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1. The Farmer: A Reproducible Profile-fitting Photometry Package for Deep Galaxy Surveys

   https://doi.org/10.3847/1538-4365/acf850  

   Weaver, J R ; Zalesky, L ; Kokorev, V ; McPartland, C_J R ; Chartab, N ; Gould, K_M L ; Shuntov, M ; Davidzon, I ; Faisst, A ; Stickley, N ; et al ( November 2023 , The Astrophysical Journal Supplement Series)

   While space-borne optical and near-infrared facilities have succeeded in delivering a precise and spatially resolved picture of our Universe, their small survey area is known to underrepresent the true diversity of galaxy populations. Ground-based surveys have reached comparable depths but at lower spatial resolution, resulting in source confusion that hampers accurate photometry extractions. What once was limited to the infrared regime has now begun to challenge ground-based ultradeep surveys, affecting detection and photometry alike. Failing to address these challenges will mean forfeiting a representative view into the distant Universe. We introduceThe Farmer: an automated, reproducible profile-fitting photometry package that pairs a library of smooth parametric models fromThe Tractorwith a decision tree that determines the best-fit model in concert with neighboring sources. Photometry is measured by fitting the models on other bands leaving brightness free to vary. The resulting photometric measurements are naturally total, and no aperture corrections are required. Supporting diagnostics (e.g.,χ²) enable measurement validation. As fitting models is relatively time intensive,The Farmeris built with high-performance computing routines. We benchmarkThe Farmeron a set of realistic COSMOS-like images and find accurate photometry, number counts, and galaxy shapes.The Farmeris already being utilized to produce catalogs for several large-area deep extragalactic surveys where it has been shown to tackle some of the most challenging optical and near-infrared data available, with the promise of extending to other ultradeep surveys expected in the near future.The Farmeris available to download from GitHub (https://github.com/astroweaver/the_farmer) and Zenodo (https://doi.org/10.5281/zenodo.8205817).

    

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2. Connecting the Light Curves of Type IIP Supernovae to the Properties of Their Progenitors

   https://doi.org/10.3847/1538-4357/ac77f3  

   Barker, Brandon L. ; Harris, Chelsea E. ; Warren, MacKenzie L. ; O’Connor, Evan P. ; Couch, Sean M. ( July 2022 , The Astrophysical Journal)

   Observations of core-collapse supernovae (CCSNe) reveal a wealth of information about the dynamics of the supernova ejecta and its composition but very little direct information about the progenitor. Constraining properties of the progenitor and the explosion requires coupling the observations with a theoretical model of the explosion. Here we begin with the CCSN simulations of Couch et al., which use a nonparametric treatment of the neutrino transport while also accounting for turbulence and convection. In this work we use the SuperNova Explosion Code to evolve the CCSN hydrodynamics to later times and compute bolometric light curves. Focusing on Type IIP SNe (SNe IIP), we then (1) directly compare the theoretical STIR explosions to observations and (2) assess how properties of the progenitor’s core can be estimated from optical photometry in the plateau phase alone. First, the distribution of plateau luminosities (L₅₀) and ejecta velocities achieved by our simulations is similar to the observed distributions. Second, we fit our models to the light curves and velocity evolution of some well-observed SNe. Third, we recover well-known correlations, as well as the difficulty of connecting any one SN property to zero-age main-sequence mass. Finally, we show that there is a usable, linear correlation between iron core mass andL₅₀such that optical photometry alone of SNe IIP can give us insights into the cores of massive stars. Illustrating this by application to a few SNe, we find iron core masses of 1.3–1.5M_⊙with typical errors of 0.05M_⊙. Data are publicly available online on Zenodo: doi:10.5281/zenodo.6631964.

