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We present a measurement of the rate of distant Type Ia supernovae derived using 4 large subsets of data from the Supernova Cosmology Project. Within this fiducial sample, which surveyed about 12 square degrees, thirty-eight supernovae were detected at redshifts 0.25--0.85. In a spatially-flat cosmological model consistent with the results obtained by the Supernova Cosmology Project, we derive a rest-frame Type Ia supernova rate at a mean redshift $zsimeq0.55$ of $1.53 {^{+0.28}_{-0.25}} {^{+0.32}_{-0.31}} 10^{-4} h^3 {rm Mpc}^{-3} {rm yr}^{-1}$ or $0.58 {^{+0.10}_{-0.09}} {^{+0.10}_{-0.09}} h^2 {rm SNu}$ (1 SNu = 1 supernova per century per $10^{10}$Lbsun), where the first uncertainty is statistical and the second includes systematic effects. The dependence of the rate on the assumed cosmological parameters is studied and the redshift dependence of the rate per unit comoving volume is contrasted with local estimates in the context of possible cosmic star formation histories and progenitor models.
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It is thought that type Ia supernovae (SNe Ia) are explosions of carbon-oxygen white dwarfs (CO WDs). Two main evolutionary channels are proposed for the WD to reach the critical density required for a thermonuclear explosion: the single degenerate scenario (SD), in which a CO WD accretes from a non-degenerate companion, and the double degenerate scenario (DD), in which two CO WDs merge. However, it remains difficult to reproduce the observed SN Ia rate with these two scenarios. With a binary population synthesis code we study the main evolutionary channels that lead to SNe Ia and we calculate the SN Ia rates and the associated delay time distributions. We find that the DD channel is the dominant formation channel for the longest delay times. The SD channel with helium-rich donors is the dominant channel at the shortest delay times. Our standard model rate is a factor five lower than the observed rate in galaxy clusters. We investigate the influence of ill-constrained aspects of single- and binary-star evolution and uncertain initial binary distributions on the rate of type Ia SNe. These distributions, as well as uncertainties in both helium star evolution and common envelope evolution, have the greatest influence on our calculated rates. Inefficient common envelope evolution increases the relative number of SD explosions such that for $alpha_{rm ce} = 0.2$ they dominate the SN Ia rate. Our highest rate is a factor three less than the galaxy-cluster SN Ia rate, but compatible with the rate determined in a field-galaxy dominated sample. If we assume unlimited accretion onto WDs, to maximize the number of SD explosions, our rate is compatible with the observed galaxy-cluster rate.
We present the first measurement of the rate of Type Ia supernovae at high redshift. The result is derived using a large subset of data from the Supernova Cosmology Project as described in more detail at this meeting by Perlmutter et al. (1996). We present our methods for estimating the numbers of galaxies and the number of solar luminosities to which the survey is sensitive, the supernova detection efficiency and hence the control time. We derive a rest-frame Type Ia supernova rate at z~0.4 of 0.82^+0.54_-0.37 ^+0.42_-0.32 h^2 SNu where the first uncertainty is statistical and the second includes systematic effects.
We present a progress report on a project to derive the evolution of the volumetric supernova Type Ia rate from the Supernova Legacy Survey. Our preliminary estimate of the rate evolution divides the sample from Neill et al. (2006) into two redshift bins: 0.2 < z < 0.4, and 0.4 < z < 0.6. We extend this by adding a bin from the sample analyzed in Sullivan et al. (2006) in the range 0.6 < z < 0.75 from the same time period. We compare the derived trend with previously published rates and a supernova Type Ia production model having two components: one component associated closely with star formation and an additional component associated with host galaxy mass. Our observed trend is consistent with this model, which predicts a rising SN Ia rate out to at least z=2.
We present the EROS nearby supernova ($z sim 0.02 - 0.2$) search and the analysis of the first year of data (1997). A total of 80 square degrees were surveyed. Eight supernov{ae} were detected, four of which were spectroscopically identified as type Ia supernov{ae}. The search efficiency was determined with a Monte-Carlo simulation taking into account the efficiencies for both supernova detection and host galaxy identification. Assuming that for a given galaxy the supernova rate is proportional to the galactic luminosity, we compute a type Ia supernova explosion rate of: ${cal R} = 0.44 {}_{-0.21}^{+0.35} {}_{-0.07}^{+0.13} h^2: / 10^{10} lbsun / 100 {rm yrs}$ at an average redshift of $sim 0.1$ where the errors are respectively statistical and systematic (type misidentification included).
We present a measurement of the volumetric Type Ia supernova (SN Ia) rate (SNR_Ia) as a function of redshift for the first four years of data from the Canada-France-Hawaii Telescope (CFHT) Supernova Legacy Survey (SNLS). This analysis includes 286 spectroscopically confirmed and more than 400 additional photometrically identified SNe Ia within the redshift range 0.1<z<1.1. The volumetric SNR_Ia evolution is consistent with a rise to z~1.0 that follows a power-law of the form (1+z)^alpha, with alpha=2.11+/-0.28. This evolutionary trend in the SNLS rates is slightly shallower than that of the cosmic star-formation history over the same redshift range. We combine the SNLS rate measurements with those from other surveys that complement the SNLS redshift range, and fit various simple SN Ia delay-time distribution (DTD) models to the combined data. A simple power-law model for the DTD (i.e., proportional to t^-beta) yields values from beta=0.98+/-0.05 to beta=1.15+/-0.08 depending on the parameterization of the cosmic star formation history. A two-component model, where SNR_Ia is dependent on stellar mass (Mstellar) and star formation rate (SFR) as SNR_Ia(z)=AxMstellar(z) + BxSFR(z), yields the coefficients A=1.9+/-0.1 SNe/yr/M_solar and B=3.3+/-0.2 SNe/yr/(M_solar/yr). More general two-component models also fit the data well, but single Gaussian or exponential DTDs provide significantly poorer matches. Finally, we split the SNLS sample into two populations by the light curve width (stretch), and show that the general behavior in the rates of faster-declining SNe Ia (0.8<s<1.0) is similar, within our measurement errors, to that of the slower objects (1.0<s<1.3) out to z~0.8.
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