分类： 天文学 >> 天文学 提交时间： 2023-02-19
Ping Chen
Subo Dong
C. S. Kochanek
K. Z. Stanek
R. S. Post
M. D. Stritzinger
J. L. Prieto
Alexei V. Filippenko
Juna A. Kollmeier
N. Elias-Rosa
Boaz Katz
Lina Tomasella
S. Bose
Chris Ashall
S. Benetti
D. Bersier
Joseph Brimacombe
Thomas G. Brink
P. Brown
David A. H. Buckley
摘要： The CNIa0.02 project aims to collect a complete, nearby sample of Type Ia supernovae (SNe Ia) light curves, and the SNe are volume-limited with host-galaxy redshifts z_host < 0.02. The main scientific goal is to infer the distributions of key properties (e.g., the luminosity function) of local SNe Ia in a complete and unbiased fashion in order to study SN explosion physics. We spectroscopically classify any SN candidate detected by the All-Sky Automated Survey for Supernovae (ASAS-SN) that reaches peak brightness < 16.5 mag. Since ASAS-SN scans the full sky and does not target specific galaxies, our target selection is effectively unbiased by host-galaxy properties. We perform multi-band photometric observations starting from the time of discovery. In the first data release (DR1), we present the optical light curves obtained for 247 SNe from our project (including 148 SNe in the complete sample), and we derive parameters such as the peak fluxes, dm15 and s_BV.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Ping Chen
Subo Dong
C. S. Kochanek
K. Z. Stanek
R. S. Post
M. D. Stritzinger
J. L. Prieto
Alexei V. Filippenko
Juna A. Kollmeier
N. Elias-Rosa
Boaz Katz
Lina Tomasella
S. Bose
Chris Ashall
S. Benetti
D. Bersier
Joseph Brimacombe
Thomas G. Brink
P. Brown
David A. H. Buckley
摘要： The CNIa0.02 project aims to collect a complete, nearby sample of Type Ia supernovae (SNe Ia) light curves, and the SNe are volume-limited with host-galaxy redshifts z_host < 0.02. The main scientific goal is to infer the distributions of key properties (e.g., the luminosity function) of local SNe Ia in a complete and unbiased fashion in order to study SN explosion physics. We spectroscopically classify any SN candidate detected by the All-Sky Automated Survey for Supernovae (ASAS-SN) that reaches peak brightness < 16.5 mag. Since ASAS-SN scans the full sky and does not target specific galaxies, our target selection is effectively unbiased by host-galaxy properties. We perform multi-band photometric observations starting from the time of discovery. In the first data release (DR1), we present the optical light curves obtained for 247 SNe from our project (including 148 SNe in the complete sample), and we derive parameters such as the peak fluxes, dm15 and s_BV.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Stéphane Blondin
Sergei Blinnikov
Fionntan P. Callan
Christine E. Collins
Luc Dessart
Wesley Even
Andreas Flörs
Andrew G. Fullard
D. John Hillier
Anders Jerkstrand
Daniel Kasen
Boaz Katz
Wolfgang Kerzendorf
Alexandra Kozyreva
Jack O'Brien
Ezequiel A. Pássaro
Nathaniel Roth
Ken J. Shen
Luke Shingles
Stuart A. Sim
摘要： We present the first results of a comprehensive supernova (SN) radiative-transfer (RT) code-comparison initiative (StaNdaRT), where the emission from the same set of standardized test models is simulated by currently-used RT codes. A total of ten codes have been run on a set of four benchmark ejecta models of Type Ia supernovae. We consider two sub-Chandrasekhar-mass ($M_\mathrm{tot} = 1.0$ M$_\odot$) toy models with analytic density and composition profiles and two Chandrasekhar-mass delayed-detonation models that are outcomes of hydrodynamical simulations. We adopt spherical symmetry for all four models. The results of the different codes, including the light curves, spectra, and the evolution of several physical properties as a function of radius and time, are provided in electronic form in a standard format via a public repository. We also include the detailed test model profiles and several python scripts for accessing and presenting the input and output files. We also provide the code used to generate the toy models studied here. In this paper, we describe in detail the test models, radiative-transfer codes and output formats and provide access to the repository. We present example results of several key diagnostic features.
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