Educational and training programs designed to reduce racial bias often focus on increasing people's awareness of psychological sources of their biases. However, when people learn about their biases, they often respond defensively, which can undermine the effectiveness of antibias interventions and the success of prejudice regulation. Using process (Quad) modeling, we provide one of the first investigations of the relationships between (a) controlled and automatic cognitive processes that underpin performance on the Implicit Association Test and (b) defensive reactions to unflattering implicit racial bias feedback. In two correlational samples (one preregistered; N = 8,000) and one experiment in which the provision of bias feedback was manipulated (N = 547), we find racially biased associations and some control over these associations among White people. Nonetheless, more defensiveness to bias feedback consistently predicted weaker ability to control biased associations. We also find correlational evidence that lower levels of biased associations predict more defensiveness, but did not replicate this observation in the experimental study. These results are critical for theories of implicit attitudes, models of prejudice regulation, and strategies for antibias interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cosmic reionization is thought to be primarily fueled by the first generations of galaxies. We examine their stellar and gaseous properties, focusing on the star formation rates and the escape of ionizing photons, as a function of halo mass, redshift, and environment using the full suite of the {\it Renaissance Simulations} with an eye to provide better inputs to global reionization simulations. This suite, carried out with the adaptive mesh refinement code Enzo, is unprecedented in terms of their size and physical ingredients. The simulations probe overdense, average, and underdense regions of the universe of several hundred comoving Mpc$^3$, each yielding a sample of over 3,000 halos in the mass range $10^7 - 10^{9.5}~\Ms$ at their final redshifts of 15, 12.5, and 8, respectively. In the process, we simulate the effects of radiative and supernova feedback from 5,000 to 10,000 metal-free (Population III) stars in each simulation. We find that halos as small as $10^7~\Ms$ are able to form stars due to metal-line cooling from earlier enrichment by massive Population III stars. However, we find such halos do not form stars continuously. Using our large sample, we find that the galaxy-halo occupation fraction drops from unity at virial masses above $10^{8.5}~\Ms$ to $\sim$50\% at $10^8 ~\Ms$ and $\sim$10\% at $10^7~\Ms$, quite independent of redshift and region. Their average ionizing escape fraction is $\sim$5\% in the mass range $10^8 - 10^9~\Ms$ and increases with decreasing halo mass below this range, reaching 40--60\% at $10^7~\Ms$. Interestingly, we find that the escape fraction varies between 10--20\% in halos with virial masses $\sim 3 \times 10^9~\Ms$. Taken together, our results confirm the importance of the smallest galaxies as sources of ionizing radiation contributing to the reionization of the universe.

This document presents (off-line) computing requrements and challenges for Cosmic Frontier science, covering the areas of data management, analysis, and simulations. We invite contributions to extend the range of covered topics and to enhance the current descriptions.

Over the last decade block-structured adaptive mesh refinement (SAMR) has found increasing use in large, publicly available codes and frameworks. SAMR frameworks have evolved along different paths. Some have stayed focused on specific domain areas, others have pursued a more general functionality, providing the building blocks for a larger variety of applications. In this survey paper we examine a representative set of SAMR packages and SAMR-based codes that have been in existence for half a decade or more, have a reasonably sized and active user base outside of their home institutions, and are publicly available. The set consists of a mix of SAMR packages and application codes that cover a broad range of scientific domains. We look at their high-level frameworks, their design trade-offs and their approach to dealing with the advent of radical changes in hardware architecture. The codes included in this survey are BoxLib, Cactus, Chombo, Enzo, FLASH, and Uintah.

Using an isolated Milky Way-mass galaxy simulation, we compare results from nine state-of-the-art gravito-hydrodynamics codes widely used in the numerical community. We utilize the infrastructure we have built for the AGORA High-resolution Galaxy Simulations Comparison Project. This includes the common disk initial conditions, common physics models (e.g., radiative cooling and UV background by the standardized package Grackle) and common analysis toolkit yt, all of which are publicly available. Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production are carefully constrained across code platforms. With numerical accuracy that resolves the disk scale height, we find that the codes overall agree well with one another in many dimensions including: gas and stellar surface densities, rotation curves, velocity dispersions, density and temperature distribution functions, disk vertical heights, stellar clumps, star formation rates, and Kennicutt-Schmidt relations. Quantities such as velocity dispersions are very robust (agreement within a few tens of percent at all radii) while measures like newly formed stellar clump mass functions show more significant variation (difference by up to a factor of ∼3). Systematic differences exist, for example, between mesh-based and particle-based codes in the low-density region, and between more diffusive and less diffusive schemes in the high-density tail of the density distribution. Yet intrinsic code differences are generally small compared to the variations in numerical implementations of the common subgrid physics such as supernova feedback. Our experiment reassures that, if adequately designed in accordance with our proposed common parameters, results of a modern high-resolution galaxy formation simulation are more sensitive to input physics than to intrinsic differences in numerical schemes.