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Highly excited Rydberg states and their interactions play an important role in quantum computing and simulation. These properties can be predicted accurately for alkali atoms with simple Rydberg level structures. However, an extension of these methods to more complex atoms such as alkaline-earth atoms has not been demonstrated or experimentally validated. Here, we present multichannel quantum defect models for highly excited ${}^{174}\mathrm{Yb}$and ${}^{171}\mathrm{Yb}$Rydberg states with $L\le 2$. The models are developed using a combination of existing literature data and new, high-precision laser and microwave spectroscopy in an atomic beam, and validated by detailed comparison with experimentally measured Stark shifts and magnetic moments. We then use these models to compute interaction potentials between two Yb atoms, and find excellent agreement with direct measurements in an optical tweezer array. From the computed interaction potential, we identify an anomalous Förster resonance that likely degraded the fidelity of previous entangling gates in ${}^{171}\mathrm{Yb}$using $F=3/2$Rydberg states. We then identify a more suitable $F=1/2$state, and achieve a state-of-the-art controlled- gate fidelity of $\mathcal{F}=0.994\left(1\right)$, with the remaining error fully explained by known sources. This work establishes a solid foundation for the continued development of quantum computing, simulation, and entanglement-enhanced metrology with Yb neutral atom arrays. Published by the American Physical Society2025 

RNA-binding proteins (RBPs) participate in all stages of RNA life cycle from transcription, splicing, to translation. Under the ENCODE project, a large number of RBPs were knocked down in human cancer cell lines, offering an excellent opportunity to infer targets of RBPs. Taking both RBP binding sites and RNA-seq profiles of RBP knockdown samples as input, we present a pipeline to identify causal RBP RNA interactions. The pipeline employs a recent functional chi-square test (FunChisq) that deciphers directional association, and utilizes a novel functional index that measures the effect size of functional dependency. We examined ∼45 million RBP RNA pairs in leukemia (K562) and liver cancer (HepG2) cell lines for functional patterns as causal interaction candidates. Here, we report a total of 936,707 RBP RNA pairs in the two cell lines that show statistically significant linear or nonlinear functional patterns. About 31% of these pairs have supportive biological evidence from other sources, suggesting the effectiveness of the pipeline. The interactions constitute RBP specific regulatory networks that may potentially represent core mechanisms in the two cancers. The pipeline is implemented through an R interface with pre-computed results and data libraries for users to query specific networks and visualize RBP RNA interactions. Such networks serve as a useful resource for studying RNA dysregulation in cancer.