We investigate the proximity spin-orbit and exchange couplings in ABA ABC trilayer graphene encapsulated within monolayers of semiconducting transition-metal dichalcogenides ferromagnetic semiconductor Cr$_2$Ge$_2$Te$_6$. Employing first-principles calculations we obtain electronic structures multilayer stacks extract relevant proximity-induced orbital spin interaction parameters by fitting low...

Obtaining ground states of Hamiltonians is important in the condensed matter physics and quantum chemistry. The interaction typically contain not only diagonal but also off-diagonal elements. Although annealing provides a way to obtain state Hamiltonian, we can use Hamiltonian with Ising by using currently available commercial devices. In this work, propose for XXZ model, which contains both en...

Three-dimensional spin models of the Ising and XY universality classes are studied by a combination of high-temperature expansions and Monte Carlo simulations applied to improved Hamiltonians. The critical exponents and the critical equation of state are determined to very high precision.

We study descendants of inhomogeneous vertex models with boundary reflections when the spin-spin scattering is assumed to be quasi–classical. This corresponds to consider certain power expansion of the boundary-Yang-Baxter equation (or reflection equation). As final product, integrable su(2)-spin chains interacting with a long range with XXZ anisotropy are obtained. The spin-spin couplings are ...

The main point of this paper is that stochastic neural networks have a mathematical structure that corresponds quite closely with that of quantum field theory. Neural network Liouvillians and Lagrangians can be derived, just as can spin Hamiltonians and Lagrangians in QFf. It remains to show the efficacy of such a description.