In the next decade, transient searches from the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope will increase the sample of known Type Ia Supernovae (SN Ia) from $\sim10^3$ to $10^5$. With this reduction of statistical uncertainties on cosmological measurements, new methods are needed to reduce systematic uncertainties. Characterizing the underlying spectroscopic evolution of SN Ia remains a major systematic uncertainty in current cosmological analyses, motivating a new simulation tool for the next era of SN Ia cosmology: Build Your Own Spectral Energy Distribution (BYOSED). BYOSED is used within the SNANA framework to simulate light curves by applying spectral variations to model SEDs, enabling flexible testing of possible systematic shifts in SN Ia distance measurements. We test the framework by comparing a nominal Roman SN Ia survey simulation using a baseline SED model to simulations using SEDs perturbed with BYOSED, and investigate the impact of neglecting specific SED features in the analysis. These features include semi-empirical models of two possible, predicted relationships: between SN ejecta velocity and light curve observables, and a redshift-dependent relationship between SN Hubble residuals and host galaxy mass. We analyze each BYOSED simulation using the SALT2 & BBC framework, and estimate changes in the measured value of the dark energy equation-of-state parameter, $w$. We find a difference of $Δw=-0.023$ for SN velocity and $Δw=0.021$ for redshift-evolving host mass when compared to simulations without these features. By using BYOSED for SN Ia cosmology simulations, future analyses (e.g., Rubin and Roman SN Ia samples) will have greater flexibility to constrain or reduce such SN Ia modeling uncertainties.
The Supernova Legacy Survey (SNLS) has produced a high-quality, homogeneous sample of Type Ia supernovae (SNe Ia) out to redshifts greater than z=1. In its first four years of full operation (to June 2007), the SNLS discovered more than 3000 transient candidates, 373 of which have been confirmed spectroscopically as SNe Ia. Use of these SNe Ia in precision cosmology critically depends on an analysis of the observational biases incurred in the SNLS survey due to the incomplete sampling of the underlying SN Ia population. This paper describes our real-time supernova detection and analysis proced…
We study different one-parametric models of type Ia Supernova magnitude evolution on cosmic time scales. Constraints on cosmological and Supernova evolution parameters are obtained by combined fits on the actual data coming from Supernovae, the cosmic microwave background, and baryonic acoustic oscillations. We find that data prefer a magnitude evolution such that high-redshift Supernova are brighter than would be expected in a standard cosmos with a dark energy component. Data however are consistent with non-evolving magnitudes at the one-sigma level, except special cases. We simulate a futur…
Simulations of Type Ia Supernovae (SNIa) surveys are a critical tool for correcting biases in the analysis of SNIa to infer cosmological parameters. Large scale Monte Carlo simulations include a thorough treatment of observation history, measurement noise, intrinsic scatter models and selection effects. In this paper, we improve simulations with a robust technique to evaluate the underlying populations of SNIa color and stretch that correlate with luminosity. In typical analyses, the standardized SNIa brightness is determined from linear `Tripp' relations between the light curve color and lumi…
We present a new technique to create a bin-averaged Hubble Diagram (HD) from photometrically identified SN~Ia data. The resulting HD is corrected for selection biases and contamination from core collapse (CC) SNe, and can be used to infer cosmological parameters. This method, called "BBC" (BEAMS with Bias Corrections), includes two fitting stages. The first BBC fitting stage uses a posterior distribution that includes multiple SN likelihoods, a Monte Carlo simulation to bias-correct the fitted SALT-II parameters, and CC probabilities determined from a machine learning technique. The BBC fit de…
Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on state-of-the-art simulations of photometrically identified SN Ia samples and determine cosmological biases due to such 'non-Ia' contamination in the Dark Energy Survey (DES) 5-year SN sample. As part of the analysis, we test on our DES simulations the performance of SuperNNova, a photometric SN classifier based on recurrent neural networks. Depending on the choice of non-I…
We make use of publicly available results from N-body Millennium Simulation to create mock samples of lensed supernovae type Ia and core-collapse. Simulating galaxy-galaxy lensing we derive the rates of lensed supernovae and find than at redshifts higher that 0.5 about 0.06 per cent of supernovae will be lensed by a factor two or more. Future wide field surveys like Gaia or LSST should be able to detect lensed supernovae in their unbiased sky monitoring. Gaia (from 2013) will detect at least 2 cases whereas LSST (from 2018) will see more than 500 a year. Large number of future lensed supernova…
