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Peter Nugent

Bio: Peter Nugent is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Supernova & Light curve. The author has an hindex of 127, co-authored 754 publications receiving 92988 citations. Previous affiliations of Peter Nugent include Liverpool John Moores University & National Autonomous University of Mexico.
Topics: Supernova, Light curve, Galaxy, Redshift, White dwarf


Papers
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Journal ArticleDOI
TL;DR: In this article, a broad-line Type Ic supernova (SN), PTF 10bzf (SN 2010ah), was detected by the Palomar Transient Factory (PTF) on 2010 February 23.
Abstract: We present the discovery and follow-up observations of a broad-line Type Ic supernova (SN), PTF 10bzf (SN 2010ah), detected by the Palomar Transient Factory (PTF) on 2010 February 23. The SN distance is ≅218 Mpc, greater than GRB 980425/SN 1998bw and GRB 060218/SN 2006aj, but smaller than the other SNe firmly associated with gamma-ray bursts (GRBs). We conducted a multi-wavelength follow-up campaign with Palomar 48 inch, Palomar 60 inch, Gemini-N, Keck, Wise, Swift, the Allen Telescope Array, Combined Array for Research in Millimeter-wave Astronomy, Westerbork Synthesis Radio Telescope, and Expanded Very Large Array. Here we compare the properties of PTF 10bzf with those of SN 1998bw and other broad-line SNe. The optical luminosity and spectral properties of PTF 10bzf suggest that this SN is intermediate, in kinetic energy and amount of ^(56)Ni, between non-GRB-associated SNe like 2002ap or 1997ef, and GRB-associated SNe like 1998bw. No X-ray or radio counterpart to PTF 10bzf was detected. X-ray upper limits allow us to exclude the presence of an underlying X-ray afterglow as luminous as that of other SN-associated GRBs such as GRB 030329 or GRB 031203. Early-time radio upper limits do not show evidence for mildly relativistic ejecta. Late-time radio upper limits rule out the presence of an underlying off-axis GRB, with energy and wind density similar to the SN-associated GRB 030329 and GRB 031203. Finally, by performing a search for a GRB in the time window and at the position of PTF 10bzf, we find that no GRB in the interplanetary network catalog could be associated with this SN.

