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Joshua Frieman

Publications and source records attributed to Joshua Frieman.

At least 37 records · Page 2Linked to original sources

Hubble Space Telescope and Ground-Based Observations of the Type Iax Supernovae SN 2005hk and SN 2008A

We present Hubble Space Telescope (HST) and ground-based optical and near-infrared observations of SN 2005hk and SN 2008A, typical members of the Type Iax class of supernovae (SNe). Here we focus on late-time observations, where these objects deviate most dramatically from all other SN types. Instead of the dominant nebular emission lines that are observed in other SNe at late phases, spectra of SNe 2005hk and 2008A show lines of Fe II, Ca II, and Fe I more than a year past maximum light, along with narrow [Fe II] and [Ca II] emission. We use spectral features to constrain the temperature and density of the ejecta, and find high densities at late times, with n_e >~ 10^9 cm^-3. Such high densities should yield enhanced cooling of the ejecta, making these objects good candidates to observe the expected "infrared catastrophe," a generic feature of SN Ia models. However, our HST photometry of SN 2008A does not match the predictions of an infrared catastrophe. Moreover, our HST observations rule out a "complete deflagration" that fully disrupts the white dwarf for these peculiar SNe, showing no evidence for unburned material at late times. Deflagration explosion models that leave behind a bound remnant can match some of the observed properties of SNe Iax, but no published model is consistent with all of our observations of SNe 2005hk and 2008A.

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Facilities for Dark Energy Investigations

The discovery of cosmic acceleration has inspired ambitious experimental and observational efforts to understand its origin. Many of these take the form of large astronomical surveys, sometimes using new, special-purpose instrumentation, and in some cases entirely new facilities. This Report summarizes some of the major ongoing and planned dark energy experiments, focusing on those in which the U.S. community has a leading or significant supporting role. It provides background information for other Reports from the "Dark Energy and CMB" working group of the APS Division of Particles and Fields long-term planning exercise. We provide 1-2 page summaries of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) and its SDSS-IV successor eBOSS, the Dark Energy Survey (DES), the Subaru Hyper-Suprime Camera (HSC) and Prime Focus Spectrograph (PFS), the Hobby-Eberley Telescope Dark Energy Experiment (HEDTEX), the Dark Energy Spectroscopic Instrument (DESI), the Large Synpotic Survey Telescope (LSST), and the Euclid and AFTA-WFIRST (Wide Field Infrared Survey Telescope) space missions. Over the next one to two decades, these experiments seek to improve the precision of measurements of the cosmic expansion history and cosmic structure growth by factors of 10-100, while simultaneously increasing their redshift range and tightening control and cross-checks of sytematic effects. These measurements will dramatically improve the empirical constraints on theoretical explanations of cosmic acceleration and could lead to breakthroughs in our understanding of the nature of gravity and spacetime or the forms of energy present in the universe.

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The Multi-Object, Fiber-Fed Spectrographs for SDSS and the Baryon Oscillation Spectroscopic Survey

We present the design and performance of the multi-object fiber spectrographs for the Sloan Digital Sky Survey (SDSS) and their upgrade for the Baryon Oscillation Spectroscopic Survey (BOSS). Originally commissioned in Fall 1999 on the 2.5-m aperture Sloan Telescope at Apache Point Observatory, the spectrographs produced more than 1.5 million spectra for the SDSS and SDSS-II surveys, enabling a wide variety of Galactic and extra-galactic science including the first observation of baryon acoustic oscillations in 2005. The spectrographs were upgraded in 2009 and are currently in use for BOSS, the flagship survey of the third-generation SDSS-III project. BOSS will measure redshifts of 1.35 million massive galaxies to redshift 0.7 and Lyman-alpha absorption of 160,000 high redshift quasars over 10,000 square degrees of sky, making percent level measurements of the absolute cosmic distance scale of the Universe and placing tight constraints on the equation of state of dark energy. The twin multi-object fiber spectrographs utilize a simple optical layout with reflective collimators, gratings, all-refractive cameras, and state-of-the-art CCD detectors to produce hundreds of spectra simultaneously in two channels over a bandpass covering the near ultraviolet to the near infrared, with a resolving power R = λ/FWHM ~ 2000. Building on proven heritage, the spectrographs were upgraded for BOSS with volume-phase holographic gratings and modern CCD detectors, improving the peak throughput by nearly a factor of two, extending the bandpass to cover 360 < λ< 1000 nm, and increasing the number of fibers from 640 to 1000 per exposure. In this paper we describe the original SDSS spectrograph design and the upgrades implemented for BOSS, and document the predicted and measured performances.

