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Saurabh Jha

Publications and source records attributed to Saurabh Jha.

At least 73 records · Page 4Linked to original sources

P-HGRMS: A Parallel Hypergraph Based Root Mean Square Algorithm for Image Denoising

This paper presents a parallel Salt and Pepper (SP) noise removal algorithm in a grey level digital image based on the Hypergraph Based Root Mean Square (HGRMS) approach. HGRMS is generic algorithm for identifying noisy pixels in any digital image using a two level hierarchical serial approach. However, for SP noise removal, we reduce this algorithm to a parallel model by introducing a cardinality matrix and an iteration factor, k, which helps us reduce the dependencies in the existing approach. We also observe that the performance of the serial implementation is better on smaller images, but once the threshold is achieved in terms of image resolution, its computational complexity increases drastically. We test P-HGRMS using standard images from the Berkeley Segmentation dataset on NVIDIAs Compute Unified Device Architecture (CUDA) for noise identification and attenuation. We also compare the noise removal efficiency of the proposed algorithm using Peak Signal to Noise Ratio (PSNR) to the existing approach. P-HGRMS maintains the noise removal efficiency and outperforms its sequential counterpart by 6 to 18 times (6x - 18x) in computational efficiency.

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Exploiting Data Parallelism in the yConvex Hypergraph Algorithm for Image Representation using GPGPUs

To define and identify a region-of-interest (ROI) in a digital image, the shape descriptor of the ROI has to be described in terms of its boundary characteristics. To address the generic issues of contour tracking, the yConvex Hypergraph (yCHG) model was proposed by Kanna et al [1]. In this work, we propose a parallel approach to implement the yCHG model by exploiting massively parallel cores of NVIDIA's Compute Unified Device Architecture (CUDA). We perform our experiments on the MODIS satellite image database by NASA, and based on our analysis we observe that the performance of the serial implementation is better on smaller images, but once the threshold is achieved in terms of image resolution, the parallel implementation outperforms its sequential counterpart by 2 to 10 times (2x-10x). We also conclude that an increase in the number of hyperedges in the ROI of a given size does not impact the performance of the overall algorithm.

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Testing Models of Intrinsic Brightness Variations in Type Ia Supernovae, and their Impact on Measuring Cosmological Parameters

For spectroscopically confirmed Type Ia supernovae we evaluate models of intrinsic brightness variations with detailed data/Monte Carlo comparisons of the dispersion in the following quantities: Hubble-diagram scatter, color difference (B-V-c) between the true B-V color and the fitted color (c) from the SALT-II light curve model, and photometric redshift residual. The data sample includes 251 ugriz light curves from the 3-season Sloan Digital Sky Survey-II, and 191 griz light curves from the Supernova Legacy Survey 3-year data release. We find that the simplest model of a wavelength-independent (coherent) scatter is not adequate, and that to describe the data the intrinsic scatter model must have wavelength-dependent variations. We use Monte Carlo simulations to examine the standard approach of adding a coherent scatter term in quadrature to the distance-modulus uncertainty in order to bring the reduced chi2 to unity when fitting a Hubble diagram. If the light curve fits include model uncertainties with the correct wavelength dependence of the scatter, we find that the bias on the dark energy equation of state parameter $w$ is negligible. However, incorrect model uncertainties can lead to a significant bias on the distance moduli, with up to ~0.05 mag redshift-dependent variation. For the recent SNLS3 cosmology results we estimate that this effect introduces an additional systematic uncertainty on $w$ of ~0.02, well below the total uncertainty. However, this uncertainty depends on the samples used, and thus this small $w$-uncertainty is not guaranteed in future cosmology results.

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A highly magnified candidate for a young galaxy seen when the Universe was 500 Myrs old

