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Masao Sako

Publications and source records attributed to Masao Sako.

At least 73 records · Page 4Linked to original sources

Photometric SN Ia Candidates from the Three-Year SDSS-II SN Survey Data

We analyze the three-year SDSS-II Superernova (SN) Survey data and identify a sample of 1070 photometric SN Ia candidates based on their multi-band light curve data. This sample consists of SN candidates with no spectroscopic confirmation, with a subset of 210 candidates having spectroscopic redshifts of their host galaxies measured, while the remaining 860 candidates are purely photometric in their identification. We describe a method for estimating the efficiency and purity of photometric SN Ia classification when spectroscopic confirmation of only a limited sample is available, and demonstrate that SN Ia candidates from SDSS-II can be identified photometrically with ~91% efficiency and with a contamination of ~6%. Although this is the largest uniform sample of SN candidates to date for studying photometric identification, we find that a larger spectroscopic sample of contaminating sources is required to obtain a better characterization of the background events. A Hubble diagram using SN candidates with no spectroscopic confirmation, but with host galaxy spectroscopic redshifts, yields a distance modulus dispersion that is only ~20 - 40% larger than that of the spectroscopically-confirmed SN Ia sample alone with no significant bias. A Hubble diagram with purely photometric classification and redshift-distance measurements, however, exhibit biases that require further investigation for precision cosmology.

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A More General Model for the Intrinsic Scatter in Type Ia Supernova Distance Moduli

We describe a new formalism to fit the parameters $α$ and $β$ that are used in the SALT2 model to determine the standard magnitudes of Type Ia supernovae. The new formalism describes the intrinsic scatter in Type Ia supernovae by a covariance matrix in place of the single parameter normally used. We have applied this formalism to the Sloan Digital Sky Survey Supernova Survey (SDSS-II) data and conclude that the data are best described by $α=0.135_{-.017}^{+.033}$ and $β=3.19_{-0.24}^{+0.14}$, where the error is dominated by the uncertainty in the form of the intrinsic scatter matrix. Our result depends on the introduction of a more general form for the intrinsic scatter of the distance moduli of Type Ia supernovae than is conventional, resulting in a larger value of $β$ and a larger uncertainty than the conventional approach. Although this analysis results in a larger value of $β$ and a larger error, the SDSS data differ (at a 98% confidence level) with $β=4.1$, the value expected for extinction by the type of dust found in the Milky Way. We have modeled the distribution of supernovae Ia in terms of their color and conclude that there is strong evidence that variation in color is a significant contributor to the scatter of supernovae Ia around their standard candle magnitude.

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Line Profiles of Intermediate Redshift Type Ia Supernovae

We present the temporal evolution of line profiles ranging from near ultraviolet to optical wavelengths by analyzing 59 Subaru telescope spectra of normal Type Ia Supernovae (SNe Ia) in the intermediate redshift range (0.05 < z < 0.4) discovered by the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. We derive line velocities, peak wavelengths and pseudo-equivalent widths (pEWs) of these lines. Additionally, we compare the line profiles around the date of maximum brightness with those from their nearby counterparts. We find that line profiles represented by their velocities and pEWs for intermediate redshift SNe Ia are consistent with their nearby counterparts within 2 $σ$. These findings support the picture that SNe Ia are a "standard" candle for the intermediate redshift range as has been shown between SNe Ia at nearby and high redshifts. There is a hint that the "MgII λ4300" pEW distribution for intermediate redshift SNe Ia is larger than for the nearby sample, which could be interpreted as a difference in the progenitor abundance.

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Subaru Spectroscopy of SDSS-II Supernovae

The Sloan Digital Sky Survey II (SDSS-II) Supernova Survey discovered Type Ia supernovae (SNe Ia) in an almost unexplored intermediate redshift range of $0.05 < z < 0.4$ and provided densely sampled multi-color light curves for SN candidates. Followup spectroscopy of this survey was carried out with the Subaru telescope and spectra of 71 SN Ia candidates were obtained. One spectrum was observed per candidate except for a peculiar variable. This paper presents the method for processing these spectra. The observed wavelength ranges of our spectra are 4000 to 9000 Å for Year 2005 and 3600 to 9000 Å for Year 2006. Most SN Ia spectra have signal to noise ratios (S/N) between 4 and 10 per 2 Å averaged over the entire wavelength region. We developed a new code to extract the SN spectral component from spectra contaminated by the host galaxy. Of 71 SN Ia candidates, 59 are identified as normal SNe Ia and 3 are peculiar SNe Ia. The range of spectral phases varies from -7 days to +30 days from maximum brightness. There are also 7 SNe II, 1 possible hypernova and 1 AGN.

