arXiv subjects

S. Fabbro

Publications and source records attributed to S. Fabbro.

At least 19 recordsLinked to original sources

arXiv2026

UNIONS-3500 Weak Lensing: IV. 2D cosmological constraints in harmonic space

The Ultraviolet Near Infrared Optical Northern Survey (UNIONS) is a photometric survey in the northern sky. The quality of the data in the $r$ band provides precise shape measurements to measure the growth of structures using cosmic shear. This work aims to constrain cosmological parameters using a harmonic-space estimator of the cosmic shear signal, known as pseudo-$C_\ell$, in a non-tomographic analysis. We perform our analysis in the context of the standard $\Lambda$CDM cosmology. We model astrophysical systematic effects such as baryonic feedback and intrinsic alignments of galaxies. We verify that the point spread function systematic contribution does not affect our results. We assess the impact of different scale cuts and modelling choices on the constraints. We find $S_8 \equiv \sigma_8 \sqrt{\Omega_{\rm m}/0.3} = 0.891^{+0.057}_{-0.084}$, consistent at the $0.79 \, \sigma$ level with \emph{Planck} and between $0.87$ to $1.51 \, \sigma$ with other weak lensing surveys. Our results are robust to analysis choices, and we use lognormal simulations to assess the consistency between configuration and harmonic space results, finding a $2.18 \, \sigma$ agreement between the two statistics. The degeneracy between $S_8$ and the amplitude of the intrinsic alignment, $A_{\rm IA}$, sampled from a prior obtained from direct measurements, is one of the largest sources of uncertainty. This work is part of the first cosmological analysis of the UNIONS survey using cosmic shear and paves the way for future tomographic and $3 \times 2$ point cross-correlation analyses, exploiting the unique overlap of UNIONS with deep spectroscopic surveys in the northern hemisphere.

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arXiv2026

UNIONS-3500 Weak Lensing: III. 2D Cosmological Constraints in Configuration Space

We present the first cosmological constraints from the cosmic shear analysis of the UNIONS-3500 weak lensing galaxy catalogue in configuration space. The Ultraviolet Near Infrared Optical Northern Survey (UNIONS) is the largest and deepest photometric survey of the northern hemisphere to date, with the UNIONS-3500 catalogue using high-quality $r$-band imaging across 3500 deg2 of the sky. We perform a 2D cosmic shear analysis with a single tomographic bin, using the two-point correlation function (2PCF) statistic. Assuming a flat LCDM model, we obtain constraints on the clustering amplitude of S_8 = 0.831^{+0.067}_{-0.078}, which is consistent with constraints from Planck CMB measurements and precedent cosmic shear results within 1sigma. We outline the construction of our cosmological inference pipeline, including the estimation of the source redshift distribution, shear calibration, and covariance matrix, and describe methodologies for the mitigation of systematic effects arising from PSF systematics and B-modes. We demonstrate that our results are robust to variations in analysis choices, including scale cuts, prior ranges, and nonlinear modelling. This paper is part of a coordinated release which collectively demonstrates the maturity and readiness of UNIONS to deliver competitive cosmological results, positioning it as a key stepping stone towards the forthcoming era of Stage IV weak lensing experiments.

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arXiv2026

UNIONS-3500 Weak Lensing: I. A Galaxy Shape Catalogue in the Northern Sky

Weak gravitational lensing has become a widely used effect to characterise the dark-matter distribution on large scales in the Universe by measuring galaxy ellipticities and their statistical correlations. We present the first weak gravitational lensing catalogue for cosmic-shear cosmology of the Ultraviolet Near Infrared Optical Northern Survey (UNIONS). We analyse approximately $3\,500$ square degrees of sky area in the Northern Hemisphere, observed in the $r$-band by MegaCam on the Canada-France Hawai'i Telescope, achieving a median seeing of 0.7 arcsec. Starting from images calibrated for astrometry and photometry, we describe the steps from image processing to catalogue creation. These steps include masking, source detection and selection, star selection, point spread function (PSF) modelling, shape measurement, and calibration. We conduct extensive validation tests, particularly to assess and mitigate the leakage of PSF ellipticity into galaxy shapes. We demonstrate the robustness of the catalogue by investigating correlations between ellipticity and other observational variables as well as structural elements, such as observer-frame image positions and proximity to bright stars. The final galaxy catalogue contains $62$ million galaxies, corresponding to an effective source density of $4.96$ arcmin$^{-2}$. The ellipticity dispersion, commonly referred to as shape noise, is $\sigma_\epsilon = 0.27$. Initiating the first major cosmological analysis by the UNIONS collaboration, this is the first in a series of five papers which cover the various aspects of a robust cosmic shear analysis. Two companion papers discuss the robustness of the catalogue, one through the level of $B$-mode contamination and another by producing and analysing dedicated image simulations for shear calibration, while the other two present cosmological results in real and harmonic space.

