Ferroelectric and ferroelastic domain walls are 2D topological defects with thicknesses
approaching the unit cell level. When this spatial confinement is combined with observations …

Many qualitative features of the emerging collective dynamics in neuronal networks, such as
correlated activity, stability, response to inputs, and chaotic and regular behavior, can be …

In this work, the computational complexity of a spin-glass three-dimensional (3D) Ising
model (for the lattice size N= lmn, where l, m, n are the numbers of lattice points along three …

Dynamical mean-field theory (DMFT) replaces the many-body dynamical problem with one
for a single degree of freedom in a thermal bath whose features are determined self …

A thermodynamically motivated neural network model is described that self-organizes to
transport charge associated with internal and external potentials while in contact with a …

Optimization or sampling of arbitrary pairwise Ising models, in a quantum annealing protocol
of constrained interaction topology, can be enabled by a minor-embedding procedure. The …

A key question in theoretical neuroscience is the relation between the connectivity structure
and the collective dynamics of a network of neurons. Here we study the connectivity …

Various problems in practice are mathematically described by a regression model in which
the linear relation between possibly noisy outputs and their corresponding inputs is to be …

The Potts model is a generalization of the Ising model with Q> 2 components. In the fully
connected ferromagnetic Potts model, a first-order phase transition is induced by varying …

The research considers the minimization of spin glass energy via learning and evolution.
The Sherrington-Kirkpatrick spin-glass model is used. A population of autonomous agents is …