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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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Type Ia Supernova Properties as a Function of the Distance to the Host Galaxy in the SDSS-II SN Survey

We use type-Ia supernovae (SNe Ia) discovered by the SDSS-II SN Survey to search for dependencies between SN Ia properties and the projected distance to the host galaxy center, using the distance as a proxy for local galaxy properties (local star-formation rate, local metallicity, etc.). The sample consists of almost 200 spectroscopically or photometrically confirmed SNe Ia at redshifts below 0.25. The sample is split into two groups depending on the morphology of the host galaxy. We fit light-curves using both MLCS2k2 and SALT2, and determine color (AV, c) and light-curve shape (delta, x1) parameters for each SN Ia, as well as its residual in the Hubble diagram. We then correlate these parameters with both the physical and the normalized distances to the center of the host galaxy and look for trends in the mean values and scatters of these parameters with increasing distance. The most significant (at the 4-sigma level) finding is that the average fitted AV from MLCS2k2 and c from SALT2 decrease with the projected distance for SNe Ia in spiral galaxies. We also find indications that SNe in elliptical galaxies tend to have narrower light-curves if they explode at larger distances, although this may be due to selection effects in our sample. We do not find strong correlations between the residuals of the distance moduli with respect to the Hubble flow and the galactocentric distances, which indicates a limited correlation between SN magnitudes after standardization and local host metallicity.

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Photometric Supernova Cosmology with BEAMS and SDSS-II

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 (Ω_m,Ω_Λ) 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 Ω_m(BEAMS)=0.194\pm0.07. This illustrates the potential power of BEAMS for future large photometric supernova surveys such as LSST.

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The SDSS-II Supernova Survey: Parameterizing the Type Ia Supernova Rate as a Function of Host Galaxy Properties

Using data from the Sloan Digital Sky Supernova Survey-II, we measure the rate of Type Ia Supernovae (SNe Ia) as a function of galaxy properties at intermediate redshift. A sample of 342 SNe Ia with 0.05<z<0.25 is constructed. Using broad-band photometry we use the PEGASE spectral energy distributions (SEDs) to estimate host galaxy stellar masses and recent star-formation rates. We find that the rate of SNe Ia per unit stellar mass is significantly higher (by a factor of ~30) in highly star-forming galaxies compared to passive galaxies. When parameterizing the SN Ia rate (SNR_Ia) based on host galaxy properties, we find that the rate of SNe Ia in passive galaxies is not linearly proportional to the stellar mass, instead a SNR_Ia proportional to M^0.68 is favored. However, such a parameterization does not describe the observed SN Ia rate in star-forming galaxies. The SN Ia rate in star-forming galaxies is well fit by SNR_Ia = 1.05\pm0.16x10^{-10} M ^{0.68\pm0.01} + 1.01\pm0.09x10^{-3} SFR^{1.00\pm0.05} (statistical errors only), where M is the host galaxy mass and SFR is the star-formation rate. These results are insensitive to the selection criteria used, redshift limit considered and the inclusion of non-spectroscopically confirmed SNe Ia. We also show there is a dependence between the distribution of the MLCS light-curve decline rate parameter, Δ, and host galaxy type. Passive galaxies host less luminous SNe Ia than seen in moderately and highly star-forming galaxies, although a population of luminous SNe is observed in passive galaxies, contradicting previous assertions that these SNe Ia are only observed in younger stellar systems. The MLCS extinction parameter, A_V, is similar in passive and moderately star-forming galaxies, but we find indications that it is smaller, on average, in highly star-forming galaxies. We confirm these results using the SALT2 light-curve fitter.

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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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Spectroscopic Determination of the Low Redshift Type Ia Supernova Rate from the Sloan Digital Sky Survey

Supernova rates are directly coupled to high mass stellar birth and evolution. As such, they are one of the few direct measures of the history of cosmic stellar evolution. In this paper we describe an probabilistic technique for identifying supernovae within spectroscopic samples of galaxies. We present a study of 52 type Ia supernovae ranging in age from -14 days to +40 days extracted from a parent sample of \simeq 50,000 spectra from the SDSS DR5. We find a Supernova Rate (SNR) of 0.472^{+0.048}_{-0.039}(Systematic)^{+0.081}_{-0.071}(Statistical)SNu at a redshift of = 0.1. This value is higher than other values at low redshift at the 1σ, but is consistent at the 3σ level. The 52 supernova candidates used in this study comprise the third largest sample of supernovae used in a type Ia rate determination to date. In this paper we demonstrate the potential for the described approach for detecting supernovae in future spectroscopic surveys.