Cosmological simulations make use of sub-grid recipes for the implementation of galactic winds driven by massive stars because direct injection of supernova energy in thermal form leads to strong radiative losses, rendering the feedback inefficient. We argue that the main cause of the catastrophic cooling is a mismatch between the mass of the gas in which the energy is injected and the mass of the parent stellar population. Because too much mass is heated, the temperatures are too low and the cooling times too short. We use analytic arguments to estimate, as a function of the gas density and t…
Traditional cosmological inference using Type Ia supernovae (SNeIa) have used stretch- and color-corrected fits of SN Ia light curves and assumed a resulting fiducial mean and symmetric intrinsic dispersion for the resulting relative luminosity. As systematics become the main contributors to the error budget, it has become imperative to expand supernova cosmology analyses to include a more general likelihood to model systematics to remove biases with losses in precision. To illustrate an example likelihood analysis, we use a simple model of two populations with a relative luminosity shift, ind…
Improving the use of Type Ia supernovae (SNIa) as standard candles requires a better approach to incorporate the relationship between SNIa and the properties of their host galaxies. Using a spectroscopically-confirmed sample of $\sim$1600 SNIa, we develop the first empirical model of underlying populations for SNIa light-curve properties that includes their dependence on host-galaxy stellar mass. These populations are important inputs to simulations that are used to model selection effects and correct distance biases within the BEAMS with Bias Correction (BBC) framework. Here we improve BBC to…
We use simulated SN Ia samples, including both photometry and spectra, to perform the first direct validation of cosmology analysis using the SALT-II light curve model. This validation includes residuals from the light curve training process, systematic biases in SN Ia distance measurements, and the bias on the dark energy equation of state parameter w. Using the SN-analysis package SNANA, we simulate and analyze realistic samples corresponding to the data samples used in the SNLS3 analysis: 120 low-redshift (z < 0.1) SNe Ia, 255 SDSS SNe Ia (z < 0.4), and 290 SNLS SNe Ia (z <= 1). To probe sy…
We describe catalog-level simulations of Type Ia supernova (SN~Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN), and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project (CSP). These simulations are used to model biases from selection effects and light curve analysis, and to determine bias corrections for SN~Ia distance moduli that are used to measure cosmological parameters. To generate realistic light curves, the simulation uses a detailed SN~Ia model, incorporates information from observations (PSF, sky noise, zero point), an…
Peculiar velocities of type Ia supernova (SNIa) host galaxies affect the dark-energy parameter constraints in a small but very specific way: the parameters are biased in a single direction in parameter space that is a-priori knowable for a given SNIa dataset. We demonstrate the latter fact with a combination of inference from a cosmological N-body simulation with overwhelming statistics applied to the Pantheon SNIa data set, then confirm it by simple quantitative arguments. We quantify small modifications to the current analyses that would ensure that the effect of cosmological parameters is e…
We present simulations for the Dark Energy Survey (DES) using a new code suite (SNANA) that generates realistic supernova light curves accounting for atmospheric seeing conditions and intrinsic supernova luminosity variations using MLCS2k2 or SALT2 models. Errors include stat-noise from photo-statistics and sky noise. We applied SNANA to simulate DES supernova observations and employed an MLCS-based fitter to obtain the distance modulus for each simulated light curve. We harnessed the light curves in order to study selection biases for high-redshift supernovae and to constrain the optimal DES …
The original formulation of BEAMS - Bayesian Estimation Applied to Multiple Species - showed how to use a dataset contaminated by points of multiple underlying types to perform unbiased parameter estimation. An example is cosmological parameter estimation from a photometric supernova sample contaminated by unknown Type Ibc and II supernovae. Where other methods require data cuts to increase purity, BEAMS uses all of the data points in conjunction with their probabilities of being each type. Here we extend the BEAMS formalism to allow for correlations between the data and the type probabilities…
New supernova surveys such as the Dark Energy Survey, Pan-STARRS and the LSST will produce an unprecedented number of photometric supernova candidates, most with no spectroscopic data. Avoiding biases in cosmological parameters due to the resulting inevitable contamination from non-Ia supernovae can be achieved with the BEAMS formalism, allowing for fully photometric supernova cosmology studies. Here we extend BEAMS to deal with the case in which the supernovae are correlated by systematic uncertainties. The analytical form of the full BEAMS posterior requires evaluating 2^N terms, where N is …
