The future of the computing curriculum:how the computing curriculum instills values and subjectivity in young people

In these early stages of implementation of the English computing curriculum policy reforms, there are uncertainties with regards to the intentions of computing to young people. To date, research regarding the English computing curriculum has been mostly concerned with the content of the curriculum, its delivery and surrounding pedagogy. In contrast this paper seeks to explore the underlying motivation and values embedded in the computing curriculum. We propose that this curriculum has been driven by the needs of industry and the economy. We use Schwartz’s values to examine how the teaching of computing has been primarily embedded within the value of self-enhancement. We conclude, that by looking at this context and the underlying value structure, we can reflect on the dramatic effects of the narrative and discourse around the content, delivery and purpose of teaching computing to young people. We propose the narratives of curriculum, influence pedagogy and this in turn, has a powerful impact on the young people’s view of themselves and the world we want to equip them to create

On the effect of charge self-consistency in DFT+DMFT calculations for complex transition metal oxides

We investigate the effect of charge self-consistency (CSC) in density functional theory plus dynamical mean-field theory (DFT+DMFT) calculations compared to simpler "one-shot" calculations for materials where interaction effects lead to a strong redistribution of electronic charges between different orbitals or between different sites. We focus on two systems close to a metal-insulator transition, for which the importance of CSC is currently not well understood. Specifically, we analyze the strain-related orbital polarization in the correlated metal CaVO$_3$ and the spontaneous electronic charge disproportionation in the rare-earth nickelate LuNiO$_3$. In both cases, we find that the CSC treatment reduces the charge redistribution compared to cheaper one-shot calculations. However, while the MIT in CaVO$_3$ is only slightly shifted due to the reduced orbital polarization, the effect of the site polarization on the MIT in LuNiO$_3$ is more subtle. Furthermore, we highlight the role of the double-counting correction in CSC calculations containing different inequivalent sites.Comment: 11 pages, 6 figure

Signatures of Hund Metal and Fermi Liquid Behavior in Sr2_2RuO4_4 Revealed by Electronic Raman Scattering

We investigate the electronic Raman scattering of Sr$_2$RuO$_4$ using a material-realistic dynamical mean-field theory approach. We identify the low-energy Fermi liquid behavior and point out that the enhanced Raman response at higher energies displays clear signatures of Hund metals physics. These signatures originate in the two-stage coherence of Hund metals and associated quasiparticle 'unrenormalization'. In agreement with recent experimental observations we find a strong dichotomy between the $\mathrm{B}_{1g}$ and $\mathrm{B}_{2g}$ response, but our calculations suggest a novel interpretation of this dichotomy. The $\mathrm{B}_{1g}$ response is dominated by the $xy$ orbital and the $\mathrm{B}_{2g}$ response receives contributions from all orbitals and is strongly affected by interband nesting at finite frequencies.Comment: 7 pages, 4 figures. SM: 5 pages, 8 figure

Training biases in machine learning for the analytic continuation of quantum many-body Green's functions

We address the problem of analytic continuation of imaginary-frequency Green's functions, which is crucial in many-body physics, using machine learning based on a multi-level residual neural network. We specifically address potential biases that can be introduced due to the use of artificially created spectral functions that are employed to train the neural network. We also implement an uncertainty estimation of the predicted spectral function, based on Monte Carlo dropout, which allows to identify frequency regions where the prediction might not be accurate, and we study the effect of noise, in particular also for situations where the noise level during training is different from that in the actual data. Our analysis demonstrates that this method can indeed achieve a high quality of prediction, comparable or better than the widely used maximum entropy method, but that further improvement is currently limited by the lack of true data that can be used for training. We also benchmark our approach by applying it to the case of SrVO$_3$, where an accurate spectral function has been obtained from dynamical mean-field theory using a solver that works directly on the real frequency axis

Charge self-consistent electronic structure calculations with dynamical mean-field theory using Quantum ESPRESSO, Wannier90 and TRIQS

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 the Quantum ESPRESSO package for the density functional theory calculations, the Wannier90 code for the up-/downfolding and the TRIQS software 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 other ab-initio electronic structure codes.Comment: 13 pages, 11 figure

Automatic, high-order, and adaptive algorithms for Brillouin zone integration

We present efficient methods for Brillouin zone integration with a non-zero but possibly very small broadening factor $\eta$, focusing on cases in which downfolded Hamiltonians can be evaluated efficiently using Wannier interpolation. We describe robust, high-order accurate algorithms automating convergence to a user-specified error tolerance $\varepsilon$, emphasizing an efficient computational scaling with respect to $\eta$. After analyzing the standard equispaced integration method, applicable in the case of large broadening, we describe a simple iterated adaptive integration algorithm effective in the small $\eta$ regime. Its computational cost scales as $\mathcal{O}(\log^3(\eta^{-1}))$ as $\eta \to 0^+$ in three dimensions, as opposed to $\mathcal{O}(\eta^{-3})$ for equispaced integration. We argue that, by contrast, tree-based adaptive integration methods scale only as $\mathcal{O}(\log(\eta^{-1})/\eta^{2})$ for typical Brillouin zone integrals. In addition to its favorable scaling, the iterated adaptive algorithm is straightforward to implement, particularly for integration on the irreducible Brillouin zone, for which it avoids the tetrahedral meshes required for tree-based schemes. We illustrate the algorithms by calculating the spectral function of SrVO$_3$ with broadening on the meV scale

Make your brand heard: A qualitative study on the use of corporate podcasts as a branding tool

As an increasingly popular on-demand medium, podcasts have become more professional and commercialized in recent times. This is also evident from a look at corporate communications, where many companies add podcasts into their communication mix. To align these corporate podcasts with other communication channels, the concept of corporate branding can be helpful. This approach has not been considered by empirical studies so far. Our qualitative interview study wants to investigate the role of corporate podcasts in corporate branding and examines their integration into the communication strategy of nationally and internationally operating companies. 13 experts from large companies responsible for the respective podcast have been interviewed. The research results show that podcasts are mostly integrated into the company’s overarching communications strategy and incorporate company-specific branding aspects to varying degrees. Corporate podcasts are primarily used to highlight innovative and modern aspects of the brands, especially through the tone of voice. The intended impact of corporate podcasts is often a personal and emotional connection, interaction, and resonance with listeners. Increasing reputation, visibility, and conveying authenticity is also targeted. As a branding tool, podcasts are evaluated rather implicitly. The general evaluation is perceived as challenging and tends to focus on qualitative performance measurement. This study underscores the high need for research on corporate podcasts as a branding tool as well as for key performance indicators (KPIs) of podcasts

Low rank Green's function representations applied to dynamical mean-field theory

Several recent works have introduced highly compact representations of single-particle Green's functions in the imaginary time and Matsubara frequency domains, as well as efficient interpolation grids used to recover the representations. In particular, the intermediate representation with sparse sampling and the discrete Lehmann representation (DLR) make use of low-rank compression techniques to obtain optimal approximations with controllable accuracy. We consider the use of the DLR in dynamical mean-field theory (DMFT) calculations, and in particular, show that the standard full Matsubara frequency grid can be replaced by the compact grid of DLR Matsubara frequency nodes. We test the performance of the method for a DMFT calculation of Sr$_2$RuO$_4$ at temperature $50$K using a continuous-time quantum Monte Carlo impurity solver, and demonstrate that Matsubara frequency quantities can be represented on a grid of only $36$ nodes with no reduction in accuracy, or increase in the number of self-consistent iterations, despite the presence of significant Monte Carlo noise.Comment: 5 pages, 4 figure