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Author

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, Graham et al. presented an optical spectrum at 1342 days after peak from Keck Observatory, in which the broad component of Hα emission persists with a similar profile as in early-time observations.
Abstract: Author(s): Graham, ML; Harris, CE; Fox, OD; Nugent, PE; Kasen, D; Silverman, JM; Filippenko, AV | Abstract: The optical transient PTF11kx exhibited both the characteristic spectral features of Type Ia supernovae (SNe Ia) and the signature of ejecta interacting with circumstellar material (CSM) containing hydrogen, indicating the presence of a nondegenerate companion. We present an optical spectrum at 1342 days after peak from Keck Observatory, in which the broad component of Hα emission persists with a similar profile as in early-time observations. We also present Spitzer IRAC detections obtained 1237 and 1818 days after peak, and an upper limit from Hubble Space Telescope ultraviolet imaging at 2133 days. We interpret our late-time observations in the context of published results - and reinterpret the early-time observations - in order to constrain the CSM's physical parameters and to compare to theoretical predictions for recurrent-nova systems. We find that the CSM's radial extent may be several times the distance between the star and the CSM's inner edge, and that the CSM column density may be two orders of magnitude lower than previous estimates. We show that the Hα luminosity decline is similar to other SNe with CSM interaction and demonstrate how our infrared photometry is evidence for newly formed, collisionally heated dust. We create a model for PTF11kx's late-time CSM interaction and find that X-ray reprocessing by photoionization and recombination cannot reproduce the observed Hα luminosity, suggesting that the X-rays are thermalized and that Hα radiates from collisional excitation. Finally, we discuss the implications of our results regarding the progenitor scenario and the geometric properties of the CSM for the PTF11kx system.

20 citations

Journal ArticleDOI
Jason Rhodes1, Jason Rhodes2, Alexandre Refregier2, Richard Massey3, Justin Albert2, David Bacon, Gary Bernstein4, Richard S. Ellis2, Bhuvnesh Jain4, Alex G. Kim5, M. L. Lampton6, Timothy A. McKay7, Carl W. Akerlof7, Greg Aldering5, Rahman Amanullah8, Pierre Astier9, C. Baltay10, E. Barrelet9, Chris Bebek5, Lars Bergström8, J. Bercovitz5, Manfred Bester6, B. Bigelow7, Ralph C. Bohlin11, Alain Bonissent9, C. R. Bower12, Michael E. Brown7, Myron Campbell7, William Carithers5, Eugene D. Commins6, C. T. Day5, Susana E. Deustua13, R. DiGennaro5, Anne Ealet9, W. Emmet10, M. Eriksson8, Dominique Fouchez, A. S. Fruchter11, J. F. Genat9, D. W. Gerdes7, L. Gladney4, Gerson Goldhaber6, Ariel Goobar8, Donald E. Groom5, S. Harris6, Peter Harvey6, H. Heetderks6, S.E. Holland5, Dragan Huterer14, William E. Johnston5, Armin Karcher5, William F. Kolbe5, B. Krieger5, G. Kushner5, N. Kuznetsova5, R. Lafever5, J. I. Lamoureux5, M. E. Levi5, Eric V. Linder5, S. C. Loken5, Wolfgang Lorenzon7, Roger F. Malina, Alain Mazure, Shawn McKee7, Ramon Miquel5, N. Morgan10, Edvard Mörtsell8, Nick Mostek12, S. L. Mufson12, J. A. Musser12, Peter Nugent5, Hakeem M. Oluseyi5, Reynald Pain9, N. Palaio5, David H. Pankow6, Saul Perlmutter5, R. Pratt6, Eric Prieto, David Rabinowitz10, K. Robinson5, Natalie A. Roe5, D. Rusin4, Michael Schubnell7, Michael Sholl6, G. Smadja15, Roger Smith2, George F. Smoot6, J. Snyder10, A. L. Spadafora5, Andrew Szymkowiak10, Gregory Tarle7, Keith Taylor2, Andre Tilquin, A. D. Tomasch7, H. von der Lippe5, D. Vincent9, J.-P. Walder5, Guofeng Wang5 
TL;DR: In this paper, the Supernova/Acceleration Probe (SNAP) is considered and the major contributions to this telescope's point spread function (PSF) are quantified.

