Abstract We present Young Supernova Experimentgrizyphotometry of SN 2021hpr, the third Type Ia supernova sibling to explode in the Cepheid calibrator galaxy, NGC 3147. Siblings are useful for improving SN-host distance estimates and investigating their contributions toward the SN Ia intrinsic scatter (post-standardization residual scatter in distance estimates). We thus develop a principled Bayesian framework for analyzing SN Ia siblings. At its core is the cosmology-independent relative intrinsic scatter parameter,σRel: the dispersion of siblings distance estimates relative to one another within a galaxy. It quantifies the contribution toward the total intrinsic scatter,σ0, from within-galaxy variations about the siblings’ common properties. It also affects the combined distance uncertainty. We present analytic formulae for computing aσRelposterior from individual siblings distances (estimated using any SN model). Applying a newly trainedBayeSNmodel, we fit the light curves of each sibling in NGC 3147 individually, to yield consistent distance estimates. However, the wideσRelposterior meansσRel≈σ0is not ruled out. We thus combine the distances by marginalizing overσRelwith an informative prior:σRel∼U(0,σ0). Simultaneously fitting the trio’s light curves improves constraints on distanceandeach sibling’s individual dust parameters, compared to individual fits. Higher correlation also tightens dust parameter constraints. Therefore,σRelmarginalization yields robust estimates of siblings distances for cosmology, as well as dust parameters for sibling–host correlation studies. Incorporating NGC 3147's Cepheid distance yieldsH0= 78.4 ± 6.5 km s−1Mpc−1. Our work motivates analyses of homogeneous siblings samples, to constrainσReland its SN-model dependence.
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Modeling the Nonlinear–To–Linear Relationship Between Bulk and Pore Water Electrical Conductivity in Saturated Porous Media Using a Padé Approximant
Abstract A petrophysical model that accurately relates bulk electrical conductivity (σ) to pore fluid conductivity (σw) is critical to the interpretation of geophysical measurements. Classical models are either only applicable over a limited salinity regime or incorrectly explain the nonlinear‐to‐linear behavior of the σ(σw) relationship. In this study, asymptotic limits at zero and infinite salinity are first established in which, σ is expressed as a linear function of σwwith four parameters: cementation exponent (m), the equivalent value of volumetric surface electrical conductivity (σs), the volume fraction of overlapped diffuse layer (ϕod) and parameter χ representing the ratio of the volume fraction of the water phase to that of the solid phases in the surface conduction pathway. Subsequently, we bridge the gap between the two extremes by employing the Padé approximant (PA). Given that parameter χ exhibits a marginal influence on the σ(σw) curve, based on measurements for 15 samples, we identify its optimal value to be 0.4. After setting the optimal value ofχ, we proceed to evaluate the performance of the PA model by comparing its estimates and estimates made by two existing models to measured values from 27 rock samples and eight sediment samples. The comparison confirms that the PA model estimates are more accurate than estimates made by existing models, particularly at low salinity and for samples with higher cation exchange capacity. The PA model is advantageous in scenarios involving the interpretation of electrical data in freshwater environments.
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- Award ID(s):
- 2037504
- PAR ID:
- 10558492
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 60
- Issue:
- 12
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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