Rubin-LSST

Abstract:

We present an expanded template library for the supernova identification (SNID) software, along with updated source files that make it easy to merge our templates—and other major SNID libraries—into the base code. This expansion, dubbed “Super-SNID,” increases the number of spectra for under-represented supernova classes (e.g., SNe Ia-02cx, Ibn) and adds new classes (e.g., SLSNe, TDEs, LFBOTs). Super-SNID includes 841 spectral templates for 161 objects, primarily from the Public ESO Spectroscopic Survey of Transient Objects Data Releases 1–4. The library is available on GitHub with simple installation instructions.

Abstract:

Recent results from Type Ia supernovae, baryon acoustic oscillations (BAOs), and the cosmic microwave background (CMB) indicate (1) potentially discrepant measurements of the matter density Ωm and Hubble constant H0 in the ΛCDM model when analyzed individually and (2) hint of dynamical dark energy in a w0waCDM model when data are combined in a joint analysis. We examine whether underlying dynamical dark energy cosmologies favored by data would result in biases in Ωm and H0 for each probe when analyzed individually under ΛCDM. We generate mock data sets in w0waCDM cosmologies, fit the individual probes under the ΛCDM model, and find that expected biases in Ωm are ∼0.03. Notably, the Ωm differences between probes are consistent with values observed in real data sets. We also observe that mock DESI-BAO data sets generated in the w0wa CDM cosmologies will lead to a biased measurement of H0 higher by ∼1.2 km s−1 Mpc−1 when fitted under ΛCDM, appearing to mildly improve the Hubble tension, but as the true underlying H0 is lower, the tension is in fact worsened. We find that the Ωm discrepancies, the high BAO H0 relative to the CMB, and the joint dynamical dark energy signal are all related effects that could be explained simultaneously with either new physics or new systematics. While it is possible to unite many of the discrepancies seen in recent analyses along a single axis, our results underscore the importance of understanding systematic differences in data sets, as they have unique impacts in different cosmological parameter spaces.