59 citations

Journal ArticleDOI
M. Smith1, Mark Sullivan1, P. Wiseman1, Richard Kessler2, Daniel Scolnic3, D. J. Brout4, C. B. D'Andrea5, C. B. D'Andrea4, Tamara M. Davis6, Ryan J. Foley7, C. Frohmaier8, Lluís Galbany9, R. R. Gupta10, Claudia P. Gutiérrez1, Samuel Hinton6, L. Kelsey1, C. Lidman11, E. Macaulay12, E. Macaulay8, Anais Möller13, Anais Möller11, Robert C. Nichol8, Peter Nugent14, Peter Nugent10, Antonella Palmese15, Antonella Palmese2, M. Pursiainen1, M. Sako4, E. Swann8, R. C. Thomas10, Brad E. Tucker11, M. Vincenzi8, Daniela Carollo16, Geraint F. Lewis17, N. E. Sommer11, T. M. C. Abbott, Michel Aguena18, S. Allam15, Santiago Avila19, E. Bertin20, Sunayana Bhargava21, David J. Brooks22, E. Buckley-Geer15, D. L. Burke23, D. L. Burke24, A. Carnero Rosell, M. Carrasco Kind25, M. Carrasco Kind26, M. Costanzi16, L. N. da Costa, J. De Vicente, S. Desai27, H. T. Diehl15, Peter Doel22, Tim Eifler28, Tim Eifler29, S. Everett7, B. Flaugher15, Pablo Fosalba30, Josh Frieman15, Josh Frieman2, Juan Garcia-Bellido19, Enrique Gaztanaga30, Karl Glazebrook31, Daniel Gruen23, Daniel Gruen24, Robert A. Gruendl26, Robert A. Gruendl25, J. Gschwend, G. Gutierrez15, W. G. Hartley22, W. G. Hartley32, W. G. Hartley33, D. L. Hollowood7, K. Honscheid34, David J. James35, Elisabeth Krause28, Kyler Kuehn36, Kyler Kuehn37, N. Kuropatkin15, Marcus Lima18, Niall MacCrann34, M. A. G. Maia, Jennifer L. Marshall38, Paul Martini34, Peter Melchior39, Felipe Menanteau25, Felipe Menanteau26, Ramon Miquel40, Ramon Miquel41, F. Paz-Chinchón42, F. Paz-Chinchón26, A. A. Plazas39, A. K. Romer21, A. Roodman24, A. Roodman23, Eli S. Rykoff23, Eli S. Rykoff24, E. J. Sanchez, V. Scarpine15, Michael Schubnell43, S. Serrano30, I. Sevilla-Noarbe, E. Suchyta44, M. E. C. Swanson26, G. Tarle43, Daniel Thomas8, Douglas L. Tucker15, T. N. Varga45, T. N. Varga46, A. R. Walker 
TL;DR: In this article, the authors present improved photometric measurements for the host galaxies of 206 spectroscopically confirmed type Ia supernovae discovered by the Dark Energy Survey Supernova Program (DES-SN) and used in the first DES-SN cosmological analysis.
Abstract: We present improved photometric measurements for the host galaxies of 206 spectroscopically confirmed type Ia supernovae discovered by the Dark Energy Survey Supernova Program (DES-SN) and used in the first DES-SN cosmological analysis. For the DES-SN sample, when considering a 5D (z, x(1), c, alpha, #) bias correction, we find evidence of a Hubble residual 'mass step', where SNe Ia in high-mass galaxies (>10(10)M(circle dot)) are intrinsically more luminous (after correction) than their low-mass counterparts by gamma = 0.040 +/- 0.019 mag. This value is larger by 0.031 mag than the value found in the first DES-SN cosmological analysis. This difference is due to a combination of updated photometric measurements and improved star formation histories and is not from host-galaxy misidentification. When using a 1D (redshift-only) bias correction the inferred mass step is larger, with gamma = 0.066 +/- 0.020 mag. The 1D-5D gamma difference for DES-SN is 0.026 +/- 0.009 mag. We show that this difference is due to a strong correlation between host galaxy stellar mass and the x(1) component of the 5D distance-bias correction. Including an intrinsic correlation between the observed properties of SNe Ia, stretch and colour, and stellar mass in simulated SN Ia samples, we show that a 5D fit recovers gamma with -9 mmag bias compared to a +2 mmag bias for a 1D fit. This difference can explain part of the discrepancy seen in the data. Improvements in modelling correlations between galaxy properties and SN is necessary to ensure unbiased precision estimates of the dark energy equation of state as we enter the era of LSST.

59 citations

Journal ArticleDOI
TL;DR: The PTF photometric catalog 1.0 as discussed by the authors contains calibrated R_PTF-filter magnitudes for about 21 million sources brighter than magnitude 19, over an area of about 11233 deg^2.
Abstract: We construct a photometrically calibrated catalog of non-variable sources from the Palomar Transient Factory (PTF) observations. The first version of this catalog presented here, the PTF photometric catalog 1.0, contains calibrated R_PTF-filter magnitudes for about 21 million sources brighter than magnitude 19, over an area of about 11233 deg^2. The magnitudes are provided in the PTF photometric system, and the color of a source is required in order to convert these magnitudes into other magnitude systems. We estimate that the magnitudes in this catalog have typical accuracy of about 0.02 mag with respect to magnitudes from the Sloan Digital Sky Survey. The median repeatability of our catalog's magnitudes for stars between 15 and 16 mag, is about 0.01 mag, and it is better than 0.03 mag for 95% of the sources in this magnitude range. The main goal of this catalog is to provide reference magnitudes for photometric calibration of visible light observations. Subsequent versions of this catalog, which will be published incrementally online, will be extended to a larger sky area and will also include g_PTF-filter magnitudes, as well as variability and proper motion information.

