Abstract
Empirical models of supernova (SN) spectral energy distributions (SEDs) are widely used for SN survey simulations and photometric classifications. The existing library of SED models has excellent optical templates, but limited, poorly constrained coverage of ultraviolet (UV) and infrared (IR) wavelengths. However, both regimes are critical for the design and operation of future SN surveys, particularly at IR wavelengths that will be accessible with the James Webb Space Telescope and the Wide-Field Infrared Survey Telescope. We create a public repository of improved empirical SED templates using a sampling of Type Ia and core-collapse (CC) photometric light curves to extend the Type Ia parameterized SALT2 model and a set of SN Ib, SN Ic, and SN II SED templates into the UV and near-IR. We apply this new repository of extrapolated SN SED models to examine how future surveys can discriminate between CC and Type Ia SNe at UV and IR wavelengths, and present an open-source software package written in Python, SNSEDextend, that enables users to generate their own extrapolated SEDs.
Highlights
Photometric templates and models of supernova (SN) spectral energy distributions (SEDs) are critical tools for gleaning physical properties of supernovae (SNe) from observations, determining how those properties evolve over time, and performing SN classifications
Extending the SED templates into near-infrared (NIR) wavelengths is necessary for those classification tools to be applicable for the generation of telescopes—such as the James Webb Space Telescope (JWST), the Wide-Field Infrared Survey Telescope (WFIRST), and the Large Synoptic Survey Telescope (LSST)—which will provide a plethora of new SN observations that span wavelengths from the optical to the far-IR (Dahlén & Fransson 1999; Mesinger & Johnson 2006; Ivezic et al 2008; Spergel et al 2015)
The primary output of this work is the open-source SNSEDextend software package, which is written in Python (Pierel et al 2018)
Summary
Photometric templates and models of supernova (SN) spectral energy distributions (SEDs) are critical tools for gleaning physical properties of supernovae (SNe) from observations, determining how those properties evolve over time, and performing SN classifications. Many SN analysis tools, such as the widely used SuperNova ANAlysis (SNANA; Kessler et al 2009) and SNCosmo (Barbary 2014) software packages, utilize a common set of empirically derived SEDs that represent a variety of core-collapse (CC) and Type Ia SNe. Most existing template SEDs, are only constrained by data at optical wavelengths (Blondin & Tonry 2007). In this work we provide a more rigorous extension of ultraviolet (UV) and NIR coverage for current SEDs. First, we describe a new open-source software tool, SNSEDextend, that is capable of extrapolating SN SEDs to match photometric observations. We provide a new repository of SEDs extrapolated to cover the wavelength range ∼1700–25000 Å, and in Section 4 we apply these SEDs to explore photometric SN classifications in IR bands. That would require retraining of the model, which is beyond the scope of this work
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