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arXiv2024

The New Horizons Extended Mission Target: Arrokoth Search and Discovery

Following the Pluto fly-by of the New Horizons spacecraft, the mission provided a unique opportunity to explore the Kuiper Belt in-situ. The possibility existed to fly-by a Kuiper Belt object (KBO) as well as to observe additional objects at distances closer than are feasible from earth-orbit facilities. However, at the time of launch no KBOs were known about that were accessible by the spacecraft. In this paper we present the results of 10 years of observations and three uniquely dedicated efforts -- two ground-based using the Subaru Suprime Camera, the Magellan MegaCam and IMACS Cameras, and one with the Hubble Space Telescope -- to find such KBOs for study. In this paper we overview the search criteria and strategies employed in our work and detail the analysis efforts to locate and track faint objects in the galactic plane. We also present a summary of all of the KBOs that were discovered as part of our efforts and how spacecraft targetability was assessed, including a detailed description of our astrometric analysis which included development of an extensive secondary calibration network. Overall, these efforts resulted in the discovery of 89 KBOs including 11 which became objects for distant observation by New Horizons and (486958) Arrokoth which became the first post-Pluto fly-by destination.

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arXiv2023

The treasure behind the haystack: MUSE analysis of five recently discovered globular clusters

After the second data release of Gaia, the number of new globular cluster candidates has increased importantly. However, most of them need to be properly characterised, both spectroscopically and photometrically, by means of radial velocities, metallicities, and deeper photometric observations. Our goal is to provide an independent confirmation of the cluster nature of Gran 4, a recently discovered globular cluster, with follow-up spectroscopic observations. The derived radial velocity for individual stars, coupled with proper motions, allows us to isolate cluster members from field stars, while the analysis of their spectra allows us to derive metallicities. By including in the analysis the recently confirmed clusters Gran 1, 2, 3, and 5, we aim to completely characterise the sample presented in Gran et al. 2022. Using Gaia DR3 and VVV catalogue data and MUSE@VLT observations, we performed a selection of cluster members based on their proper motions, radial velocities and their position in colour-magnitude diagrams. Furthermore, full spectral synthesis was performed on the cluster members, extracting surface parameters and metallicity from MUSE spectra. Finally, a completeness estimation was performed on the total globular cluster population of the Milky Way. We confirm the nature of Gran 4, a newly discovered globular cluster behind the Galactic bulge, with a mean radial velocity of ${\rm RV} = -265.28 \pm 3.92$ km s$^{-1}$ and a mean metallicity of ${\rm [Fe/H] = -1.72 \pm 0.32}$ dex. Additionally, independent measurements of the metallicities were derived for Gran 1, 2, 3, and 5. We also revise the observational lower mass limit for a globular cluster to survive in the bulge/disk environment. We estimate that $\sim 12-26$ globular clusters have still to be discovered on the other side of the Galaxy (i.e., behind the bulge/bar/disk), up to 20 kpc.

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arXiv2023

Beyond Gaia DR3: Tracing the [$\alpha$/M]-[M/H] bimodality from the inner to the outer Milky Way disc with Gaia-RVS and convolutional neural networks

In June 2022, Gaia DR3 has provided the astronomy community with about one million spectra from the Radial Velocity Spectrometer (RVS) covering the CaII triplet region. However, one-third of the published spectra have 15<S/N<25 per pixel such that they pose problems for classical spectral analysis pipelines, and therefore, alternative ways to tap into these large datasets need to be devised. We aim to leverage the versatility and capabilities of machine learning techniques for supercharged stellar parametrisation by combining Gaia-RVS spectra with the full set of Gaia products and high-resolution, high-quality ground-based spectroscopic reference datasets. We developed a hybrid convolutional neural network (CNN) that combines the Gaia DR3 RVS spectra, photometry (G, G_BP, G_RP), parallaxes, and XP coefficients to derive atmospheric parameters (Teff, log(g) as well as overall [M/H]) and chemical abundances ([Fe/H] and [{\alpha}/M]). We trained the CNN with a high-quality training sample based on APOGEE DR17 labels. With this CNN, we derived homogeneous atmospheric parameters and abundances for 886080 RVS stars that show remarkable precision and accuracy compared to external datasets (such as GALAH and asteroseismology). The CNN is robust against noise in the RVS data, and we derive very precise labels down to S/N=15. We managed to characterise the [{\alpha}/M]-[M/H] bimodality from the inner regions to the outer parts of the Milky Way, which has never been done using RVS spectra or similar datasets. This work is the first to combine machine learning with such diverse datasets and paves the way for large-scale machine learning analysis of Gaia-RVS spectra from future data releases. Large, high-quality datasets can be optimally combined thanks to the CNN, thereby realising the full power of spectroscopy, astrometry, and photometry.

