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Magnetic microcalorimeters (MMCs) are cryogenic, energy-dispersive single-particle detectors providing excellent energy resolution, intrinsically fast signal rise time, quantum efficiency close to 100%, large dynamic range as well as almost ideal linear response. One of the remaining challenges to be overcome to ultimately allow for the utilization of large-scale MMC based detector arrays with thousands to millions of individual pixels is the realization of a SQUID based multiplexing technique particularly tailored for MMC readout. Within this context, we report on the first demonstration of a frequency-division multiplexed readout of an MMC based detector array using both, a custom microwave SQUID multiplexer as well as a dedicated software-defined radio (SDR) readout electronics. We successfully performed a simultaneous readout up to eight multiplexer channels, each monitoring two detector pixels. We show that the signal shape is not changed as compared to a dc-SQUID readout and that similar values for the energy resolution can be obtained. Nevertheless, we observed an influence of the internal quality factor of the microwave resonators used for frequency encoding on the energy resolution that affects the resolution of the co-added sum spectrum.

The Adolescent Brain Cognitive Development (ABCD) Study®is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N= 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N= 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N= 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.

This article gives an overview of reduced-order modeling work performed in the DLR project Digital-X. Parametric aerodynamic reduced-order models (ROMs) are used to predict surface pressure distributions based on high-fidelity computational fluid dynamics (CFD), but at lower evaluation time and storage than the original CFD model. ROMs for steady aerodynamic applications are built using proper orthogonal decomposition and Isomap, a manifold learning method. Approximate solutions in the so-obtained low-dimensional representations of the data are found with interpolation techniques, or by minimizing the corresponding steady flow-solver residual. The latter approach produces physics-based ROMs driven by the governing equations. The steady ROMs are used to predict the static aeroelastic loads in a multidisciplinary design and optimization context, where the structural model is to be sized for the (aerodynamic) loads. They are also used in a process where an a priori identification of the critical load cases is of interest and the sheer number of load cases to be considered does not lend itself to high-fidelity CFD. An approach to correct a linear loads analysis model using steady CFD solutions at various Mach numbers and angles of attack and a ROM of the corrected aerodynamic influence coefficients is also shown. This results in a complete loads analysis model preserving aerodynamic nonlinearities while allowing fast evaluation across all model parameters. The different ROM methods are applied to a 3D test case of a transonic wing-body transport aircraft configuration.