representation for vector fields, which can be employed in the construction of machine-learning energy models of solids…
Collective spontaneous emission of two entangled atoms near an oscillating mirror
Marta Reina, Michelangelo Domina, Alessandro Ferreri +4
We consider the cooperative spontaneous emission of a system of two identical atoms, interacting with the electromagnetic field in the vacuum state and in the presence of an oscill…
Spontaneous emission of an atom near an oscillating mirror
Alessandro Ferreri, Michelangelo Domina, Lucia Rizzuto +1
We investigate the spontaneous emission of one atom placed near an oscillating reflecting plate. We consider the atom modeled as a two-level system, interacting with the quantum el…
Analysis of high-harmonic generation in terms of complex Floquet spectral analysis
Hidemasa Yamane, Satoshi Tanaka, Michelangelo Domina +2
Recent developments on intense laser sources is opening a new field of optical sciences. An intense coherent light beam strongly interacting with the matter causes a coherent motio…