2,544 research outputs found
Rival bishops, rival cathedrals : the election of Cormac, archdeacon of Sodor, as bishop in 1331
Peer reviewedPublisher PD
Protein folding rates correlate with heterogeneity of folding mechanism
By observing trends in the folding kinetics of experimental 2-state proteins
at their transition midpoints, and by observing trends in the barrier heights
of numerous simulations of coarse grained, C-alpha model, Go proteins, we show
that folding rates correlate with the degree of heterogeneity in the formation
of native contacts. Statistically significant correlations are observed between
folding rates and measures of heterogeneity inherent in the native topology, as
well as between rates and the variance in the distribution of either
experimentally measured or simulated phi-values.Comment: 11 pages, 3 figures, 1 tabl
Exploring the Structure of Distant Galaxies with Adaptive Optics on the Keck-II Telescope
We report on the first observation of cosmologically distant field galaxies
with an high order Adaptive Optics (AO) system on an 8-10 meter class
telescope. Two galaxies were observed at 1.6 microns at an angular resolution
as high as 50 milliarcsec using the AO system on the Keck-II telescope. Radial
profiles of both objects are consistent with those of local spiral galaxies and
are decomposed into a classic exponential disk and a central bulge. A
star-forming cluster or companion galaxy as well as a compact core are detected
in one of the galaxies at a redshift of 0.37+/-0.05. We discuss possible
explanations for the core including a small bulge, a nuclear starburst, or an
active nucleus. The same galaxy shows a peak disk surface brightness that is
brighter than local disks of comparable size. These observations demonstrate
the power of AO to reveal details of the morphology of distant faint galaxies
and to explore galaxy evolution.Comment: 5 pages, Latex, 3 figures. Accepted for publication in P.A.S.
A Flexible Parametric Modelling Framework for Survival Analysis
We introduce a general, flexible, parametric survival modelling framework which encompasses key shapes of hazard function (constant, increasing, decreasing, up-then-down, down-then-up), various common survival distributions (log-logistic, Burr type XII, Weibull, Gompertz), and includes defective distributions (cure models). This generality is achieved using four distributional parameters: two scale-type parameters – which, respectively, relate to accelerated failure time (AFT) and proportional hazards (PH) modelling – and two shape parameters. Furthermore, we advocate “multi-parameter regression” whereby more than one distributional parameter depends on covariates – rather than the usual convention of having a single covariate-dependent (scale) parameter. This general formulation unifies the most popular survival models, allowing us to consider the practical value of possible modelling choices. In particular, we suggest introducing covariates through just one or other of the two scale parameters (covering AFT and PH models), and through a “power” shape parameter (covering more complex non-AFT/non-PH effects); the other shape parameter remains covariate-independent, and handles automatic selection of the baseline distribution. We explore inferential issues and compare with alternative models through various simulation studies, with particular focus on evidence concerning the need, or otherwise, to include both AFT and PH parameters. We illustrate the efficacy of our modelling framework using data from lung cancer, melanoma, and kidney function studies. Censoring is accommodated throughout
PHotometry Assisted Spectral Extraction (PHASE) and identification of SNLS supernovae
Aim: We present new extraction and identification techniques for supernova
(SN) spectra developed within the Supernova Legacy Survey (SNLS) collaboration.
Method: The new spectral extraction method takes full advantage of
photometric information from the Canada-France-Hawai telescope (CFHT) discovery
and reference images by tracing the exact position of the supernova and the
host signals on the spectrogram. When present, the host spatial profile is
measured on deep multi-band reference images and is used to model the host
contribution to the full (supernova + host) signal. The supernova is modelled
as a Gaussian function of width equal to the seeing. A chi-square minimisation
provides the flux of each component in each pixel of the 2D spectrogram. For a
host-supernova separation greater than <~ 1 pixel, the two components are
recovered separately and we do not use a spectral template in contrast to more
standard analyses. This new procedure permits a clean extraction of the
supernova separately from the host in about 70% of the 3rd year ESO/VLT spectra
of the SNLS. A new supernova identification method is also proposed. It uses
the SALT2 spectrophotometric template to combine the photometric and spectral
data. A galaxy template is allowed for spectra for which a separate extraction
of the supernova and the host was not possible.