The early Universe at redshift z\sim6-11 marks the reionization of the intergalactic medium, following the formation of the first generation of stars. However, those young galaxies at a cosmic age of \lesssim 500 million years (Myr, at z \gtrsim 10) remain largely unexplored as they are at or beyond the sensitivity limits of current large telescopes. Gravitational lensing by galaxy clusters enables the detection of high-redshift galaxies that are fainter than what otherwise could be found in the deepest images of the sky. We report the discovery of an object found in the multi-band observations of the cluster MACS1149+22 that has a high probability of being a gravitationally magnified object from the early universe. The object is firmly detected (12 sigma) in the two reddest bands of HST/WFC3, and not detected below 1.2 μm, matching the characteristics of z\sim9 objects. We derive a robust photometric redshift of z = 9.6 \pm 0.2, corresponding to a cosmic age of 490 \pm 15Myr (i.e., 3.6% of the age of the Universe). The large number of bands used to derive the redshift estimate make it one of the most accurate estimates ever obtained for such a distant object. The significant magnification by cluster lensing (a factor of \sim15) allows us to analyze the object's ultra-violet and optical luminosity in its rest-frame, thus enabling us to constrain on its stellar mass, star-formation rate and age. If the galaxy is indeed at such a large redshift, then its age is less than 200 Myr (at the 95% confidence level), implying a formation redshift of zf \lesssim 14. The object is the first z>9 candidate that is bright enough for detailed spectroscopic studies with JWST, demonstrating the unique potential of galaxy cluster fields for finding highly magnified, intrinsically faint galaxies at the highest redshifts.

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CLASH: Precise New Constraints on the Mass Profile of Abell 2261

We precisely constrain the inner mass profile of Abell 2261 (z=0.225) for the first time and determine this cluster is not "over-concentrated" as found previously, implying a formation time in agreement with ΛCDM expectations. These results are based on strong lensing analyses of new 16-band HST imaging obtained as part of the Cluster Lensing and Supernova survey with Hubble (CLASH). Combining this with revised weak lensing analyses of Subaru wide field imaging with 5-band Subaru + KPNO photometry, we place tight new constraints on the halo virial mass M_vir = 2.2\pm0.2\times10^15 M\odot/h70 (within r \approx 3 Mpc/h70) and concentration c = 6.2 \pm 0.3 when assuming a spherical halo. This agrees broadly with average c(M,z) predictions from recent ΛCDM simulations which span 5 <~ <~ 8. Our most significant systematic uncertainty is halo elongation along the line of sight. To estimate this, we also derive a mass profile based on archival Chandra X-ray observations and find it to be ~35% lower than our lensing-derived profile at r2500 ~ 600 kpc. Agreement can be achieved by a halo elongated with a ~2:1 axis ratio along our line of sight. For this elongated halo model, we find M_vir = 1.7\pm0.2\times10^15 M\odot/h70 and c_vir = 4.6\pm0.2, placing rough lower limits on these values. The need for halo elongation can be partially obviated by non-thermal pressure support and, perhaps entirely, by systematic errors in the X-ray mass measurements. We estimate the effect of background structures based on MMT/Hectospec spectroscopic redshifts and find these tend to lower Mvir further by ~7% and increase cvir by ~5%.

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Cluster Lensing And Supernova survey with Hubble (CLASH): An Overview

The Cluster Lensing And Supernova survey with Hubble (CLASH) is a 524-orbit multi-cycle treasury program to use the gravitational lensing properties of 25 galaxy clusters to accurately constrain their mass distributions. The survey, described in detail in this paper, will definitively establish the degree of concentration of dark matter in the cluster cores, a key prediction of CDM. The CLASH cluster sample is larger and less biased than current samples of space-based imaging studies of clusters to similar depth, as we have minimized lensing-based selection that favors systems with overly dense cores. Specifically, twenty CLASH clusters are solely X-ray selected. The X-ray selected clusters are massive (kT > 5 keV; 5 - 30 x 10^14 M_solar) and, in most cases, dynamically relaxed. Five additional clusters are included for their lensing strength (Einstein radii > 35 arcsec at z_source = 2) to further quantify the lensing bias on concentration, to yield high resolution dark matter maps, and to optimize the likelihood of finding highly magnified high-redshift (z > 7) galaxies. The high magnification, in some cases, provides angular resolutions unobtainable with any current UVOIR facility and can yield z > 7 candidates bright enough for spectroscopic follow-up. A total of 16 broadband filters, spanning the near-UV to near-IR, are employed for each 20-orbit campaign on each cluster. These data are used to measure precise (sigma_phz < 0.02(1+z)) photometric redshifts for dozens of newly discovered multiply-lensed images per cluster. Observations of each cluster are spread over 8 epochs to enable a search, primarily in the parallel fields, for Type Ia supernovae at z > 1 to improve constraints on the time dependence of the dark energy equation of state and the evolution of such supernovae in an epoch when the universe is matter dominated.

