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Möller, A.

Publications and source records attributed to Möller, A..

At least 19 records

Constraints on compact objects from the Dark Energy Survey 5-yr supernova sample

ABSTRACT Gravitational lensing magnification of Type Ia supernovae (SNe Ia) allows information to be obtained about the distribution of matter on small scales. In this paper, we derive limits on the fraction $\alpha$ of the total matter density in compact objects (which comprise stars, stellar remnants, small stellar groupings, and primordial black holes) of mass M > 0.03 ${\rm M}_{\odot }$ over cosmological distances. Using 1532 SNe Ia from the Dark Energy Survey Year 5 sample (DES-SN5YR) combined with a Bayesian prior for the absolute magnitude M, we obtain α < 0.12 at the 95 per cent confidence level after marginalization over cosmological parameters, lensing due to large-scale structure, and intrinsic non-Gaussianity. Similar results are obtained using priors from the cosmic microwave background, baryon acoustic oscillations, and galaxy weak lensing, indicating our results do not depend on the background cosmology. We argue our constraints are likely to be conservative (in the sense of the values we quote being higher than the truth), but discuss scenarios in which they could be weakened by systematics of the order of $\Delta \alpha \sim 0.04$.

79 ASTRONOMY AND ASTROPHYSICS↗

The Dark Energy Survey Supernova Program: Cosmological Analysis and Systematic Uncertainties

We present the full Hubble diagram of photometrically classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7000 host galaxies. Based on the light-curve quality, we select 1635 photometrically identified SNe Ia with spectroscopic redshift 0.10 < z < 1.13, which is the largest sample of supernovae from any single survey and increases the number of known z > 0.5 supernovae by a factor of 5. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are ${\sigma }_{{{\rm{\Omega }}}_{M},\mathrm{stat}+\mathrm{sys}}^{{\rm{\Lambda }}\mathrm{CDM}}=$ 0.017 in a flat ΛCDM model, and $({\sigma }_{{{\rm{\Omega }}}_{M}},{\sigma }_{w}{)}_{\mathrm{stat}+\mathrm{sys}}^{w\mathrm{CDM}}$ = (0.082, 0.152) in a flat wCDM model. Combining the DES SN data with the highly complementary cosmic microwave background measurements by Planck Collaboration reduces by a factor of 4 uncertainties on cosmological parameters. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗

The Dark Energy Survey Supernova Program: Light Curves and 5 Yr Data Release

We present griz photometric light curves for the full 5 yr of the Dark Energy Survey Supernova (DES-SN) program, obtained with both forced point-spread function photometry on difference images (DiffImg) performed during survey operations, and scene modelling photometry (SMP) on search images processed after the survey. This release contains 31,636 DiffImg and 19,706 high-quality SMP light curves, the latter of which contain 1635 photometrically classified SNe that pass cosmology quality cuts. This sample spans the largest redshift (z) range ever covered by a single SN survey (0.1 < z < 1.13) and is the largest single sample from a single instrument of SNe ever used for cosmological constraints. We describe in detail the improvements made to obtain the final DES-SN photometry and provide a comparison to what was used in the 3 yr DES-SN spectroscopically confirmed Type Ia SN sample. We also include a comparative analysis of the performance of the SMP photometry with respect to the real-time DiffImg forced photometry and find that SMP photometry is more precise, more accurate, and less sensitive to the host-galaxy surface brightness anomaly. The public release of the light curves and ancillary data can be found at github.com/des-science/DES-SN5YR and doi:10.5281/zenodo.12720777.

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Dark Energy Survey: A 2.1% measurement of the angular baryonic acoustic oscillation scale at redshift z eff = 0.85 from the final dataset

Here, we present the angular diameter distance measurement obtained with the baryonic acoustic oscillation (BAO) feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6 < z <1.2, with an effective redshift at z eff = 0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to D M ⁡(z eff )/r d = 19.51 ± 0.41 (at 68.3% confidence interval), resulting from comparing the BAO position in our data to that predicted by planck Λ⁢CDM via the BAO shift parameter α =(D M /r d )/(D M /r d ) PLANCK . To achieve this, the BAO shift is measured with three different methods, angular correlation function (ACF), angular power spectrum (APS), and projected correlation function (PCF), obtaining α = 0.952 ± 0.023, 0.962 ± 0.022, and 0.955 ± 0.020, respectively, which we combine to α = 0.957 ± 0.020, including systematic errors. When compared with the Λ⁢CDM model that best fits planck data, this measurement is found to be 4.3% and 2.1⁢σ below the angular BAO scale predicted. To date, it represents the most precise angular BAO measurement at z > 0.75 from any survey and the most precise measurement at any redshift from photometric surveys. The analysis was performed blinded to the BAO position, and it is shown to be robust against analysis choices, data removal, redshift calibrations, and observational systematics.

