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Olivine lattice preferred orientation (LPO), or texture, forms in relation to deformation mechanisms such as dislocation creep and can be observed in the upper mantle as seismic anisotropy. Olivine is also mechanically anisotropic, meaning that it responds to stresses differently depending on the direction of the stress. Understanding the interplay between anisotropic viscosity (AV) and LPO, and their role in deformation, is necessary for relating seismic anisotropy to mantle flow patterns. In this study, we employ three methods to predict olivine texture (D-Rex, MDM, and MDM+AV) in a shear box model and a subduction model. D-Rex and MDM are two representative texture development methods that have been compared before, and our results are in line with previous studies showing that textures computed by D-Rex develop faster and are stronger and more point-like than textures calculated with MDM. MDM+AV uses the same isotropic mantle stresses and particle paths as D-Rex and MDM but includes the effect of AV for texture predictions. MDM+AV predicts a texture similar to MDM with a distinct girdle-like orientation for simple shear deformation or at low strain in the subduction model. At larger strains, MDM+AV’s textures are more point-like and stronger compared to the other two methods. The effective viscosity for MDM+AV drops by up to 60% in a shear box model and can be either strengthened or weakened relative to isotropic viscosity for different regions of the subduction model experiencing different patterns of deformation. Our results emphasize the significant role of AV in olivine texture development, which could substantially affect geodynamic processes in the upper mantle. 

Abstract Gravitational-wave (GW) radiation from a coalescing compact binary is a standard siren, as the luminosity distance of each event can be directly measured from the amplitude of the signal. One possibility to constrain cosmology using the GW siren is to perform statistical inference on a population of binary black hole (BBH) events. In essence, this statistical method can be viewed as follows. We can modify the shape of the distribution of observed BBH events by changing the cosmological parameters until it eventually matches the distribution constructed from an astrophysical population model, thereby allowing us to determine the cosmological parameters. In this work, we derive the Cramér–Rao bound for both cosmological parameters and those governing the astrophysical population model from this statistical dark siren method by examining the Fisher information contained in the event distribution. Our study provides analytical insights and enables fast yet accurate estimations of the statistical accuracy of dark siren cosmology. Furthermore, we consider the bias in cosmology due to unmodeled substructures in the merger rate and mass distribution. We find that a 1% deviation in the astrophysical model can lead to a more than 1% error in the Hubble constant. This could limit the accuracy of dark siren cosmology when there are more than 10⁴BBH events detected.