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V. Ruhlmann-Kleider

Publications and source records attributed to V. Ruhlmann-Kleider.

At least 19 recordsLinked to original sources

Constraints on Neutrino Physics from DESI DR2 BAO and DR1 Full Shape

The Dark Energy Spectroscopic Instrument (DESI) Collaboration has obtained robust measurements of baryon acoustic oscillations (BAO) in the redshift range, $0.1 < z < 4.2$, based on the Lyman-$α$ forest and galaxies from Data Release 2 (DR2). We combine these measurements with external cosmic microwave background (CMB) data from Planck and ACT to place our tightest constraints yet on the sum of neutrino masses. Assuming the cosmological $Λ$CDM model and three degenerate neutrino states, we find $\sum m_ν<0.0642$ eV (95%) with a marginalized error of $σ(\sum m_ν)=0.020$ eV. We also constrain the effective number of neutrino species, finding $N_\rm{eff} = 3.23^{+0.35}_{-0.34}$ (95%), in line with the Standard Model prediction. When accounting for neutrino oscillation constraints, we find a preference for the normal mass ordering and an upper limit on the lightest neutrino mass of $m_l < 0.023$ eV (95%). However, we determine using frequentist and Bayesian methods that our constraints are in tension with the lower limits derived from neutrino oscillations. Correcting for the physical boundary at zero mass, we report a 95% Feldman-Cousins upper limit of $\sum m_ν<0.053$ eV, breaching the lower limit from neutrino oscillations. Considering a more general Bayesian analysis with an effective cosmological neutrino mass parameter, $\sum m_{ν,\rm{eff}}$, that allows for negative energy densities and removes unsatisfactory prior weight effects, we derive constraints that are in $3σ$ tension with the same oscillation limit. In the absence of unknown systematics, this finding could be interpreted as a hint of new physics not necessarily related to neutrinos. The preference of DESI and CMB data for an evolving dark energy model offers one possible solution. In the $w_0w_a$CDM model, we find $\sum m_ν<0.163$ eV (95%), relaxing the neutrino tension. [Abridged]

astro-ph.CO

Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys

In this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as UNIONS or the Vera C. Rubin LSST. This work is conducted in the context of DESI-II, the next phase of DESI, which will start around 2029. We use deep imaging data from HSC and CLAUDS on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the $u, g, r, i$ and $z$ bands to UNIONS depth. The Random Forest algorithm is trained with the $u,g,r,i$ and $z$ bands to classify LBGs in the $2.5 < z < 3.5$ range. We find that fixing a target density budget of $1,100$ deg$^{-2}$, the Random Forest approach gives a density of $z>2$ targets of $873$ deg$^{-2}$, and a density of $493$ deg$^{-2}$ of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg$^2$. We predict uncertainties on Alcock-Paczynski parameters $α_\perp$ and $α_{\parallel}$ to be 0.7$\%$ and 1$\%$ for $2.6<z<3.2$, resulting in a potential 2$\%$ measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict $σ_{f_{\rm NL}}\approx 7$, which would be comparable to the current best precision achieved by \textit{Planck}. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models ($σ_{f_{\rm NL}} \approx 1$) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.

astro-ph.CO

Mitigation of DESI fiber assignment incompleteness effect on two-point clustering with small angular scale truncated estimators

We present a method to mitigate the effects of fiber assignment incompleteness in two-point power spectrum and correlation function measurements from galaxy spectroscopic surveys, by truncating small angular scales from estimators. We derive the corresponding modified correlation function and power spectrum windows to account for the small angular scale truncation in the theory prediction. We validate this approach on simulations reproducing the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) with and without fiber assignment. We show that we recover unbiased cosmological constraints using small angular scale truncated estimators from simulations with fiber assignment incompleteness, with respect to standard estimators from complete simulations. Additionally, we present an approach to remove the sensitivity of the fits to high $k$ modes in the theoretical power spectrum, by applying a transformation to the data vector and window matrix. We find that our method efficiently mitigates the effect of fiber assignment incompleteness in two-point correlation function and power spectrum measurements, at low computational cost and with little statistical loss.

astro-ph.CO

DESI 2024: Reconstructing Dark Energy using Crossing Statistics with DESI DR1 BAO data

We implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negligible presence of dark energy at $z\gtrsim 1$, at varying significance depending on the data sets combined. In all these reconstructions, the cosmological constant lies outside the $95\%$ confidence intervals for some redshift ranges. This dark energy behaviour, reconstructed using Crossing Statistics, is in agreement with results from the conventional $w_0$--$w_a$ dark energy equation of state parametrization reported in the DESI Key cosmology paper. Our results add an extensive class of model-agnostic reconstructions with acceptable fits to the data, including models where cosmic acceleration slows down at low redshifts. We also report constraints on $H_0r_d$ from our model-agnostic analysis, independent of the pre-recombination physics.

astro-ph.CO

The clustering of Lyman Alpha Emitting galaxies at z=2-3

We measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs at z=2.45 and 3.1 in 9 sq.deg. centered on the COSMOS field with median LyA fluxes of 10^{-16}erg/s/cm2. Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length of r_0=(3.0\pm 0.2)Mpc/h. Within our fiducial cosmology these correspond to 3D number densities of 10^{-3} h^3/Mpc^3 and, from our mock catalogs, biases of 1.7 and 2.0 at z=2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology.

astro-ph.CO

DESI 2024: Constraints on Physics-Focused Aspects of Dark Energy using DESI DR1 BAO Data

Baryon acoustic oscillation data from the first year of the Dark Energy Spectroscopic Instrument (DESI) provide near percent-level precision of cosmic distances in seven bins over the redshift range $z=0.1$-$4.2$. We use this data, together with other distance probes, to constrain the cosmic expansion history using some well-motivated physical classes of dark energy. In particular, we explore three physics-focused behaviors of dark energy from the equation of state and energy density perspectives: the thawing class (matching many simple quintessence potentials), emergent class (where dark energy comes into being recently, as in phase transition models), and mirage class (where phenomenologically the distance to CMB last scattering is close to that from a cosmological constant $Λ$ despite dark energy dynamics). All three classes fit the data at least as well as $Λ$CDM, and indeed can improve on it by $Δχ^2\approx -5$ to $-17$ for the combination of DESI BAO with CMB and supernova data, while having one more parameter. The mirage class does essentially as well as $w_0w_a$CDM while having one less parameter. These classes of dynamical behaviors highlight worthwhile avenues for further exploration into the nature of dark energy.

astro-ph.CO

The DESI Survey Validation: Results from Visual Inspection of Bright Galaxies, Luminous Red Galaxies, and Emission Line Galaxies

The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect (VI) DESI spectra of approximately 2,500 bright galaxies, 3,500 luminous red galaxies (LRGs), and 10,000 emission line galaxies (ELGs), to obtain robust redshift identifications. We then utilize the VI redshift information to characterize the performance of the DESI operation. Based on the VI catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than $99\%$. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km/s for bright galaxies and ELGs and approximately 40 km/s for LRGs. The average redshift accuracy is within 10 km/s for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Ly$α$ emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases.

astro-ph.CO

Type Ia supernova Hubble diagrams with host galaxy photometric redshifts

The case of SN Ia Hubble diagrams from photometrically selected samples using photometric SN host galaxy redshifts is investigated. The host redshift uncertainties and the contamination by core collapse SNe are addressed. As a test, we use the 3-year photometric SN Ia sample of the SuperNova Legacy Survey (SNLS), made of 437 objects between 0.1 and 1.05 in redshift. We combine this sample with non-SNLS objects of the JLA spectroscopic sample, made of 501 objects mostly below 0.4 in redshift. We study two options for the origin of the redshifts of the photometric sample, either provided entirely from the host photometric redshift catalogue or a mixed origin where 75% of the sample can be assigned spectroscopic redshifts. Using light curve simulations subject to the same photometric selection as data, we study the impact of photometric redshift uncertainties and contamination on flat $ΛCDM$ fits to Hubble diagrams from such combined samples. We find that photometric redshifts and contamination lead to biased cosmological parameters. The magnitude of the bias is similar for both redshift options. This bias can be largely accounted for if photometric redshift uncertainties and contamination are taken into account when computing the SN magnitude bias correction due to selection effects. To reduce the cosmological bias further, we explore two methods to propagate redshift uncertainties into the cosmological likelihood computation, either by refitting photometric redshifts with cosmology or by sampling the redshift resolution function. Redshift refitting fails at correcting the cosmological bias whatever the redshift option, while sampling slightly reduces it in both cases. For actual data, we find compatible results with the JLA ones for mixed photometric and spectroscopic redshifts, while the full photometric option is biased but consistent with JLA when all uncertainties are included.