The case of SN Ia Hubble diagrams from photometrically selected samples using photometric SN host galaxy redshifts is investigated. The host redshift uncertainties and the contamination by core collapse SNe are addressed. As a test, we use the 3-year photometric SN Ia sample of the SuperNova Legacy Survey (SNLS), made of 437 objects between 0.1 and 1.05 in redshift. We combine this sample with non-SNLS objects of the JLA spectroscopic sample, made of 501 objects mostly below 0.4 in redshift. We study two options for the origin of the redshifts of the photometric sample, either provided entirel…
Gamma-Ray Bursts (GRBs) are very energetic cosmological transients. Long GRBs are usually associated with Type Ib/c Supernovae (SNe), and we refer to them as GRB-SNe. Since the associated SN for a given GRB is observed only at low redshift, a possible selection effect exists when we consider intrinsically faint sources which cannot be observed at high redshift. Thus, it is important to explore the possible relationships between GRB and SN parameters after these have been corrected for astrophysical biases due to the instrumental selection effects and redshift evolution of the variables involve…
We present self-consistent high-resolution simulations of NGC4038/4039 (the "Antennae galaxies") including star formation, supernova feedback and magnetic fields performed with the N-body/SPH code Gadget, in which magnetohydrodynamics are followed with the SPH method. We vary the initial magnetic field in the progenitor disks from 1 nG to 100 muG. At the time of the best match with the central region of the Antennae system the magnetic field has been amplified by compression and shear flows to an equilibrium field of approximately 10 muG, independent of the initial seed field. These simulation…
We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we used manifold learning to build a three-dimensional parameterization of the intrinsic diversity of SNe Ia at maximum light that we call the "Twins Embedding". In this article, we discuss how the Twins Embedding can be used to improve the standardization of SNe Ia. With a single spectrophotometrically-calibrated spectrum near maximum light, we can standardize our sample of SNe Ia with an RMS of $0.101 \pm 0.007$ mag, which corresponds to $0.084 \…
Supernova cosmology without spectra will be an important component of future surveys such as LSST. This lack of supernova spectra results in uncertainty in the redshifts which, if ignored, leads to significantly biased estimates of cosmological parameters. Here we present a hierarchical Bayesian formalism -- zBEAMS -- that addresses this problem by marginalising over the unknown or uncertain supernova redshifts to produce unbiased cosmological estimates that are competitive with supernova data with spectroscopically confirmed redshifts. zBEAMS provides a unified treatment of both photometric r…
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 betwee…
More luminous Type Ia supernovae (SNe Ia) prefer less massive hosts and regions of higher star formation. This correlation is inverted during width-color-luminosity light curve standardization resulting in step-like biases of distance measurements with respect to host properties. Using the PISCO supernova host sample and SDSS, GALEX, and 2MASS photometry, we compare host stellar mass and specific star formation rate (sSFR) from different observation methods, including local vs. global, and fitting techniques to measure their impact on the host step biases. Mass step measurements for all our ma…
FlowSN: Neural Simulation-Based Inference under Realistic Selection Effects applied to Supernova Cosmology
University of Cambridge（剑桥大学）；National Center for Supercomputing Applications（国家超级计算应用中心）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of Chicago（芝加哥大学）
We present three-dimensional, adaptive mesh simulations of dwarf galaxy out- flows driven by supersonic turbulence. Here we develop a subgrid model to track not only the thermal and bulk velocities of the gas, but also its turbulent velocities and length scales. This allows us to deposit energy from supernovae directly into supersonic turbulence, which acts on scales much larger than a particle mean free path, but much smaller than resolved large-scale flows. Unlike previous approaches, we are able to simulate a starbursting galaxy modeled after NGC 1569, with realistic radiative cooling throu…
Only a few cases of type Ic supernovae (SNe) with high-velocity ejecta have been discovered and studied. Here we present our analysis of radio and X-ray observations of a Type Ic SN, PTF12gzk. The radio emission rapidly declined less than 10 days after explosion, suggesting SN ejecta expanding at high velocity (~0.3c). The radio data also indicate that the density of the circumstellar material (CSM) around the supernova is lower by a factor of ~10 than the CSM around normal Type Ic SNe. Our observations of this rapidly declining radio SN at a distance of 58 Mpc demonstrates the potential to de…