Result: These new techniques have been tested against more standard
extraction and identification procedures. They permit a secure type and
redshift determination in about 80% of cases. The present paper illustrates
their performances on a few sample spectra.Comment: 27 pages, 18 Figures, 1 Table. Accepted for publication in A&
The Supernova Gamma-Ray Burst Connection
The chief distinction between ordinary supernovae and long-soft gamma-ray
bursts (GRBs) is the degree of differential rotation in the inner several solar
masses when a massive star dies, and GRBs are rare mainly because of the
difficulty achieving the necessary high rotation rate. Models that do provide
the necessary angular momentum are discussed, with emphasis on a new single
star model whose rapid rotation leads to complete mixing on the main sequence
and avoids red giant formation. This channel of progenitor evolution also gives
a broader range of masses than previous models, and allows the copious
production of bursts outside of binaries and at high redshifts. However, even
the production of a bare helium core rotating nearly at break up is not, by
itself, a sufficient condition to make a gamma-ray burst. Wolf-Rayet mass loss
must be low, and will be low in regions of low metallicity. This suggests that
bursts at high redshift (low metallicity) will, on the average, be more
energetic, have more time structure, and last longer than bursts nearby. Every
burst consists of three components: a polar jet (~0.1 radian), high energy,
subrelativistic mass ejection (~1 radian), and low velocity equatorial mass
that can fall back after the initial explosion. The relative proportions of
these three components can give a diverse assortment of supernovae and high
energy transients whose properties may vary with redshift.Comment: 10 pages, to appear in AIP Conf. Proc. "Gamma Ray Bursts in the Swift
Era", Eds. S. S. Holt, N. Gehrels, J. Nouse
Deep recurrent neural networks for supernovae classification
We apply deep recurrent neural networks, which are capable of learning complex sequential information, to classify supernovae (code available at https://github.com/adammoss/supernovae). The observational time and filter fluxes are used as inputs to the network, but since the inputs are agnostic, additional data such as host galaxy information can also be included. Using the Supernovae Photometric Classification Challenge (SPCC) data, we find that deep networks are capable of learning about light curves, however the performance of the network is highly sensitive to the amount of training data. For a training size of 50% of the representational SPCC data set (around 104 supernovae) we obtain a type-Ia versus non-type-Ia classification accuracy of 94.7%, an area under the Receiver Operating Characteristic curve AUC of 0.986 and an SPCC figure-of-merit F 1 = 0.64. When using only the data for the early-epoch challenge defined by the SPCC, we achieve a classification accuracy of 93.1%, AUC of 0.977, and F 1 = 0.58, results almost as good as with the whole light curve. By employing bidirectional neural networks, we can acquire impressive classification results between supernovae types I, II and III at an accuracy of 90.4% and AUC of 0.974. We also apply a pre-trained model to obtain classification probabilities as a function of time and show that it can give early indications of supernovae type. Our method is competitive with existing algorithms and has applications for future large-scale photometric surveys
Calibration of centre-of-mass energies at LEP 2 for a precise measurement of the W boson mass
The determination of the centre-of-mass energies for all LEP 2 running is
presented. Accurate knowledge of these energies is of primary importance to set
the absolute energy scale for the measurement of the W boson mass. The beam
energy between 80 and 104 GeV is derived from continuous measurements of the
magnetic bending field by 16 NMR probes situated in a number of the LEP
dipoles. The relationship between the fields measured by the probes and the
beam energy is defined in the NMR model, which is calibrated against precise
measurements of the average beam energy between 41 and 61 GeV made using the
resonant depolarisation technique. The validity of the NMR model is verified by
three independent methods: the flux-loop, which is sensitive to the bending
field of all the dipoles of LEP; the spectrometer, which determines the energy
through measurements of the deflection of the beam in a magnet of known
integrated field; and an analysis of the variation of the synchrotron tune with
the total RF voltage. To obtain the centre-of-mass energies, corrections are
then applied to account for sources of bending field external to the dipoles,
and variations in the local beam energy at each interaction point. The relative
error on the centre-of-mass energy determination for the majority of LEP 2
running is 1.2 x 10^{-4}, which is sufficiently precise so as not to introduce
a dominant uncertainty on the W mass measurement.Comment: 79 pages, 45 figures, submitted to EPJ
Direct Confirmation of the Asymmetry of the Cas A Supernova with Light Echoes
We report the first detection of asymmetry in a supernova (SN) photosphere
based on SN light echo (LE) spectra of Cas A from the different perspectives of
dust concentrations on its LE ellipsoid. New LEs are reported based on
difference images, and optical spectra of these LEs are analyzed and compared.
After properly accounting for the effects of finite dust-filament extent and
inclination, we find one field where the He I and H alpha features are
blueshifted by an additional ~4000 km/s relative to other spectra and to the
spectra of the Type IIb SN 1993J. That same direction does not show any shift
relative to other Cas A LE spectra in the Ca II near-infrared triplet feature.
We compare the perspectives of the Cas A LE dust concentrations with recent
three-dimensional modeling of the SN remnant (SNR) and note that the location
having the blueshifted He I and H alpha features is roughly in the direction of
an Fe-rich outflow and in the opposite direction of the motion of the compact
object at the center of the SNR. We conclude that Cas A was an intrinsically
asymmetric SN. Future LE spectroscopy of this object, and of other historical
SNe, will provide additional insight into the connection of explosion mechanism
to SN to SNR, as well as give crucial observational evidence regarding how
stars explode.Comment: 13 pages, 7 figures, accepted for publication in Ap
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