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arXiv2021

Strong lensing in UNIONS: Toward a pipeline from discovery to modeling

We present a search for galaxy-scale strong gravitational lenses in the initial 2 500 square degrees of the Canada-France Imaging Survey (CFIS). We designed a convolutional neural network (CNN) committee that we applied to a selection of 2 344 002 exquisite-seeing $r$-band images of color-selected luminous red galaxies (LRGs). Our classification uses a realistic training set where the lensing galaxies and the lensed sources are both taken from real data, namely the CFIS $r$-band images themselves and the Hubble Space Telescope (HST). A total of 9 460 candidates obtain a score above 0.5 with the CNN committee. After a visual inspection of the candidates, we find a total of 133 lens candidates, of which 104 are completely new. The set of false positives mainly contains ring, spiral, and merger galaxies, and to a lesser extent galaxies with nearby companions. We classify 32 of the lens candidates as secure lenses and 101 as maybe lenses. For the 32 highest quality lenses, we also fit a singular isothermal ellipsoid mass profile with external shear along with an elliptical Sersic profile for the lens and source light. This automated modeling step provides distributions of properties for both sources and lenses that have Einstein radii in the range $0.5\arcsec<\theta_E<2.5\arcsec$. Finally, we introduce a new lens and/or source single-band deblending algorithm based on auto-encoder representation of our candidates. This is the first time an end-to-end lens-finding and modeling pipeline is assembled together, in view of future lens searches in a single band, as will be possible with Euclid.

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arXiv2021

Discovery of Strongly Lensed Quasars in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS)

We report the discovery of five new doubly-imaged lensed quasars from the first 2500 square degrees of the ongoing Canada-France Imaging Survey (CFIS), which is a component of the Ultraviolet Near Infrared Optical Northern Survey (UNIONS), selected from initial catalogues of either Gaia pairs or MILLIQUAS quasars. We take advantage of the deep, 0.6'' median-seeing $r$-band imaging of CFIS to confirm the presence of multiple point sources with similar colour of $u-r$, via convolution of the Laplacian of the point spread function. Requiring similar-colour point sources with flux ratios less than 2.5 mag in $r$-band, reduces the number of candidates from 256314 to 7815. After visual inspection we obtain 30 high-grade candidates, and prioritise spectroscopic follow-up for those showing signs of a lensing galaxy upon subtraction of the point sources. We obtain long-slit spectra for 18 candidates with ALFOSC on the 2.56-m Nordic Optical Telescope (NOT), confirming five new doubly lensed quasars with $1.21<z<3.36$ and angular separations from 0.8'' to 2.5''. One additional system is a probable lensed quasar based on the CFIS imaging and existing SDSS spectrum. We further classify six objects as nearly identical quasars -- still possible lenses but without the detection of a lensing galaxy. Given our recovery rate ($83\%$) of existing optically bright lenses within the CFIS footprint, we expect that a similar strategy, coupled with $u-r$ colour-selection from CFIS alone, will provide an efficient and complete discovery of small-separation lensed quasars of source redshifts below $z=2.7$ within the CFIS $r$-band magnitude limit of 24.1 mag.

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arXiv2019

LRP2020: Machine Learning Advantages in Canadian Astrophysics

The application of machine learning (ML) methods to the analysis of astrophysical datasets is on the rise, particularly as the computing power and complex algorithms become more powerful and accessible. As the field of ML enjoys a continuous stream of breakthroughs, its applications demonstrate the great potential of ML, ranging from achieving tens of millions of times increase in analysis speed (e.g., modeling of gravitational lenses or analysing spectroscopic surveys) to solutions of previously unsolved problems (e.g., foreground subtraction or efficient telescope operations). The number of astronomical publications that include ML has been steadily increasing since 2010. With the advent of extremely large datasets from a new generation of surveys in the 2020s, ML methods will become an indispensable tool in astrophysics. Canada is an unambiguous world leader in the development of the field of machine learning, attracting large investments and skilled researchers to its prestigious AI Research Institutions. This provides a unique opportunity for Canada to also be a world leader in the application of machine learning in the field of astrophysics, and foster the training of a new generation of highly skilled researchers.

