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Nagai, Yuki

Publications and source records attributed to Nagai, Yuki.

DMFT Reveals the Non-Hermitian Topology and Fermi Arcs in Heavy-Fermion Systems

When a strongly correlated system supports well-defined quasiparticles, it allows for an elegant one-body effective description within the non-Hermitian topological theory. While the microscopic many-body Hamiltonian of a closed system remains Hermitian, the one-body quasiparticle Hamiltonian is non-Hermitian due to the finite quasiparticle lifetime. We use such a non-Hermitian description in the heavy-fermion two-dimensional systems with the momentum-dependent hybridization to reveal a fascinating phenomenon which can be directly probed by the spectroscopic measurements, the bulk “Fermi arcs.” Starting from a simple two-band model, we first combine the phenomenological approach with the perturbation theory to show the existence of the Fermi arcs and reveal their connection to the topological exceptional points, special points in the Brillouin zone where the Hamiltonian is nondiagonalizable. The appearance of such points necessarily requires that the electrons belonging to different orbitals have different lifetimes. This requirement is naturally satisfied in the heavy-fermion systems, where the itinerant c electrons experience much weaker interaction than the localized f electrons. We then utilize the dynamical mean field theory to numerically calculate the spectral function and confirm our findings. We show here that the concept of the exceptional points in the non-Hermitian quasiparticle Hamiltonians is a powerful tool for predicting new phenomena in strongly correlated electron systems.

36 MATERIALS SCIENCE↗

Self-learning Monte Carlo method: Continuous-time algorithm

The recently introduced self-learning Monte Carlo method is a general-purpose numerical method that speeds up Monte Carlo simulations by training an effective model to propose uncorrelated configurations in the Markov chain. We implement this method in the framework of a continuous-time Monte Carlo method with an auxiliary field in quantum impurity models. We introduce and train a diagram generating function (DGF) to model the probability distribution of auxiliary field configurations in continuous imaginary time, at all orders of diagrammatic expansion. Furthermore, by using DGF to propose global moves in configuration space, we show that the self-learning continuous-time Monte Carlo method can significantly reduce the computational complexity of the simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spin Resonance in the New-Structure-Type Iron-Based Superconductor CaKFe 4 As 4

Here, the dynamical spin susceptibility in the new-structure-type iron-based superconductor CaKFe 4 As 4 was investigated by using a combination of inelastic neutron scattering (INS) measurements and random phase approximation (RPA) calculations. Powder INS measurements show that the spin resonance at Q res = 1.17(1) Å –1 , corresponding to the (π,π) nesting wave vector in tetragonal notation, evolves below T c . The characteristic energy of the spin resonance E res = 12.5 meV is smaller than twice the size of the superconducting gap (2Δ). The broad energy feature of the dynamical susceptibility of the spin resonance can be explained by the RPA calculations, in which the different superconducting gaps on different Fermi surfaces are taken into account. Our INS and PRA studies demonstrate that the superconducting pairing nature in CaKFe 4 As 4 is the s ± symmetry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