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Estimating the Redshift Distribution of Photometric Galaxy Samples II. Applications and Tests of a New Method

In Lima et al. 2008 we presented a new method for estimating the redshift distribution, N(z), of a photometric galaxy sample, using photometric observables and weighted sampling from a spectroscopic subsample of the data. In this paper, we extend this method and explore various applications of it, using both simulations of and real data from the SDSS. In addition to estimating the redshift distribution for an entire sample, the weighting method enables accurate estimates of the redshift probability distribution, p(z), for each galaxy in a photometric sample. Use of p(z) in cosmological analyses can substantially reduce biases associated with traditional photometric redshifts, in which a single redshift estimate is associated with each galaxy. The weighting procedure also naturally indicates which galaxies in the photometric sample are expected to have accurate redshift estimates, namely those that lie in regions of photometric-observable space that are well sampled by the spectroscopic subsample. In addition to providing a method that has some advantages over standard photo-z estimates, the weights method can also be used in conjunction with photo-z estimates, e.g., by providing improved estimation of N(z) via deconvolution of N(photo-z) and improved estimates of photo-z scatter and bias. We present a publicly available p(z) catalog for ~78 million SDSS DR7 galaxies.

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Constraining the Scatter in the Mass-Richness Relation of maxBCG Clusters With Weak Lensing and X-ray Data

We measure the logarithmic scatter in mass at fixed richness for clusters in the maxBCG cluster catalog, an optically selected cluster sample drawn from SDSS imaging data. Our measurement is achieved by demanding consistency between available weak lensing and X-ray measurements of the maxBCG clusters, and the X-ray luminosity--mass relation inferred from the 400d X-ray cluster survey, a flux limited X-ray cluster survey. We find σ_{\ln M|N_{200}}=0.45^{+0.20}_{-0.18} (95% CL) at N_{200} ~ 40, where N_{200} is the number of red sequence galaxies in a cluster. As a byproduct of our analysis, we also obtain a constraint on the correlation coefficient between \ln Lx and \ln M at fixed richness, which is best expressed as a lower limit, r_{L,M|N} >= 0.85 (95% CL). This is the first observational constraint placed on a correlation coefficient involving two different cluster mass tracers. We use our results to produce a state of the art estimate of the halo mass function at z=0.23 -- the median redshift of the maxBCG cluster sample -- and find that it is consistent with the WMAP5 cosmology. Both the mass function data and its covariance matrix are presented.

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Dark Energy and the Accelerating Universe

The discovery ten years ago that the expansion of the Universe is accelerating put in place the last major building block of the present cosmological model, in which the Universe is composed of 4% baryons, 20% dark matter, and 76% dark energy. At the same time, it posed one of the most profound mysteries in all of science, with deep connections to both astrophysics and particle physics. Cosmic acceleration could arise from the repulsive gravity of dark energy -- for example, the quantum energy of the vacuum -- or it may signal that General Relativity breaks down on cosmological scales and must be replaced. We review the present observational evidence for cosmic acceleration and what it has revealed about dark energy, discuss the various theoretical ideas that have been proposed to explain acceleration, and describe the key observational probes that will shed light on this enigma in the coming years.

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Estimating the Redshift Distribution of Faint Galaxy Samples

We present an empirical method for estimating the underlying redshift distribution N(z) of galaxy photometric samples from photometric observables. The method does not rely on photometric redshift (photo-z) estimates for individual galaxies, which typically suffer from biases. Instead, it assigns weights to galaxies in a spectroscopic subsample such that the weighted distributions of photometric observables (e.g., multi-band magnitudes) match the corresponding distributions for the photometric sample. The weights are estimated using a nearest-neighbor technique that ensures stability in sparsely populated regions of color-magnitude space. The derived weights are then summed in redshift bins to create the redshift distribution. We apply this weighting technique to data from the Sloan Digital Sky Survey as well as to mock catalogs for the Dark Energy Survey, and compare the results to those from the estimation of photo-z's derived by a neural network algorithm. We find that the weighting method accurately recovers the underlying redshift distribution, typically better than the photo-z reconstruction, provided the spectroscopic subsample spans the range of photometric observables covered by the photometric sample.

