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Creators/Authors contains: "Strolger, L"

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  1. Abstract In an effort to search for faint sources of emission over arbitrary timescales, we present a novel method for analyzing forced photometry light curves in difference imaging from optical surveys. Our method “ATLAS Clean,” or ATClean, utilizes the reported fluxes, uncertainties, and fits to the point-spread function (PSF) from difference images to quantify the statistical significance of individual measurements. We apply this method to control light curves across the image to determine whether any source of flux is present in the data for a range of specific timescales. From ATLASo-band imaging at the site of the Type II supernova (SN) 2023ixf in M101 from 2015–2023, we show that this method accurately reproduces the 3σflux limits produced from other, more computationally expensive methods. We derive limits for emission on timescales of 5 days and 80–300 days at the site of SN 2023ixf, which are 19.8 and 21.3 mag, respectively. The latter limits rule out variability for unextinguished red supergiants with initial masses >22M, comparable to the most luminous predictions for the SN 2023ixf progenitor system. We also compare our limits to short-timescale outbursts, similar to those expected for Type IIn SN progenitor stars or the Type II SN 2020tlf, and rule out outburst ejecta masses of >0.021M, much lower than the inferred mass of circumstellar matter around SN 2023ixf in the literature. In the future, these methods can be applied to any forced photometry on difference imaging from other surveys, such as Rubin optical imaging. 
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    Free, publicly-accessible full text available January 21, 2026
  2. Abstract A bright (mF150W,AB= 24 mag),z= 1.95 supernova (SN) candidate was discovered in JWST/NIRCam imaging acquired on 2023 November 17. The SN is quintuply imaged as a result of strong gravitational lensing by a foreground galaxy cluster, detected in three locations, and remarkably is the second lensed SN found in the same host galaxy. The previous lensed SN was called “Requiem,” and therefore the new SN is named “Encore.” This makes the MACS J0138.0−2155 cluster the first known system to produce more than one multiply imaged SN. Moreover, both SN Requiem and SN Encore are Type Ia SNe (SNe Ia), making this the most distant case of a galaxy hosting two SNe Ia. Using parametric host fitting, we determine the probability of detecting two SNe Ia in this host galaxy over a ∼10 yr window to be ≈3%. These observations have the potential to yield a Hubble constant (H0) measurement with ∼10% precision, only the third lensed SN capable of such a result, using the three visible images of the SN. Both SN Requiem and SN Encore have a fourth image that is expected to appear within a few years of ∼2030, providing an unprecedented baseline for time-delay cosmography. 
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  3. Abstract A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 (∼2800–8700 Å central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2μm with the open-source model-training softwareSALTshaker, which can easily accommodate future observations. Using simulated data, we show that the training process constrains the NIR model to ∼2%–3% across the phase range (−20 to 50 days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to ∼30% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to ∼20%. For SN Ia observations expected from the Roman Space Telescope, SALT3-NIR increases the amount of usable data in the SALT framework by ∼20% at redshiftz≲ 0.4 and by ∼50% atz≲ 0.15. The SALT3-NIR model is part of the open-sourceSNCosmoandSNANASN Ia cosmology packages. 
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