Nationality Heterogeneity and Interpersonal Relationships at Work

In this dissertation I test three new approaches to extend the ‘classical’ model of workplace diversity. The ‘classical’ model of workplace diversity assumes that diversity affects work outcomes via the mediating effects of social networks. I hypothesize that this model fruitfully can be extended by 1) considering that diversity forms a context in which employees act, 2) testing alternative predictors of network formation and employee behavior (i.e., employee voice), and 3) integrating diversity and social network perspectives in a contingency model. Three empirical studies support these hypotheses. In the first study, I show that the association between leadership and employee voice is stronger for nationality dissimilar employees. The second study finds that employee voice affects the strength of friendship relations but that this effect is contingent on employees’ past position in the social network. Finally, the third study demonstrates that group performance is maximized at moderate levels of task network centralization but lowest at high and low levels of centralization but that this relation is moderated by nationality diversity. Nationality diverse teams required more centralization to achieve high performance than homogeneous teams. Finally, I discuss the implications of these findings for research on diversity and social networks

HMcode-2020::Improved modelling of non-linear cosmological power spectra with baryonic feedback

We present an updated version of the HMcode augmented halo model that can be used to make accurate predictions of the non-linear matter power spectrum over a wide range of cosmologies. Major improvements include modelling of BAO damping in the power spectrum and an updated treatment of massive neutrinos. We fit our model to simulated power spectra and show that we can match the results with an RMS error of 2.5 per cent across a range of cosmologies, scales $k < 10\,h\mathrm{Mpc}^{-1}$, and redshifts $z<2$. The error rarely exceeds 5 per cent and never exceeds 16 per cent. The worst-case errors occur at $z\simeq2$, or for cosmologies with unusual dark-energy equations of state. This represents a significant improvement over previous versions of HMcode, and over other popular fitting functions, particularly for massive-neutrino cosmologies with high neutrino mass. We also present a simple halo model that can be used to model the impact of baryonic feedback on the power spectrum. This six-parameter physical model includes gas expulsion by AGN feedback and encapsulates star formation. By comparing this model to data from hydrodynamical simulations we demonstrate that the power spectrum response to feedback is matched at the $<1$ per cent level for $z<1$ and $k<20\,h\mathrm{Mpc}^{-1}$. We also present a single-parameter variant of this model, parametrized in terms of feedback strength, which is only slightly less accurate. We make code available for our non-linear and baryon models at https://github.com/alexander-mead/HMcode and it is also available within CAMB and soon within CLASS.Comment: 17 pages, 5 figures, 4 appendices; v2 - matches accepted version, new appendix with comparisons between HMcode and 6 different emulator

A hydrodynamical halo model for weak-lensing cross correlations

On the scale of galactic haloes, the distribution of matter in the cosmos is affected by energetic, non-gravitational processes; so-called baryonic feedback. A lack of knowledge about the details of how feedback processes redistribute matter is a source of uncertainty for weak-lensing surveys, which accurately probe the clustering of matter in the Universe over a wide range of scales. We develop a cosmology-dependent model for the matter distribution that simultaneously accounts for the clustering of dark matter, gas and stars. We inform our model by comparing it to power spectra measured from the BAHAMAS suite of hydrodynamical simulations. As well as considering matter power spectra, we also consider spectra involving the electron-pressure field, which directly relates to the thermal Sunyaev-Zel'dovich (tSZ) effect. We fit parameters in our model so that it can simultaneously model both matter and pressure data and such that the distribution of gas as inferred from tSZ has influence on the matter spectrum predicted by our model. We present two variants; one that matches the feedback-induced suppression seen in the matter-matter power spectrum at the per-cent level and a second that matches the matter-matter data slightly less well (~2 per cent), but that is able to simultaneously model the matter-electron pressure spectrum at the ~15 per-cent level. We envisage our models being used to simultaneously learn about cosmological parameters and the strength of baryonic feedback using a combination of tSZ and lensing auto- and cross-correlation data

Geometry-based tunability enhancement of flexible thin-film varactors

In this letter, flexible voltage-controlled capacitors (varactors) based on an amorphous Indium–Gallium–Zinc–Oxide (a-IGZO) semiconductor are presented. Two different varactor designs and their influence on the capacitance tuning characteristics are investigated. The first design consists of a top electrode finger structure which yields a maximum capacitance tunability of 6.9 at 10 kHz. Second, a novel interdigitated varactor structure results in a maximum tunability of 93.7 at 100 kHz. The design- and frequency-dependencies of the devices are evaluated through C–V measurements. Furthermore, we show bending stability of the devices down to a tensile radius of 6 mm without altering the performance. Finally, a varactor is combined with a thin-film resistor to demonstrate a tunable RC-circuit for impedance matching and low-pass filtering applications. The device fabrication flow and material stack are compatible with standard flexible thin-film transistor fabrication which enables parallel implementation of analog or logic circuitry and varactor devices

Finite strain Landau theory of high pressure phase transformations

The properties of materials near structural phase transitions are often successfully described in the framework of Landau theory. While the focus is usually on phase transitions, which are induced by temperature changes approaching a critical temperature T-c, here we will discuss structural phase transformations driven by high hydrostatic pressure, as they are of major importance for understanding processes in the interior of the earth. Since at very high pressures the deformations of a material are generally very large, one needs to apply a fully nonlinear description taking physical as well as geometrical nonlinearities (finite strains) into account. In particular it is necessary to retune conventional Landau theory to describe such phase transitions. In Troster et al (2002 Phys. Rev. Lett. 88 55503) we constructed a Landau-type free energy based on an order parameter part, an order parameter-(finite) strain coupling and a nonlinear elastic term. This model provides an excellent and efficient framework for the systematic study of phase transformations for a wide range of materials up to ultrahigh pressures

Painting with baryons: augmenting N-body simulations with gas using deep generative models

Running hydrodynamical simulations to produce mock data of large-scale structure and baryonic probes, such as the thermal Sunyaev-Zeldovich (tSZ) effect, at cosmological scales is computationally challenging. We propose to leverage the expressive power of deep generative models to find an effective description of the large-scale gas distribution and temperature. We train two deep generative models, a variational auto-encoder and a generative adversarial network, on pairs of matter density and pressure slices from the BAHAMAS hydrodynamical simulation. The trained models are able to successfully map matter density to the corresponding gas pressure. We then apply the trained models on 100 lines-of-sight from SLICS, a suite of N-body simulations optimised for weak lensing covariance estimation, to generate maps of the tSZ effect. The generated tSZ maps are found to be statistically consistent with those from BAHAMAS. We conclude by considering a specific observable, the angular cross-power spectrum between the weak lensing convergence and the tSZ effect and its variance, where we find excellent agreement between the predictions from BAHAMAS and SLICS, thus enabling the use of SLICS for tSZ covariance estimation