Comet NEOWISE

For the past several years, Space Exploration Technologies Corporation (SpaceX) has been propulsively landing first stage rocket boosters for reuse. Because the boosters return at supersonic speeds, they produce a sonic boom. As the landing cadence continues to increase, it is important to understand these sonic booms and how they propagate to the surrounding areas. This abstract reports on measurements made of the SpaceX Transporter-8 launch and landing of a Falcon-9 rocket at Vandenberg Space Force Base. A unique triple-boom shape is preserved over propagation distances as close as 300 m and as far as 25 km from the landing pad. At distances greater than about 1 km, the sonic boom peak overpressure exceeds the launch peak pressure. Additionally, sound exposure metrics indicate that the sonic boom itself is comparable to the rest of the launch noise. Conclusions from these results include that sonic booms should be considered alongside launch noise when considering sound exposure and that there remain several mysteries regarding the propagation of these unique triple booms.

Many material properties can be traced back to properties of their grain boundaries. Grain boundary energy (GBE), as a result, is a key quantity of interest in the analysis and modeling of microstructure. A standard method for calculating grain boundary energy is molecular dynamics (MD); however, on-the-fly MD calculations are not tenable due to the extensive computational time required. Lattice matching (LM) is a reduced-order method for estimating GBE quickly; however, it has only been tested against a relatively limited set of data, and does not have a suitable means for assessing error. In this work, we use the recently published dataset of Homer et al. (2022) to assess the performance of LM over the full range of GB space, and to equip LM with a metric for error estimation. LM is used to generate energy estimates, along with predictions of facet morphology, for each of the 7,304 boundaries in the Homer dataset. The relative and absolute error of LM, based on the reported MD data, is found to be 5%-8%. An essential part of the LM method is the faceting relaxation, which corrects the expected energy by convexification across the compact space (S2) S 2) of boundary plane orientations. The original Homer dataset did not promote faceting, but upon extended annealing, it is shown that facet patterns similar to those predicted by LM emerge.

Due to the difficulty and expense of underwater field trials, a high-fidelity underwater simulator is a necessity for testing and developing algorithms. To fill this need, we present HoloOcean, an open-source underwater simulator, built upon Unreal Engine 4 (UE4). HoloOcean comes equipped with multiagent support, various sensor implementations of common underwater sensors, and simulated communications support. Due to being built upon UE4, new environments are straightforward to add, enabling easy extensions to be built. HoloOcean is controlled via a simple Python interface, allowing simple installation via pip, and requiring few lines of code to execute simulations. Each agent is equipped with various control schemes and dynamics that can be customized via the Python interface. Also included is a novel sonar sensor framework that leverages an octree representation of the environment for efficient and realistic sonar imagery generation. In addition, to improve the authenticity of the imaging sonar simulation, we use a novel cluster-based multipath ray-tracing algorithm, various probabilistic noise models, and properties of reflecting surfaces. We also leverage the sonar simulation framework to simulate sidescan, single-beam, and multibeam profiling sonars.

Bronin et al. [Phys. Rev. E 108, 045209 (2023)] recently reported molecular-dynamics simulations of ultracold neutral plasmas expanding in a quadrupole magnetic field. While the main results are in agreement with prior experimental measurements, we present data showing oscillations not captured in the simulations of Bronin et al. Plasmas formed using pulsed or continuous-wave ionization processes have similar confinement times.

The past few decades have made clear that the properties and performances of emerging functional and quantum materials can depend strongly on their local atomic and/or magnetic structure, particularly when details of the local structure deviate from the long-range structure averaged over space and time. Traditional methods of structural refinement (e.g., Rietveld) are typically sensitive only to the average structure, creating a need for more advanced structural probes suitable for extracting information about structural correlations on short length- and time-scales. In this Perspective, we describe the importance of local magnetic structure in several classes of emerging materials and present the magnetic pair distribution function (mPDF) technique as a powerful tool for studying short-range magnetism from neutron total-scattering data. We then provide a selection of examples of mPDF analysis applied to magnetic materials of recent technological and fundamental interest, including the antiferromagnetic semiconductor MnTe, geometrically frustrated magnets, and iron-oxide magnetic nanoparticles. The rapid development of mPDF analysis since its formalization a decade ago puts this technique in a strong position for making continued impact in the study of local magnetism in emerging materials.