Dark energy constraints from a space-based supernova survey

Abstract

Aims. We present a forecast of dark energy constraints that could be obtained from a large sample of distances to Type Ia supernovae detected and measured from space. Methods. We simulate the supernova events as they would be observed by a EUCLID-like telescope with its two imagers, assuming those would be equipped with 4 visible and 3 near infrared swappable filters. We account for known systematic uncertainties affecting the cosmological constraints, including those arising through the training of the supernova model used to fit the supernovae light curves.Results. Using conservative assumptions and Planck priors, we find that a 18 month survey would yield constraints on the dark energy equation of state comparable to the cosmic shear approach in EUCLID: a variable two-parameter equation of state can be constrained to ∼0.03 at z 0.3. These constraints are derived from distances to about 13 000 supernovae out to z = 1.5, observed in two cones of 10 and 50 deg 2 . These constraints do not require measuring a nearby supernova sample from the ground. Conclusions. Provided swappable filters can be accommodated on EUCLID, distances to supernovae can be measured from space and contribute to obtain the most precise constraints on dark energy properties.

Type Ia Supernovae Are Excellent Standard Candles in the Near-infrared

“…Analysis of the RAISIN data will be presented in future work. The evidence from this work further emphasizes the promise of NIR wavelength observations not only for the ongoing HST RAISIN project, but also for future space studies of cosmic acceleration and dark energy (Gehrels 2010;Beaulieu et al 2010;Astier et al 2011;Hounsell et al 2017;Riess et al 2018c). Upcoming missions that could exploit nearby NIR data as a low-z anchor include the Large Synoptic Survey Telescope (LSST; Ivezic et al 2008), the NASA Wide-Field Infrared Survey Telescope (WFIRST-AFTA; Gehrels 2010; Spergel et al 2015), the European Space Agency's EUCLID mission (Beaulieu et al 2010;Wallner et al 2017), as well as the NASA James Webb Space Telescope (JWST; Clampin 2011; Greenhouse 2016).…”

Fables of reconstruction: controlling bias in the dark energy equation of state

“…For the CMB, we use a Fisher matrix forecast based on the Planck data. For the SN data, we assume 4000 SN distributed in 14 redshift bins from z = 0.15 to z = 1.55 for a deep SN survey [36]. We also include 300 low-z SN from the Nearby Supernova Factory [37] to improve the constraint and assume a Gaussian noise with a variance σ = 0.13 for all the data points.…”

Degeneracies in parametrized modified gravity models

“…In addition, to better constrain the background expansion parameters, we include simulated SNe luminosity data for a Euclid-like survey [22]. We generate 4012 data points randomly distributed in 14 redshift bins from z = 0.15 to z = 1.55.…”

“…We consider the approximate parametric form of these functions for some of the widely used MG theories in the literature and quantify how different data sets can improve on degeneracy breaking of the parameters. We use CMB temperature and polarization data from the Planck satellite [21], SNe from an Euclid-like survey [22] and large scale structure data from a photometric WL survey such as Large Synoptic Survey Telescope (LSST) [23]. We also consider pixelations of (µ, γ) as a more model-independent treatment of these functions.…”