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  1. Free, publicly-accessible full text available February 22, 2023
  2. Free, publicly-accessible full text available April 1, 2023
  3. Intermittent floodplain channels are low‐relief conduits etched into the floodplain surface and remain dry much of the year. These channels comprise expansive systems and are important because during low‐level inundation they facilitate lateral hydraulic connectivity throughout the floodplain. Nevertheless, few studies have focused on these floodplain channels due to uncertainty in how to identify and characterize these systems in digital elevation models (DEMs). In particular, their automatic extraction from widely available DEMs is challenging due to the characteristically low‐relief and low‐gradient topography of floodplains. We applied three channel extraction approaches to the Congaree River floodplain DEM and compared the resultsmore »to a channel reference map created through numerous field excursions over the past 30 years. The methods that we tested are based on flow accumulation area, topographic curvature, and mathematical morphology, or the D8, Laplacian, and bottom‐hat transform (BHT), respectively. Of the 198 km of reference channels the BHT, Laplacian, and D8 extracted 83%, 71%, and 23%, respectively, and the BHT consistently had the highest agreement with the reference network at the local (5 m) and regional (10 km) scales. The extraction results also include commission “error”, augmenting the reference map with about 100 km of channel length. Overall, the BHT method provided the best results for channel extraction, giving over 298 km in 69 km2 with a detrended regional relief of 1.9 m. Further, these analyses allow us to shed light on the meaning and use of the term “low‐relief landscapes”.« less
  4. The weighted constraint satisfaction problem (WCSP) is a powerful mathematical framework for combinatorial optimization. The branch-and-bound search paradigm is very successful in solving the WCSP but critically depends on the ordering in which variables are instantiated. In this paper, we introduce a new framework for dynamic variable ordering for solving the WCSP. This framework is inspired by regression decision tree learning. Variables are ordered dynamically based on samples of random assignments of values to variables as well as their corresponding total weights. Within this framework, we propose four variable ordering heuristics (sdr, inv-sdr, rr and inv-rr). We compare them withmore »many state-of-the-art dynamic variable ordering heuristics, and show that sdr and rr outperform them on many real-world and random benchmark instances.« less
  5. Many kinds of algorithms have been developed for solving the constraint satisfaction problem (WCSP), a combinatorial optimization problem that frequently appears in AI. Unfortunately, its NP-hardness prohibits the existence of an algorithm for solving it that is universally efficient on classical computers. Therefore, a peek into quantum computers may be imperative for solving the WCSP efficiently. In this paper, we focus on a specific type of quantum computer, called the quantum annealer, which approximately solves quadratic unconstrained binary optimization (QUBO) problems. We propose the first three hybrid quantum-classical algorithms (HQCAs) for the WCSP: one specifically for the binary Boolean WCSPmore »and the other two for the general WCSP. We experimentally show that the HQCA based on simple polynomial reformulation works well on the binary Boolean WCSP, but the HQCA based on the constraint composite graph works best on the general WCSP.« less
  6. Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hardmore »scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.« less
    Free, publicly-accessible full text available December 1, 2023
  7. Free, publicly-accessible full text available October 1, 2022
  8. How bio-membranes are self-organized to perform their functions remains a pivotal issue in biological and chemical science. Understanding the self-assembly principles of lipid-like molecules hence becomes crucial. Here we report the meso-structural evolution of amphiphilic sphere-rod conjugates (giant lipids), and study the roles of geometric parameters (head-tail ratio and cross-section area) during this course. As a prototype system, giant lipids resemble natural lipidic molecules by capturing their essential features including head-tail configuration, monodispersed molecular weight distribution and minor interpenetration of hydrophobic tails. We demonstrate the self-assembly behavior of two categories of giant lipids (I-shape and T-shape, a total of 8more »molecules). A rich variety of meso-structures are constructed in solution state and their molecular packing models are rationally understood. We streamline the driving forces of morphological evolution from both geometric and thermodynamic perspective. Giant lipids recast the phase behavior of both linear and branched lipidic molecules to certain degree, while the abundant self-assembled morphologies reveal distinct physiochemical behaviors when geometric parameters deviate from natural analogues.« less