Joint photometric cross-calibration and SED modeling in BayeSN yields G26 model with 12% NMAD scatter reduction on DES-SN5YR supernovae at z<0.7.
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6 Pith papers cite this work, alongside 156 external citations. Polarity classification is still indexing.
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Vision-language models underperform specialized astronomical methods on real observational data, with accuracy improving when physical explanations are provided in prompts and when raw numerical measurements replace rendered plots.
slicersim is a modular Python tool that simulates IFS observations including noise and instrumental effects, demonstrating that the Lazuli Space Observatory could observe 8000 SNe Ia (z=0–1.5) at S/N=25 per resolution element in 1.5 years of on-sky time.
BayeSN analysis of ZTF Type Ia supernovae confirms a ~0.1 mag intrinsic environmental step in standardized brightness that is not explained by differences in dust extinction properties.
Proposes foundation models and decision-theoretic policies to manage evolving source representations and optimize follow-up resource allocation in LSST-scale time-domain astronomy.
LStein is presented as a novel visualization approach for sparse 2.5-dimensional data, implemented in Python and demonstrated on astronomical lightcurves.
citing papers explorer
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BayeSN $\times$ Dovekie: Joint Photometric Cross-calibration and SED Modelling of Type Ia Supernovae
Joint photometric cross-calibration and SED modeling in BayeSN yields G26 model with 12% NMAD scatter reduction on DES-SN5YR supernovae at z<0.7.
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A systematic evaluation of vision-language models for observational astronomical reasoning tasks
Vision-language models underperform specialized astronomical methods on real observational data, with accuracy improving when physical explanations are provided in prompts and when raw numerical measurements replace rendered plots.
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slicersim: A python package to simulate image slicer spectroscopic observations -- application to the Lazuli Spectrograph
slicersim is a modular Python tool that simulates IFS observations including noise and instrumental effects, demonstrating that the Lazuli Space Observatory could observe 8000 SNe Ia (z=0–1.5) at S/N=25 per resolution element in 1.5 years of on-sky time.
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On the origin of the environmental step: A BayeSN view of the ZTF SN Ia DR2
BayeSN analysis of ZTF Type Ia supernovae confirms a ~0.1 mag intrinsic environmental step in standardized brightness that is not explained by differences in dust extinction properties.
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Toward decision-aware AI for LSST-scale time-domain astronomy
Proposes foundation models and decision-theoretic policies to manage evolving source representations and optimize follow-up resource allocation in LSST-scale time-domain astronomy.
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LStein: A new approach to visualizing sparse 2.5-dimensional data
LStein is presented as a novel visualization approach for sparse 2.5-dimensional data, implemented in Python and demonstrated on astronomical lightcurves.