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Results from the Supernova Photometric Classification Challenge

We report results from the Supernova Photometric Classification Challenge (SNPCC), a publicly released mix of simulated supernovae (SNe), with types (Ia, Ibc, and II) selected in proportion to their expected rate. The simulation was realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point-spread function and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). A spectroscopically confirmed subset was provided for training. We challenged scientists to run their classification algorithms and report a type and photo-z for each SN. Participants from 10 groups contributed 13 entries for the sample that included a host-galaxy photo-z for each SN, and 9 entries for the sample that had no redshift information. Several different classification strategies resulted in similar performance, and for all entries the performance was significantly better for the training subset than for the unconfirmed sample. For the spectroscopically unconfirmed subset, the entry with the highest average figure of merit for classifying SNe~Ia has an efficiency of 0.96 and an SN~Ia purity of 0.79. As a public resource for the future development of photometric SN classification and photo-z estimators, we have released updated simulations with improvements based on our experience from the SNPCC, added samples corresponding to the Large Synoptic Survey Telescope (LSST) and the SDSS, and provided the answer keys so that developers can evaluate their own analysis.

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Single or Double Degenerate Progenitors? Searching for Shock Emission in the SDSS-II Type Ia Supernovae

From the set of nearly 500 spectroscopically confirmed type~Ia supernovae and around 10,000 unconfirmed candidates from SDSS-II, we select a subset of 108 confirmed SNe Ia with well-observed early-time light curves to search for signatures from shock interaction of the supernova with a companion star. No evidence for shock emission is seen; however, the cadence and photometric noise could hide a weak shock signal. We simulate shocked light curves using SN Ia templates and a simple, Gaussian shock model to emulate the noise properties of the SDSS-II sample and estimate the detectability of the shock interaction signal as a function of shock amplitude, shock width, and shock fraction. We find no direct evidence for shock interaction in the rest-frame $B$-band, but place an upper limit on the shock amplitude at 9% of supernova peak flux ($M_B > -16.6$ mag). If the single degenerate channel dominates type~Ia progenitors, this result constrains the companion stars to be less than about 6 $M_{\odot}$ on the main sequence, and strongly disfavors red giant companions.

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The Effect of Host Galaxies on Type Ia Supernovae in the SDSS-II Supernova Survey

We present an analysis of the host galaxy dependencies of Type Ia Supernovae (SNe Ia) from the full three year sample of the SDSS-II Supernova Survey. We rediscover, to high significance, the strong correlation between host galaxy typeand the width of the observed SN light curve, i.e., fainter, quickly declining SNe Ia favor passive host galaxies, while brighter, slowly declining Ia's favor star-forming galaxies. We also find evidence (at between 2 to 3 sigma) that SNe Ia are ~0.1 magnitudes brighter in passive host galaxies, than in star-forming hosts, after the SN Ia light curves have been standardized using the light curve shape and color variations: This difference in brightness is present in both the SALT2 and MCLS2k2 light curve fitting methodologies. We see evidence for differences in the SN Ia color relationship between passive and star-forming host galaxies, e.g., for the MLCS2k2 technique, we see that SNe Ia in passive hosts favor a dust law of R_V ~1, while SNe Ia in star-forming hosts require R_V ~2. The significance of these trends depends on the range of SN colors considered. We demonstrate that these effects can be parameterized using the stellar mass of the host galaxy (with a confidence of >4 sigma) and including this extra parameter provides a better statistical fit to our data. Our results suggest that future cosmological analyses of SN Ia samples should include host galaxy information.