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arXiv2018

Searching for supernovae in the multiply-imaged galaxies behind the gravitational telescope A370

Strong lensing by massive galaxy clusters can provide magnification of the flux and even multiple images of the galaxies that lie behind them. This phenomenon facilitates observations of high-redshift supernovae (SNe), that would otherwise remain undetected. Type Ia supernovae (SNe Ia) detections are of particular interest because of their standard brightness, since they can be used to improve either cluster lensing models or cosmological parameter measurements. We present a ground-based, near-infrared search for lensed SNe behind the galaxy cluster Abell 370. Our survey was based on 15 epochs of J-band observations with the HAWK-I instrument on the Very Large Telescope (VLT). We use Hubble Space Telescope (HST) photometry to infer the global properties of the multiply-imaged galaxies. Using a recently published lensing model of Abell 370, we also present the predicted magnifications and time delays between the images. In our survey, we did not discover any live SNe from the 13 lensed galaxies with 47 multiple images behind Abell 370. This is consistent with the expectation of $0.09\pm0.02$ SNe calculated based on the measured star formation rate. We compare the expectations of discovering strongly lensed SNe in our survey and that performed with HST during the Hubble Frontier Fields (HFF) programme. We also show the expectations of search campaigns that can be conducted with future facilities, such as the James Webb Space Telescope (JWST) or the Wide-Field Infrared Survey Telescope (WFIRST). We show that the NIRCam instrument aboard the JWST will be sensitive to most SN multiple images in the strongly lensed galaxies and thus will be able to measure their time delays if observations are scheduled accordingly.

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arXiv2018

The Astropy Project: Building an inclusive, open-science project and status of the v2.0 core package

The Astropy project supports and fosters the development of open-source and openly-developed Python packages that provide commonly-needed functionality to the astronomical community. A key element of the Astropy project is the core package Astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of inter-operable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy project.

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arXiv2017

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.

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arXiv2014

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.

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arXiv2013

Photometry of supernovae in an image series : methods and application to the Supernova Legacy Survey (SNLS)

We present a technique to measure lightcurves of time-variable point sources on a spatially structured background from imaging data. The technique was developed to measure light curves of SNLS supernovae in order to infer their distances. This photometry technique performs simultaneous PSF photometry at the same sky position on an image series. We describe two implementations of the method: one that resamples images before measuring fluxes, and one which does not. In both instances, we sketch the key algorithms involved and present the validation using semi-artificial sources introduced in real images in order to assess the accuracy of the supernova flux measurements relative to that of surrounding stars. We describe the methods required to anchor these PSF fluxes to calibrated aperture catalogs, in order to derive SN magnitudes. We find a marginally significant bias of 2 mmag of the after-resampling method, and no bias at the mmag accuracy for the non-resampling method. Given surrounding star magnitudes, we determine the systematic uncertainty of SN magnitudes to be less than 1.5 mmag, which represents about one third of the current photometric calibration uncertainty affecting SN measurements. The SN photometry delivers several by-products: bright star PSF flux mea- surements which have a repeatability of about 0.6%, as for aperture measurements; we measure relative astrometric positions with a noise floor of 2.4 mas for a single-image bright star measurement; we show that in all bands of the MegaCam instrument, stars exhibit a profile linearly broadening with flux by about 0.5% over the whole brightness range.

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arXiv2011

A highly magnified supernova at z=1.703 behind the massive galaxy cluster Abell 1689

Our ability to study the most remote supernova explosions, crucial for the understanding of the evolution of the high-redshift universe and its expansion rate, is limited by the light collection capabilities of telescopes. However, nature offers unique opportunities to look beyond the range within reach of our unaided instruments thanks to the light-focusing power of massive galaxy clusters. Here we report on the discovery of one of the most distant supernovae ever found, at redshift, z=1.703. Due to a lensing magnification factor of 4.3\pm0.3, we are able to measure a lightcurve of the supernova, as well as spectroscopic features of the host galaxy with a precision comparable to what will otherwise only be possible with future generation telescopes.

