SearcharxivSearch

arXiv subjects

Stefan Liscak

Publications and source records attributed to Stefan Liscak.

2 recordsLinked to original sources

Skyrmionic Schrödinger cat states in monoaxial chiral magnets

We study the low-energy excitation spectra of a spin-1/2 quantum Heisenberg model with a monoaxial Dzyaloshinskii-Moriya interaction. Using the density matrix renormalization group method, our analysis reveals a degeneracy between skyrmion and antiskyrmion states, enabling the formation of a mesoscopic Schrödinger cat state - a quantum superposition of these topologically distinct textures. To characterize this nontrivial state, we compute two-point spin correlation functions, highlighting signatures accessible via neutron scattering experiments. Furthermore, we demonstrate that applying a magnetic field gradient induces a coherent time evolution of the cat state, offering a controllable mechanism for its manipulation. These findings provide a framework for the detection of skyrmionic Schrödinger cat states in quantum magnets.

cond-mat.mes-hall

Framework for Polarized Magnetic Neutron Scattering from Nanoparticle Assemblies with Vortex-Type Spin Textures

Within the framework of the recently introduced multi-nanoparticle power-series expansion method for the polarized small-angle neutron scattering (SANS) cross section, we present analytical expressions for the polarized SANS observables arising from dilute nanoparticle assemblies with antisymmetric vortex-type spin structures. We establish connections between the magnetic correlation coefficients and the magnetic field-dependent vortex-axes distribution function, which is related to the random orientations of the magnetocrystalline anisotropy axes of the nanoparticles. Our analytical results are validated through a comparative analysis with micromagnetic simulations. This framework contributes to a comprehensive understanding of polarized magnetic neutron scattering from spherical nanoparticle systems exhibiting vortex-type spin structures.

cond-mat.mtrl-sci