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Modeling the three-point correlation function

We present new predictions for the galaxy three-point correlation function (3PCF) using high-resolution dissipationless cosmological simulations of a flat LCDM Universe which resolve galaxy-size halos and subhalos. We create realistic mock galaxy catalogs by assigning luminosities and colors to dark matter halos and subhalos, and we measure the reduced 3PCF as a function of luminosity and color in both real and redshift space. As galaxy luminosity and color are varied, we find small differences in the amplitude and shape dependence of the reduced 3PCF, at a level qualitatively consistent with recent measurements from the SDSS and 2dFGRS. We confirm that discrepancies between previous 3PCF measurements can be explained in part by differences in binning choices. We explore the degree to which a simple local bias model can fit the simulated 3PCF. The agreement between the model predictions and galaxy 3PCF measurements lends further credence to the straightforward association of galaxies with CDM halos and subhalos.

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Photometric Redshift Error Estimators

Photometric redshift (photo-z) estimates are playing an increasingly important role in extragalactic astronomy and cosmology. Crucial to many photo-z applications is the accurate quantification of photometric redshift errors and their distributions, including identification of likely catastrophic failures in photo-z estimates. We consider several methods of estimating photo-z errors and propose new training-set based error estimators based on spectroscopic training set data. Using data from the Sloan Digital Sky Survey and simulations of the Dark Energy Survey as examples, we show that this method provides a robust, relatively unbiased estimate of photo-z errors. We show that culling objects with large, accurately estimated photo-z errors from a sample can reduce the incidence of catastrophic photo-z failures.

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A Galaxy Photometric Redshift Catalog for the Sloan Digital Sky Survey Data Release 6

We present and describe a catalog of galaxy photometric redshifts (photo-z's) for the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6). We use the Artificial Neural Network (ANN) technique to calculate photo-z's and the Nearest Neighbor Error (NNE) method to estimate photo-z errors for ~ 77 million objects classified as galaxies in DR6 with r < 22. The photo-z and photo-z error estimators are trained and validated on a sample of ~ 640,000 galaxies that have SDSS photometry and spectroscopic redshifts measured by SDSS, 2SLAQ, CFRS, CNOC2, TKRS, DEEP, and DEEP2. For the two best ANN methods we have tried, we find that 68% of the galaxies in the validation set have a photo-z error smaller than sigma_{68} =0.021 or $0.024. After presenting our results and quality tests, we provide a short guide for users accessing the public data.

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Primordial non-Gaussianity and Dark Energy constraints from Cluster Surveys

Galaxy cluster surveys will be a powerful probe of dark energy. At the same time, cluster abundance is sensitive to any non-Gaussianity of the primordial density field. It is therefore possible that non-Gaussian initial conditions might be misinterpreted as a sign of dark energy or at least degrade the expected constraints on dark energy parameters. To address this issue, we perform a likelihood analysis of an ideal cluster survey similar in size and depth to the upcoming South Pole Telescope/Dark Energy Survey (SPT-DES). We analyze a model in which the strength of the non-Gaussianity is parameterized by the constant fNL; this model has been used extensively to derive Cosmic Microwave Background (CMB) anisotropy constraints on non-Gaussianity, allowing us to make contact with those works. We find that the constraining power of the cluster survey on dark energy observables is not significantly diminished by non-Gaussianity provided that cluster redshift information is included in the analysis. We also find that even an ideal cluster survey is unlikely to improve significantly current and future CMB constraints on non-Gaussianity. However, when all systematics are under control, it could constitute a valuable cross check to CMB observations.

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Distributions of Galaxy Spectral Types in the Sloan Digital Sky Survey

We perform an objective classification of 170,000 galaxy spectra in the Sloan Digital Sky Survey (SDSS) using the Karhunen-Loève (KL) transform. With about one-sixth of the total set of galaxy spectra which will be obtained by the survey, we are able to carry out the most extensive analysis of its kind to date. The formalism proposed by Connolly and Szalay is adopted to correct for gappy regions in the spectra, and to derive eigenspectra and eigencoefficients. From this analysis, we show that this gap-correction formalism leads to a converging set of eigenspectra and KL-repaired spectra. Furthermore, KL eigenspectra of galaxies are found to be convergent not only as a function of iteration, but also as a function of the number of randomly selected galaxy spectra used in the analysis. From these data a set of ten eigenspectra of galaxy spectra are constructed, with rest-wavelength coverage 3450-8350 angstrom. The eigencoefficients describing these galaxies naturally place the spectra into several classes defined by the plane formed by the first three eigencoefficients of each spectrum. Spectral types, corresponding to different Hubble-types and galaxies with extreme emission lines, are identified for the 170,000 spectra and are shown to be complementary to existing spectral classifications. From a non-parametric classification technique, we find that the population of galaxies can be divided into three classes which correspond to early late- through to intermediate late-types galaxies. (Abridged)

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