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The Subluminous Supernova 2007qd: A Missing Link in a Family of Low-Luminosity Type Ia Supernovae

We present multi-band photometry and multi-epoch spectroscopy of the peculiar Type Ia supernova (SN Ia) 2007qd, discovered by the SDSS-II Supernova Survey. It possesses physical properties intermediate to those of the peculiar SN 2002cx and the extremely low-luminosity SN 2008ha. Optical photometry indicates that it had an extraordinarily fast rise time of <= 10 days and a peak absolute B magnitude of -15.4 +/- 0.2 at most, making it one of the most subluminous SN Ia ever observed. Follow-up spectroscopy of SN 2007qd near maximum brightness unambiguously shows the presence of intermediate-mass elements which are likely caused by carbon/oxygen nuclear burning. Near maximum brightness, SN 2007qd had a photospheric velocity of only 2800 km/s, similar to that of SN 2008ha but about 4000 and 7000 km/s less than that of SN 2002cx and normal SN Ia, respectively. We show that the peak luminosities of SN 2002cx-like objects are highly correlated with both their light-curve stretch and photospheric velocities. Its strong apparent connection to other SN 2002cx-like events suggests that SN 2007qd is also a pure deflagration of a white dwarf, although other mechanisms cannot be ruled out. It may be a critical link between SN 2008ha and the other members of the SN 2002cx-like class of objects.

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Photometric Estimates of Redshifts and Distance Moduli for Type Ia Supernovae

Large planned photometric surveys will discover hundreds of thousands of supernovae (SNe), outstripping the resources available for spectroscopic follow-up and necessitating the development of purely photometric methods to exploit these events for cosmological study. We present a light-curve fitting technique for SN Ia photometric redshift (photo-z) estimation in which the redshift is determined simultaneously with the other fit parameters. We implement this "LCFIT+Z" technique within the frameworks of the MLCS2k2 and SALT-II light-curve fit methods and determine the precision on the redshift and distance modulus. This method is applied to a spectroscopically confirmed sample of 296 SNe Ia from the SDSS-II Supernova Survey and 37 publicly available SNe Ia from the Supernova Legacy Survey (SNLS). We have also applied the method to a large suite of realistic simulated light curves for existing and planned surveys, including SDSS, SNLS, and LSST. When intrinsic SN color fluctuations are included, the photo-z precision for the simulation is consistent with that in the data. Finally, we compare the LCFIT+Z photo-z precision with previous results using color-based SN photo-z estimates.

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Measurements of the Rate of Type Ia Supernovae at Redshift z < ~0.3 from the SDSS-II Supernova Survey

We present a measurement of the volumetric Type Ia supernova (SN Ia) rate based on data from the Sloan Digital Sky Survey II (SDSS-II) Supernova Survey. The adopted sample of supernovae (SNe) includes 516 SNe Ia at redshift z \lesssim 0.3, of which 270 (52%) are spectroscopically identified as SNe Ia. The remaining 246 SNe Ia were identified through their light curves; 113 of these objects have spectroscopic redshifts from spectra of their host galaxy, and 133 have photometric redshifts estimated from the SN light curves. Based on consideration of 87 spectroscopically confirmed non-Ia SNe discovered by the SDSS-II SN Survey, we estimate that 2.04+1.61-0.95 % of the photometric SNe Ia may be misidentified. The sample of SNe Ia used in this measurement represents an order of magnitude increase in the statistics for SN Ia rate measurements in the redshift range covered by the SDSS-II Supernova Survey. If we assume a SN Ia rate that is constant at low redshift (z < 0.15), then the SN observations can be used to infer a value of the SN rate of rV = (2.69+0.34+0.21-0.30-0.01) x10^{-5} SNe yr^{-1} Mpc-3 (H0 /(70 km s^{-1} Mpc^{-1}))^{3} at a mean redshift of ~ 0.12, based on 79 SNe Ia of which 72 are spectroscopically confirmed. However, the large sample of SNe Ia included in this study allows us to place constraints on the redshift dependence of the SN Ia rate based on the SDSS-II Supernova Survey data alone. Fitting a power-law model of the SN rate evolution, r_V(z) = A_p x ((1 + z)/(1 + z0))^ν, over the redshift range 0.0 < z < 0.3 with z0 = 0.21, results in A_p = (3.43+0.15-0.15) x 10^{-5} SNe yr^{-1} Mpc-3 (H0 /(70 km s^{-1} Mpc^{-1}))^{3} and ν= 2.04+0.90-0.89.