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arXiv2011

SNLS3: Constraints on Dark Energy Combining the Supernova Legacy Survey Three Year Data with Other Probes

We present observational constraints on the nature of dark energy using the Supernova Legacy Survey three year sample (SNLS3) of Guy et al. (2010) and Conley et al. (2011). We use the 472 SNe Ia in this sample, accounting for recently discovered correlations between SN Ia luminosity and host galaxy properties, and include the effects of all identified systematic uncertainties directly in the cosmological fits. Combining the SNLS3 data with the full WMAP7 power spectrum, the Sloan Digital Sky Survey luminous red galaxy power spectrum, and a prior on the Hubble constant H0 from SHOES, in a flat universe we find omega_m=0.269+/-0.015 and w=-1.061+0.069-0.068 -- a 6.5% measure of the dark energy equation-of-state parameter w. The statistical and systematic uncertainties are approximately equal, with the systematic uncertainties dominated by the photometric calibration of the SN Ia fluxes -- without these calibration effects, systematics contribute only a ~2% error in w. When relaxing the assumption of flatness, we find omega_m=0.271+/-0.015, omega_k=-0.002+/-0.006, and w=-1.069+0.091-0.092. Parameterizing the time evolution of w as w(a)=w_0+w_a(1-a), gives w_0=-0.905+/-0.196, w_a=-0.984+1.094-1.097 in a flat universe. All of our results are consistent with a flat, w=-1 universe. The size of the SNLS3 sample allows various tests to be performed with the SNe segregated according to their light curve and host galaxy properties. We find that the cosmological constraints derived from these different sub-samples are consistent. There is evidence that the coefficient, beta, relating SN Ia luminosity and color, varies with host parameters at >4sigma significance (in addition to the known SN luminosity--host relation); however this has only a small effect on the cosmological results and is currently a sub-dominant systematic.

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arXiv2011

Supernova Constraints and Systematic Uncertainties from the First 3 Years of the Supernova Legacy Survey

We combine high redshift Type Ia supernovae from the first 3 years of the Supernova Legacy Survey (SNLS) with other supernova (SN) samples, primarily at lower redshifts, to form a high-quality joint sample of 472 SNe (123 low-$z$, 93 SDSS, 242 SNLS, and 14 {\it Hubble Space Telescope}). SN data alone require cosmic acceleration at >99.9% confidence, including systematic effects. For the dark energy equation of state parameter (assumed constant out to at least $z=1.4$) in a flat universe, we find $w = -0.91^{+0.16}_{-0.20}(\mathrm{stat}) ^{+0.07}_{-0.14} (\mathrm{sys})$ from SNe only, consistent with a cosmological constant. Our fits include a correction for the recently discovered relationship between host-galaxy mass and SN absolute brightness. We pay particular attention to systematic uncertainties, characterizing them using a systematics covariance matrix that incorporates the redshift dependence of these effects, as well as the shape-luminosity and color-luminosity relationships. Unlike previous work, we include the effects of systematic terms on the empirical light-curve models. The total systematic uncertainty is dominated by calibration terms. We describe how the systematic uncertainties can be reduced with soon to be available improved nearby and intermediate-redshift samples, particularly those calibrated onto USNO/SDSS-like systems.

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arXiv2010

The Supernova Legacy Survey 3-year sample: Type Ia Supernovae photometric distances and cosmological constraints

We present photometric properties and distance measurements of 252 high redshift Type Ia supernovae (0.15 < z < 1.1) discovered during the first three years of the Supernova Legacy Survey (SNLS). These events were detected and their multi-colour light curves measured using the MegaPrime/MegaCam instrument at the Canada-France-Hawaii Telescope (CFHT), by repeatedly imaging four one-square degree fields in four bands. Follow-up spectroscopy was performed at the VLT, Gemini and Keck telescopes to confirm the nature of the supernovae and to measure their redshifts. Systematic uncertainties arising from light curve modeling are studied, making use of two techniques to derive the peak magnitude, shape and colour of the supernovae, and taking advantage of a precise calibration of the SNLS fields. A flat LambdaCDM cosmological fit to 231 SNLS high redshift Type Ia supernovae alone gives Omega_M = 0.211 +/- 0.034(stat) +/- 0.069(sys). The dominant systematic uncertainty comes from uncertainties in the photometric calibration. Systematic uncertainties from light curve fitters come next with a total contribution of +/- 0.026 on Omega_M. No clear evidence is found for a possible evolution of the slope (beta) of the colour-luminosity relation with redshift.

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