Embedded cluster framework for core-level spectroscopies of correlated materials
Description: Quantum materials have been in the spotlight in recent years since they allow for many applications in quantum technologies. However, their underlying physics is still poorly understood or limited to weakly correlated materials. To advance our understanding of strongly correlated materials, core-level spectroscopies such as x-ray absorption spectroscopy (XAS) or resonant inelastic x-ray scattering (RIXS) have become an essential experimental tool over the last decade. In particular RIXS is in the focus due to its capability to probe energy, momentum and polarization dependence of different elementary excitations such as phonons, magnons, or d-d transitions. However, the rich spectrum of excitations needs theoretical modeling to quantify the electronic properties of the system. In particular the disentanglement of spectroscopic signatures of different excitations requires a reliable numerical tool. The goal of this project is to advance the predictive power of theoretical core-level spectroscopies of strongly correlated materials by providing a user-friendly toolbox based on an efficient computational many-body framework. The envisaged cluster embedding framework will have both a fully ab initio and a model axis. It represents a big step towards the theoretical modeling of spectroscopic signatures related to collective low-energy excitations in these materials. The novelty lies in calculating the many-body spectra using matrix-product states (MPS). Thereby, the number of spatial and orbital degrees of freedom of the embedded cluster can be increased with respect to current many-body approaches and will ultimately allow studying correlated materials spectroscopies which are out of reach for present state-of-the-art codes. Building on our developed MPS-based solver, we will extend the applicability of existing many-body techniques to calculate XAS and RIXS cross sections and to model spectroscopic signatures of collective excitations in strongly correlated materials.
Funder: Agence Nationale de la Recherche
Amount: €371,000
Funding type: research
Funder scheme: AAPG2024
Start date: 2025-03-01
Investigator: Benjamin LENZ
Institution: Sorbonne Université
Funded outputs count: 1
Funder award ID: ANR-24-CE30-5387
OpenAlex ID: G7996411105