اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدPhotometric Supernova Cosmology with BEAMS and SDSS-II
260
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Supernova cosmology without spectroscopic confirmation is an exciting new frontier which we address here with the Bayesian Estimation Applied to Multiple Species (BEAMS) algorithm and the full three years of data from the Sloan Digital Sky Survey II Supernova Survey (SDSS-II SN). BEAMS is a Bayesian framework for using data from multiple species in statistical inference when one has the probability that each data point belongs to a given species, corresponding in this context to different types of supernovae with their probabilities derived from their multi-band lightcurves. We run the BEAMS algorithm on both Gaussian and more realistic SNANA simulations with of order 10^4 supernovae, testing the algorithm against various pitfalls one might expect in the new and somewhat uncharted territory of photometric supernova cosmology. We compare the performance of BEAMS to that of both mock spectroscopic surveys and photometric samples which have been cut using typical selection criteria. The latter typically are either biased due to contamination or have significantly larger contours in the cosmological parameters due to small data-sets. We then apply BEAMS to the 792 SDSS-II photometric supernovae with host spectroscopic redshifts. In this case, BEAMS reduces the area of the (Omega_m,Omega_Lambda) contours by a factor of three relative to the case where only spectroscopically confirmed data are used (297 supernovae). In the case of flatness, the constraints obtained on the matter density applying BEAMS to the photometric SDSS-II data are Omega_m(BEAMS)=0.194pm0.07. This illustrates the potential power of BEAMS for future large photometric supernova surveys such as LSST.
قيم البحث
اقرأ أيضاً
We present the cosmological analysis of 752 photometrically-classified Type Ia Supernovae (SNe Ia) obtained from the full Sloan Digital Sky Survey II (SDSS-II) Supernova (SN) Survey, supplemented with host-galaxy spectroscopy from the SDSS-III Baryon
Oscillation Spectroscopic Survey (BOSS). Our photometric-classification method is based on the SN typing technique of Sako et al. (2011), aided by host galaxy redshifts (0.05<z<0.55). SNANA simulations of our methodology estimate that we have a SN Ia typing efficiency of 70.8%, with only 3.9% contamination from core-collapse (non-Ia) SNe. We demonstrate that this level of contamination has no effect on our cosmological constraints. We quantify and correct for our selection effects (e.g., Malmquist bias) using simulations. When fitting to a flat LambdaCDM cosmological model, we find that our photometric sample alone gives omega_m=0.24+0.07-0.05 (statistical errors only). If we relax the constraint on flatness, then our sample provides competitive joint statistical constraints on omega_m and omega_lambda, comparable to those derived from the spectroscopically-confirmed three-year Supernova Legacy Survey (SNLS3). Using only our data, the statistics-only result favors an accelerating universe at 99.96% confidence. Assuming a constant wCDM cosmological model, and combining with H0, CMB and LRG data, we obtain w=-0.96+0.10-0.10, omega_m=0.29+0.02-0.02 and omega_k=0.00+0.03-0.02 (statistical errors only), which is competitive with similar spectroscopically confirmed SNe Ia analyses. Overall this comparison is re-assuring, considering the lower redshift leverage of the SDSS-II SN sample (z<0.55) and the lack of spectroscopic confirmation used herein. These results demonstrate the potential of photometrically-classified SNe Ia samples in improving cosmological constraints.
We apply the Standardized Candle Method (SCM) for Type II Plateau supernovae (SNe II-P), which relates the velocity of the ejecta of a SN to its luminosity during the plateau, to 15 SNe II-P discovered over the three season run of the Sloan Digital S
ky Survey - II Supernova Survey. The redshifts of these SNe - 0.027 < z < 0.144 - cover a range hitherto sparsely sampled in the literature; in particular, our SNe II-P sample contains nearly as many SNe in the Hubble flow (z > 0.01) as all of the current literature on the SCM combined. We find that the SDSS SNe have a very small intrinsic I-band dispersion (0.22 mag), which can be attributed to selection effects. When the SCM is applied to the combined SDSS-plus-literature set of SNe II-P, the dispersion increases to 0.29 mag, larger than the scatter for either set of SNe separately. We show that the standardization cannot be further improved by eliminating SNe with positive plateau decline rates, as proposed in Poznanski et al. (2009). We thoroughly examine all potential systematic effects and conclude that for the SCM to be useful for cosmology, the methods currently used to determine the Fe II velocity at day 50 must be improved, and spectral templates able to encompass the intrinsic variations of Type II-P SNe will be needed.
