Semi-supervised Learning for Photometric Supernova Classification

We present a semi-supervised method for photometric supernova typing. Our approach is to first use the nonlinear dimension reduction technique diffusion map to detect structure in a database of supernova light curves and subsequently employ random forest classification on a spectroscopically confirmed training set to learn a model that can predict the type of each newly observed supernova. We demonstrate that this is an effective method for supernova typing. As supernova numbers increase, our semi-supervised method efficiently utilizes this information to improve classification, a property not enjoyed by template based methods. Applied to supernova data simulated by Kessler et al. (2010b) to mimic those of the Dark Energy Survey, our methods achieve (cross-validated) 95% Type Ia purity and 87% Type Ia efficiency on the spectroscopic sample, but only 50% Type Ia purity and 50% efficiency on the photometric sample due to their spectroscopic follow-up strategy. To improve the performance on the photometric sample, we search for better spectroscopic follow-up procedures by studying the sensitivity of our machine learned supernova classification on the specific strategy used to obtain training sets. With a fixed amount of spectroscopic follow-up time, we find that deeper magnitude-limited spectroscopic surveys are better for producing training sets. For supernova Ia (II-P) typing, we obtain a 44% (1%) increase in purity to 72% (87%) and 30% (162%) increase in efficiency to 65% (84%) of the sample using a 25th (24.5th) magnitude-limited survey instead of the shallower spectroscopic sample used in the original simulations. When redshift information is available, we incorporate it into our analysis using a novel method of altering the diffusion map representation of the supernovae. Incorporating host redshifts leads to a 5% improvement in Type Ia purity and 13% improvement in Type Ia efficiency.Comment: 16 pages, 11 figures, accepted for publication in MNRA

Role of transport performance on neuron cell morphology

The compartmental model is a basic tool for studying signal propagation in neurons, and, if the model parameters are adequately defined, it can also be of help in the study of electrical or fluid transport. Here we show that the input resistance, in different networks which simulate the passive properties of neurons, is the result of an interplay between the relevant conductances, morphology and size. These results suggest that neurons must grow in such a way that facilitates the current flow. We propose that power consumption is an important factor by which neurons attain their final morphological appearance.Comment: 9 pages with 3 figures, submitted to Neuroscience Letter

Peculiar Type II Supernovae from Blue Supergiants

The vast majority of Type II supernovae (SNe) are produced by red supergiants (RSGs), but SN 1987A revealed that blue supergiants (BSGs) can produce members of this class as well, albeit with some peculiar properties. This best studied event revolutionized our understanding of SNe, and linking it to the bulk of Type II events is essential. We present here optical photometry and spectroscopy gathered for SN 2000cb, which is clearly not a standard Type II SN and yet is not a SN 1987A analog. The light curve of SN 2000cb is reminiscent of that of SN 1987A in shape, with a slow rise to a late optical peak, but on substantially different time scales. Spectroscopically, SN 2000cb resembles a normal SN II but with ejecta velocities that far exceed those measured for SN 1987A or normal SNe II, above 18000 km/s for H-alpha at early times. The red colours, high velocities, late photometric peak, and our modeling of this object all point toward a scenario involving the high-energy explosion of a small-radius star, most likely a BSG, producing 0.1 solar masses of Ni-56. Adding a similar object to the sample, SN 2005ci, we derive a rate of about 2% of the core-collapse rate for this loosely defined class of BSG explosions.Comment: Accepted to MNRAS on March 14, 201

The Red Supergiant Progenitor of Supernova 2012aw (PTF12bvh) in Messier 95

We report on the direct detection and characterization of the probable red supergiant (RSG) progenitor of the intermediate-luminosity Type II-Plateau (II-P) supernova (SN) 2012aw in the nearby (10.0 Mpc) spiral galaxy Messier 95 (M95; NGC 3351). We have identified the star in both Hubble Space Telescope images of the host galaxy, obtained 17-18 yr prior to the explosion, and near-infrared ground-based images, obtained 6-12 yr prior to the SN. The luminous supergiant showed evidence for substantial circumstellar dust, manifested as excess line-of-sight extinction. The effective total-to-selective ratio of extinction to the star was R'_V ≈ 4.35, which is significantly different from that of diffuse interstellar dust (i.e., R_V = 3.1), and the total extinction to the star was therefore, on average, A_V ≈ 3.1 mag. We find that the observed spectral energy distribution for the progenitor star is consistent with an effective temperature of 3600 K (spectral type M3), and that the star therefore had a bolometric magnitude of –8.29. Through comparison with recent theoretical massive-star evolutionary tracks we can infer that the RSG progenitor had an initial mass 15 ≲ M_(ini)(M_☉) < 20. Interpolating by eye between the available tracks, we surmise that the star had initial mass ~17-18 M_☉. The circumstellar dust around the progenitor must have been destroyed in the explosion, as the visual extinction to the SN is found to be low (AV = 0.24 mag with R_V = 3.1)

An Early and Comprehensive Millimetre and Centimetre Wave and X-ray Study of SN 2011dh: a Non-Equipartition Blast Wave Expanding into a Massive Stellar Wind

Only a handful of supernovae (SNe) have been studied in multiwavelengths from the radio to X-rays, starting a few days after the explosion. The early detection and classification of the nearby Type IIb SN 2011dh/PTF 11eon in M51 provides a unique opportunity to conduct such observations. We present detailed data obtained at one of the youngest phase ever of a core-collapse SN (days 3–12 after the explosion) in the radio, millimetre and X-rays; when combined with optical data, this allows us to explore the early evolution of the SN blast wave and its surroundings. Our analysis shows that the expanding SN shock wave does not exhibit equipartition (ϵe/ϵB ∼ 1000), and is expanding into circumstellar material that is consistent with a density profile falling like R−2. Within modelling uncertainties we find an average velocity of the fast parts of the ejecta of 15 000 ± 1800 km s−1, contrary to previous analysis. This velocity places SN 2011dh in an intermediate blast wave regime between the previously defined compact and extended SN Type IIb subtypes. Our results highlight the importance of early (∼1 d) high-frequency observations of future events. Moreover, we show the importance of combined radio/X-ray observations for determining the microphysics ratio ϵe/ϵB

Evidence for a Compact Wolf-Rayet Progenitor for the Type Ic Supernova PTF 10vgv

We present the discovery of PTF 10vgv, a Type Ic supernova (SN) detected by the Palomar Transient Factory, using the Palomar 48 inch telescope (P48). R-band observations of the PTF 10vgv field with P48 probe the SN emission from its very early phases (about two weeks before R-band maximum) and set limits on its flux in the week prior to the discovery. Our sensitive upper limits and early detections constrain the post-shock-breakout luminosity of this event. Via comparison to numerical (analytical) models, we derive an upper-limit of R ≾ 4.5 R_☉ (R ≾ 1 R_☉) on the radius of the progenitor star, a direct indication in favor of a compact Wolf-Rayet star. Applying a similar analysis to the historical observations of SN 1994I yields R ≾ 1/4 R_☉ for the progenitor radius of this SN