Related papers: Restrictions on modeling spin injection by resisto…
The spectrum of integrable spin chains are shown to be independent of the ordering of their spins. As an application we introduce defects (local spin inhomogeneities in homogenous chains) in two-boundary spin systems and, by changing their…
Strongly correlated materials are expected to feature unconventional transport properties, such that charge, spin, and heat conduction are potentially independent probes of the dynamics. In contrast to charge transport, the measurement of…
The emergence of congestion is a critical phenomenon in transport systems. Transport is organized along pathways abstracted by links, which connect different nodes as regions to form the network. The modeling of traffic has so far mainly…
The internal representations learned by deep networks are often sensitive to architecture-specific choices, raising questions about the stability, alignment, and transferability of learned structure across models. In this paper, we…
Torsion propagation and torsion-spin coupling are studied in the perspective of the Velo-Zwanziger method of analysis; specifically, we write the most extensive dynamics of the torsion tensor and the most exhaustive coupling that is…
We study the charge conductivity in one-dimensional prototype models of interacting particles, such as the Hubbard and the t-V spinless fermion model, when coupled to some external baths injecting and extracting particles at the boundaries.…
Spin transport in magnetic tunnel junctions in the presence of spin diffusion is considered theoretically. Combining ballistic tunneling across the barrier and diffusive transport in the electrodes, we solve the spin dynamics equation in…
Employing first-principles calculations, we investigate efficiency of spin injection from a ferromagnetic (FM) electrode (Ni) into graphene and possible enhancement by using a barrier between the electrode and graphene. Three types of…
The purpose of this article is to explore the properties of integrable, purely transmitting, defects placed at the junctions of several one-dimensional domains within a network. The defect sewing conditions turn out to be quite restrictive…
Complex networks are frequently employed to model physical or virtual complex systems. When certain entities exist across multiple systems simultaneously, unveiling their corresponding relationships across the networks becomes crucial. This…
We investigate charge transport in two-dimensional ferromagnet/feromagnet junction on a topological insulator. The conductance across the interface depends sensitively on the directions of the magnetizations of the two ferromagnets, showing…
The understanding and calculation of spin transport are essential elements for the development of spintronics devices. Here, we propose a simple method to calculate analytically the spin accumulations, spin currents and magnetoresistances…
We study electronic transport in junctions consisting of a superconductor electrode and two ferromagnet (F) leads in which crossed Andreev reflections (CAR) and elastic cotunnelings are accommodated. We model the system using an extended…
We have calculated the spin-polarization effects of a current in a two dimensional electron gas which is contacted by two ferromagnetic metals. In the purely diffusive regime, the current may indeed be spin-polarized. However, for a typical…
Several recent experiments in biology study systems composed of several interacting elements, for example neuron networks. Normally, measurements describe only the collective behavior of the system, even if in most cases we would like to…
We review recent advances in experimental and theoretical understanding of spin transport in strongly interacting Fermi gases. The central new phenomenon is the observation of a lower bound on the (bare) spin diffusivity in the strongly…
In this paper, the transport phenomena of synaptic electric impulses are considered. The FitzHugh--Nagumo and FitzHugh--Rinzel models appear mathematically appropriate for evaluating these scientific issues. Moreover, applications of such…
Physics-Informed Neural Networks (PINN) are a machine learning tool that can be used to solve direct and inverse problems related to models described by Partial Differential Equations. This paper proposes an adaptive inverse PINN applied to…
We theoretically study the transport properties of a supramolecular spin valve, consisting of a carbon nanotube with two attached magnetic molecules, weakly coupled to metallic contacts. The emphasis is put on analyzing the change of the…
The dynamics of a single spin embedded in the tunnel junction (quantum point contact) between ferromagnets is addressed. Using the Keldysh technique, we derive a quantum Langevin equation. As a consequence of the spin-polarization in the…