astro-ph.CO

Target Selection and Validation of DESI Emission Line Galaxies

The Dark Energy Spectroscopic Instrument (DESI) will precisely constrain cosmic expansion and the growth of structure by collecting $\sim$40 million extra-galactic redshifts across $\sim$80\% of cosmic history and one third of the sky. The Emission Line Galaxy (ELG) sample, which will comprise about one-third of all DESI tracers, will be used to probe the Universe over the $0.6 < z < 1.6$ range, which includes the $1.1<z<1.6$ range, expected to provide the tightest constraints. We present the target selection of the DESI SV1 Survey Validation and Main Survey ELG samples, which relies on the Legacy Surveys imaging. The Main ELG selection consists of a $g$-band magnitude cut and a $(g-r)$ vs.\ $(r-z)$ color box, while the SV1 selection explores extensions of the Main selection boundaries. The Main ELG sample is composed of two disjoint subsamples, which have target densities of about 1940 deg$^{-2}$ and 460 deg$^{-2}$, respectively. We first characterize their photometric properties and density variations across the footprint. Then we analyze the DESI spectroscopic data obtained since December 2020 during the Survey Validation and the Main Survey up to December 2021. We establish a preliminary criterion to select reliable redshifts, based on the \oii~flux measurement, and assess its performance. Using that criterion, we are able to present the spectroscopic efficiency of the Main ELG selection, along with its redshift distribution. We thus demonstrate that the the main selection with higher target density sample should provide more than 400 deg$^{-2}$ reliable redshifts in both the $0.6<z<1.1$ and the $1.1<z<1.6$ ranges.

astro-ph.CO

The ESO's VLT Type Ia supernova spectral set of the final two years of SNLS

We aim to present 70 spectra of 68 new high-redshift type Ia supernovae (SNeIa) measured at ESO's VLT during the final two years of operation (2006-2008) of the Supernova Legacy Survey (SNLS). We use the full five year SNLS VLT spectral set to investigate a possible spectral evolution of SNeIa populations with redshift and study spectral properties as a function of lightcurve fit parameters and the mass of the host-galaxy. Reduction and extraction are based on both IRAF standard tasks and our own reduction pipeline. Redshifts are estimated from host-galaxy lines whenever possible or alternatively from supernova features. We used the spectrophotometric SNIa model SALT2 combined with a set of galaxy templates that model the host-galaxy contamination to assess the type Ia nature of the candidates. We identify 68 new SNeIa with redshift ranging from z=0.207 to z=0.98 ( =0.62). Each spectrum is presented individually along with its best-fit SALT2 model. The five year dataset contains 209 spectra corresponding to 192 SNeIa identified at the VLT. We also publish the redshifts of other candidates (host galaxies or other transients) whose spectra were obtained at the same time as the spectra of live SNe Ia. Using the full VLT SNeIa sample, we build composite spectra around maximum light with cuts in color, lightcurve shape parameter ('stretch'), host-galaxy mass and redshift. We find that high-z SNeIa are bluer, brighter and have weaker intermediate mass element absorption lines than their low-z counterparts at a level consistent with what is expected from selection effects. We also find a flux excess in the range [3000-3400] A for SNeIa in low mass host-galaxies or with locally blue U-V colors, and suggest that the UV flux (or local color) may be used in future cosmological studies as a third standardization parameter in addition to stretch and color.

astro-ph.GA

Constraining the $Λ$CDM and Galileon models with recent cosmological data

The Galileon theory belongs to the class of modified gravity models that can explain the late-time accelerated expansion of the Universe. In previous works, cosmological constraints on the Galileon model were derived, both in the uncoupled case and with a disformal coupling of the Galileon field to matter. There, we showed that these models agree with the most recent cosmological data. In this work, we used updated cosmological data sets to derive new constraints on Galileon models, including the case of a constant conformal Galileon coupling to matter. We also explored the tracker solution of the uncoupled Galileon model. After updating our data sets, especially with the latest \textit{Planck} data and BAO measurements, we fitted the cosmological parameters of the $Λ$CDM and Galileon models. The same analysis framework as in our previous papers was used to derive cosmological constraints, using precise measurements of cosmological distances and of the cosmic structure growth rate. We showed that all tested Galileon models are as compatible with cosmological data as the $Λ$CDM model. This means that present cosmological data are not accurate enough to distinguish clearly between both theories. Among the different Galileon models, we found that a conformal coupling is not favoured, contrary to the disformal coupling which is preferred at the $2.3σ$ level over the uncoupled case. The tracker solution of the uncoupled Galileon model is also highly disfavoured due to large tensions with supernovae and \textit{Planck}+BAO data. However, outside of the tracker solution, the general uncoupled Galileon model, as well as the general disformally coupled Galileon model, remain the most promising Galileon scenarios to confront with future cosmological data. Finally, we also discuss constraints coming from Lunar Laser Ranging experiment and gravitational wave speed of propagation.

