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 5yr Dark Energy Survey (DES) data set using the SuperNNova classifier. Our approach, which does not rely on any information from the SN hostgalaxy, recovers SNe Ia that might otherwise be lost due to a lack of an identifiable host. We select $2{,}298$ highquality SNe Ia from the DES 5yr 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 DESSN5YR 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 lightcurve 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 hostgalaxies. Future surveys such as LSST will also face an additional challenge, the scarcity of spectroscopic resources for followup. When applying our novel method to DES data, we reduce the need for followup by a factor of four and three for hostgalaxy and live SN, respectively, compared to earlier approaches. Our novel method thus leads to better optimization of spectroscopic resources for followup.
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ABSTRACT 
ABSTRACT We present a precise measurement of cosmological time dilation using the light curves of 1504 Type Ia supernovae from the Dark Energy Survey spanning a redshift range $0.1\lesssim z\lesssim 1.2$. We find that the width of supernova light curves is proportional to $(1+z)$, as expected for time dilation due to the expansion of the Universe. Assuming Type Ia supernovae light curves are emitted with a consistent duration $\Delta t_{\rm em}$, and parametrizing the observed duration as $\Delta t_{\rm obs}=\Delta t_{\rm em}(1+z)^b$, we fit for the form of time dilation using two methods. First, we find that a power of $b \approx 1$ minimizes the flux scatter in stacked subsamples of light curves across different redshifts. Secondly, we fit each target supernova to a stacked light curve (stacking all supernovae with observed bandpasses matching that of the target light curve) and find $b=1.003\pm 0.005$ (stat) $\pm \, 0.010$ (sys). Thanks to the large number of supernovae and large redshiftrange of the sample, this analysis gives the most precise measurement of cosmological time dilation to date, ruling out any nontimedilating cosmological models at very high significance.

Abstract We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated followup survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 <
z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of highqualityz > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a highquality external lowredshift sample consisting of 194 SNe Ia spanning 0.025 <z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω_{M}= 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration (q _{0}< 0 in ΛCDM) with over 5σ confidence. We find in flat $({\mathrm{\Omega}}_{\mathrm{M}},w)=({0.264}_{0.096}^{+0.074},{0.80}_{0.16}^{+0.14})$w CDM. For flatw _{0}w _{a}CDM, we find , consistent with a constant equation of state to within ∼2 $({\mathrm{\Omega}}_{\mathrm{M}},{w}_{0},{w}_{a})=({0.495}_{0.043}^{+0.033},{0.36}_{0.30}^{+0.36},{8.8}_{4.5}^{+3.7})$σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω_{M},w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses. 
Abstract 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 (DESSN5YR) photometric sample. For both DESSN5YR 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 (Δ
w ) 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 corecollapse SNe and peculiar SNe Ia in the simulation, we find that Δw 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 onw from the DESSN5YR sample of ∼0.03. We conclude that the bias onw from host galaxy mismatch is much smaller than the uncertainties expected from the DESSN5YR sample, but we encourage further studies to reduce this bias through better hostmatching algorithms or selection cuts. 
We present a measurement of the crosscorrelation between themore » « less
MagLim galaxies selected from the Dark Energy Survey (DES) first three years of observations (Y3) and cosmic microwave background (CMB) lensing from the Atacama Cosmology Telescope (ACT) Data Release 4 (DR4), reconstructed over ∼ 436 sq. deg of the sky. Our galaxy sample, which covers ∼ 4143 sq. deg, is divided into six redshift bins spanning the redshift range of 0.20 < z < 1.05. We adopt a blinding procedure until passing all consistency and systematics tests. After imposing scale cuts for the crosspower spectrum measurement, we reject the null hypothesis of no correlation at 9.1σ. We constrain cosmological parameters from a joint analysis of galaxy and CMB lensinggalaxy power spectra considering a flat ΛCDM model, marginalized over 23 astrophysical and systematic nuisance parameters. We find the clustering amplitude S_8 ≡ σ_8(Ω_m/0.3)^0.5 = 0.75+0.040.05. In addition, we constrain the linear growth of cosmic structure as a function of redshift. Our results are consistent with recent DES Y3 analyses and suggest a preference for a lower S_8 compared to results from measurements of CMB anisotropies by the Planck satellite, although at a mild level (< 2σ) of statistical significance.Free, publiclyaccessible full text available January 1, 2025 
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 5Year (DESSN5YR) photometric sample. For both DESSN5YR 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 Iaonly simulations, we find Dw = 0.0013 +/ 0.0026 with constraints from the cosmic microwave background (CMB). Including corecollapse 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 DESSN5YR 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 DESSN5YR sample, but we encourage further studies to reduce this bias through better hostmatching algorithms or selection cuts.more » « less

