Unveiling quasiparticle dynamics of topological insulators through Bayesian modelling

Quasiparticle - a key concept to describe interacting particles - characterizes electron-electron interaction in metals (Fermi liquid) and electron pairing in superconductors. While this concept essentially relies on the simplification of hard-to-solve many-body problem into one-particle picture and residual effects, a difficulty in disentangling many-body effects from experimental quasiparticle signature sometimes hinders unveiling intrinsic low-energy dynamics, as highlighted by the fierce controversy on the origin of Dirac-band anomaly in graphene and dispersion kink in high-temperature superconductors. Here, we propose an approach to solve this fundamental problem - the Bayesian modelling of quasiparticles. We have chosen a topological insulator TlBi(S,Se) 2 as a model system to formulate an inverse problem of quasiparticle spectra with semiparametric Bayesian analysis, and successfully extracted one-particle and many-body characteristics, i.e. the intrinsic energy gap and unusual lifetime in Dirac-quasiparticle bands. Our approach is widely applicable to clarify the quasiparticle dynamics of quantum materials. Extracting quasiparticle dispersion from photoemission data is challenging and often results in confusion when investigating low-energy excitations. As a solution the authors demonstrate a technique, which applies Bayesian analysis to extract the quasiparticle dynamics of a topological insulator from angle resolved photoemission spectroscopy (ARPES) data, and could be applied to other quantum materials.