59 citations

Journal ArticleDOI
TL;DR: The Fermi Gamma-ray Space Telescope has greatly expanded the number and energy window of observations of gamma-ray bursts (GRBs). However, the coarse localizations of tens to a hundred square degrees provided by the Fermia GRB Monitor instrument have posed a formidable obstacle to locating the bursts' host galaxies, measuring their redshifts, and tracking their panchromatic afterglows as mentioned in this paper.
Abstract: The Fermi Gamma-ray Space Telescope has greatly expanded the number and energy window of observations of gamma-ray bursts (GRBs). However, the coarse localizations of tens to a hundred square degrees provided by the Fermi GRB Monitor instrument have posed a formidable obstacle to locating the bursts' host galaxies, measuring their redshifts, and tracking their panchromatic afterglows. We have built a target-of-opportunity mode for the intermediate Palomar Transient Factory in order to perform targeted searches for Fermi afterglows. Here, we present the results of one year of this program: 8 afterglow discoveries out of 35 searches. Two of the bursts with detected afterglows (GRBs 130702A and 140606B) were at low redshift (z = 0.145 and 0.384, respectively) and had spectroscopically confirmed broad-line Type Ic supernovae. We present our broadband follow-up including spectroscopy as well as X-ray, UV, optical, millimeter, and radio observations. We study possible selection effects in the context of the total Fermi and Swift GRB samples. We identify one new outlier on the Amati relation. We find that two bursts are consistent with a mildly relativistic shock breaking out from the progenitor star rather than the ultra-relativistic internal shock mechanism that powers standard cosmological bursts. Finally, in the context of the Zwicky Transient Facility, we discuss how we will continue to expand this effort to find optical counterparts of binary neutron star mergers that may soon be detected by Advanced LIGO and Virgo.

59 citations


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Journal ArticleDOI
TL;DR: In this paper, the mass density, Omega_M, and cosmological-constant energy density of the universe were measured using the analysis of 42 Type Ia supernovae discovered by the Supernova Cosmology project.
Abstract: We report measurements of the mass density, Omega_M, and cosmological-constant energy density, Omega_Lambda, of the universe based on the analysis of 42 Type Ia supernovae discovered by the Supernova Cosmology Project. The magnitude-redshift data for these SNe, at redshifts between 0.18 and 0.83, are fit jointly with a set of SNe from the Calan/Tololo Supernova Survey, at redshifts below 0.1, to yield values for the cosmological parameters. All SN peak magnitudes are standardized using a SN Ia lightcurve width-luminosity relation. The measurement yields a joint probability distribution of the cosmological parameters that is approximated by the relation 0.8 Omega_M - 0.6 Omega_Lambda ~= -0.2 +/- 0.1 in the region of interest (Omega_M <~ 1.5). For a flat (Omega_M + Omega_Lambda = 1) cosmology we find Omega_M = 0.28{+0.09,-0.08} (1 sigma statistical) {+0.05,-0.04} (identified systematics). The data are strongly inconsistent with a Lambda = 0 flat cosmology, the simplest inflationary universe model. An open, Lambda = 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(Lambda > 0) = 99%, including the identified systematic uncertainties. The best-fit age of the universe relative to the Hubble time is t_0 = 14.9{+1.4,-1.1} (0.63/h) Gyr for a flat cosmology. The size of our sample allows us to perform a variety of statistical tests to check for possible systematic errors and biases. We find no significant differences in either the host reddening distribution or Malmquist bias between the low-redshift Calan/Tololo sample and our high-redshift sample. The conclusions are robust whether or not a width-luminosity relation is used to standardize the SN peak magnitudes.

16,838 citations

Journal ArticleDOI
TL;DR: In this article, the authors used spectral and photometric observations of 10 Type Ia supernovae (SNe Ia) in the redshift range 0.16 " z " 0.62.
Abstract: We present spectral and photometric observations of 10 Type Ia supernovae (SNe Ia) in the redshift range 0.16 " z " 0.62. The luminosity distances of these objects are determined by methods that employ relations between SN Ia luminosity and light curve shape. Combined with previous data from our High-z Supernova Search Team and recent results by Riess et al., this expanded set of 16 high-redshift supernovae and a set of 34 nearby supernovae are used to place constraints on the following cosmo- logical parameters: the Hubble constant the mass density the cosmological constant (i.e., the (H 0 ), () M ), vacuum energy density, the deceleration parameter and the dynamical age of the universe ) " ), (q 0 ), ) M \ 1) methods. We estimate the dynamical age of the universe to be 14.2 ^ 1.7 Gyr including systematic uncer- tainties in the current Cepheid distance scale. We estimate the likely e†ect of several sources of system- atic error, including progenitor and metallicity evolution, extinction, sample selection bias, local perturbations in the expansion rate, gravitational lensing, and sample contamination. Presently, none of these e†ects appear to reconcile the data with and ) " \ 0 q 0 " 0.