20 citations

Journal ArticleDOI
TL;DR: In this article, a large grid of synthetic spectra was used to compare early spectroscopic observations of SN 1993W with the observed spectra of SN IIP and showed that very early spectra combined with detailed models can provide constraints on the value of the power law index, the ratio of hydrogen to helium in the surface of the progenitor and the amount of radioactive nickel mixed into the outer envelope of the supernova.
Abstract: We present the results of a large grid of synthetic spectra and compare them to early spectroscopic observations of SN 1993W. This supernova was discovered close to its explosion date and at a recession velocity of 5400 km/s is located in the Hubble flow. We focus here on two early spectra that were obtained approximately 5 and 9 days after explosion. We parameterize the outer supernova envelope as a power-law density profile in homologous expansion. In order to extract information on the value of the parameters a large number of models was required. We show that very early spectra combined with detailed models can provide constraints on the value of the power law index, the ratio of hydrogen to helium in the surface of the progenitor, the progenitor metallicity and the amount of radioactive nickel mixed into the outer envelope of the supernova. The spectral fits reproduce the observed spectra exceedingly well. The spectral results combined with the early photometry predict that the explosion date was 4.7 {+-} 0.7 days before the first spectrum was obtained. The ability to obtain the metallicity from early spectra make SN IIP attractive probes of chemical evolution in the universe and by showing that we have the ability to pin down the parameters of the progenitor and mixing during the supernova explosion, it is likely to make SN IIP useful cosmological distance indicators which are at the same time complementary to SNe Ia.

20 citations

Journal ArticleDOI
TL;DR: The early phase spectra of iPTF13asv showed absence of iron absorption, indicating that synthesized iron elements are confined to low-velocity regions of the ejecta, which implies a stratified ejecta structure along the line of sight.
Abstract: In this paper, we report observations of a peculiar Type Ia supernova iPTF13asv (a.k.a., SN2013cv) from the onset of the explosion to months after its peak. The early-phase spectra of iPTF13asv show absence of iron absorption, indicating that synthesized iron elements are confined to low-velocity regions of the ejecta, which, in turn, implies a stratified ejecta structure along the line of sight. Our analysis of iPTF13asv's light curves and spectra shows that it is an intermediate case between normal and super-Chandrasekhar events. On the one hand, its light curve shape (B-band $\Delta m_{15}=1.03\pm0.01$) and overall spectral features resemble those of normal Type Ia supernovae. On the other hand, similar to super-Chandrasekhar events, it shows large peak optical and UV luminosity ($M_B=-19.84\,\rm{mag}$, $M_{uvm2}=-15.5\,\rm{mag}$) a relatively low but almost constant \ion{Si}{2} velocities of about $10,000\,\rm{km}\,\rm{s}^{-1}$, and persistent carbon absorption in the spectra. We estimate a $^{56}$Ni mass of $0.81^{+0.10}_{-0.18}M_\odot$ and a total ejecta mass of $1.59^{+0.45}_{-0.12}M_\odot$. The large ejecta mass of iPTF13asv and its stratified ejecta structure together seemingly favor a double-degenerate origin.

20 citations

Journal Article
TL;DR: In this article, the authors quantify the major contributions of the Supernova/Acceleration Probe (SNAP) to the Point Spread Function (PSF) of the Wide Field Space Telescope (WFSST).
Abstract: A wide field space-based imaging telescope is necessary to fully exploit the technique of observing dark matter via weak gravitational lensing. This first paper in a three part series outlines the survey strategies and relevant instrumental parameters for such a mission. As a concrete example of hardware design, we consider the proposed Supernova/Acceleration Probe (SNAP). Using SNAP engineering models, we quantify the major contributions to this telescope's Point Spread Function (PSF). These PSF contributions are relevant to any similar wide field space telescope. We further show that the PSF of SNAP or a similar telescope will be smaller than current ground-based PSFs, and more isotropic and stable over time than the PSF of the Hubble Space Telescope. We outline survey strategies for two different regimes - a ''wide'' 300 square degree survey and a ''deep'' 15 square degree survey that will accomplish various weak lensing goals including statistical studies and dark matter mapping.

19 citations


Cited by
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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