Infrared spectral signatures of light r-process elements in kilonovae
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2026) stag733
Abstract:
The Dark Energy Survey Supernova Program: A Reanalysis Of Cosmology Results And Evidence For Evolving Dark Energy With An Updated Type Ia Supernova Calibration
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2026) stag632
Abstract:
Abstract We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low redshift surveys, retraining the SALT3 light curve model and fixing a numerical approximation in the host galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises ∼1600 likely Type Ia SNe from DES and ∼200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain Ωm = 0.330 ± 0.015 in Flat ΛCDM which changes Ωm by −0.022 compared to DES-SN5YR. Combining DES-Dovekie with CMB data from Planck, ACT and SPT and the DESI DR2 measurements in a Flat w0waCDM cosmology, we find w0 = −0.803 ± 0.054, wa = −0.72 ± 0.21. Our results hold a significance of 3.2σ, reduced from 4.2σ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the Flat w0waCDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.Identifying Transient Hosts in LSST’s Deep Drilling Fields with Galaxy Catalogs
The Astrophysical Journal American Astronomical Society 1000:2 (2026) 289
Abstract:
The upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will enable astronomers to discover rare and distant astrophysical transients. Host-galaxy association is crucial for selecting the most scientifically interesting transients for follow-up. LSST deep drilling field (DDF) observations will detect distant transients occurring in galaxies below the detection limits of most all-sky catalogs. Here, we investigate the use of preexisting, field-specific catalogs for host identification in the DDFs and a ranking of their usefulness. We have compiled a database of 70 deep catalogs that overlap with the Rubin DDFs and constructed thin catalogs to be homogenized and combined for transient-host matching. A systematic ranking of their utility is discussed and applied based on the inclusion of information such as spectroscopic redshifts and morphological information. Utilizing this data against a Dark Energy Survey sample of supernovae with pre-identified hosts in the XMM-Large Scale Structure and the Extended Chandra Deep Field-South fields, we evaluate different methods for transient-host association in terms of both accuracy and processing speed. We also apply light data-cleaning techniques to identify and remove contaminants within our associations, such as diffraction spikes and blended galaxies where the correct host cannot be determined with confidence. We use a lightweight machine learning approach in the form of extreme gradient boosting to generate confidence scores in our contaminant selections and associated metrics. Finally, we discuss the computational expense of implementation within the LSST transient alert brokers, which will require efficient, fast-paced processing to handle the large stream of survey data.Discovery of energy-dependent phase variations in the polarization angle of Cen X-3
Astronomy & Astrophysics EDP Sciences 708 (2026) a94