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.

K-corrections and extinction corrections for Type Ia supernovae

Abstract: The measurement of the cosmological parameters from Type Ia supernovae hinges on our ability to compare nearby and distant supernovae accurately. Here we present an advance on a method for performing generalized K-corrections for Type Ia supernovae which allows us to compare these objects from the UV to near-IR over the redshift range 0 < z < 2. We discuss the errors currently associated with this method and how future data can improve upon it significantly. We also examine the effects of reddening on the K-corrections and the light curves of Type Ia supernovae. Finally, we provide a few examples of how these techniques affect our current understanding of a sample of both nearby and distant supernovae.

Time-dependent Monte Carlo Radiative Transfer Calculations for Three-dimensional Supernova Spectra, Light Curves, and Polarization

Abstract: We discuss Monte Carlo techniques for addressing the three-dimensional time-dependent radiative transfer problem in rapidly expanding supernova atmospheres. The transfer code SEDONA has been developed to calculate the light curves, spectra, and polarization of aspherical supernova models. From the onset of free expansion in the supernova ejecta, SEDONA solves the radiative transfer problem self-consistently, including a detailed treatment of gamma-ray transfer from radioactive decay and with a radiative equilibrium solution of the temperature structure. Line fluorescence processes can also be treated directly. No free parameters need be adjusted in the radiative transfer calculation, providing a direct link between multidimensional hydrodynamic explosion models and observations. We describe the computational techniques applied in SEDONA and verify the code by comparison to existing calculations. We find that convergence of the Monte Carlo method is rapid and stable even for complicated multidimensional configurations. We also investigate the accuracy of a few commonly applied approximations in supernova transfer, namely, the stationarity approximation and the two-level atom expansion opacity formalism.

Nearby Supernova Factory Observations of SN 2007if: First Total Mass Measurement of a Super-Chandrasekhar-Mass Progenitor

Abstract: We present photometric and spectroscopic observations of SN 2007if, an overluminous (M_V = -20.4), red (B-V = 0.16 at B-band maximum), slow-rising (t_rise = 24 days) type Ia supernova in a very faint (M_g = -14.10) host galaxy. A spectrum at 5 days past B-band maximum light is a direct match to the super-Chandrasekhar-mass candidate SN Ia 2003fg, showing Si II and C II at ~9000 km/s. A high signal-to-noise co-addition of the SN spectral time series reveals no Na I D absorption, suggesting negligible reddening in the host galaxy, and the late-time color evolution has the same slope as the Lira relation for normal SNe Ia. The ejecta appear to be well mixed, with no strong maximum in I-band and a diversity of iron-peak lines appearing in near-maximum-light spectra. SN2007 if also displays a plateau in the Si II velocity extending as late as +10 days, which we interpret as evidence for an overdense shell in the SN ejecta. We calculate the bolometric light curve of the SN and use it and the \ion{Si}{2} velocity evolution to constrain the mass of the shell and the underlying SN ejecta, and demonstrate that SN2007 if is strongly inconsistent with a Chandrasekhar-mass scenario. Within the context of a "tamped detonation" model appropriate for double-degenerate mergers, and assuming no host extinction, we estimate the total mass of the system to be 2.4 +/- 0.2 solar masses, with 1.6 +/- 0.1 solar masses of nickel-56 and with 0.3-0.5 solar masses in the form of an envelope of unburned carbon/oxygen. Our modeling demonstrates that the kinematics of shell entrainment provide a more efficient mechanism than incomplete nuclear burning for producing the low velocities typical of super-Chandrasekhar-mass SNeIa.

Nearby Supernova Factory Observations of SN 2005gj: Another Type Ia Supernova in a Massive Circumstellar Envelope.

Abstract: Revision 2.6, 2006/06/01 00:20:07 Nearby Supernova Factory Observations of SN 2005gj: Another Type Ia Supernova in a Massive Circumstellar Envelope. The Nearby Supernova Factory G. Aldering, P. Antilogus, S. Bailey, 1 C. Baltay, 8 A. Bauer, 8 N. Blanc, 2 S. Bongard, 1,5 Y. Copin, 2 E. Gangler, 2 S. Gilles, 3 R. Kessler, 7 D. Kocevski, 1,6 B. C. Lee, 1 S. Loken, 1 P. Nugent, 1 R. Pain, 3 E. P´ contal, 4 R. Pereira, 3 S. Perlmutter, 1,6 D. Rabinowitz, 8 e G. Rigaudier, R. Scalzo, G. Smadja, 2 R. C. Thomas, 1 L. Wang, 1 B. A. Weaver 1,5 ABSTRACT We report the independent discovery and follow-up observations of supernova 2005gj by the Nearby Supernova Factory. This is the second confirmed case of a “hybrid” Type Ia/IIn supernova, which like the prototype SN 2002ic, we inter- pret as the explosion of a white dwarf interacting with a circumstellar medium. Our early-phase photometry of SN 2005gj shows that the strength of the inter- action between the supernova ejecta and circumstellar material is much stronger than for SN 2002ic. Our first spectrum shows a hot continuum with broad and narrow Hα emission. Later spectra, spanning over 4 months from outburst, show clear Type Ia features combined with broad and narrow Hγ, Hβ, Hα and He I λλ5876,7065 in emission. At higher resolution, P Cygni profiles are appar- ent. Surprisingly, we also observe an inverted P Cygni profile for [O III ] λ5007. Physics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720 Institut de Physique Nucl´ aire de Lyon, UMR5822, CNRS-IN2P3; Universit´ Claude Bernard Lyon 1, e e F-69622 Villeurbanne France Laboratoire de Physique Nucl´ aire et des Hautes Energies IN2P3 - CNRS - Universit´ s Paris VI et Paris e e VII, 4 place Jussieu Tour 33 - Rez de chauss´ e 75252 Paris Cedex 05 e Centre de Recherche Astronomique de Lyon, 9, av. Charles Andr´ , 69561 Saint Genis Laval Cedex e University of California, Space Sciences Laboratory, Berkeley, CA 94720-7450 Department of Physics, University of California, Berkeley, CA 94720 Kavli Institute for Cosmological Physics, The University of Chicago, Chicago, IL 60637 Department of Physics, Yale University, New Haven, CT 06250-8121

Evidence for a Spectroscopic Sequence Among SNe Ia

Abstract: In this Letter we present evidence for a spectral sequence among Type Ia supernovae (SNe Ia). The sequence is based on the systematic variation of several features seen in the near-maximum light spectrum. This sequence is analogous to the recently noted photometric sequence among SNe Ia which shows a relationship between the peak brightness of a SN Ia and the shape of its light curve. In addition to the observational evidence we present a partial theoretical explanation for the sequence. This has been achieved by producing a series of non-LTE synthetic spectra in which only the effective temperature is varied. The synthetic sequence nicely reproduces most of the differences seen in the observed one and presumably corresponds to the amount of 56Ni produced in the explosion.

Measurements of Omega and Lambda from 42 High-Redshift Supernovae

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.

Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant

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.

Machine learning

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.).

Seven-year wilkinson microwave anisotropy probe (wmap *) observations: cosmological interpretation

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.

Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant To Appear in the Astronomical Journal

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