The SuperNova Legacy Survey: cosmological results from the first year data set

International audienceThe first cosmological results from the SuperNova Legacy Survey are presented. The recipe to obtain the deep, homogenous and complete set of 71 identified type Ia supernovae is described. The construction of the Hubble diagram is supported by precise distance measurement. The steps to obtain this distance are good differential photometry, precise calibration and light-curve modelling. All steps are detailled to present the Hubble diagram. finally the cosmological parameters are fitted from this diagram. A full error estimation (statistical and systematical) is presented

On the determination of the deceleration parameter from Supernovae data

Supernovae searches have shown that a simple matter-dominated and decelerating universe should be ruled out. However a determination of the present deceleration parameter $q_0$ through a simple kinematical description is not exempt of possible drawbacks. We show that, with a time dependent equation of state for the dark energy, a bias is present for $q_0$ : models which are very far from the so-called Concordance Model can be accommodated by the data and a simple kinematical analysis can lead to wrong conclusions. We present a quantitative treatment of this bias and we present our conclusions when a possible dynamical dark energy is taken into account.Comment: 4 pages, 3 figures, submitte

CNN photometric redshifts in the SDSS at r≤20r\leq 20

We release photometric redshifts, reaching $\sim$0.7, for $\sim$14M galaxies at $r\leq 20$ in the 11,500 deg$^2$ of the SDSS north and south galactic caps. These estimates were inferred from a convolution neural network (CNN) trained on $ugriz$ stamp images of galaxies labelled with a spectroscopic redshift from the SDSS, GAMA and BOSS surveys. Representative training sets of $\sim$370k galaxies were constructed from the much larger combined spectroscopic data to limit biases, particularly those arising from the over-representation of Luminous Red Galaxies. The CNN outputs a redshift classification that offers all the benefits of a well-behaved PDF, with a width efficiently signaling unreliable estimates due to poor photometry or stellar sources. The dispersion, mean bias and rate of catastrophic failures of the median point estimate are of order $\sigma_{\rm MAD}=0.014$, $=0.0015$, $\eta(|\Delta z_{\rm norm}|>0.05)=4\%$ on a representative test sample at $r<19.8$, out-performing currently published estimates. The distributions in narrow intervals of magnitudes of the redshifts inferred for the photometric sample are in good agreement with the results of tomographic analyses. The inferred redshifts also match the photometric redshifts of the redMaPPer galaxy clusters for the probable cluster members. The CNN input and output are available at: https://deepdip.iap.fr/treyer+2023.Comment: Submitted to MNRA

Making things better: the Case of Corporate Social Responsibility versus Social Entrepreneurship

This paper is concerned with varying market cracks and gaps, which have the potential to impact both environmental and social fields detrimentally. Instead of focusing on how international bodies and regulation could tackle such problems, this paper focuses on how business could decrease or repair the damages it causes. Thus, the potential of two recent fields: Corporate Social Responsibility (CSR) and Social Entrepreneurship are investigated, addressing the extent to which they can tackle market cracks and gaps. To have a better understanding of what solutions they provide, as well as what problems they encounter, case study research is employed. The research demonstrates the clear positive impact created by such ventures, without underestimating the main debates surrounding those approaches. Yet as positive outcomes remain prevalent, the paper calls for a convergence between the two fields of CSR and Social Entrepreneurship, through the development of partnerships and other innovative initiatives

MIMAC: MIcro-tpc MAtrix of Chambers for dark matter directional detection

Directional detection of non-baryonic Dark Matter is a promising search strategy for discriminating WIMP events from neutrons, the ultimate background for dark matter direct detection. This strategy requires both a precise measurement of the energy down to a few keV and 3D reconstruction of tracks down to a few mm. The MIMAC (MIcro-tpc MAtrix of Chambers) collaboration has developed in the last years an original prototype detector based on the direct coupling of large pixelized micromegas with a special developed fast self-triggered electronics showing the feasibility of a new generation of directional detectors. The first bi-chamber prototype has been installed at Modane, underground laboratory in June 2012. The first undergournd background events, the gain stability and calibration are shown. The first spectrum of nuclear recoils showing 3D tracks coming from the radon progeny is presented.Comment: Proceedings of the 4th International Conference on Directional Dark Matter Detection CYGNUS2013, held in Toyoma (Japan), June 201

SiFTO: An Empirical Method for Fitting SNe Ia Light Curves

We present SiFTO, a new empirical method for modeling type Ia supernovae (SNe Ia) light curves by manipulating a spectral template. We make use of high-redshift SN observations when training the model, allowing us to extend it bluer than rest frame U. This increases the utility of our high-redshift SN observations by allowing us to use more of the available data. We find that when the shape of the light curve is described using a stretch prescription, applying the same stretch at all wavelengths is not an adequate description. SiFTO therefore uses a generalization of stretch which applies different stretch factors as a function of both the wavelength of the observed filter and the stretch in the rest-frame B band. We compare SiFTO to other published light-curve models by applying them to the same set of SN photometry, and demonstrate that SiFTO and SALT2 perform better than the alternatives when judged by the scatter around the best fit luminosity distance relationship. We further demonstrate that when SiFTO and SALT2 are trained on the same data set the cosmological results agree.Comment: Modified to better match published version in Ap

Two superluminous supernovae from the early universe discovered by the Supernova Legacy Survey

We present spectra and lightcurves of SNLS 06D4eu and SNLS 07D2bv, two hydrogen-free superluminous supernovae discovered by the Supernova Legacy Survey. At z = 1.588, SNLS 06D4eu is the highest redshift superluminous SN with a spectrum, at M_U = -22.7 is one of the most luminous SNe ever observed, and gives a rare glimpse into the restframe ultraviolet where these supernovae put out their peak energy. SNLS 07D2bv does not have a host galaxy redshift, but based on the supernova spectrum, we estimate it to be at z ~ 1.5. Both supernovae have similar observer-frame griz lightcurves, which map to restframe lightcurves in the U-band and UV, rising in ~ 20 restframe days or longer, and declining over a similar timescale. The lightcurves peak in the shortest wavelengths first, consistent with an expanding blackbody starting near 15,000 K and steadily declining in temperature. We compare the spectra to theoretical models, and identify lines of C II, C III, Fe III, and Mg II in the spectrum of SNLS 06D4eu and SCP 06F6, and find that they are consistent with an expanding explosion of only a few solar masses of carbon, oxygen, and other trace metals. Thus the progenitors appear to be related to those suspected for SNe Ic. A high kinetic energy, 10^52 ergs, is also favored. Normal mechanisms of powering core- collapse or thermonuclear supernovae do not seem to work for these supernovae. We consider models powered by 56Ni decay and interaction with circumstellar material, but find that the creation and spin-down of a magnetar with a period of 2ms, magnetic field of 2 x 10^14 Gauss, and a 3 solar mass progenitor provides the best fit to the data.Comment: ApJ, accepted, 43 pages, 15 figure

Probing Dark Energy with Supernovae : a concordant or a convergent model?

We present a revised interpretation of recent analysis of supernovae data. We evaluate the effect of the priors on the extraction of the dark energy equation of state. We find that the conclusions depend strongly on the $\Omega_M$ prior value and on its uncertainty, and show that a biased fitting procedure applied on non concordant simulated data can converge to the "concordance model". Relaxing the prior on $\Omega_M$ points to other sets of solutions, which are not excluded by observational data.Comment: 1+4 pages, 6 figures, submitted to Phys. Re