Ultra-cold Fermi gases exhibit a rich array of quantum mechanical properties, including the
transition from a fermionic superfluid Bardeen-Cooper-Schrieffer (BCS) state to a bosonic …

The Variational Monte Carlo (VMC) method has recently seen important advances through
the use of neural network quantum states. While more and more sophisticated ansatze have …

We apply a variational Ansatz based on neural networks to the problem of spin-$1/2$
fermions in a harmonic trap interacting through a short distance potential. We showed that …

We present an overview of the method of Neural Quantum States applied to the many-body
problem of atomic nuclei. Through the lens of group representation theory, we focus on the …

We study the ground-state properties of fully-polarized, trapped, one-dimensional fermions
interacting through a Gaussian potential using a variational wavefunction represented by an …

We study the ground-state entanglement between two atoms in a two-dimensional isotropic
harmonic trap. We consider a finite-range soft-core interaction that can be applied to …

In this work we compute the ground-state properties of one-dimensional systems composed
of fully-polarized fermions interacting through an attractive Gaussian potential. If the …

In this work we study the ground-state properties of three different one-dimensional systems
of N identical, non-interacting, spinless fermions trapped in a potential well. We consider a …

In this work, I have used Artificial Neural Networks to find the ground state of the 2D quantum
harmonic oscillator. I have trained networks in two different ways: by using a mesh of points …