Unveiling quasiparticle dynamics of topological insulators through Bayesian modelling

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. 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