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The dark energy survey supernova program: investigating beyond-ΛCDM

We report constraints on a variety of non-standard cosmological models using the full 5-yr photometrically classified type Ia supernova sample from the Dark Energy Survey (DES-SN5YR). Both Akaike Information Criterion (AIC) and Suspiciousness calculations find no strong evidence for or against any of the non-standard models we explore. When combined with external probes, the AIC and Suspiciousness agree that 11 of the 15 models are moderately preferred over Flat-|$\Lambda$|CDM suggesting additional flexibility in our cosmological models may be required beyond the cosmological constant. We also provide a detailed discussion of all cosmological assumptions that appear in the DES supernova cosmology analyses, evaluate their impact, and provide guidance on using the DES Hubble diagram to test non-standard models. An approximate cosmological model, used to perform bias corrections to the data holds the biggest potential for harbouring cosmological assumptions. We show that even if the approximate cosmological model is constructed with a matter density shifted by |$\Delta \Omega _{\rm m}\sim 0.2$| from the true matter density of a simulated data set the bias that arises is subdominant to statistical uncertainties. Nevertheless, we present and validate a methodology to reduce this bias.

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Core-collapse supernovae in the Dark Energy Survey: luminosity functions and host galaxy demographics

ABSTRACT We present the luminosity functions and host galaxy properties of the Dark Energy Survey (DES) core-collapse supernova (CCSN) sample, consisting of 69 Type II and 50 Type Ibc spectroscopically and photometrically confirmed supernovae over a redshift range 0.045 < z < 0.25. We fit the observed DES griz CCSN light curves and K-correct to produce rest-frame R-band light curves. We compare the sample with lower redshift CCSN samples from Zwicky Transient Facility (ZTF) and Lick Observatory Supernova Search (LOSS). Comparing luminosity functions, the DES and ZTF samples of SNe II are brighter than that of LOSS with significances of 3.0σ and 2.5σ, respectively. While this difference could be caused by redshift evolution in the luminosity function, simpler explanations such as differing levels of host extinction remain a possibility. We find that the host galaxies of SNe II in DES are on average bluer than in ZTF, despite having consistent stellar mass distributions. We consider a number of possibilities to explain this – including galaxy evolution with redshift, selection biases in either the DES or ZTF samples, and systematic differences due to the different photometric bands available – but find that none can easily reconcile the differences in host colour between the two samples and thus its cause remains uncertain.

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Radio transients and variables in the tenth Deeper, Wider, Faster observing run

The Deeper, Wider, Faster (DWF) program coordinates observations with telescopes across the electromagnetic spectrum, searching for transients on time-scales of milliseconds to days. The tenth DWF observing run was carried out in near real-time during September 2021, and consisted of six consecutive days of observations of the NGC 6744 galaxy group and a field containing the repeating fast radio burst FRB 190711 with the Australian Square Kilometre Array Pathfinder, the Dark Energy Camera, the Hard X-ray Modulation Telescope, and the Parkes 64-m ‘Murriyang’ radio telescope. Here, in this work, we present the results of an image-domain search for transient, variable, and circularly polarized sources carried out with ASKAP, using data from the observing run along with test observations prior to the run and follow-up observations carried out during and after the run. We identified eight variable radio sources, consisting of one pulsar, six stellar systems (five of which exhibit circularly polarized emission), and one previously uncatalogued source. Of particular interest is the detection of pulses from the ultra-cool dwarf SCR J1845–6357 with a period of 14.2 ± 0.3 h in good agreement with the known optical rotation period, making this the slowest rotating radio-loud ultra-cool dwarf discovered.

