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Recent advancements in large language models (LLMs) have achieved promising performances across various applications. Nonetheless, the ongoing challenge of integrating long-tail knowledge continues to impede the seamless adoption of LLMs in specialized domains. In this work, we introduce DALK, a.k.a. Dynamic Co-Augmentation of LLMs and KG, to address this limitation and demonstrate its ability on studying Alzheimer's Disease (AD), a specialized sub-field in biomedicine and a global health priority. With a synergized framework of LLM and KG mutually enhancing each other, we first leverage LLM to construct an evolving AD-specific knowledge graph (KG) sourced from AD-related scientific literature, and then we utilize a coarse-to-fine sampling method with a novel self-aware knowledge retrieval approach to select appropriate knowledge from the KG to augment LLM inference capabilities. The experimental results, conducted on our constructed AD question answering (ADQA) benchmark, underscore the efficacy of DALK. Additionally, we perform a series of detailed analyses that can offer valuable insights and guidelines for the emerging topic of mutually enhancing KG and LLM. 

We develop a consistent adaptive framework in a multilevel collocated grid layout for simulating two-phase flows with adaptive mesh refinement (AMR). The conservative mo-mentum equations and the mass equation are solved in the present consistent framework. This consistent mass and momentum transport treatment greatly improves the accuracy and robustness for simulating two-phase flows with a high density ratio and high Reynolds number. The interface capturing level set method is coupled with the conservative form of the Navier–Stokes equations, and the multilevel reinitialization technique is applied for mass conservation. This adaptive framework allows us to advance all variables level by level using either the subcycling or the non-subcycling method to decouple the data ad-vancement on each level. The accuracy and robustness of the framework are validated by a variety of canonical two-phase flow problems. We demonstrate that the consistent scheme results in a numerically stable solution in flows with high density ratios(up to 106) and high Reynolds numbers(up to 106), while the inconsistent scheme exhibits non-physical fluid behaviors in these tests. Furthermore, it is shown that the subcycling and non-subcycling methods provide consistent results and that both of them can accurately resolve the interfaces of the two-phase flows with surface tension effects. Finally, a 3D breaking wave problem is simulated to show the efficiency and significant speedup of the proposed framework using AMR. 

We develop a consistent adaptive framework in a multilevel collocated grid layout for simulating two-phase flows with adaptive mesh refinement (AMR). The conservative mo-mentum equations and the mass equation are solved in the present consistent framework. This consistent mass and momentum transport treatment greatly improves the accuracy and robustness for simulating two-phase flows with a high density ratio and high Reynolds number. The interface capturing level set method is coupled with the conservative form of the Navier–Stokes equations, and the multilevel reinitialization technique is applied for mass conservation. This adaptive framework allows us to advance all variables level by level using either the subcycling or the non-subcycling method to decouple the data ad-vancement on each level. The accuracy and robustness of the framework are validated by a variety of canonical two-phase flow problems. We demonstrate that the consistent scheme results in a numerically stable solution in flows with high density ratios(up to 106) and high Reynolds numbers(up to 106), while the inconsistent scheme exhibits non-physical fluid behaviors in these tests. Furthermore, it is shown that the subcycling and non-subcycling methods provide consistent results and that both of them can accurately resolve the interfaces of the two-phase flows with surface tension effects. Finally, a 3D breaking wave problem is simulated to show the efficiency and significant speedup of the proposed framework using AMR. 

Abstract By measuring a linear response function directly, such as the dynamic susceptibility, one can understand fundamental material properties. However, a fresh perspective can be offered by studying fluctuations. This can be related back to the dynamic susceptibility through the fluctuation–dissipation theorem, which relates the fluctuations in a system to its response, an alternate route to access the physics of a material. Here, we describe a new X-ray tool for material characterization that will offer an opportunity to uncover new physics in quantum materials using this theorem. We provide details of the method and discuss the requisite analysis techniques in order to capitalize on the potential to explore an uncharted region of phase space. This is followed by recent results on a topological chiral magnet, together with a discussion of current work in progress. We provide a perspective on future measurements planned for work in unconventional superconductivity. Graphical abstract We describe a new X-ray tool for material characterization that will offer an opportunity to uncover new physics in quantum materials using coherent, short-pulsed X-rays. We provide details of the method and discuss the requisite analysis techniques in order to capitalize on the potential to explore an uncharted region of phase space. This is followed by recent results on a topological chiral magnet, together with a discussion of current work in progress. We provide a perspective on future measurements planned for work in unconventional superconductivity. 

Clusters of inertial particles in turbulence are usually identified from the spatial coherence of the particle concentration field, neglecting their temporal persistence. The latter is in fact essential to the ability of the particles to interact with each other and to modify the flow. Here, we leverage simulations of homogeneous isotropic turbulence laden with small heavy particles and develop a Lagrangian framework to follow them before, during and after their time as part of a coherent cluster. We define a criterion to establish whether a cluster survives over successive time steps, and use it to characterize its lifetime. We find that cluster lives have typical durations of a few Kolmogorov time scales, with positive correlation between cluster size and lifetime. Increasing inertia and gravitational settling both lead to longer lifetimes. Small clusters emerge from the coagulation of non-clustered particles, quickly followed by disintegration into prevalently non-clustered particles. By contrast, large clusters result from the recombination of other large clusters. The birth of a cluster is preceded by an exponential contraction of the particle cloud, and its death coincides with the beginning of a slower exponential expansion, The contraction is simultaneous to a decline in the local small-scale turbulence activity, while the expansion is accompanied by its recovery. Therefore, during their lifetime, the clusters experience lower-than-average enstrophy and strain rate in the fluid. This relatively quiescent state of the flow is thus a necessary condition for the cluster survival, at least in the considered range of turbulence intensity and particle inertia. 

The development of new modes at x-ray free electron lasers has inspired novel methods for studying fluctuations at different energies and timescales. For closely spaced x-ray pulses that can be varied on ultrafast time scales, we have constructed a pair of advanced instruments to conduct studies targeting quantum materials. We first describe a prototype instrument built to test the proof-of-principle of resonant magnetic scattering using ultrafast pulse pairs. This is followed by a description of a new endstation, the so-called fluctuation–dissipation measurement instrument, which was used to carry out studies with a fast area detector. In addition, we describe various types of diagnostics for single-shot contrast measurements, which can be used to normalize data on a pulse-by-pulse basis and calibrate pulse amplitude ratios, both of which are important for the study of fluctuations in materials. Furthermore, we present some new results using the instrument that demonstrates access to higher momentum resolution.