Showing papers by "Peter Nugent published in 2000"

Metallicity Effects in Non-LTE Model Atmospheres of Type Ia Supernovae

Abstract: We have calculated a grid of photospheric phase atmospheres of Type Ia supernovae (SNe Ia) with metallicities from 10 times to 1/30 the solar metallicity in the C+O layer of the deflagration model, W7. We have modeled the spectra using the multipurpose non-LTE model atmosphere and spectrum synthesis code PHOENIX. We show models for the epochs 7, 10, 15, 20, and 35 days after explosion. When compared to observed spectra obtained at the approximately corresponding epochs, these synthetic spectra fit reasonably well. The spectra show variation in the overall level of the UV continuum with lower fluxes for models with higher metallicity in the unburned C+O layer. This is consistent with the classical surface cooling and line-blocking effect due to metals in the outer layers of C+O. The UV features also move consistently to the blue with higher metallicity, demonstrating that they are forming at shallower and faster layers in the atmosphere. The potentially most useful effect is the blueward movement of the Si II feature at 6150 A with increasing C+O layer metallicity. We also demonstrate the more complex effects of metallicity variations by modifying the 54Fe content of the incomplete burning zone in W7 at maximum light. We briefly address some shortcomings of the W7 model when compared to observations. Finally, we identify that the split in the Ca H+K feature produced in W7 and observed in some SNe Ia is due to a blending effect of Ca II and Si II and does not necessarily represent a complex abundance or ionization effect in Ca II.

The Rise Times of High- and Low-Redshift Type Ia Supernovae Are Consistent

Abstract: We present a self-consistent comparison of the rise times for low- and high-redshift Type Ia supernovae. Following previous studies, the early light curve is modeled using a t2 law, which is then mated with a modified Leibundgut template light curve. The best-fit t2 law is determined for ensemble samples of low- and high-redshift supernovae by fitting simultaneously for all light-curve parameters for all supernovae in each sample. Our method fully accounts for the nonnegligible covariance among the light-curve fitting parameters, which previous analyses have neglected. Contrary to recent results by Riess et al., we find fair to good agreement between the rise times of the low- and high-redshift Type Ia supernovae. The uncertainty in the rise time of the high-redshift Type Ia supernovae is presently quite large (roughly ±1.2 days statistical), making any search for evidence of evolution based on a comparison of rise times premature. Furthermore, systematic effects on rise-time determinations from the high-redshift observations, due to the form of the late-time light curve and the manner in which the light curves of these supernovae were sampled, can bias the high-redshift rise-time determinations by up to days under extreme situations. The peak brightnesses—used for cosmology—do not suffer any significant bias, nor any significant increase in uncertainty.

A strategy for finding gravitationally-lensed distant supernovae

Abstract: Distant Type Ia and II supernovae (SNe) can serve as valuable probes of the history of the cosmic expansion and star formation, and provide important information on their progenitor models. At present, however, there are few observational constraints on the abundance of SNe at high redshifts. A major science driver for the Next Generation Space Telescope is the study of such very distant SNe. In this paper we discuss strategies for finding and counting distant SNe by using repeat imaging of supercritical intermediate redshift clusters whose mass distributions are well constrained via modelling of strongly lensed features. For a variety of different models for the star formation history and supernova progenitors, we estimate the likelihood of detecting lensed SNe as a function of their redshift. In the case of a survey conducted with Hubble Space Telescope (HST), we predict a high probability of seeing a supernova in a single return visit with either Wide Field Planetary Camera 2 or Advanced Camera for Surveys, and a much higher probability of detecting examples with z > 1 in the lensed case. Most events would represent magnified SNe II at z ≃ 1, and a fraction will be more distant examples. We discuss various ways to classify such events using ground-based infrared photometry. We demonstrate an application of the method using the HST archival data and discuss the case of a possible event found in the rich cluster AC 114 (z = 0.31).

The Acceleration of the Universe:. Measurements of Cosmological Parameters from Type Ia Supernovae

Abstract: The fate of the Universe, infinite expansion or a ldquo;big crunchrdquo;, can be determined by measuring the redshifts and brightness of very distant supernovae. These provide a record of changes in the expansion rate of the Universe over the past several billion years. The mass density, ?M, and cosmological-constant energy density ??, are measured from a data-set consisting of 42 high-redshift Type Ia supernovae discovered by the Supernova Cosmology Project. The magnitude-redshift data for these supernovae, at redshifts between 0.18 and 0.83, are fit jointly with a set of supernovae from the Cal?n/Tololo Supernova Survey, at redshifts below 0.1, to yield values for the cosmological parameters. We find ?Mflat = 0.28+0.09-0.08 (1? statistical)+0.05-0.04 (identified systematics). The data are strongly inconsistent with a ? = 0 flat cosmology, the simplest inflationary universe model. An open, ? = 0 cosmology also does not fit the data well: the data indicate that the cosmological constant is non-zero and positive, with a confidence of P(?>0) = 99%, including the identified systematic uncertainties. Thus, the Universe is found to be accelerating, i.e., q0 = ?M/2 - ?? < 0. The best-fit age of the universe relative to the Hubble time is t0flat = 14.9+1.4-1.1 (0.63/h) Gyr for a flat cosmology.

The Rise Times of High and Low Redshift Type Ia Supernovae are Consistent

Abstract: We present a self-consistent comparison of the rise times for low- and high-redshift Type Ia supernovae. Following previous studies, the early light curve is modeled using a t-squared law, which is then mated with a modified Leibundgut template light curve. The best-fit t-squared law is determined for ensemble samples of low- and high-redshift supernovae by fitting simultaneously for all light curve parameters for all supernovae in each sample. Our method fully accounts for the non-negligible covariance amongst the light curve fitting parameters, which previous analyses have neglected. Contrary to Riess et al. (1999), we find fair to good agreement between the rise times of the low- and high-redshift Type Ia supernovae. The uncertainty in the rise time of the high-redshift Type Ia supernovae is presently quite large (roughly +/- 1.2 days statistical), making any search for evidence of evolution based on a comparison of rise times premature. Furthermore, systematic effects on rise time determinations from the high-redshift observations, due to the form of the late-time light curve and the manner in which the light curves of these supernovae were sampled, can bias the high-redshift rise time determinations by up to +3.6/-1.9 days under extreme situations. The peak brightnesses - used for cosmology - do not suffer any significant bias, nor any significant increase in uncertainty.

Cosmological-Model-Parameter Determination from Satellite-Acquired Type Ia and IIP Supernova Data

Abstract: We examine the constraints that satellite-acquired Type Ia and IIP supernova apparent magnitude versus redshift data will place on cosmological model parameters in models with and without a constant or time-variable cosmological constant $\Lambda$. High-quality data which could be acquired in the near future will result in tight constraints on these parameters. For example, if all other parameters of a spatially-flat model with a constant $\Lambda$ are known, the supernova data should constrain the non-relativistic matter density parameter $\Omega_0$ to better than 1% (2%, 0.5%) at 1$\sigma$ with neutral (worst case, best case) assumptions about data quality.