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A Measurement of the Rate of Type Ia Supernovae in Galaxy Clusters from the SDSS-II Supernova Survey

ABRIDGED We present measurements of the Type Ia supernova (SN) rate in galaxy clusters based on data from the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. The cluster SN Ia rate is determined from 9 SN events in a set of 71 C4 clusters at z <0.17 and 27 SN events in 492 maxBCG clusters at 0.1 < z < 0.3$. We find values for the cluster SN Ia rate of $({0.37}^{+0.17+0.01}_{-0.12-0.01}) \mathrm{SNu}r h^{2}$ and $({0.55}^{+0.13+0.02}_{-0.11-0.01}) \mathrm{SNu}r h^{2}$ ($\mathrm{SNu}x = 10^{-12} L_{x\sun}^{-1} \mathrm{yr}^{-1}$) in C4 and maxBCG clusters, respectively, where the quoted errors are statistical and systematic, respectively. The SN rate for early-type galaxies is found to be $({0.31}^{+0.18+0.01}_{-0.12-0.01}) \mathrm{SNu}r h^{2}$ and $({0.49}^{+0.15+0.02}_{-0.11-0.01})$ $\mathrm{SNu}r h^{2}$ in C4 and maxBCG clusters, respectively. The SN rate for the brightest cluster galaxies (BCG) is found to be $({2.04}^{+1.99+0.07}_{-1.11-0.04}) \mathrm{SNu}r h^{2}$ and $({0.36}^{+0.84+0.01}_{-0.30-0.01}) \mathrm{SNu}r h^{2}$ in C4 and maxBCG clusters. The ratio of the SN Ia rate in cluster early-type galaxies to that of the SN Ia rate in field early-type galaxies is ${1.94}^{+1.31+0.043}_{-0.91-0.015}$ and ${3.02}^{+1.31+0.062}_{-1.03-0.048}$, for C4 and maxBCG clusters. The SN rate in galaxy clusters as a function of redshift...shows only weak dependence on redshift. Combining our current measurements with previous measurements, we fit the cluster SN Ia rate data to a linear function of redshift, and find $r_{L} = $ $[(0.49^{+0.15}_{-0.14}) +$ $(0.91^{+0.85}_{-0.81}) \times z]$ $\mathrm{SNu}B$ $h^{2}$. A comparison of the radial distribution of SNe in cluster to field early-type galaxies shows possible evidence for an enhancement of the SN rate in the cores of cluster early-type galaxies... we estimate the fraction of cluster SNe that are hostless to be $(9.4^+8._3-5.1)%$.

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The Rise and Fall of Type Ia Supernova Light Curves in the SDSS-II Supernova Survey

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.

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Type II-P Supernovae from the SDSS-II Supernova Survey and the Standardized Candle Method

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 Sky 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.

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SNANA: A Public Software Package for Supernova Analysis

We describe a general analysis package for supernova (SN) light curves, called SNANA, that contains a simulation, light curve fitter, and cosmology fitter. The software is designed with the primary goal of using SNe Ia as distance indicators for the determination of cosmological parameters, but it can also be used to study efficiencies for analyses of SN rates, estimate contamination from non-Ia SNe, and optimize future surveys. Several SN models are available within the same software architecture, allowing technical features such as K-corrections to be consistently used among multiple models, and thus making it easier to make detailed comparisons between models. New and improved light-curve models can be easily added. The software works with arbitrary surveys and telescopes and has already been used by several collaborations, leading to more robust and easy-to-use code. This software is not intended as a final product release, but rather it is designed to undergo continual improvements from the community as more is learned about SNe. Below we give an overview of the SNANA capabilities, as well as some of its limitations. Interested users can find software downloads and more detailed information from the manuals at http://www.sdss.org/supernova/SNANA.html .

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The Sloan Digital Sky Survey-II: Photometry and Supernova Ia Light Curves from the 2005 data

We present ugriz light curves for 146 spectroscopically confirmed or spectroscopically probable Type Ia supernovae from the 2005 season of the SDSS-II Supernova survey. The light curves have been constructed using a photometric technique that we call scene modelling, which is described in detail here; the major feature is that supernova brightnesses are extracted from a stack of images without spatial resampling or convolution of the image data. This procedure produces accurate photometry along with accurate estimates of the statistical uncertainty, and can be used to derive photometry taken with multiple telescopes. We discuss various tests of this technique that demonstrate its capabilities. We also describe the methodology used for the calibration of the photometry, and present calibrated magnitudes and fluxes for all of the spectroscopic SNe Ia from the 2005 season.

