Realistic many-body models for Manganese Monoxide under pressure

In materials like transition metals oxides where electronic Coulomb correlations impede a description in terms of standard band-theories, the application of genuine many-body techniques is inevitable. Interfacing the realism of density-functional based methods with the virtues of Hubbard-like Hamiltonians, requires the joint ab initio construction of transfer integrals and interaction matrix elements (like the Hubbard U) in a localized basis set. In this work, we employ the scheme of maximally localized Wannier functions and the constrained random phase approximation to create effective low-energy models for Manganese monoxide, and track their evolution under external pressure. We find that in the low pressure antiferromagnetic phase, the compression results in an increase of the bare Coulomb interaction for specific orbitals. As we rationalized in recent model considerations [Phys. Rev. B 79, 235133 (2009)], this seemingly counter-intuitive behavior is a consequence of the delocalization of the respective Wannier functions. The change of screening processes does not alter this tendency, and thus, the screened on-site component of the interaction - the Hubbard U of the effective low-energy system - increases with pressure as well. The orbital anisotropy of the effects originates from the orientation of the orbitals vis-a-vis the deformation of the unit-cell. Within the high pressure paramagnetic phase, on the other hand, we find the significant increase of the Hubbard U is insensitive to the orbital orientation and almost exclusively owing to a substantial weakening of screening channels upon compression.Comment: 13 pages, 6 figure

Wind Forced Variability in Eddy Formation, Eddy Shedding, and the Separation of the East Australian Current

The East Australian Current (EAC), like many other subtropical western boundary currents, is believed to be penetrating further poleward in recent decades. Previous observational and model studies have used steady state dynamics to relate changes in the westerly winds to changes in the separation behavior of the EAC. As yet, little work has been undertaken on the impact of forcing variability on the EAC and Tasman Sea circulation. Here using an eddy‐permitting regional ocean model, we present a suite of simulations forced by the same time‐mean fields, but with different atmospheric and remote ocean variability. These eddy‐permitting results demonstrate the nonlinear response of the EAC to variable, nonstationary inhomogeneous forcing. These simulations show an EAC with high intrinsic variability and stochastic eddy shedding. We show that wind stress variability on time scales shorter than 56 days leads to increases in eddy shedding rates and southward eddy propagation, producing an increased transport and southward reach of the mean EAC extension. We adopt an energetics framework that shows the EAC extension changes to be coincident with an increase in offshore, upstream eddy variance (via increased barotropic instability) and increase in subsurface mean kinetic energy along the length of the EAC. The response of EAC separation to regional variable wind stress has important implications for both past and future climate change studies

“Where’s the I-O?” Artificial Intelligence and Machine Learning in Talent Management Systems

Artificial intelligence (AI) and machine learning (ML) have seen widespread adoption by organizations seeking to identify and hire high-quality job applicants. Yet the volume, variety, and velocity of professional involvement among I-O psychologists remains relatively limited when it comes to developing and evaluating AI/ML applications for talent assessment and selection. Furthermore, there is a paucity of empirical research that investigates the reliability, validity, and fairness of AI/ML tools in organizational contexts. To stimulate future involvement and research, we share our review and perspective on the current state of AI/ML in talent assessment as well as its benefits and potential pitfalls; and in addressing the issue of fairness, we present experimental evidence regarding the potential for AI/ML to evoke adverse reactions from job applicants during selection procedures. We close by emphasizing increased collaboration among I-O psychologists, computer scientists, legal scholars, and members of other professional disciplines in developing, implementing, and evaluating AI/ML applications in organizational contexts

Downfolded Self-Energy of Many-Electron Systems

Starting from the full many-body Hamiltonian of interacting electrons the effective self-energy acting on electrons residing in a subspace of the full Hilbert space is derived. This subspace may correspond to, for example, partially filled narrow bands, which often characterize strongly correlated materials. The formalism delivers naturally the frequency-dependent effective interaction (the Hubbard U) and provides a general framework for constructing theoretical models based on the Green function language. It also furnishes a general scheme for first-principles calculations of complex systems in which the main correlation effects are concentrated on a small subspace of the full Hilbert space.Comment: 5 page

Bubble-Mediated Gas Transfer and Gas Transfer Suppression of DMS and CO2

Direct dimethyl sulfide (DMS) flux measurements using eddy covariance have shown a suppression of gas transfer at medium to high wind speed. However, not all eddy covariance measurements show evidence of this suppression. Processes, such as wave-wind interaction and surfactants, have been postulated to cause this suppression. We measured DMS and carbon dioxide eddy covariance fluxes during the Asian summer monsoon in the western tropical Indian Ocean (July and August 2014). Both fluxes and their respective gas transfer velocities show signs of a gas transfer suppression above 10 m/s. Using a wind-wave interaction, we describe a flow separation process that could be responsible for a suppression of gas transfer. As a result we provide a Reynolds number-based parameterization, which states the likelihood of a gas transfer suppression for this cruise and previously published gas transfer data. Additionally, we compute the difference in the gas transfer velocities of DMS and CO2 to estimate the bubble-mediated gas transfer using a hybrid model with three whitecap parameterizations

Chronos and KAIROS: MOSFIRE observations of post-starburst galaxies in z ∼ 1 clusters and groups

We present an exploration of ∼500 spectroscopically confirmed galaxies in and around two large-scale structures (LSSs) at z ∼ 1 drawn from the Observations of Redshift Evolution in Large Scale Environments survey, an ongoing, wide-field photometric and spectroscopic campaign targeting a large ensemble of LSSs at 0.6 < z < 1.3. A sub-sample of these galaxies (∼150) was targeted for the initial phase of a near-infrared MOSFIRE spectroscopic campaign investigating the differences in selections of galaxies that had recently ended a burst of star formation and/or had rapidly quenched (i.e. post-starburst/K+A galaxies). Selection with MOSFIRE utilizing the H α and [N II] emission features resulted in a post-starburst sample more than double that selected by traditional z ∼ 1 (observed-frame optical) methods even after the removal of the relatively large fraction of dusty starburst galaxies selected through traditional methods. While the traditional post-starburst fraction increased with increasing global density, the MOSFIRE-selected post-starburst fraction was found to be constant across field, group, and cluster environments. However, this fraction computed relative to the number of star-forming galaxies was observed to elevate in the cluster environment. Post-starbursts selected with MOSFIRE exhibited moderately strong [O II] emission originating from activity other than star formation. Such galaxies, termed K+A with ImposteR [O II]-derived Star formation (KAIROS) galaxies, were found to be younger than and likely undergoing feedback absent or diminished in their optically selected counterparts. A comparison between the environments of the two types of post-starbursts suggested a picture in which the evolution of a post-starburst galaxy is considerably different in cluster environments than in the more rarefied environments of a group or the field