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Register a new userMany-pole model of inelastic losses in x-ray absorption spectra
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Inelastic losses are crucial to a quantitative analysis of x-ray absorption spectra. However, current treatments are semi-phenomenological in nature. Here a first-principles, many-pole generalization of the plasmon-pole model is developed for improved calculations of inelastic losses. The method is based on the GW approximation for the self-energy and real space multiple scattering calculations of the dielectric function for a given system. The model retains the efficiency of the plasmon-pole model and is applicable both to periodic and aperiodic materials over a wide energy range. The same many-pole model is applied to extended GW calculations of the quasiparticle spectral function. This yields estimates of multi-electron excitation effects, e.g., the many-body amplitude factor $S_0^2$ due to intrinsic losses. Illustrative calculations are compared with other GW calculations of the self-energy, the inelastic mean free path, and experimental x-ray absorption spectra.
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Inelastic losses in core level x-ray spectra arise from many-body excitations, leading to broadening and damping as well as satellite peaks in x-ray photoemission (XPS) and x-ray absorption (XAS) spectra. Here we present a practical approach for calculating these losses based on a cumulant representation of the particle-hole Greens function, a quasi-boson approximation, and a partition of the cumulant into extrinsic, intrinsic and interference terms. The intrinsic losses are calculated using real-time, time-dependent density functional theory while the extrinsic losses are obtained from the GW approximation of the photo-electron self-energy and the interference terms are approximated. These effects are included in the spectra using a convolution with an energy dependent particle-hole spectral function. The approach elucidates the nature of the spectral functions in XPS and XAS and explains the significant cancellation between extrinsic and intrinsic losses. Edge-singularity effects in metals are also accounted for. Illustrative results are presented for the XPS and XAS for both weakly and more correlated systems.
With the examples of the C $K$-edge in graphite and the B $K$-edge in hexagonal BN, we demonstrate the impact of vibrational coupling and lattice distortions on the X-ray absorption near-edge structure (XANES) in 2D layered materials. Theoretical XANES spectra are obtained by solving the Bethe-Salpeter equation of many-body perturbation theory, including excitonic effects through the correlated motion of core-hole and excited electron. We show that accounting for zero-point motion is important for the interpretation and understanding of the measured X-ray absorption fine structure in both materials, in particular for describing the $sigma^*$-peak structure.
Motivated by the recent synthesis of Ba$_2$CuO$_{3+delta}$ (BCO), a high temperature superconducting cuprate with putative $d_{3z^2-r^2}$ ground state symmetry, we investigated its electronic structure by means of Cu $L_3$ x-ray absorption (XAS) and resonant inelastic x-ray scattering (RIXS) at the Cu $L_3$ edge on a polycrystalline sample. We show that the XAS profile of BCO is characterised by two peaks associated to inequivalent Cu sites, and that its RIXS response features a single, sharp peak associated to crystal-field excitations. We argue that these observations are only partially compatible with the previously proposed crystal structure of BCO. Based on our spectroscopic results and on previously published powder diffraction measurements, we propose a crystalline structure characterized by two inequivalent Cu sites located at alternated planes along the $c$ axis: nominally trivalent Cu(1) belonging to very short Cu-O chains, and divalent Cu(2) in the oxygen deficient CuO$_ {1.5}$ planes. We also analyze the low-energy region of the RIXS spectra to estimate the magnitude of the magnetic interactions in BCO and find that in-plane nearest neighbor superexchange exceeds 120~meV, similarly to that of other layered cuprates. Although these results do not support the pure $d_{3z^2-r^2}$ ground state scenario, they hint at a significant departure from the common quasi-2D electronic structure of superconducting cuprates of pure $d_{x^2-y^2}$ symmetry.
The advent of massive data repositories has propelled machine learning techniques to the front lines of many scientific fields, and exploring new frontiers by leveraging the predictive power of machine learning will greatly accelerate big data-assisted discovery. In this work, we show that graph-based neural networks can be used to predict the near edge x-ray absorption structure spectra of molecules with exceptional accuracy. The predicted spectra reproduce nearly all the prominent peaks, with 90% of the predicted peak locations within 1 eV of the ground truth. Our study demonstrates that machine learning models can achieve practically the same accuracy as first-principles calculations in predicting complex physical quantities, such as spectral functions, but at a fraction of the cost.
A new method is presented for describing vibrational effects in x-ray absorption spectroscopy (XAS) and resonant inelastic x-ray scattering (RIXS) using a combination of the classical Franck-Condon (FC) approximation and classical trajectories run on the core-excited state. The formulation of RIXS is an extension of the semiclassical Kramers-Heisenberg (SCKH) formalism of Ref. {Ljungberg_2010} to the resonant case, retaining approximately the same computational cost. To overcome difficulties with connecting the absorption and emission processes in RIXS the classical FC approximation is used for the absorption, which is seen to work well provided that a zero-point-energy correction is included. In the case of core-excited states with dissociative character the method is capable of closely reproducing the main features for one-dimensional test systems, compared to the quantum mechanical formulation. Due to the good accuracy combined with the relatively low computational cost, the method has large potential of being used for complex systems with many degrees of freedom, such as liquids and surface adsorbates.
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