Signatures of a jet cocoon in early spectra of a supernova associated with a γ-ray burst

Izzo, L.; Postigo, A. de Ugarte; Maeda, Keiichi; Thöne, C. C.; Канн, Д. А.; Valle, M. Della; Carracedo, Ana Sagués; Michalowski, Michal; Schady, P.; Schmidl, S.; Selsing, J.; Starling, R. L. C.; Suzuki, Akihiro; Bensch, K.; Bolmer, J.; Campana, S.; Cano, Z.; Covino, S.; Fynbo, J. P. U.; Hartmann, D. H.; Heintz, K. E.; Hjorth, J.; Japelj, J.; Kamiński, K.; Kaper, L.; Kouveliotou, C.; Krużyński, M.; Kwiatkowski, T.; Leloudas, G.; Levan, A. J.; Malesani, D.; Michałowski, Tadeusz; Piranomonte, S.; Pugliese, G.; Rossi, A.; Sánchez-Ramírez, R.; Schulze, S.; Steeghs, D.; Tanvir, N. R.; Ulaczyk, K.; Vergani, S. D.; Wiersema, K.

doi:10.1038/s41586-018-0826-3

Cited by 123 publications

(176 citation statements)

References 60 publications

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“…In this work and in Ashall et al (2018) it was found that there was no need to enhance the outer density structure in the outer layers for SN 2016jca, and an increase in abundance of Fe-group elements was sufficient. This was not tested by Izzo et al (2019), and it could in fact be an alternative solution. In the case presented here blobs of 56 Ni could have been dredged up from the centre of the explosion by the jet.…”

Section: Determining the Ni Distribution In The Outer Layersmentioning

confidence: 99%

Extracting high-level information from gamma-ray burst supernova spectra

Ashall

Mazzali

2020

Monthly Notices of the Royal Astronomical Society

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Radiation transport codes are often used in astrophysics to construct spectral models. In this work we demonstrate how producing these models for a time series of data can provide unique information about supernovae (SNe). Unlike previous work, we specifically concentrate on the method for obtaining the best synthetic spectral fits, and the errors associated with the preferred model parameters. We demonstrate how varying the ejecta mass, bolometric luminosity (L bol ) and photospheric velocity (v ph ), affects the outcome of the synthetic spectra. As an example we analyze the photospheric phase spectra of the GRB-SN 2016jca. It is found that for most epochs (where the afterglow subtraction is small) the error on L bol and v ph was ∼5%. The uncertainty on ejecta mass and E kin was found to be ∼20%, although this can be expected to dramatically decrease if models of nebular phase data can be simultaneously produced. We also demonstrate how varying the elemental abundance in the ejecta can produce better synthetic spectral fits. In the case of SN 2016jca it is found that a decreasing 56 Ni abundance as a function of decreasing velocity produces the best fit models. This could be the case if the 56 Ni was sythesised at the side of the GRB jet, or dredged up from the centre of the explosion. The work presented here can be used as a guideline for future studies on supernovae which use the same or similar radiation transfer code.

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Section: Determining the Ni Distribution In The Outer Layersmentioning

confidence: 99%

Extracting high-level information from gamma-ray burst supernova spectra

Ashall

Mazzali

2020

Monthly Notices of the Royal Astronomical Society

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“…Alternatively, ref. [117] recently suggested that SN 2006aj/GRB 060218 harbored a long-lived [42,43,44], SN 2006aj/GRB060219 [80,90,91], SN 2007fz [25], SN 2008D [80,92,93], SN 2011dh [94], SN 2011fu [95], SN 2013df [91,96], SN 2016gkg [97,98], and SN 2017iuk/GRB171205A [99]. Right: Kepler aperture photometry of two SNe IIP taken with unprecedented cadence and photometric accuracy [100].…”