16,674 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
TL;DR: In this article, a combination of seven-year data from WMAP and improved astrophysical data rigorously tests the standard cosmological model and places new constraints on its basic parameters and extensions.
Abstract: The combination of seven-year data from WMAP and improved astrophysical data rigorously tests the standard cosmological model and places new constraints on its basic parameters and extensions. By combining the WMAP data with the latest distance measurements from the baryon acoustic oscillations (BAO) in the distribution of galaxies and the Hubble constant (H0) measurement, we determine the parameters of the simplest six-parameter ΛCDM model. The power-law index of the primordial power spectrum is ns = 0.968 ± 0.012 (68% CL) for this data combination, a measurement that excludes the Harrison–Zel’dovich–Peebles spectrum by 99.5% CL. The other parameters, including those beyond the minimal set, are also consistent with, and improved from, the five-year results. We find no convincing deviations from the minimal model. The seven-year temperature power spectrum gives a better determination of the third acoustic peak, which results in a better determination of the redshift of the matter-radiation equality epoch. Notable examples of improved parameters are the total mass of neutrinos, � mν < 0.58 eV (95% CL), and the effective number of neutrino species, Neff = 4.34 +0.86 −0.88 (68% CL), which benefit from better determinations of the third peak and H0. The limit on a constant dark energy equation of state parameter from WMAP+BAO+H0, without high-redshift Type Ia supernovae, is w =− 1.10 ± 0.14 (68% CL). We detect the effect of primordial helium on the temperature power spectrum and provide a new test of big bang nucleosynthesis by measuring Yp = 0.326 ± 0.075 (68% CL). We detect, and show on the map for the first time, the tangential and radial polarization patterns around hot and cold spots of temperature fluctuations, an important test of physical processes at z = 1090 and the dominance of adiabatic scalar fluctuations. The seven-year polarization data have significantly improved: we now detect the temperature–E-mode polarization cross power spectrum at 21σ , compared with 13σ from the five-year data. With the seven-year temperature–B-mode cross power spectrum, the limit on a rotation of the polarization plane due to potential parity-violating effects has improved by 38% to Δα =− 1. 1 ± 1. 4(statistical) ± 1. 5(systematic) (68% CL). We report significant detections of the Sunyaev–Zel’dovich (SZ) effect at the locations of known clusters of galaxies. The measured SZ signal agrees well with the expected signal from the X-ray data on a cluster-by-cluster basis. However, it is a factor of 0.5–0.7 times the predictions from “universal profile” of Arnaud et al., analytical models, and hydrodynamical simulations. We find, for the first time in the SZ effect, a significant difference between the cooling-flow and non-cooling-flow clusters (or relaxed and non-relaxed clusters), which can explain some of the discrepancy. This lower amplitude is consistent with the lower-than-theoretically expected SZ power spectrum recently measured by the South Pole Telescope Collaboration.

11,309 citations

01 Jan 1998
TL;DR: The spectral and photometric observations of 10 type Ia supernovae (SNe Ia) in the redshift range 0.16 � z � 0.62 were presented in this paper.
Abstract: We present spectral and photometric observations of 10 type Ia supernovae (SNe Ia) in the redshift range 0.16 � z � 0.62. The luminosity distances of these objects are determined by methods that employ relations between SN Ia luminosity and light curve shape. Combined with previous data from our High-Z Supernova Search Team (Garnavich et al. 1998; Schmidt et al. 1998) and Riess et al. (1998a), this expanded set of 16 high-redshift supernovae and a set of 34 nearby supernovae are used to place constraints on the following cosmological parameters: the Hubble constant (H0), the mass density (M), the cosmological constant (i.e., the vacuum energy density, �), the deceleration parameter (q0), and the dynamical age of the Universe (t0). The distances of the high-redshift SNe Ia are, on average, 10% to 15% farther than expected in a low mass density (M = 0.2) Universe without a cosmological constant. Different light curve fitting methods, SN Ia subsamples, and prior constraints unanimously favor eternally expanding models with positive cosmological constant (i.e., � > 0) and a current acceleration of the expansion (i.e., q0 < 0). With no prior constraint on mass density other than M � 0, the spectroscopically confirmed SNe Ia are statistically consistent with q0 < 0 at the 2.8�

11,197 citations