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تسجيل مستخدم جديدHow to Find Gravitationally Lensed Type Ia Supernovae
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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.
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We report the discovery of a multiply-imaged gravitationally lensed Type Ia supernova, iPTF16geu (SN 2016geu), at redshift $z=0.409$. This phenomenon could be identified because the light from the stellar explosion was magnified more than fifty times
by the curvature of space around matter in an intervening galaxy. We used high spatial resolution observations to resolve four images of the lensed supernova, approximately 0.3 from the center of the foreground galaxy. The observations probe a physical scale of $sim$1 kiloparsec, smaller than what is typical in other studies of extragalactic gravitational lensing. The large magnification and symmetric image configuration implies close alignment between the line-of-sight to the supernova and the lens. The relative magnifications of the four images provide evidence for sub-structures in the lensing galaxy.
We present a spatio-temporal AI framework that concurrently exploits both the spatial and time-variable features of gravitationally lensed supernovae in optical images to ultimately aid in the discovery of such exotic transients in wide-field surveys
. Our spatio-temporal engine is designed using recurrent convolutional layers, while drawing from recent advances in variational inference to quantify approximate Bayesian uncertainties via a confidence score. Using simulated Young Supernova Experiment (YSE) images as a showcase, we find that the use of time-series images yields a substantial gain of nearly 20 per cent in classification accuracy over single-epoch observations, with a preliminary application to mock observations from the Legacy Survey of Space and Time (LSST) yielding around 99 per cent accuracy. Our innovative deep learning machinery adds an extra dimension in the search for gravitationally lensed supernovae from current and future astrophysical transient surveys.
There is compelling evidence that the peak brightness of a Type Ia supernova is affected by the electron fraction Ye at the time of the explosion. The electron fraction is set by the aboriginal composition of the white dwarf and the reactions that oc
cur during the pre explosive convective burning. To date, determining the makeup of the white dwarf progenitor has relied on indirect proxies, such as the average metallicity of the host stellar population. In this paper, we present analytical calculations supporting the idea that the electron fraction of the progenitor systematically influences the nucleosynthesis of silicon group ejecta in Type Ia supernovae. In particular, we suggest the abundances generated in quasi nuclear statistical equilibrium are preserved during the subsequent freezeout. This allows one to potential recovery of Ye at explosion from the abundances recovered from an observed spectra. We show that measurement of 28Si, 32S, 40Ca, and 54Fe abundances can be used to construct Ye in the silicon rich regions of the supernovae. If these four abundances are determined exactly, they are sufficient to recover Ye to 6 percent. This is because these isotopes dominate the composition of silicon-rich material and iron rich material in quasi nuclear statistical equilibrium. Analytical analysis shows that the 28Si abundance is insensitive to Ye, the 32S abundance has a nearly linear trend with Ye, and the 40Ca abundance has a nearly quadratic trend with Ye. We verify these trends with post-processing of 1D models and show that these trends are reflected in model synthetic spectra.
We explore the effects of the deflagration to detonation transition (DDT) density on the production of Ni-56 in thermonuclear supernova explosions (type Ia supernovae). Within the DDT paradigm, the transition density sets the amount of expansion duri
ng the deflagration phase of the explosion and therefore the amount of nuclear statistical equilibrium (NSE) material produced. We employ a theoretical framework for a well-controlled statistical study of two-dimensional simulations of thermonuclear supernovae with randomized initial conditions that can, with a particular choice of transition density, produce a similar average and range of Ni-56 masses to those inferred from observations. Within this framework, we utilize a more realistic simmered white dwarf progenitor model with a flame model and energetics scheme to calculate the amount of Ni-56 and NSE material synthesized for a suite of simulated explosions in which the transition density is varied in the range 1-3x10^7 g/cc. We find a quadratic dependence of the NSE yield on the log of the transition density, which is determined by the competition between plume rise and stellar expansion. By considering the effect of metallicity on the transition density, we find the NSE yield decreases by 0.055 +/- 0.004 solar masses for a 1 solar metallicity increase evaluated about solar metallicity. For the same change in metallicity, this result translates to a 0.067 +/- 0.004 solar mass decrease in the Ni-56 yield, slightly stronger than that due to the variation in electron fraction from the initial composition. Observations testing the dependence of the yield on metallicity remain somewhat ambiguous, but the dependence we find is comparable to that inferred from some studies.
Time delays between the multiple images of strongly lensed Type Ia supernovae (glsneia) have the potential to deliver precise cosmological constraints, but the effects of microlensing on the measurement have not been studied in detail. Here we quanti
fy the effect of microlensing on the glsnia yield of the Large Synoptic Survey Telescope (LSST) and the effect of microlensing on the precision and accuracy of time delays that can be extracted from LSST glsneia. Microlensing has a negligible effect on the LSST glsnia yield, but it can be increased by a factor of $sim$2 to 930 systems using a novel photometric identification technique based on spectral template fitting. Crucially, the microlensing of glsneia is achromatic until 3 rest-frame weeks after the explosion, making the early-time color curves microlensing-insensitive time delay indicators. By fitting simulated flux and color observations of microlensed glsneia with their underlying, unlensed spectral templates, we forecast the distribution of absolute time delay error due to microlensing for LSST, which is unbiased at the sub-percent level and peaked at 1% for color curve observations in the achromatic phase, while for light curve observations it is comparable to state-of-the-art mass modeling uncertainties (4%). About 70% of LSST glsnia images should be discovered during the achromatic phase, indicating that microlensing time delay uncertainties can be minimized if prompt multicolor follow-up observations are obtained. Accounting for microlensing, the 1--2 day time delay on the recently discovered glsnia iPTF16geu can be measured to 40% precision, limiting its cosmological utility.
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