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First-year Sloan Digital Sky Survey-II (SDSS-II) Supernova Results: Hubble Diagram and Cosmological Parameters

We present measurements of the Hubble diagram for 103 Type Ia supernovae (SNe) with redshifts 0.04 < z < 0.42, discovered during the first season (Fall 2005) of the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey. These data fill in the redshift "desert" between low- and high-redshift SN Ia surveys. We combine the SDSS-II measurements with new distance estimates for published SN data from the ESSENCE survey, the Supernova Legacy Survey, the Hubble Space Telescope, and a compilation of nearby SN Ia measurements. Combining the SN Hubble diagram with measurements of Baryon Acoustic Oscillations from the SDSS Luminous Red Galaxy sample and with CMB temperature anisotropy measurements from WMAP, we estimate the cosmological parameters w and Omega_M, assuming a spatially flat cosmological model (FwCDM) with constant dark energy equation of state parameter, w. For the FwCDM model and the combined sample of 288 SNe Ia, we find w = -0.76 +- 0.07(stat) +- 0.11(syst), Omega_M = 0.306 +- 0.019(stat) +- 0.023(syst) using MLCS2k2 and w = -0.96 +- 0.06(stat) +- 0.12(syst), Omega_M = 0.265 +- 0.016(stat) +- 0.025(syst) using the SALT-II fitter. We trace the discrepancy between these results to a difference in the rest-frame UV model combined with a different luminosity correction from color variations; these differences mostly affect the distance estimates for the SNLS and HST supernovae. We present detailed discussions of systematic errors for both light-curve methods and find that they both show data-model discrepancies in rest-frame $U$-band. For the SALT-II approach, we also see strong evidence for redshift-dependence of the color-luminosity parameter (beta). Restricting the analysis to the 136 SNe Ia in the Nearby+SDSS-II samples, we find much better agreement between the two analysis methods but with larger uncertainties.

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The Carnegie Supernova Project: First Near-Infrared Hubble Diagram to z~0.7

The Carnegie Supernova Project (CSP) is designed to measure the luminosity distance for Type Ia supernovae (SNe Ia) as a function of redshift, and to set observational constraints on the dark energy contribution to the total energy content of the Universe. The CSP differs from other projects to date in its goal of providing an I-band {rest-frame} Hubble diagram. Here we present the first results from near-infrared (NIR) observations obtained using the Magellan Baade telescope for SNe Ia with 0.1 < z < 0.7. We combine these results with those from the low-redshift CSP at z <0.1 (Folatelli et al. 2009). We present light curves and an I-band Hubble diagram for this first sample of 35 SNe Ia and we compare these data to 21 new SNe Ia at low redshift. These data support the conclusion that the expansion of the Universe is accelerating. When combined with independent results from baryon acoustic oscillations (Eisenstein et al. 2005), these data yield Omega_m = 0.27 +/- 0.0 (statistical), and Omega_DE = 0.76 +/- 0.13 (statistical) +/- 0.09 (systematic), for the matter and dark energy densities, respectively. If we parameterize the data in terms of an equation of state, w, assume a flat geometry, and combine with baryon acoustic oscillations, we find that w = -1.05 +/- 0.13 (statistical) +/- 0.09 (systematic). The largest source of systematic uncertainty on w arises from uncertainties in the photometric calibration, signaling the importance of securing more accurate photometric calibrations for future supernova cosmology programs. Finally, we conclude that either the dust affecting the luminosities of SNe Ia has a different extinction law (R_V = 1.8) than that in the Milky Way (where R_V = 3.1), or that there is an additional intrinsic color term with luminosity for SNe Ia independent of the decline rate.

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Type II Supernovae as Probes of Cosmology

- Constraining the cosmological parameters and understanding Dark Energy have tremendous implications for the nature of the Universe and its physical laws. - The pervasive limit of systematic uncertainties reached by cosmography based on Cepheids and Type Ia supernovae (SNe Ia) warrants a search for complementary approaches. - Type II SNe have been shown to offer such a path. Their distances can be well constrained by luminosity-based or geometric methods. Competing, complementary, and concerted efforts are underway, to explore and exploit those objects that are extremely well matched to next generation facilities. Spectroscopic follow-up will be enabled by space- based and 20-40 meter class telescopes. - Some systematic uncertainties of Type II SNe, such as reddening by dust and metallicity effects, are bound to be different from those of SNe Ia. Their stellar progenitors are known, promising better leverage on cosmic evolution. In addition, their rate - which closely tracks the ongoing star formation rate - is expected to rise significantly with look- back time, ensuring an adequate supply of distant examples. - These data will competitively constrain the dark energy equation of state, allow the determination of the Hubble constant to 5%, and promote our understanding of the processes involved in the last dramatic phases of massive stellar evolution.

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