gr-qc

A Type II Supernova Hubble diagram from the CSP-I, SDSS-II, and SNLS surveys

The coming era of large photometric wide-field surveys will increase the detection rate of supernovae by orders of magnitude. Such numbers will restrict spectroscopic follow-up in the vast majority of cases, and hence new methods based solely on photometric data must be developed. Here, we construct a complete Hubble diagram of Type II supernovae combining data from three different samples: the Carnegie Supernova Project-I, the Sloan Digital Sky Survey-II SN, and the Supernova Legacy Survey. Applying the Photometric Colour Method (PCM) to 73 Type II supernovae (SNe~II) with a redshift range of 0.01--0.5 and with no spectral information, we derive an intrinsic dispersion of 0.35 mag. A comparison with the Standard Candle Method (SCM) using 61 SNe~II is also performed and an intrinsic dispersion in the Hubble diagram of 0.27 mag is derived, i.e., 13\% in distance uncertainties. Due to the lack of good statistics at higher redshifts for both methods, only weak constraints on the cosmological parameters are obtained. However, assuming a flat Universe and using the PCM, we derive a Universe's matter density: $Ω_{m}$=0.32$^{+0.30}_{-0.21}$ providing a new independent evidence for dark energy at the level of two sigma.

astro-ph.CO

Photometric classification of type Ia supernovae in the SuperNova Legacy Survey with supervised learning

In the era of large astronomical surveys, photometric classification of supernovae (SNe) has become an important research field due to limited spectroscopic resources for candidate follow-up and classification. In this work, we present a method to photometrically classify type Ia supernovae based on machine learning with redshifts that are derived from the SN light-curves. This method is implemented on real data from the SNLS deferred pipeline, a purely photometric pipeline that identifies SNe Ia at high-redshifts ($0.2<z<1.1$). Our method consists of two stages: feature extraction (obtaining the SN redshift from photometry and estimating light-curve shape parameters) and machine learning classification. We study the performance of different algorithms such as Random Forest and Boosted Decision Trees. We evaluate the performance using SN simulations and real data from the first 3 years of the Supernova Legacy Survey (SNLS), which contains large spectroscopically and photometrically classified type Ia samples. Using the Area Under the Curve (AUC) metric, where perfect classification is given by 1, we find that our best-performing classifier (Extreme Gradient Boosting Decision Tree) has an AUC of $0.98$. We show that it is possible to obtain a large photometrically selected type Ia SN sample with an estimated contamination of less than $5\%$. When applied to data from the first three years of SNLS, we obtain 529 events. We investigate the differences between classifying simulated SNe, and real SN survey data. In particular, we find that applying a thorough set of selection cuts to the SN sample is essential for good classification. This work demonstrates for the first time the feasibility of machine learning classification in a high-$z$ SN survey with application to real SN data.

astro-ph.IM

The Volumetric Rate of Superluminous Supernovae at z~1

We present a measurement of the volumetric rate of superluminous supernovae (SLSNe) at z~1, measured using archival data from the first four years of the Canada-France-Hawaii Telescope Supernova Legacy Survey (SNLS). We develop a method for the photometric classification of SLSNe to construct our sample. Our sample includes two previously spectroscopically-identified objects, and a further new candidate selected using our classification technique. We use the point-source recovery efficiencies from Perrett et.al. (2010) and a Monte Carlo approach to calculate the rate based on our SLSN sample. We find that the three identified SLSNe from SNLS give a rate of 91 (+76/-36) SNe/Yr/Gpc^3 at a volume-weighted redshift of z=1.13. This is equivalent to 2.2 (+1.8/-0.9) x10^-4 of the volumetric core collapse supernova rate at the same redshift. When combined with other rate measurements from the literature, we show that the rate of SLSNe increases with redshift in a manner consistent with that of the cosmic star formation history. We also estimate the rate of ultra-long gamma ray bursts (ULGRBs) based on the events discovered by the Swift satellite, and show that it is comparable to the rate of SLSNe, providing further evidence of a possible connection between these two classes of events. We also examine the host galaxies of the SLSNe discovered in SNLS, and find them to be consistent with the stellar-mass distribution of other published samples of SLSNe.

