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.

Confined dense circumstellar material surrounding a regular type II supernova

Abstract: With the advent of new wide-field, high-cadence optical transient surveys, our understanding of the diversity of core-collapse supernovae has grown tremendously in the last decade. However, the pre-supernova evolution of massive stars, which sets the physical backdrop to these violent events, is theoretically not well understood and difficult to probe observationally. Here we report the discovery of the supernova iPTF 13dqy = SN 2013fs a mere ~3 h after explosion. Our rapid follow-up observations, which include multiwavelength photometry and extremely early (beginning at ~6 h post-explosion) spectra, map the distribution of material in the immediate environment (≲10^(15) cm) of the exploding star and establish that it was surrounded by circumstellar material (CSM) that was ejected during the final ~1 yr prior to explosion at a high rate, around 10^(−3) solar masses per year. The complete disappearance of flash-ionized emission lines within the first several days requires that the dense CSM be confined to within ≲10^(15) cm, consistent with radio non-detections at 70–100 days. The observations indicate that iPTF 13dqy was a regular type II supernova; thus, the finding that the probable red supergiant progenitor of this common explosion ejected material at a highly elevated rate just prior to its demise suggests that pre-supernova instabilities may be common among exploding massive stars.

TYPE Ia SUPERNOVAE STRONGLY INTERACTING WITH THEIR CIRCUMSTELLAR MEDIUM

Abstract: Owing to their utility for measurements of cosmic acceleration, Type Ia supernovae (SNe Ia) are perhaps the best-studied class of SNe, yet the progenitor systems of these explosions largely remain a mystery. A rare subclass of SNe Ia shows evidence of strong interaction with their circumstellar medium (CSM), and in particular, a hydrogen-rich CSM; we refer to them as SNe Ia-CSM. In the first systematic search for such systems, we have identified 16 SNe Ia-CSM, and here we present new spectra of 13 of them. Six SNe Ia-CSM have been well studied previously, three were previously known but are analyzed in depth for the first time here, and seven are new discoveries from the Palomar Transient Factory. The spectra of all SNe Ia-CSM are dominated by Hα emission (with widths of ~2000 km s^(–1)) and exhibit large Hα/Hβ intensity ratios (perhaps due to collisional excitation of hydrogen via the SN ejecta overtaking slower-moving CSM shells); moreover, they have an almost complete lack of He I emission. They also show possible evidence of dust formation through a decrease in the red wing of Hα 75-100 days past maximum brightness, and nearly all SNe Ia-CSM exhibit strong Na I D absorption from the host galaxy. The absolute magnitudes (uncorrected for host-galaxy extinction) of SNe Ia-CSM are found to be –21.3 mag ≤ M_R ≤ –19 mag, and they also seem to show ultraviolet emission at early times and strong infrared emission at late times (but no detected radio or X-ray emission). Finally, the host galaxies of SNe Ia-CSM are all late-type spirals similar to the Milky Way, or dwarf irregulars like the Large Magellanic Cloud, which implies that these objects come from a relatively young stellar population. This work represents the most detailed analysis of the SN Ia-CSM class to date.

SN 2011dh: Discovery of a Type IIb Supernova from a Compact Progenitor in the Nearby Galaxy M51

Abstract: On 2011 May 31 UT a supernova (SN) exploded in the nearby galaxy M51 (the Whirlpool Galaxy). We discovered this event using small telescopes equipped with CCD cameras and also detected it with the Palomar Transient Factory survey, rapidly confirming it to be a Type II SN. Here, we present multi-color ultraviolet through infrared photometry which is used to calculate the bolometric luminosity and a series of spectra. Our early-time observations indicate that SN 2011dh resulted from the explosion of a relatively compact progenitor star. Rapid shock-breakout cooling leads to relatively low temperatures in early-time spectra, compared to explosions of red supergiant stars, as well as a rapid early light curve decline. Optical spectra of SN 2011dh are dominated by H lines out to day 10 after explosion, after which He I lines develop. This SN is likely a member of the cIIb (compact IIb) class, with progenitor radius larger than that of SN 2008ax and smaller than the eIIb (extended IIb) SN 1993J progenitor. Our data imply that the object identified in pre-explosion Hubble Space Telescope images at the SN location is possibly a companion to the progenitor or a blended source, and not the progenitor star itself, as its radius (~10^(13) cm) would be highly inconsistent with constraints from our post-explosion spectra.

Precursors Prior to Type IIn Supernova Explosions are Common: Precursor Rates, Properties, and Correlations

Abstract: There is a growing number of Type IIn supernovae (SNe) which present an outburst prior to their presumably final explosion. These precursors may affect the SN display, and are likely related to poorly charted phenomena in the final stages of stellar evolution. By coadding Palomar Transient Factory (PTF) images taken prior to the explosion, here we present a search for precursors in a sample of 16 Type IIn SNe. We find five SNe IIn that likely have at least one possible precursor event (PTF 10bjb, SN 2010mc, PTF 10weh, SN 2011ht, and PTF 12cxj), three of which are reported here for the first time. For each SN we calculate the control time. We find that precursor events among SNe IIn are common: at the one-sided 99% confidence level, >50% of SNe IIn have at least one pre-explosion outburst that is brighter than 3 × 10^7 L_☉ taking place up to 1/3 yr prior to the SN explosion. The average rate of such precursor events during the year prior to the SN explosion is likely ≳ 1 yr^(–1), and fainter precursors are possibly even more common. Ignoring the two weakest precursors in our sample, the precursors rate we find is still on the order of one per year. We also find possible correlations between the integrated luminosity of the precursor and the SN total radiated energy, peak luminosity, and rise time. These correlations are expected if the precursors are mass-ejection events, and the early-time light curve of these SNe is powered by interaction of the SN shock and ejecta with optically thick circumstellar material.

Discovery of the nearby long, soft GRB 100316D with an associated supernova

Abstract: We report the Swift discovery of nearby long, soft gamma-ray burst GRB 100316D, and the subsequent unveiling of its low redshift host galaxy and associated supernova. We derive the redshift of the event to be z = 0.0591 +/- 0.0001 and provide accurate astrometry for the GRB-SN. We study the extremely unusual prompt emission with time-resolved gamma-ray to X-ray spectroscopy, and find that the spectrum is best modelled with a thermal component in addition to a synchrotron emission component with a low peak energy. The X-ray light curve has a remarkably shallow decay out to at least 800 s. The host is a bright, blue galaxy with a highly disturbed morphology and we use Gemini South, VLT and HST observations to measure some of the basic host galaxy properties. We compare and contrast the X-ray emission and host galaxy of GRB 100316D to a subsample of GRB-SNe. GRB 100316D is unlike the majority of GRB-SNe in its X-ray evolution, but resembles rather GRB 060218, and we find that these two events have remarkably similar high energy prompt emission properties. Comparison of the host galaxies of GRB-SNe demonstrates, however, that there is a great diversity in the environments in which GRB-SNe can be found. GRB 100316D is an important addition to the currently sparse sample of spectroscopically confirmed GRB-SNe, from which a better understanding of long GRB progenitors and the GRB--SN connection can be gleaned.

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