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Register a new userLensed Type Ia Supernovae as Probes of Cluster Mass Models
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Using three magnified Type Ia supernovae (SNe Ia) detected behind CLASH clusters, we perform a first pilot study to see whether standardizable candles can be used to calibrate cluster mass maps created from strong lensing observations. Such calibrations will be crucial when next generation HST cluster surveys (e.g. FRONTIER) provide magnification maps that will, in turn, form the basis for the exploration of the high redshift Universe. We classify SNe using combined photometric and spectroscopic observations, finding two of the three to be clearly of type SN Ia and the third probable. The SNe exhibit significant amplification, up to a factor of 1.7 at $sim5sigma$ significance (SN-L2). We conducted this as a blind study to avoid fine tuning of parameters, finding a mean amplification difference between SNe and the cluster lensing models of $0.09 pm 0.09^{stat} pm 0.05^{sys}$ mag. This impressive agreement suggests no tension between cluster mass models and high redshift standardized SNe Ia. However, the measured statistical dispersion of $sigma_{mu}=0.21$ mag appeared large compared to the dispersion expected based on statistical uncertainties ($0.14$). Further work with the supernova and cluster lensing models, post unblinding, reduced the measured dispersion to $sigma_{mu}=0.12$. An explicit choice should thus be made as to whether SNe are used unblinded to improve the model, or blinded to test the model. As the lensed SN samples grow larger, this technique will allow improved constraints on assumptions regarding e.g. the structure of the dark matter halo.
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Recently, there have been two landmark discoveries of gravitationally lensed supernovae: the first multiply-imaged SN, Refsdal, and the first Type Ia SN resolved into multiple images, SN iPTF16geu. Fitting the multiple light curves of such objects can deliver measurements of the lensing time delays, which are the difference in arrival times for the separate images. These measurements provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Over the next decade, accurate time delay measurements will be needed for the tens to hundreds of lensed SNe to be found by wide-field time-domain surveys such as LSST and WFIRST. We have developed an open source software package for simulations and time delay measurements of multiply-imaged SNe, including an improved characterization of the uncertainty caused by microlensing. We describe simulations using the package that suggest a before-peak detection of the leading image enables a more accurate and precise time delay measurement (by ~1 and ~2 days, respectively), when compared to an after-peak detection. We also conclude that fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data, but that employing a Gaussian Process Regression (GPR) technique is sufficient for determining the uncertainty due to microlensing.
Type Ia supernova cosmology depends on the ability to fit and standardize observations of supernova magnitudes with an empirical model. We present here a series of new models of Type Ia Supernova spectral time series that capture a greater amount of supernova diversity than possible with the models that are currently customary. These are entitled SuperNova Empirical MOdels (textsc{SNEMO}footnote{https://snfactory.lbl.gov/snemo}). The models are constructed using spectrophotometric time series from $172$ individual supernovae from the Nearby Supernova Factory, comprising more than $2000$ spectra. Using the available observations, Gaussian Processes are used to predict a full spectral time series for each supernova. A matrix is constructed from the spectral time series of all the supernovae, and Expectation Maximization Factor Analysis is used to calculate the principal components of the data. K-fold cross-validation then determines the selection of model parameters and accounts for color variation in the data. Based on this process, the final models are trained on supernovae that have been dereddened using the Fitzpatrick and Massa extinction relation. Three final models are presented here: textsc{SNEMO2}, a two-component model for comparison with current Type~Ia models; textsc{SNEMO7}, a seven component model chosen for standardizing supernova magnitudes which results in a total dispersion of $0.100$~mag for a validation set of supernovae, of which $0.087$~mag is unexplained (a total dispersion of $0.113$~mag with unexplained dispersion of $0.097$~mag is found for the total set of training and validation supernovae); and textsc{SNEMO15}, a comprehensive $15$ component model that maximizes the amount of spectral time series behavior captured.
Type Ia supernovae (SNe Ia) that are multiply imaged by gravitational lensing can extend the SN Ia Hubble diagram to very high redshifts $(zgtrsim 2)$, probe potential SN Ia evolution, and deliver high-precision constraints on $H_0$, $w$, and $Omega_m$ via time delays. However, only one, iPTF16geu, has been found to date, and many more are needed to achieve these goals. To increase the multiply imaged SN Ia discovery rate, we present a simple algorithm for identifying gravitationally lensed SN Ia candidates in cadenced, wide-field optical imaging surveys. The technique is to look for supernovae that appear to be hosted by elliptical galaxies, but that have absolute magnitudes implied by the apparent hosts photometric redshifts that are far brighter than the absolute magnitudes of normal SNe Ia (the brightest type of supernovae found in elliptical galaxies). Importantly, this purely photometric method does not require the ability to resolve the lensed images for discovery. AGN, the primary sources of contamination that affect the method, can be controlled using catalog cross-matches and color cuts. Highly magnified core-collapse supernovae will also be discovered as a byproduct of the method. Using a Monte Carlo simulation, we forecast that LSST can discover up to 500 multiply imaged SNe Ia using this technique in a 10-year $z$-band search, more than an order of magnitude improvement over previous estimates (Oguri & Marshall 2010). We also predict that ZTF should find up to 10 multiply imaged SNe Ia using this technique in a 3-year $R$-band search---despite the fact that this survey will not resolve a single system.
Empirically, Type Ia supernovae are the most useful, precise, and mature tools for determining astronomical distances. Acting as calibrated candles they revealed the presence of dark energy and are being used to measure its properties. However, the nature of the SN Ia explosion, and the progenitors involved, have remained elusive, even after seven decades of research. But now new large surveys are bringing about a paradigm shift --- we can finally compare samples of hundreds of supernovae to isolate critical variables. As a result of this, and advances in modeling, breakthroughs in understanding all aspects of SNe Ia are finally starting to happen.
To use strongly lensed Type Ia supernovae (LSNe Ia) for cosmology, a time-delay measurement between the multiple supernova (SN) images is necessary. The sharp rise and decline of SN Ia light curves make them promising for measuring time delays, but microlensing can distort these light curves and therefore add large uncertainties to the measurements. An alternative approach is to use color curves where uncertainties due to microlensing are significantly reduced for a certain period of time known as the achromatic phase. In this work, we investigate in detail the achromatic phase, testing four different SN Ia models with various microlensing configurations. We find on average an achromatic phase of around three rest-frame weeks or longer for most color curves but the spread in the duration of the achromatic phase (due to different microlensing maps and filter combinations) is quite large and an achromatic phase of just a few days is also possible. Furthermore, the achromatic phase is longer for smoother microlensing maps, lower macro-magnifications and larger mean Einstein radii of microlenses. From our investigations, we do not find a strong dependency on the model or on asymmetries in the SN ejecta. Further, we find that three independent LSST color curves exhibit features such as extreme points or turning points within the achromatic phase, which make them promising for time-delay measurements. These curves contain combinations of rest-frame bands $u$, $g$, $r$, and $i$ and to observe them for typical LSN Ia redshifts, it would be ideal to cover (observer-frame) filters $r$, $i$, $z$, $y$, $J$, and $H$.
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