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Abstract Recent in situ observations from Parker Solar Probe (PSP) near perihelia reveal ion beams, temperature anisotropies, and kinetic wave activity. These features are likely linked to solar wind heating and acceleration. During PSP Encounter 17 (at 11.4R_s) on 2023 September 26, the PSP/FIELDS instrument detected enhanced ion-scale wave activity associated with deviations from local thermodynamic equilibrium in ion velocity distribution functions (VDFs) observed by the PSP/Solar Probe Analyzers-Ion. Dense beams (secondary populations) were present in the proton VDFs during this wave activity. Using bi-Maxwellian fits to the proton VDFs, we found that the density of the proton beam population increased during the wave activity and, unexpectedly, surpassed the core population at certain intervals. Interestingly, the wave power was reduced during the intervals when the beam population density exceeded the core density. The drift velocity of the beams decreases from 0.9 to 0.7 of the Alfvén speed, and the proton core shows a higher temperature anisotropy (T_⊥/T_∥ > 2.5) during these intervals. We conclude that the observations during these intervals are consistent with a reconnection event during a heliospheric current sheet crossing. During this event,α-particle parameters (density, velocity, and temperature anisotropy) remained nearly constant. Using linear analysis, we examined how the proton beam drives instability or wave dissipation. Furthermore, we investigated the nonlinear evolution of ion kinetic instabilities using hybrid kinetic simulations. This study provides direct clues about energy transfer between particles and waves in the young solar wind. 

Score distillation sampling (SDS) has proven to be an important tool, enabling the use of large-scale diffusion priors for tasks operating in data-poor domains. Unfortunately, SDS has a number of characteristic artifacts that limit its usefulness in general-purpose applications. In this paper, we make progress toward understanding the behavior of SDS and its variants by viewing them as solving an optimal-cost transport path from a source distribution to a target distribution. Under this new interpretation, these methods seek to transport corrupted images (source) to the natural image distribution (target). We argue that current methods’ characteristic artifacts are caused by (1) linear approximation of the optimal path and (2) poor estimates of the source distribution. We show that calibrating the text conditioning of the source distribution can produce high-quality generation and translation results with little extra overhead. Our method can be easily applied across many domains, matching or beating the performance of specialized methods. We demonstrate its utility in text-to-2D, text-based NeRF optimization, translating paintings to real images, optical illusion generation, and 3D sketch-to-real. We compare our method to existing approaches for score distillation sampling and show that it can produce high-frequency details with realistic colors. 

We investigate intermittent plasticity in nanopillars of nanocrystalline molybdenum based on in situ transmission electron microscopy observations. By correlating electron imaging results with the measured nanopillar mechanical response, we demonstrate that the intermittent plasticity in nanocrystalline molybdenum is largely caused by dislocation avalanches. Electron imaging further reveals three types of dislocation avalanches, from intragranular to transgranular to cross-granular avalanches. The measured strain bursts resulted from avalanches have similar magnitudes to those reported for the molybdenum single-crystal pillars, while the corresponding flow stress in nanocrystalline molybdenum is greatly enhanced by the small grain size. Statistical analysis also shows that the avalanches behavior has similar characteristic as single crystals in the mean field theory model. Together, our findings here provide critical insights into the deformation mechanisms in a nanostructured body-centered-cubic metal.