Optimizing Type Ia supernova follow-up in future dark energy surveys
Creators
- 1. Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)
Description
In the next-generation supernova surveys (Palomar Transient Factory, Dark Energy Survey, LSST, JDEM, etc.) maximizing the cosmological return on each supernova and limiting the systematic uncertainties will be crucial for determining the nature of dark energy. Here we present recent results from the Nearby Supernova Factory, a program that has followed almost 200 SN Ia in the Hubble flow with spectrophotometry. We have used the code SYNAPPS, a combination of the SYNOW spectrum synthesis fitter and the APPSPACK optimization code to automatically perform a highly parameterized fit to observational spectra, to begin the work of identifying the spectral features in a SN Ia that are most important for using these explosions as cosmological probes
Availability note (English)
Available from http://dx.doi.org/10.1088/1742-6596/125/1/012011Additional details
Identifiers
Publishing Information
- Journal Title
- Journal of Physics. Conference Series (Online)
- Journal Volume
- 125
- Journal Issue
- 1
- Journal Page Range
- [7 p.]
- ISSN
- 1742-6596
Conference
- Title
- Annual conference on scientific discovery through advanced computing program (SciDAC)
- Acronym
- SciDAC 2008
- Dates
- 13-17 Jul 2008
- Place
- Seattle, WA (United States)
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 40048862
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- A CODES; COMPUTER CALCULATIONS; COSMOLOGY; DISTRIBUTED DATA PROCESSING; ENERGY SPECTRA; NONLUMINOUS MATTER; OPTIMIZATION; S CODES; SPECTROPHOTOMETRY; SUPERNOVAE; TRANSIENTS
- Descriptors DEC
- BINARY STARS; COMPUTER CODES; DATA PROCESSING; ERUPTIVE VARIABLE STARS; MATTER; PROCESSING; SPECTRA; STARS; VARIABLE STARS