On the origin of magnetic anisotropy in two dimensional CrI3_3

The observation of ferromagnetic order in a monolayer of CrI$_3$ has been recently reported, with a Curie temperature of 45 Kelvin and off-plane easy axis. Here we study the origin of magnetic anisotropy, a necessary ingredient to have magnetic order in two dimensions, combining two levels of modeling, density functional calculations and spin model Hamiltonians. We find two different contributions to the magnetic anisotropy of the material, both favoring off-plane magnetization and contributing to open a gap in the spin wave spectrum. First, ferromagnetic super-exchange across the $\simeq$ 90 degree Cr-I-Cr bonds, are anisotropic, due to the spin orbit interaction of the ligand I atoms. Second, a much smaller contribution that comes from the single ion anisotropy of the $S=3/2$ Cr atom. Our results permit to establish the XXZ Hamiltonian, with a very small single ion anisotropy, as the adequate spin model for this system. Using spin wave theory we estimate the Curie temperature and we highlight the essential role played by the gap that magnetic anisotropy induces on the magnon spectrum.Comment: 8 pages, 5 figure

Noncollinear magnetic phases and edge states in graphene quantum Hall bars

Application of a perpendicular magnetic field to charge neutral graphene is expected to result in a variety of broken symmetry phases, including antiferromagnetic, canted and ferromagnetic. All these phases open a gap in bulk but have very different edge states and non-collinear spin order, recently confirmed experimentally. Here we provide an integrated description of both edge and bulk for the various magnetic phases of graphene Hall bars making use of a non-collinear mean field Hubbard model. Our calculations show that, at the edges, the three types of magnetic order are either enhanced (zigzag) or suppressed (armchair). Interestingly, we find that preformed local moments in zigzag edges interact with the quantum Spin Hall like edge states of the ferromagnetic phase and can induce back-scattering.Comment: 5 pages, 4 figure

Single exciton spectroscopy of semimagnetic quantum dots

A photo-excited II-VI semiconductor nanocrystal doped with a few Mn spins is considered. The effects of spin-exciton interactions and the resulting multi-spin correlations on the photoluminescence are calculated by numerical diagonalization of the Hamiltonian, including exchange interaction between electrons, holes and Mn spins, as well as spin-orbit interaction. The results provide a unified description of recent experiments of photoluminesnce of dots with one and many Mn atoms as well as optically induced ferromagnetism in semimagnetic nanocrystals.Comment: 5 pages, 3 figure

Optical control of the spin state of two Mn atoms in a quantum dot

We report on the optical spectroscopy of the spin of two magnetic atoms (Mn) embedded in an individual quantum dot interacting with either a single electron, a single exciton and single trion. As a result of their interaction to a common entity, the Mn spins become correlated. The dynamics of this process is probed by time resolved spectroscopy, that permits to determine the optical orientation time in the range of a few tens of $ns$. In addition, we show that the energy of the collective spin states of the two Mn atoms can be tuned through the optical Stark effect induced by a resonant laser field

Quantum spin Hall phase in multilayer graphene

The so called quantum spin Hall phase is a topologically non trivial insulating phase that is predicted to appear in graphene and graphene-like systems. In this work we address the question of whether this topological property persists in multilayered systems. We consider two situations: purely multilayer graphene and heterostructures where graphene is encapsulated by trivial insulators with a strong spin-orbit coupling. We use a four orbital tight-binding model that includes the full atomic spin-orbit coupling and we calculate the $Z_{2}$ topological invariant of the bulk states as well as the edge states of semi-infinite crystals with armchair termination. For homogeneous multilayers we find that even when the spin-orbit interaction opens a gap for all the possible stackings, only those with odd number of layers host gapless edge states while those with even number of layers are trivial insulators. For the heterostructures where graphene is encapsulated by trivial insulators, it turns out that the interlayer coupling is able to induce a topological gap whose size is controlled by the spin-orbit coupling of the encapsulating materials, indicating that the quantum spin Hall phase can be induced by proximity to trivial insulators.Comment: 7 pages, 6 figure

Electronic Structure of gated graphene and graphene ribbons

We study the electronic structure of gated graphene sheets. We consider both infinite graphene and finite width ribbons. The effect of Coulomb interactions between the electrically injected carriers and the coupling to the external gate are computed self-consistently in the Hartree approximation. We compute the average density of extra carriers, $n_{2D}$, the number of occupied subbands and the density profiles as a function of the gate potential $V_g$. We discuss quantum corrections to the classical capacitance and we calculate the threshold $V_g$ above which semiconducting armchair ribbons conduct. We find that the ideal conductance of perfectly transmitting wide ribbons is proportional to the square root of the gate voltage.Comment: 8 pages, 6 figure

Performance limits of graphene-ribbon-based field effect transistors

The performance of field effect transistors based on an single graphene ribbon with a constriction and a single back gate are studied with the help of atomistic models. It is shown how this scheme, unlike that of traditional carbon-nanotube-based transistors, reduces the importance of the specifics of the chemical bonding to the metallic electrodes in favor of the carbon-based part of device. The ultimate performance limits are here studied for various constriction and metal-ribbon contact models. In particular we show that, even for poorly contacting metals, properly taylored constrictions can give promising values for both the on-conductance and the subthreshold swing.Comment: 5 pages, 4 figure

Spin splitting in a polarized quasi-two-dimensional exciton gas

We have observed a large spin splitting between "spin" $+1$ and $-1$ heavy-hole excitons, having unbalanced populations, in undoped GaAs/AlAs quantum wells in the absence of any external magnetic field. Time-resolved photoluminescence spectroscopy, under excitation with circularly polarized light, reveals that, for high excitonic density and short times after the pulsed excitation, the emission from majority excitons lies above that of minority ones. The amount of the splitting, which can be as large as 50% of the binding energy, increases with excitonic density and presents a time evolution closely connected with the degree of polarization of the luminescence. Our results are interpreted on the light of a recently developed model, which shows that, while intra-excitonic exchange interaction is responsible for the spin relaxation processes, exciton-exciton interaction produces a breaking of the spin degeneracy in two-dimensional semiconductors.Comment: Revtex, four pages; four figures, postscript file Accepted for publication in Physical Review B (Rapid Commun.

Real space mapping of topological invariants using artificial neural networks

Topological invariants allow to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wavefunctions under twisted boundary conditions. However, those procedures do not allow to calculate a topological invariant by evaluating the system locally, and thus require information about the wavefunctions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a 1-D topological superconductor and a 2-D quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the Kernel Polynomial Method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.Comment: 9 pages, 6 figure