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CANDELS: The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey - The Hubble Space Telescope Observations, Imaging Data Products and Mosaics

This paper describes the Hubble Space Telescope imaging data products and data reduction procedures for the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS). This survey is designed to document the evolution of galaxies and black holes at $z\sim1.5-8$, and to study Type Ia SNe beyond $z>1.5$. Five premier multi-wavelength sky regions are selected, each with extensive multiwavelength observations. The primary CANDELS data consist of imaging obtained in the Wide Field Camera 3 / infrared channel (WFC3/IR) and UVIS channel, along with the Advanced Camera for Surveys (ACS). The CANDELS/Deep survey covers \sim125 square arcminutes within GOODS-N and GOODS-S, while the remainder consists of the CANDELS/Wide survey, achieving a total of \sim800 square arcminutes across GOODS and three additional fields (EGS, COSMOS, and UDS). We summarize the observational aspects of the survey as motivated by the scientific goals and present a detailed description of the data reduction procedures and products from the survey. Our data reduction methods utilize the most up to date calibration files and image combination procedures. We have paid special attention to correcting a range of instrumental effects, including CTE degradation for ACS, removal of electronic bias-striping present in ACS data after SM4, and persistence effects and other artifacts in WFC3/IR. For each field, we release mosaics for individual epochs and eventual mosaics containing data from all epochs combined, to facilitate photometric variability studies and the deepest possible photometry. A more detailed overview of the science goals and observational design of the survey are presented in a companion paper.

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The Massive Progenitor of the Possible Type II-Linear Supernova 2009hd in Messier 66

We present observations of SN2009hd in the nearby galaxy M66. This SN is one of the closest to us in recent years but heavily obscured by dust, rendering it unusually faint in the optical, given its proximity. We find that the observed properties of SN2009hd support its classification as a possible Type II-L SN, a relatively rare subclass of CC-SNe. High-precision relative astrometry has been employed to attempt to identify a SN progenitor candidate, based on a pixel-by-pixel comparison between HST F555W and F814W images of the SN site prior to explosion and at late times. A progenitor candidate is identified in the F814W images only; this object is undetected in F555W. Significant uncertainty exists in the astrometry, such that we cannot definitively identify this object as the SN progenitor. Via insertion of artificial stars into the pre-SN HST images, we are able to constrain the progenitor's properties to those of a possible supergiant, with M(F555W)0>-7.6 mag and (V-I) 0>0.99 mag. The magnitude and color limits are consistent with a luminous RSG; however, they also allow for the possibility that the star could have been more yellow than red. From a comparison with theoretical massive-star evolutionary tracks, which include rotation and pulsationally enhanced mass loss, we can place a conservative upper limit on the initial mass for the progenitor of <20 M_sun. If the actual mass of the progenitor is near the upper range allowed by our derived mass limit, then it would be consistent with that for the identified progenitors of the SNII-L 2009kr and the high-luminosity SNII-P 2008cn. The progenitors of these three SNe may possibly bridge the gap between lower-mass RSG that explode as SNeII-P and LBV, or more extreme RSG, from which the more exotic SNeII-n may arise. Very late-time imaging of the SN2009hd site may provide us with more clues regarding the true nature of its progenitor.

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Nearby Supernova Rates from the Lick Observatory Supernova Search. II. The Observed Luminosity Functions and Fractions of Supernovae in a Complete Sample

This is the second paper of a series in which we present new measurements of the observed rates of supernovae (SNe) in the local Universe, determined from the Lick Observatory Supernova Search (LOSS). In this paper, a complete SN sample is constructed, and the observed (uncorrected for host-galaxy extinction) luminosity functions (LFs) of SNe are derived. These LFs solve two issues that have plagued previous rate calculations for nearby SNe: the luminosity distribution of SNe and the host-galaxy extinction. We select a volume-limited sample of 175 SNe, collect photometry for every object, and fit a family of light curves to constrain the peak magnitudes and light-curve shapes. The volume-limited LFs show that they are not well represented by a Gaussian distribution. There are notable differences in the LFs for galaxies of different Hubble types (especially for SNe Ia). We derive the observed fractions for the different subclasses in a complete SN sample, and find significant fractions of SNe II-L (10%), IIb (12%), and IIn (9%) in the SN II sample. Furthermore, we derive the LFs and the observed fractions of different SN subclasses in a magnitude-limited survey with different observation intervals, and find that the LFs are enhanced at the high-luminosity end and appear more "standard" with smaller scatter, and that the LFs and fractions of SNe do not change significantly when the observation interval is shorter than 10 days. We also discuss the LFs in different galaxy sizes and inclinations, and for different SN subclasses. Some notable results are ... (abridged).