Section: Shock Breakout and Cooling Envelope Emissionmentioning

confidence: 99%

New regimes in the observation of core-collapse supernovae

2019

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Core-collapse Supernovae (CCSNe) mark the deaths of stars more massive than about eight times the mass of the sun (M ) and are intrinsically the most common kind of catastrophic cosmic explosions. They can teach us about many important physical processes, such as nucleosynthesis and stellar evolution, and thus, they have been studied extensively for decades. However, many crucial questions remain unanswered, including the most basic ones regarding which kinds of massive stars achieve which kind of explosions and how. Observationally, this question is related to the open puzzles of whether CCSNe can be divided into distinct types or whether they are drawn from a population with a continuous set of properties, and of what progenitor characteristics drive the diversity of observed explosions. Recent developments in wide-field surveys and rapid-response followup facilities are helping us answer these questions by providing two new tools: (1) large statistical samples which enable population studies of the most common SNe, and reveal rare (but extremely informative) events that question our standard understanding of the explosion physics involved, and (2) observations of early SNe emission taken shortly after explosion which carries signatures of the progenitor structure and mass loss history. Future facilities will increase our capabilities and allow us to answer many open questions related to these extremely energetic phenomena of the Universe.We focus this short review on a few open questions which are being tackled by new facilities for quick discovery and rapidresponse followup, as well as for studying CCSNe in large numbers. For a more exhaustive review of the field see recent compilations such as the Handbook of Supernovae [1]. The CCSN Classification LandscapeSN classification has been a challenge since the 1940's [2], but especially recently, as innovative surveys have brought a large increase of new and debated types. Classification schemes are important as physically motivated ones can give crucial insight into the explosion physics and stellar evolution pathways that lead to the different kinds of important explosions.The classical classification scheme [e.g., 3, 4] relies mostly on spectra and has two main types: Type I SNe (SNe I) which do not show hydrogen lines, and Type II SNe (SNe II) which do.In Figure 1 (left panel), we present spectra around peak brightness of the main CCSN classes. Among them, SNe II are perhaps the most heterogeneous class with a large range of observed photometric and spectroscopic properties. Because of this diversity, they can be further divided into several subclasses. The first historical subclassification was based on the light curve shape: SNe showing a linear decline (in magnitudes) in their light curve were named SNe IIL, while SNe showing a quasiconstant luminosity or a plateau for several weeks were called SNe IIP [13]. Later it was discovered that Type IIP and IIL SNe can also be distinguished by a subtle difference in their spectra, with SNe IIP showing deeper absor...

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“…Since the SNPhotCC challenge, the number of published core collapse SNe has significantly increased, with the release of large samples of spectroscopic (Modjaz et al 2014;Hicken et al 2017;Stritzinger et al 2018a;Shivvers et al 2019) and photometric (Arcavi et al 2012;Taddia et al 2013;Bianco et al 2014;Hicken et al 2017;Gutiérrez et al 2017a,b;Stritzinger et al 2018a;Taddia et al 2018) data, alongside many single object studies of interesting or unusual events (e.g., Pignata et al 2011;Terreran et al 2017;Arcavi et al 2017a;Bersten et al 2018;Anderson et al 2018;Izzo et al 2019). UV coverage of core collapse SNe has also improved, with observations from the Swift satellite using the Ultra-Violet/Optical Telescope (UVOT) instrument (Roming et al 2005;Bufano et al 2009;Brown et al 2014Brown et al , 2015, and follow-up programs using the Hubble Space Telescope and GALEX (e.g., Gal-Yam et al 2008;Ben-Ami et al 2012.…”

Section: Introductionmentioning

confidence: 99%

Spectrophotometric templates for core-collapse supernovae and their application in simulations of time-domain surveys

Vincenzi

Sullivan

Firth

et al. 2019

Monthly Notices of the Royal Astronomical Society

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The design and analysis of time-domain sky surveys requires the ability to simulate accurately realistic populations of core collapse supernova (SN) events. We present a set of spectral time-series templates designed for this purpose, for both hydrogen-rich (type II, IIn, IIb) and stripped envelope (types Ib, Ic, Ic-BL) core collapse supernovae. We use photometric and spectroscopic data for 67 core collapse supernovae from the literature, and for each generate a time-series spectral template. The techniques used to build the templates are fully data-driven with no assumption of any parametric form or model for the light curves. The template-building code is open-source, and can be applied to any transient for which well-sampled multi-band photometry and multiple spectroscopic observations are available. We extend these spectral templates into the near-ultraviolet to λ 1600Å using observer-frame ultraviolet photometry. We also provide a set of templates corrected for host galaxy dust extinction, and provide a set of luminosity functions that can be used with our spectral templates in simulations. We give an example of how these templates can be used by integrating them within the popular SN simulation package snana, and simulating core collapse supernovae in photometrically-selected cosmological type Ia supernova samples, prone to contamination from core collapse events.Spectrophotometric templates for core collapse SNe 3 SN template (host extinction corrected)Mangling: Spectra are flux calibrated by mangling to match the broad-band photometry Near-UV extension:Near-UV photometry is combined with spectrophotometry into a {time, wavelength} grid and the surface Flux(time, wavelength) is interpolated using two dimensional gaussian processes. Increase sampling of the spectral time-series: where spectrophotometry is too sparse, additional spectra are extrapolated from the fitted surface Flux(time, wavelength) Re-mangling: Refined flux calibration of extended spectra using Near-UV, IR, optical photometry Apply host extinction back Correction to rest-frame Multi-band Photometry Spectroscopy Light curve fitting: Multi-band photometry is interpolated using gaussian processes Correct for Dust Extinction (MW and host galaxy dust corrected) Early and late time extrapolation SN template (original host extinction included)

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Signatures of a jet cocoon in early spectra of a supernova associated with a γ-ray burst

Abstract: Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 123 publications

References 60 publications

Extracting high-level information from gamma-ray burst supernova spectra

Extracting high-level information from gamma-ray burst supernova spectra

New regimes in the observation of core-collapse supernovae

Spectrophotometric templates for core-collapse supernovae and their application in simulations of time-domain surveys

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