The coming era of large photometric wide-field surveys will increase the detection rate of supernovae by orders of magnitude. Such numbers will restrict spectroscopic follow-up in the vast majority of cases, and hence new methods based solely on phot
ometric data must be developed. Here, we construct a complete Hubble diagram of Type II supernovae combining data from three different samples: the Carnegie Supernova Project-I, the Sloan Digital Sky Survey-II SN, and the Supernova Legacy Survey. Applying the Photometric Colour Method (PCM) to 73 Type II supernovae (SNe~II) with a redshift range of 0.01--0.5 and with no spectral information, we derive an intrinsic dispersion of 0.35 mag. A comparison with the Standard Candle Method (SCM) using 61 SNe~II is also performed and an intrinsic dispersion in the Hubble diagram of 0.27 mag is derived, i.e., 13% in distance uncertainties. Due to the lack of good statistics at higher redshifts for both methods, only weak constraints on the cosmological parameters are obtained. However, assuming a flat Universe and using the PCM, we derive a Universes matter density: $Omega_{m}$=0.32$^{+0.30}_{-0.21}$ providing a new independent evidence for dark energy at the level of two sigma.
We present an analysis of the luminosity distances of Type Ia Supernovae from the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey in conjunction with other intermediate redshift (z<0.4) cosmological measurements including redshift-space distor
tions from the Two-degree Field Galaxy Redshift Survey (2dFGRS), the Integrated Sachs-Wolfe (ISW) effect seen by the SDSS, and the latest Baryon Acoustic Oscillation (BAO) distance scale from both the SDSS and 2dFGRS. We have analysed the SDSS-II SN data alone using a variety of model-independent methods and find evidence for an accelerating universe at >97% level from this single dataset. We find good agreement between the supernova and BAO distance measurements, both consistent with a Lambda-dominated CDM cosmology, as demonstrated through an analysis of the distance duality relationship between the luminosity (d_L) and angular diameter (d_A) distance measures. We then use these data to estimate w within this restricted redshift range (z<0.4). Our most stringent result comes from the combination of all our intermediate-redshift data (SDSS-II SNe, BAO, ISW and redshift-space distortions), giving w = -0.81 +0.16 -0.18(stat) +/- 0.15(sys) and Omega_M=0.22 +0.09 -0.08 assuming a flat universe. This value of w, and associated errors, only change slightly if curvature is allowed to vary, consistent with constraints from the Cosmic Microwave Background. We also consider more limited combinations of the geometrical (SN, BAO) and dynamical (ISW, redshift-space distortions) probes.
We analyze the rise and fall times of type Ia supernova (SN Ia) light curves discovered by the SDSS-II Supernova Survey. From a set of 391 light curves k-corrected to the rest frame B and V bands, we find a smaller dispersion in the rising portion of
the light curve compared to the decline. This is in qualitative agreement with computer models which predict that variations in radioactive nickel yield have less impact on the rise than on the spread of the decline rates. The differences we find in the rise and fall properties suggest that a single stretch correction to the light curve phase does not properly model the range of SN Ia light curve shapes. We select a subset of 105 light curves well-observed in both rise and fall portions of the light curves and develop a 2-stretch fit algorithm which estimates the rise and fall times independently. We find the average time from explosion to B-band peak brightness is 17.38 +/- 0.17 days. Our average rise time is shorter than the 19.5 days found in previous studies; this reflects both the different light curve template used and the application of the 2-stretch algorithm. We find that slow declining events tend to have fast rise times, but that the distribution of rise minus fall time is broad and single-peaked. This distribution is in contrast to the bimodality in this parameter that was first suggested by Strovink (2007) from an analysis of a small set of local SNe Ia. We divide the SDSS-II sample in half based on the rise minus fall value, tr-tf <= 2 days and tr-tf>2 days, to search for differences in their host galaxy properties and Hubble residuals; we find no difference in host galaxy properties or Hubble residuals in our sample.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
