ABSTRACT
A key advantage of utilizing van-der-Waals (vdW) materials as defect-hosting platforms for quantum applications is the controllable proximity of the defect to the surface or the substrate allowing for improved light extraction, enhanced coupling with photonic elements, or more sensitive metrology. However, this aspect results in a significant challenge for defect identification and characterization, as the defect's properties depend on the the atomic environment. This study explores how the environment can influence the properties of carbon impurity centers in hexagonal boron nitride (hBN). It compares the optical and electronic properties of such defects between bulk-like and few-layer films, showing alteration of the zero-phonon line energies and their phonon sidebands, and enhancements of inhomogeneous broadenings. To disentangle the mechanisms responsible for these changes, including the atomic structure, electronic wavefunctions, and dielectric screening, it combines ab initio calculations with a quantum-embedding approach. By studying various carbon-based defects embedded in monolayer and bulk hBN, it demonstrates that the dominant effect of the change in the environment is the screening of density-density Coulomb interactions between the defect orbitals. The comparative analysis of experimental and theoretical findings paves the way for improved identification of defects in low-dimensional materials and the development of atomic scale sensors for dielectric environments.
ABSTRACT
We present a fully charge self-consistent implementation of dynamical mean field theory (DMFT) combined with density functional theory (DFT) for electronic structure calculations of materials with strong electronic correlations. The implementation uses theQuantum ESPRESSOpackage for the DFT calculations, theWannier90code for the up-/down-folding and theTRIQSsoftware package for setting up and solving the DMFT equations. All components are available under open source licenses, are MPI-parallelized, fully integrated in the respective packages, and use an hdf5 archive interface to eliminate file parsing. We show benchmarks for three different systems that demonstrate excellent agreement with existing DFT + DMFT implementations in otherab initioelectronic structure codes.
ABSTRACT
A livestock population can be characterized by different population genetic parameters, such as linkage disequilibrium and recombination rate between pairs of genetic markers. The population structure, which may be caused by family stratification, has an influence on the estimates of these parameters. An expectation maximization algorithm has been proposed for estimating these parameters in half-sibs without phasing the progeny. It, however, overlooks the fact that the underlying likelihood function may have two maxima. The magnitudes of the maxima depend on the maternal allele frequencies at the investigated marker pair. Which maximum the algorithm converges to depends on the chosen start values. We present a stepwise procedure in which the relationship between the two modes is exploited. The expectation maximization algorithm for the parameter estimation is applied twice using different start values, followed by a decision process to assess the most likely estimate. This approach was validated using simulated genotypes of half-sibs. It was also applied to a dairy cattle dataset consisting of multiple half-sib families and 39,780 marker genotypes, leading to estimates for 12,759,713 intrachromosomal marker pairs. Furthermore, the proper order of markers was verified by studying the mean of estimated recombination rates in a window adjacent to the investigated locus as well as in a window at its most distant chromosome end. Putatively misplaced markers or marker clusters were detected by comparing the results with the revised bovine genome assembly UMD 3.1.1. In total, 40 markers were identified as candidates of misplacement. This outcome may help improving the physical order of markers which is also required for refining the bovine genetic map.