    

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3. The Dark Energy Survey 5-yr photometrically classified type Ia supernovae without host-galaxy redshifts

   https://doi.org/10.1093/mnras/stae1953  

   Möller, A. ; Wiseman, P. ; Smith, M. ; Lidman, C. ; Davis, T_M ; Kessler, R. ; Sako, M. ; Sullivan, M. ; Galbany, L. ; Lee, J. ; et al ( August 2024 , Monthly Notices of the Royal Astronomical Society)

   Current and future Type Ia Supernova (SN Ia) surveys will need to adopt new approaches to classifying SNe and obtaining their redshifts without spectra if they wish to reach their full potential. We present here a novel approach that uses only photometry to identify SNe Ia in the 5-yr Dark Energy Survey (DES) data set using the SuperNNova classifier. Our approach, which does not rely on any information from the SN host-galaxy, recovers SNe Ia that might otherwise be lost due to a lack of an identifiable host. We select $2{,}298$ high-quality SNe Ia from the DES 5-yr data set an almost complete sample of detected SNe Ia. More than 700 of these have no spectroscopic host redshift and are potentially new SNIa compared to the DES-SN5YR cosmology analysis. To analyse these SNe Ia, we derive their redshifts and properties using only their light curves with a modified version of the SALT2 light-curve fitter. Compared to other DES SN Ia samples with spectroscopic redshifts, our new sample has in average higher redshift, bluer and broader light curves, and fainter host-galaxies. Future surveys such as LSST will also face an additional challenge, the scarcity of spectroscopic resources for follow-up. When applying our novel method to DES data, we reduce the need for follow-up by a factor of four and three for host-galaxy and live SN, respectively, compared to earlier approaches. Our novel method thus leads to better optimization of spectroscopic resources for follow-up.

    

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4. The Dark Energy Survey Supernova Program: Cosmological Biases from Host Galaxy Mismatch of Type Ia Supernovae

   https://doi.org/10.3847/1538-4357/ad251d  

   Qu, H. ; Sako, M. ; Vincenzi, M. ; Sánchez, C. ; Brout, D. ; Kessler, R. ; Chen, R. ; Davis, T. ; Galbany, L. ; Kelsey, L. ; et al ( March 2024 , The Astrophysical Journal)

   Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is nontrivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5 Yr (DES-SN5YR) photometric sample. For both DES-SN5YR data and simulations, we employ the directional light radius method for host galaxy matching. In our SN Ia simulations, we find that 1.7% of SNe are matched to the wrong host galaxy, with redshift differences between the true and matched hosts of up to 0.6. Using our analysis pipeline, we determine the shift in the dark energy equation of state parameter (Δw) due to including SNe with incorrect host galaxy matches. For SN Ia–only simulations, we find Δw= 0.0013 ± 0.0026 with constraints from the cosmic microwave background. Including core-collapse SNe and peculiar SNe Ia in the simulation, we find that Δwranges from 0.0009 to 0.0032, depending on the photometric classifier used. This bias is an order of magnitude smaller than the expected total uncertainty onwfrom the DES-SN5YR sample of ∼0.03. We conclude that the bias onwfrom host galaxy mismatch is much smaller than the uncertainties expected from the DES-SN5YR sample, but we encourage further studies to reduce this bias through better host-matching algorithms or selection cuts.

    

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5. The Dark Energy Survey Supernova Program: Cosmological Biases from Host Galaxy Mismatch of Type Ia Supernovae

   Qu, H. ; Sako, M. ; Vincenzi, M. ; Sanchez, C. ; Brout, D. ; Kessler, R. ; Chen, R. ; Galbany, L. ; Kelsey, L. ; Lee, J. ; et al ( July 2023 , The Astrophysical journal)

   Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is non-trivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5-Year (DES-SN5YR) photometric sample. For both DES-SN5YR data and simulations, we employ the directional light radius method for host galaxy matching. In our SN Ia simulations, we find that 1.7% of SNe are matched to the wrong host galaxy, with redshift difference between the true and matched host of up to 0.6. Using our analysis pipeline, we determine the shift in the dark energy equation of state parameter (Dw) due to including SNe with incorrect host galaxy matches. For SN Ia-only simulations, we find Dw = 0.0013 +/- 0.0026 with constraints from the cosmic microwave background (CMB). Including core-collapse SNe and peculiar SNe Ia in the simulation, we find that Dw ranges from 0.0009 to 0.0032 depending on the photometric classifier used. This bias is an order of magnitude smaller than the expected total uncertainty on w from the DES-SN5YR sample of around 0.03. We conclude that the bias on w from host galaxy mismatch is much smaller than the uncertainties expected from the DES-SN5YR sample, but we encourage further studies to reduce this bias through better host-matching algorithms or selection cuts. 

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