scholarly journals Three-dimensional delayed-detonation models with nucleosynthesis for Type Ia supernovae

2012 ◽  
Vol 429 (2) ◽  
pp. 1156-1172 ◽  
Author(s):  
Ivo R. Seitenzahl ◽  
Franco Ciaraldi-Schoolmann ◽  
Friedrich K. Röpke ◽  
Michael Fink ◽  
Wolfgang Hillebrandt ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Type Ia ◽  
Ia Supernovae

scholarly journals TURBULENCE IN A THREE-DIMENSIONAL DEFLAGRATION MODEL FOR TYPE Ia SUPERNOVAE. I. SCALING PROPERTIES

2009 ◽  
Vol 696 (2) ◽  
pp. 1491-1497 ◽  
Author(s):  
F. Ciaraldi-Schoolmann ◽  
W. Schmidt ◽  
J. C. Niemeyer ◽  
F. K. Röpke ◽  
W. Hillebrandt
Keyword(s):  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Scaling Properties ◽  
Type Ia ◽  
Ia Supernovae

scholarly journals Three-dimensional pure deflagration models with nucleosynthesis and synthetic observables for Type Ia supernovae

2013 ◽  
Vol 438 (2) ◽  
pp. 1762-1783 ◽  
Author(s):  
Michael Fink ◽  
Markus Kromer ◽  
Ivo R. Seitenzahl ◽  
Franco Ciaraldi-Schoolmann ◽  
Friedrich K. Röpke ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Type Ia ◽  
Ia Supernovae

scholarly journals Three-dimensional modeling of type Ia supernovae – The power of late time spectra

2005 ◽  
Vol 437 (3) ◽  
pp. 983-995 ◽  
Author(s):  
C. Kozma ◽  
C. Fransson ◽  
W. Hillebrandt ◽  
C. Travaglio ◽  
J. Sollerman ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Late Time ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling ◽  
Type Ia ◽  
Ia Supernovae

scholarly journals Erratum: three-dimensional delayed-detonation models with nucleosynthesis for Type Ia supernovae

2014 ◽  
Vol 444 (1) ◽  
pp. 350-351 ◽  
Author(s):  
Ivo R. Seitenzahl ◽  
Franco Ciaraldi-Schoolmann ◽  
Friedrich K. Röpke ◽  
Michael Fink ◽  
Wolfgang Hillebrandt ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Type Ia ◽  
Ia Supernovae

scholarly journals A Numerical Study of the Chemo-Dynamical Evolution of Elliptical Galaxies

2003 ◽  
Vol 208 ◽  
pp. 413-414
Author(s):  
Daisuke Kawata ◽  
Brad K. Gibson
Keyword(s):  
Chemical Elements ◽  
Numerical Study ◽  
Three Dimensional ◽  
Dynamical Evolution ◽  
Elliptical Galaxies ◽  
Type Ia Supernovae ◽  
Type Ii ◽  
End Products ◽  
Type Ia ◽  
Ia Supernovae

We investigate the chemo-dynamical evolution of elliptical galaxies, to understand the origin of the mass-dependence of photometric properties such as the colour-magnitude relation (CMR). Our three-dimensional TREE N-body/SPH numerical simulation takes into account both Type II and Type Ia supernovae and follows the evolution of the abundances of several chemical elements. We derive the photometric properties of the simulation end-products and compare them with the observed CMR.

scholarly journals Three-dimensional simulations of type Ia supernovae

2002 ◽  
Vol 391 (3) ◽  
pp. 1167-1172 ◽  
Author(s):  
M. Reinecke ◽  
W. Hillebrandt ◽  
J. C. Niemeyer
Keyword(s):  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Type Ia ◽  
Ia Supernovae ◽  
Three Dimensional Simulations

Three‐dimensional Delayed‐Detonation Model of Type Ia Supernovae

2005 ◽  
Vol 623 (1) ◽  
pp. 337-346 ◽  
Author(s):  
Vadim N. Gamezo ◽  
Alexei M. Khokhlov ◽  
Elaine S. Oran
Keyword(s):  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Type Ia ◽  
Ia Supernovae ◽  
Detonation Model

Three‐dimensional Models for High‐Velocity Features in Type Ia Supernovae

2006 ◽  
Vol 645 (1) ◽  
pp. 470-479 ◽  
Author(s):  
Masaomi Tanaka ◽  
Paolo A. Mazzali ◽  
Keiichi Maeda ◽  
Ken’ichi Nomoto
Keyword(s):  
High Velocity ◽  
Three Dimensional ◽  
Type Ia Supernovae ◽  
Type Ia ◽  
Dimensional Models ◽  
Three Dimensional Models ◽  
Ia Supernovae

scholarly journals ParSNIP: Generative Models of Transient Light Curves with Physics-enabled Deep Learning

2021 ◽  
Vol 162 (6) ◽  
pp. 275
Author(s):  
Kyle Boone
Keyword(s):  
Three Dimensional ◽  
Generative Models ◽  
Light Curves ◽  
Type Ia Supernovae ◽  
Data Sets ◽  
Data Set ◽  
Out Of Sample ◽  
Type Ia ◽  
Ia Supernovae

Abstract We present a novel method to produce empirical generative models of all kinds of astronomical transients from data sets of unlabeled light curves. Our hybrid model, which we call ParSNIP, uses a neural network to model the unknown intrinsic diversity of different transients and an explicit physics-based model of how light from the transient propagates through the universe and is observed. The ParSNIP model predicts the time-varying spectra of transients despite only being trained on photometric observations. With a three-dimensional intrinsic model, we are able to fit out-of-sample multiband light curves of many different kinds of transients with model uncertainties of 0.04–0.06 mag. The representation learned by the ParSNIP model is invariant to redshift, so it can be used to perform photometric classification of transients even with heavily biased training sets. Our classification techniques significantly outperform state-of-the-art methods on both simulated (PLAsTiCC) and real (PS1) data sets with 2.3× and 2× less contamination, respectively, for classification of Type Ia supernovae. We demonstrate how our model can identify previously unobserved kinds of transients and produce a sample that is 90% pure. The ParSNIP model can also estimate distances to Type Ia supernovae in the PS1 data set with an rms of 0.150 ± 0.007 mag compared to 0.155 ± 0.008 mag for the SALT2 model on the same sample. We discuss how our model could be used to produce distance estimates for supernova cosmology without the need for explicit classification.

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