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  1. Free, publicly-accessible full text available June 11, 2024
  2. Free, publicly-accessible full text available April 1, 2024
  3. Abstract Galactic science encompasses a wide range of subjects in the study of the Milky Way and Magellanic Clouds, from young stellar objects to X-ray binaries. Mapping these populations, and exploring transient phenomena within them, are among the primary science goals of the Vera C. Rubin Observatory’s Legacy Survey of Space and Time. While early versions of the survey strategy dedicated relatively few visits to the Galactic Plane region, more recent strategies under consideration envision a higher cadence within selected regions of high scientific interest. The range of galactic science presents a challenge in evaluating which strategies deliver the highest scientific returns. Here we present metrics designed to evaluate Rubin survey strategy simulations, based on the cadence of observations they deliver within regions of interest to different topics in galactic science, using variability categories defined by timescale. We also compare the fractions of exposures obtained in each filter with those recommended for the different science goals. We find that the baseline _ v2.x simulations deliver observations of the high-priority regions at sufficiently high cadence to reliably detect variability on timescales >10 days or more. Follow-up observations may be necessary to properly characterize variability, especially transients, on shorter timescales. Combining the regions of interest for all the science cases considered, we identify those areas of the Galactic Plane and Magellanic Clouds of highest priority. We recommend that these refined survey footprints be used in future simulations to explore rolling cadence scenarios, and to optimize the sequence of observations in different bandpasses. 
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    Free, publicly-accessible full text available July 1, 2024
  4. Organic trisradicals featuring three-fold symmetry have attracted significant interest because of their unique magnetic properties associated with spin frustration. Herein, we describe the synthesis and characterization of a triangular prism-shaped organic cage for which we have coined the name PrismCage6+ and its trisradical trication—TR3(•+). PrismCage6+ is composed of three 4,4'-bipyridinium dications and two 1,3,5-phenylene units bridged by six methylene groups. In the solid state, PrismCage6+ adopts a highly twisted conformation with close to C3 symmetry as a result of encapsulating one PF6− anion as a guest. PrismCage6+ undergoes stepwise reduction to its mono-, di- and trisradical cations in MeCN on account of strong electronic communication between its 4,4'-bipyridinium units. TR3(•+), which is obtained by reduction of PrismCage6+ employing CoCp2, adopts a triangular prism-shaped conformation with close to C2v symmetry in the solid state. Temperature-dependent continuous-wave and nutation frequency-selective EPR spectra of TR3(•+) in frozen N,N-dimethylformamide indicate its doublet ground state. The doublet-quartet energy gap of TR3(•+) is estimated to be −0.06 kcal mol−1 and the critical temperature of spin-state conversion is found to be ca. 50 K, suggesting that it displays pronounced spin-frustration at the molecular level. To the best of our knowledge, this example is the first organic radical cage to exhibit spin frustration. The trisradical trication of PrismCage6+ opens up new possibilities for fundamental investigations and potential applications in the fields of both organic cages and spin chemistry. 
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    Free, publicly-accessible full text available June 1, 2024
  5. Many scientific applications rely on sparse direct solvers for their numerical robustness. However, performance optimization for these solvers remains a challenging task, especially on GPUs. This is due to workloads of small dense matrices that are different in size. Matrix decompositions on such irregular workloads are rarely addressed on GPUs. This paper addresses irregular workloads of matrix computations on GPUs, and their application to accelerate sparse direct solvers. We design an interface for the basic matrix operations supporting problems of different sizes. The interface enables us to develop irrLU-GPU, an LU decomposition on matrices of different sizes. We demonstrate the impact of irrLU-GPU on sparse direct LU solvers using NVIDIA and AMD GPUs. Experimental results are shown for a sparse direct solver based on a multifrontal sparse LU decomposition applied to linear systems arising from the simulation, using finite element discretization on unstructured meshes, of a high-frequency indefinite Maxwell problem. 
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