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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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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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Supernova Photometric Classification Challenge

We have publicly released a blinded mix of simulated SNe, with types (Ia, Ib, Ic, II) selected in proportion to their expected rate. The simulation is 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). We challenge scientists to run their classification algorithms and report a type for each SN. A spectroscopically confirmed subset is provided for training. The goals of this challenge are to (1) learn the relative strengths and weaknesses of the different classification algorithms, (2) use the results to improve classification algorithms, and (3) understand what spectroscopically confirmed sub-sets are needed to properly train these algorithms. The challenge is available at www.hep.anl.gov/SNchallenge, and the due date for classifications is May 1, 2010.

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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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CfA3: 185 Type Ia Supernova Light Curves from the CfA

We present multi-band photometry of 185 type-Ia supernovae (SN Ia), with over 11500 observations. These were acquired between 2001 and 2008 at the F. L. Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics (CfA). This sample contains the largest number of homogeneously-observed and reduced nearby SN Ia (z < 0.08) published to date. It more than doubles the nearby sample, bringing SN Ia cosmology to the point where systematic uncertainties dominate. Our natural system photometry has a precision of 0.02 mag or better in BVRIr'i' and roughly 0.04 mag in U for points brighter than 17.5 mag. We also estimate a systematic uncertainty of 0.03 mag in our SN Ia standard system BVRIr'i' photometry and 0.07 mag for U. Comparisons of our standard system photometry with published SN Ia light curves and comparison stars, where available for the same SN, reveal agreement at the level of a few hundredths mag in most cases. We find that 1991bg-like SN Ia are sufficiently distinct from other SN Ia in their color and light-curve-shape/luminosity relation that they should be treated separately in light-curve/distance fitter training samples. The CfA3 sample will contribute to the development of better light-curve/distance fitters, particularly in the few dozen cases where near-infrared photometry has been obtained and, together, can help disentangle host-galaxy reddening from intrinsic supernova color, reducing the systematic uncertainty in SN Ia distances due to dust.

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Improved Dark Energy Constraints from ~100 New CfA Supernova Type Ia Light Curves

We combine the CfA3 supernova Type Ia (SN Ia) sample with samples from the literature to calculate improved constraints on the dark energy equation of state parameter, w. The CfA3 sample is added to the Union set of Kowalski et al. (2008) to form the Constitution set and, combined with a BAO prior, produces 1+w=0.013 +0.066/-0.068 (0.11 syst), consistent with the cosmological constant. The CfA3 addition makes the cosmologically-useful sample of nearby SN Ia between 2.6 and 2.9 times larger than before, reducing the statistical uncertainty to the point where systematics play the largest role. We use four light curve fitters to test for systematic differences: SALT, SALT2, MLCS2k2 (R_V=3.1), and MLCS2k2 (R_V=1.7). SALT produces high-redshift Hubble residuals with systematic trends versus color and larger scatter than MLCS2k2. MLCS2k2 overestimates the intrinsic luminosity of SN Ia with 0.7 < Delta < 1.2. MLCS2k2 with R_V=3.1 overestimates host-galaxy extinction while R_V=1.7 does not. Our investigation is consistent with no Hubble bubble. We also find that, after light-curve correction, SN Ia in Scd/Sd/Irr hosts are intrinsically fainter than those in E/S0 hosts by 2 sigma, suggesting that they may come from different populations. We also find that SN Ia in Scd/Sd/Irr hosts have low scatter (0.1 mag) and reddening. Current systematic errors can be reduced by improving SN Ia photometric accuracy, by including the CfA3 sample to retrain light-curve fitters, by combining optical SN Ia photometry with near-infrared photometry to understand host-galaxy extinction, and by determining if different environments give rise to different intrinsic SN Ia luminosity after correction for light-curve shape and color.

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