Snowmass CF1 Summary: WIMP Dark Matter Direct Detection

As part of the Snowmass process, the Cosmic Frontier WIMP Direct Detection subgroup (CF1) has drawn on input from the Cosmic Frontier and the broader Particle Physics community to produce this document. The charge to CF1 was (a) to summarize the current status and projected sensitivity of WIMP direct detection experiments worldwide, (b) motivate WIMP dark matter searches over a broad parameter space by examining a spectrum of WIMP models, (c) establish a community consensus on the type of experimental program required to explore that parameter space, and (d) identify the common infrastructure required to practically meet those goals.Comment: Snowmass CF1 Final Summary Report: 47 pages and 28 figures with a 5 page appendix on instrumentation R&

Momentum-Net: Fast and convergent iterative neural network for inverse problems

Iterative neural networks (INN) are rapidly gaining attention for solving inverse problems in imaging, image processing, and computer vision. INNs combine regression NNs and an iterative model-based image reconstruction (MBIR) algorithm, often leading to both good generalization capability and outperforming reconstruction quality over existing MBIR optimization models. This paper proposes the first fast and convergent INN architecture, Momentum-Net, by generalizing a block-wise MBIR algorithm that uses momentum and majorizers with regression NNs. For fast MBIR, Momentum-Net uses momentum terms in extrapolation modules, and noniterative MBIR modules at each iteration by using majorizers, where each iteration of Momentum-Net consists of three core modules: image refining, extrapolation, and MBIR. Momentum-Net guarantees convergence to a fixed-point for general differentiable (non)convex MBIR functions (or data-fit terms) and convex feasible sets, under two asymptomatic conditions. To consider data-fit variations across training and testing samples, we also propose a regularization parameter selection scheme based on the "spectral spread" of majorization matrices. Numerical experiments for light-field photography using a focal stack and sparse-view computational tomography demonstrate that, given identical regression NN architectures, Momentum-Net significantly improves MBIR speed and accuracy over several existing INNs; it significantly improves reconstruction quality compared to a state-of-the-art MBIR method in each application.Comment: 28 pages, 13 figures, 3 algorithms, 4 tables, submitted revision to IEEE T-PAM

Finding Room for Fairness in Formalism--The Sliding Scale Approach to Unconscionability

This Article evaluates the sliding scale approach to unconscionability, defends its use, and advocates for its continued and expanded application to consumer standard form contracts. Part I describes the sliding scale approach and its recent popularity in state courts, thereby filling a gap in the scholarly doctrine, which has to date failed to fully examine this trend. Parts II and III defend the sliding scale approach, praising its potential to align the unconscionability analysis with interdisciplinary research regarding consumer behavior and to balance formalist concerns about judicial regulation of unfair terms in standard form contracts. Finally, Part IV calls for calibrations to the sliding scale approach and its application to standardized forms that will ensure its success as a protective device for consumers