ABSTRACT Clusters of galaxies trace the most nonlinear peaks in the cosmic density field. The weak gravitational lensing of background galaxies by clusters can allow us to infer their masses. However, galaxies associated with the local environment of the cluster can also be intrinsically aligned due to the local tidal gradient, contaminating any cosmology derived from the lensing signal. We measure this intrinsic alignment in Dark Energy Survey (DES) Year 1 redMaPPer clusters. We find evidence of a nonzero mean radial alignment of galaxies within clusters between redshifts 0.1–0.7. We find a significant systematic in the measured ellipticities of cluster satellite galaxies that we attribute to the central galaxy flux and other intracluster light. We attempt to correct this signal, and fit a simple model for intrinsic alignment amplitude (AIA) to the measurement, finding AIA = 0.15 ± 0.04, when excluding data near the edge of the cluster. We find a significantly stronger alignment of the central galaxy with the cluster dark matter halo at low redshift and with higher richness and central galaxy absolute magnitude (proxies for cluster mass). This is an important demonstration of the ability of large photometric data sets like DES to provide direct constraints on the intrinsic alignment of galaxies within clusters. These measurements can inform improvements to smallscale modelling and simulation of the intrinsic alignment of galaxies to help improve the separation of the intrinsic alignment signal in weak lensing studies.

ABSTRACT Crosscorrelation between weak lensing of the Cosmic Microwave Background (CMB) and weak lensing of galaxies offers a way to place robust constraints on cosmological and astrophysical parameters with reduced sensitivity to certain systematic effects affecting individual surveys. We measure the angular crosspower spectrum between the Atacama Cosmology Telescope (ACT) DR4 CMB lensing and the galaxy weak lensing measured by the Dark Energy Survey (DES) Y3 data. Our baseline analysis uses the CMB convergence map derived from ACTDR4 and Planck data, where most of the contamination due to the thermal Sunyaev Zel’dovich effect is removed, thus avoiding important systematics in the crosscorrelation. In our modelling, we consider the nuisance parameters of the photometric uncertainty, multiplicative shear bias and intrinsic alignment of galaxies. The resulting crosspower spectrum has a signaltonoise ratio = 7.1 and passes a set of null tests. We use it to infer the amplitude of the fluctuations in the matter distribution (S8 ≡ σ8(Ωm/0.3)0.5 = 0.782 ± 0.059) with informative but wellmotivated priors on the nuisance parameters. We also investigate the validity of these priors by significantly relaxing them and checking the consistency of the resulting posteriors, finding them consistent, albeit only with relatively weak constraints. This crosscorrelation measurement will improve significantly with the new ACTDR6 lensing map and form a key component of the joint 6×2pt analysis between DES and ACT.

We measure the impact of source galaxy clustering on higher order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show that this effect can exceed measurement uncertainties for common higher order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey (DES) Year 3 (Y3) data, we construct null tests for the sourceclusteringfree case, finding a pvalue of p = 4 × 10−3 (2.6σ) using thirdorder map moments and p = 3 × 10−11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either included in the model or minimized through ad hoc procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher order gravitational lensing statistics, e.g. higher order Npoint functions, waveletmoment observables, and deep learning or fieldlevel summary statistics of weak lensing maps.more » « less

Free, publiclyaccessible full text available February 9, 2025