79 ASTRONOMY AND ASTROPHYSICS↗

Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey

ABSTRACT Recent analyses have found intriguing correlations between the colour (c) of type Ia supernovae (SNe Ia) and the size of their ‘mass-step’, the relationship between SN Ia host galaxy stellar mass (Mstellar) and SN Ia Hubble residual, and suggest that the cause of this relationship is dust. Using 675 photometrically classified SNe Ia from the Dark Energy Survey 5-yr sample, we study the differences in Hubble residual for a variety of global host galaxy and local environmental properties for SN Ia subsamples split by their colour. We find a 3σ difference in the mass-step when comparing blue (c < 0) and red (c > 0) SNe. We observe the lowest r.m.s. scatter (∼0.14 mag) in the Hubble residual for blue SNe in low mass/blue environments, suggesting that this is the most homogeneous sample for cosmological analyses. By fitting for c-dependent relationships between Hubble residuals and Mstellar, approximating existing dust models, we remove the mass-step from the data and find tentative ∼2σ residual steps in rest-frame galaxy U − R colour. This indicates that dust modelling based on Mstellar may not fully explain the remaining dispersion in SN Ia luminosity. Instead, accounting for a c-dependent relationship between Hubble residuals and global U − R, results in ≤1σ residual steps in Mstellar and local U − R, suggesting that U − R provides different information about the environment of SNe Ia compared to Mstellar, and motivating the inclusion of galaxy U − R colour in SN Ia distance bias correction.

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The Dark Energy Survey Supernova Program results: type Ia supernova brightness correlates with host galaxy dust

ABSTRACT Cosmological analyses with type Ia supernovae (SNe Ia) often assume a single empirical relation between colour and luminosity (β) and do not account for varying host-galaxy dust properties. However, from studies of dust in large samples of galaxies, it is known that dust attenuation can vary significantly. Here, we take advantage of state-of-the-art modelling of galaxy properties to characterize dust parameters (dust attenuation AV, and a parameter describing the dust law slope RV) for 1100 Dark Energy Survey (DES) SN host galaxies. Utilizing optical and infrared data of the hosts alone, we find three key aspects of host dust that impact SN cosmology: (1) there exists a large range (∼1–6) of host RV; (2) high-stellar mass hosts have RV on average ∼0.7 lower than that of low-mass hosts; (3) for a subsample of 81 spectroscopically classified SNe there is a significant (>3σ) correlation between the Hubble diagram residuals of red SNe Ia and the host RV that when corrected for reduces scatter by $\sim 13{{\ \rm per\ cent}}$ and the significance of the ‘mass step’ to ∼1σ. These represent independent confirmations of recent predictions based on dust that attempted to explain the puzzling ‘mass step’ and intrinsic scatter (σint) in SN Ia analyses.

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Using host galaxy spectroscopy to explore systematics in the standardization of Type Ia supernovae

We use stacked spectra of the host galaxies of photometrically identified Type Ia supernovae (SNe Ia) from the Dark Energy Survey (DES) to search for correlations between Hubble diagram residuals and the spectral properties of the host galaxies. Utilizing full spectrum fitting techniques on stacked spectra binned by Hubble residual, we find no evidence for trends between Hubble residuals and properties of the host galaxies that rely on spectral absorption features (<1.3σ), such as stellar population age, metallicity, and mass-to-light ratio. However, we find significant trends between the Hubble residuals and the strengths of [O ii] (4.4σ) and the Balmer emission lines (3σ). These trends are weaker than the well-known trend between Hubble residuals and host galaxy stellar mass (7.2σ) that is derived from broad-band photometry. After light-curve corrections, we see fainter SNe Ia residing in galaxies with larger line strengths. We also find a trend (3σ) between Hubble residual and the Balmer decrement (a measure of reddening by dust) using H β and H γ. The trend, quantified by correlation coefficients, is slightly more significant in the redder SNe Ia, suggesting that the bluer SNe Ia are relatively unaffected by dust in the interstellar medium of the host and that dust contributes to current Hubble diagram scatter impacting the measurement of cosmological parameters.

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Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

Abstract Current and future cosmological analyses with Type Ia supernovae (SNe Ia) face three critical challenges: (i) measuring the redshifts from the SNe or their host galaxies; (ii) classifying the SNe without spectra; and (iii) accounting for correlations between the properties of SNe Ia and their host galaxies. We present here a novel approach that addresses each of these challenges. In the context of the Dark Energy Survey (DES), we analyze an SN Ia sample with host galaxies in the redMaGiC galaxy catalog, a selection of luminous red galaxies. redMaGiC photo- z estimates are expected to be accurate to σ Δ z /(1+ z ) ∼ 0.02. The DES-5YR photometrically classified SN Ia sample contains approximately 1600 SNe, and 125 of these SNe are in redMaGiC galaxies. We demonstrate that redMaGiC galaxies almost exclusively host SNe Ia, reducing concerns relating to classification uncertainties. With this subsample, we find similar Hubble scatter (to within ∼0.01 mag) using photometric redshifts in place of spectroscopic redshifts. With detailed simulations, we show that the bias due to using redMaGiC photo- z s on the measurement of the dark energy equation of state w is up to Δ w ∼ 0.01–0.02. With real data, we measure a difference in w when using the redMaGiC photo- z s versus the spec- z s of Δ w = 0.005. Finally, we discuss how SNe in redMaGiC galaxies appear to comprise a more standardizable population, due to a weaker relation between color and luminosity ( β ) compared to the DES-3YR population by ∼5 σ . These results establish the feasibility of performing redMaGiC SN cosmology with photometric survey data in the absence of spectroscopic data.