astro-ph.HE

SNIa detection in the SNLS photometric analysis using Morphological Component Analysis

Detection of supernovae and, more generally, of transient events in large surveys can provide numerous false detections.In the case of a deferred processing of survey images, this implies reconstructing complete light curves for all detections, requiring sizable processing time and resources.Optimizing the detection of transient events is thus an important issue for both present and future surveys.We present here the optimization done in the SuperNova Legacy Survey (SNLS) for the 5-year data deferred photometric analysis. In this analysis, detections are derived from stacks of subtracted images with one stack per lunation.The 3-year analysis provided 300,000 detections dominated by signals of bright objects that were not perfectly subtracted.Allowing these artifacts to be detected leads not only to a waste of resources but also to possible signal coordinate contamination.We developed a subtracted image stack treatment to reduce the number of non SN-like events using morphological component analysis.This technique exploits the morphological diversity of objects to be detected to extract the signal of interest.At the level of our subtraction stacks, SN-like events are rather circular objects while most spurious detections exhibit different shapes.A two-step procedure was necessary to have a proper evaluation of the noise in the subtracted image stacks and thus a reliable signal extraction.We also set up a new detection strategy to obtain coordinates with good resolution for the extracted signal.SNIa MC generated images were used to study detection efficiency and coordinate resolution.When tested on SNLS 3 data this procedure decreases the number of detections by a factor of two, while losing only 10% of SN-like events, almost all faint.MC results show that SNIa detection efficiency is equivalent to that of the original method for bright events, while the coordinate resolution is improved.

astro-ph.IM

First experimental constraints on the disformally coupled Galileon model

The Galileon model is a modified gravity model that can explain the late-time accelerated expansion of the Universe. In a previous work, we derived experimental constraints on the Galileon model with no explicit coupling to matter and showed that this model agrees with the most recent cosmological data. In the context of braneworld constructions or massive gravity, the Galileon model exhibits a disformal coupling to matter, which we study in this paper. After comparing our constraints on the uncoupled model with recent studies, we extend the analysis framework to the disformally coupled Galileon model and derive the first experimental constraints on that coupling, using precise measurements of cosmological distances and the growth rate of cosmic structures. In the uncoupled case, with updated data, we still observe a low tension between the constraints set by growth data and those from distances. In the disformally coupled Galileon model, we obtain better agreement with data and favour a non-zero disformal coupling to matter at the $2.5σ$ level. This gives an interesting hint of the possible braneworld origin of Galileon theory.

gr-qc

Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples

We present cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations. The data set includes several low-redshift samples (z<0.1), all 3 seasons from the SDSS-II (0.05 < z < 0.4), and 3 years from SNLS (0.2 <z < 1) and totals \ntotc spectroscopically confirmed type Ia supernovae with high quality light curves. We have followed the methods and assumptions of the SNLS 3-year data analysis except for the following important improvements: 1) the addition of the full SDSS-II spectroscopically-confirmed SN Ia sample in both the training of the SALT2 light curve model and in the Hubble diagram analysis (\nsdssc SNe), 2) inter-calibration of the SNLS and SDSS surveys and reduced systematic uncertainties in the photometric calibration, performed blindly with respect to the cosmology analysis, and 3) a thorough investigation of systematic errors associated with the SALT2 modeling of SN Ia light-curves. We produce recalibrated SN Ia light-curves and associated distances for the SDSS-II and SNLS samples. The large SDSS-II sample provides an effective, independent, low-z anchor for the Hubble diagram and reduces the systematic error from calibration systematics in the low-z SN sample. For a flat LCDM cosmology we find Omega_m=0.295+-0.034 (stat+sys), a value consistent with the most recent CMB measurement from the Planck and WMAP experiments. Our result is 1.8sigma (stat+sys) different than the previously published result of SNLS 3-year data. The change is due primarily to improvements in the SNLS photometric calibration. When combined with CMB constraints, we measure a constant dark-energy equation of state parameter w=-1.018+-0.057 (stat+sys) for a flat universe. Adding BAO distance measurements gives similar constraints: w=-1.027+-0.055.

astro-ph.CO

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.

astro-ph.CO