Penalized Regression with Correlation Based Penalty

A new regularization method for regression models is proposed. The criterion to be minimized contains a penalty term which explicitly links strength of penalization to the correlation between predictors. As the elastic net, the method encourages a grouping effect where strongly correlated predictors tend to be in or out of the model together. A boosted version of the penalized estimator, which is based on a new boosting method, allows to select variables. Real world data and simulations show that the method compares well to competing regularization techniques. In settings where the number of predictors is smaller than the number of observations it frequently performs better than competitors, in high dimensional settings prediction measures favor the elastic net while accuracy of estimation and stability of variable selection favors the newly proposed method

Boosting Correlation Based Penalization in Generalized Linear Models

In high dimensional regression problems penalization techniques are a useful tool for estimation and variable selection. We propose a novel penalization technique that aims at the grouping effect which encourages strongly correlated predictors to be in or out of the model together. The proposed penalty uses the correlation between predictors explicitly. We consider a simple version that does not select variables and a boosted version which is able to reduce the number of variables in the model. Both methods are derived within the framework of generalized linear models. The performance is evaluated by simulations and by use of real world data sets

Combining Quadratic Penalization and Variable Selection via Forward Boosting

Quadratic penalties can be used to incorporate external knowledge about the association structure among regressors. Unfortunately, they do not enforce single estimated regression coefficients to equal zero. In this paper we propose a new approach to combine quadratic penalization and variable selection within the framework of generalized linear models. The new method is called Forward Boosting and is related to componentwise boosting techniques. We demonstrate in simulation studies and a real-world data example that the new approach competes well with existing alternatives especially when the focus is on interpretable structuring of predictors

Comparative study of the growth of sputtered aluminum oxide films on organic and inorganic substrates

We present a comparative study of the growth of the technologically highly relevant gate dielectric and encapsulation material aluminum oxide in inorganic and also organic heterostructures. Atomic force microscopy studies indicate strong similarities in the surface morphology of aluminum oxide films grown on these chemically different substrates. In addition, from X-ray reflectivity measurements we extract the roughness exponent \beta of aluminum oxide growth on both substrates. By renormalising the aluminum oxide roughness by the roughness of the underlying organic film we find good agreement with \beta as obtained from the aluminum oxide on silicon oxide (\beta = 0.38 \pm 0.02), suggesting a remarkable similarity of the aluminum oxide growth on the two substrates under the conditions employed

Frequency Domain Multiplexing for MKIDs: Comparing the Xilinx ZCU111 RFSoC with their new 2x2 RFSoC board

The Xilinx ZCU111 Radio Frequency System on Chip (RFSoC) is a promising solution for reading out large arrays of microwave kinetic inductance detectors (MKIDs). The board boasts eight on-chip 12-bit / 4.096 GSPS analogue-to-digital converters (ADCs) and eight 14-bit / 6.554 GSPS digital-to-analogue converters (DACs), as well as field programmable gate array (FPGA) resources of 930,000 logic cells and 4,272 digital signal processing (DSP) slices. While this is sufficient data converter bandwidth for the readout of 8,000 MKIDs, with a 2 MHz channel-spacing, and a 1 MHz sampling rate (per channel), additional FPGA resources are needed to perform the DSP needed to process this large number of MKIDs. A solution to this problem is the new Xilinx RFSoC 2x2 board. This board costs only one fifth of the ZCU111 while still providing the same logic resources as the ZCU111, albeit with only a quarter of the data converter resources. Thus, using multiple RFSoC 2x2 boards would provide a better balance between FPGA resources and data converters, allowing the full utilization of the RF bandwidth provided by the data converters, while also lowering the cost per pixel value of the readout system, from approximately EUR2.50 per pixel with the ZCU111, to EUR1 per pixel.Comment: 7 pages, 6 figures. Presented at 19$^{th}$ International Workshop on Low Temperature Detectors, 21$^{st}$ July 2023. Resubmission to correct minor typo in author lis

Reversibly compressible and freestanding monolithic carbon spherogels

We present a versatile strategy to tailor the nanostructure of monolithic carbon aerogels. By use of an aqueous colloidal solution of polystyrene in the sol-gel processing of resorcinol-formaldehyde gels, we can prepare, after supercritical drying and successive carbonization, freestanding monolithic carbon aerogels, solely composed of interconnected and uniformly sized hollow spheres, which we name carbon spherogels. Each sphere is enclosed by a microporous carbon wall whose thickness can be adjusted by the polystyrene concentration, which affects the pore texture as well as the mechanical properties of the aerogel monolith. In this study, we used monodisperse polystyrene spheres of approximately 250 nm diameter, which result in an inner diameter of the final hollow carbon spheres of approximately 200 ± 5 nm due to shrinkage during the carbonization process. The excellent homogeneity of the samples, as well as uniform sphere geometries, are confirmed by small- and angle X-ray scattering. The presence of macropores between the hollow spheres creates a monolithic network with the benefit of being reversibly compressible up to 10% linear strain without destruction. Electrochemical tests demonstrate the applicability of ground and CO2 activated carbon spherogels as electrode materials

DARKNESS: A Microwave Kinetic Inductance Detector Integral Field Spectrograph for High-Contrast Astronomy

We present DARKNESS (the DARK-speckle Near-infrared Energy-resolving Superconducting Spectrophotometer), the first of several planned integral field spectrographs to use optical/near-infrared Microwave Kinetic Inductance Detectors (MKIDs) for high-contrast imaging. The photon counting and simultaneous low-resolution spectroscopy provided by MKIDs will enable real-time speckle control techniques and post-processing speckle suppression at framerates capable of resolving the atmospheric speckles that currently limit high-contrast imaging from the ground. DARKNESS is now operational behind the PALM-3000 extreme adaptive optics system and the Stellar Double Coronagraph at Palomar Observatory. Here we describe the motivation, design, and characterization of the instrument, early on-sky results, and future prospects.Comment: 17 pages, 17 figures. PASP Publishe

DARKNESS: A Microwave Kinetic Inductance Detector Integral Field Spectrograph for High-contrast Astronomy

We present DARKNESS (the DARK-speckle Near-infrared Energy-resolving Superconducting Spectrophotometer), the first of several planned integral field spectrographs to use optical/near-infrared Microwave Kinetic Inductance Detectors (MKIDs) for high-contrast imaging. The photon counting and simultaneous low-resolution spectroscopy provided by MKIDs will enable real-time speckle control techniques and post-processing speckle suppression at frame rates capable of resolving the atmospheric speckles that currently limit high-contrast imaging from the ground. DARKNESS is now operational behind the PALM-3000 extreme adaptive optics system and the Stellar Double Coronagraph at Palomar Observatory. Here, we describe the motivation, design, and characterization of the instrument, early on-sky results, and future prospects