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A galaxy-driven model of type Ia supernova luminosity variations

ABSTRACT Type Ia supernovae (SNe Ia) are used as standardizable candles to measure cosmological distances, but differences remain in their corrected luminosities which display a magnitude step as a function of host galaxy properties such as stellar mass and rest-frame U−R colour. Identifying the cause of these steps is key to cosmological analyses and provides insight into SN physics. Here we investigate the effects of SN progenitor ages on their light-curve properties using a galaxy-based forward model that we compare to the Dark Energy Survey 5-yr SN Ia sample. We trace SN Ia progenitors through time and draw their light-curve width parameters from a bimodal distribution according to their age. We find that an intrinsic luminosity difference between SNe of different ages cannot explain the observed trend between step size and SN colour. The data split by stellar mass are better reproduced by following recent work implementing a step in total-to-selective dust extinction ratio (RV) between low- and high-mass hosts, although an additional intrinsic luminosity step is still required to explain the data split by host galaxy U−R. Modelling the RV step as a function of galaxy age provides a better match overall. Additional age versus luminosity steps marginally improve the match to the data, although most of the step is absorbed by the width versus luminosity coefficient α. Furthermore, we find no evidence that α varies with SN age.

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DeepZipper: A Novel Deep-learning Architecture for Lensed Supernovae Identification

Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to be identified soon after it begins. To quickly identify LSNe in optical survey data sets, we designed ZipperNet, a multibranch deep neural network that combines convolutional layers (traditionally used for images) with long short-term memory layers (traditionally used for time series). We tested ZipperNet on the task of classifying objects from four categories—no lens, galaxy-galaxy lens, lensed Type-Ia supernova, lensed core-collapse supernova—within high-fidelity simulations of three cosmic survey data sets: the Dark Energy Survey, Rubin Observatory’s Legacy Survey of Space and Time (LSST), and a Dark Energy Spectroscopic Instrument (DESI) imaging survey. Among our results, we find that for the LSST-like data set, ZipperNet classifies LSNe with a receiver operating characteristic area under the curve of 0.97, predicts the spectroscopic type of the lensed supernovae with 79% accuracy, and demonstrates similarly high performance for LSNe 1–2 epochs after first detection. We anticipate that a model like ZipperNet, which simultaneously incorporates spatial and temporal information, can play a significant role in the rapid identification of lensed transient systems in cosmic survey experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dark Energy Survey Year 3 results: A 2.7% measurement of baryon acoustic oscillation distance scale at redshift 0.835

We present angular diameter measurements obtained by measuring the position of baryon acoustic oscillations (BAO) in an optimized sample of galaxies from the first three years of Dark Energy Survey data (DES Y3). The sample consists of 7 million galaxies distributed over a footprint of 4100 deg 2 with 0.6 < z photo < 1.1 and a typical redshift uncertainty of 0.03 ( 1 + z ) . The sample selection is the same as in the BAO measurement with the first year of DES data, but the analysis presented here uses three times the area, extends to higher redshift, and makes a number of improvements, including a fully analytical BAO template, the use of covariances from both theory and simulations, and an extensive preunblinding protocol. We used two different statistics; angular correlation function and power spectrum, and validate our pipeline with an ensemble of over 1500 realistic simulations. Both statistics yield compatible results. We combine the likelihoods derived from angular correlations and spherical harmonics to constrain the ratio of comoving angular diameter distance D M at the effective redshift of our sample to the sound horizon scale at the drag epoch. We obtain D M ( z eff = 0.835 ) / r d = 18.92 ± 0.51 , which is consistent with, but smaller than, the Planck prediction assuming flat Λ CDM , at the level of 2.3 σ . The analysis was performed blind and is robust to changes in a number of analysis choices. It represents the most precise BAO distance measurement from imaging data to date, and is competitive with the latest transverse ones from spectroscopic samples at z > 0.75 . When combined with DES 3 x 2 pt + SNIa , they lead to improvements in H 0 and Ω m constraints by ∼ 20 % .

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OzDES reverberation mapping program: Lag recovery reliability for 6-yr C iv analysis

ABSTRACT We present the statistical methods that have been developed to analyse the OzDES reverberation mapping sample. To perform this statistical analysis we have created a suite of customizable simulations that mimic the characteristics of each source in the OzDES sample. These characteristics include: the variability in the photometric and spectroscopic light curves, the measurement uncertainties, and the observational cadence. By simulating the sources in the OzDES sample that contain the C iv emission line, we developed a set of criteria that rank the reliability of a recovered time-lag depending on the agreement between different recovery methods, the magnitude of the uncertainties, and the rate at which false positives were found in the simulations. These criteria were applied to simulated light curves and these results used to estimate the quality of the resulting Radius–Luminosity relation. We grade the results using three quality levels (gold, silver, and bronze). The input slope of the R–L relation was recovered within 1σ for each of the three quality samples, with the gold standard having the lowest dispersion with a recovered a R–L relation slope of 0.454 ± 0.016 with an input slope of 0.47. Future work will apply these methods to the entire OzDES sample of 771 AGN.

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OzDES Reverberation Mapping Programme: the first Mg ii lags from 5 yr of monitoring

ABSTRACT Reverberation mapping is a robust method to measure the masses of supermassive black holes outside of the local Universe. Measurements of the radius–luminosity (R−L) relation using the Mg ii emission line are critical for determining these masses near the peak of quasar activity at z ≈ 1−2, and for calibrating secondary mass estimators based on Mg ii that can be applied to large samples with only single-epoch spectroscopy. We present the first nine Mg ii lags from our 5-yr Australian Dark Energy Survey reverberation mapping programme, which substantially improves the number and quality of Mg ii lag measurements. As the Mg ii feature is somewhat blended with iron emission, we model and subtract both the continuum and iron contamination from the multiepoch spectra before analysing the Mg ii line. We also develop a new method of quantifying correlated spectroscopic calibration errors based on our numerous, contemporaneous observations of F-stars. The lag measurements for seven of our nine sources are consistent with both the H β and Mg ii R−L relations reported by previous studies. Our simulations verify the lag reliability of our nine measurements, and we estimate that the median false positive rate of the lag measurements is $4{{\ \rm per\ cent}}$.

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Rates and delay times of type Ia supernovae in the Dark Energy Survey

We use a sample of 809 photometrically classified Type Ia supernovae (SNe Ia) discovered by the Dark Energy Survey (DES) along with 40 415 field galaxies to calculate the rate of SNe Ia per galaxy in the redshift range 0.2 < z < 0.6. We recover the known correlation between SN Ia rate and galaxy stellar mass across a broad range of scales 8.5 ≤ log (M*/M ⊙ ) ≤ 11.25. We find that the SN Ia rate increases with stellar mass as a power law with index 0.63 ± 0.02, which is consistent with the previous work. We use an empirical model of stellar mass assembly to estimate the average star formation histories (SFHs) of galaxies across the stellar mass range of our measurement. Combining the modelled SFHs with the SN Ia rates to estimate constraints on the SN Ia delay time distribution (DTD), we find that the data are fit well by a power-law DTD with slope index β = –1.13 ± 0.05 and normalization A = 2.11 ± 0.05 × 10 –13 SNe M ⊙ –1 yr –1 , which corresponds to an overall SN Ia production efficiency N Ia /M * = 0.9 $^{+4.0}_{–0.7}$ × 10 –3 SNe M$^{–1}_{⊙}$. Upon splitting the SN sample by properties of the light curves, we find a strong dependence on DTD slope with the SN decline rate, with slower-declining SNe exhibiting a steeper DTD slope. We interpret this as a result of a relationship between intrinsic luminosity and progenitor age, and explore the implications of the result in the context of SN Ia progenitors.

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The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination

ABSTRACT The analysis of current and future cosmological surveys of Type Ia supernovae (SNe Ia) at high redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core-collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions, and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-yr photometric SN sample, comparing our simulations of DES with the observed DES transient populations. We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 7.2 to 11.7 per cent, with an average of 8.8 per cent and an r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty.

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