arXiv subjects

A. Möller

Publications and source records attributed to A. Möller.

At least 73 records · Page 4Linked to original sources

arXiv2019

First Cosmological Results using Type Ia Supernovae from the Dark Energy Survey: Measurement of the Hubble Constant

We present an improved measurement of the Hubble constant (H_0) using the 'inverse distance ladder' method, which adds the information from 207 Type Ia supernovae (SNe Ia) from the Dark Energy Survey (DES) at redshift 0.018 < z < 0.85 to existing distance measurements of 122 low redshift (z < 0.07) SNe Ia (Low-z) and measurements of Baryon Acoustic Oscillations (BAOs). Whereas traditional measurements of H_0 with SNe Ia use a distance ladder of parallax and Cepheid variable stars, the inverse distance ladder relies on absolute distance measurements from the BAOs to calibrate the intrinsic magnitude of the SNe Ia. We find H_0 = 67.8 +/- 1.3 km s-1 Mpc-1 (statistical and systematic uncertainties, 68% confidence). Our measurement makes minimal assumptions about the underlying cosmological model, and our analysis was blinded to reduce confirmation bias. We examine possible systematic uncertainties and all are below the statistical uncertainties. Our H_0 value is consistent with estimates derived from the Cosmic Microwave Background assuming a LCDM universe (Planck Collaboration et al. 2018).

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arXiv2019

First Cosmology Results using Type Ia Supernova from the Dark Energy Survey: Simulations to Correct Supernova Distance Biases

We describe catalog-level simulations of Type Ia supernova (SN~Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN), and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project (CSP). These simulations are used to model biases from selection effects and light curve analysis, and to determine bias corrections for SN~Ia distance moduli that are used to measure cosmological parameters. To generate realistic light curves, the simulation uses a detailed SN~Ia model, incorporates information from observations (PSF, sky noise, zero point), and uses summary information (e.g., detection efficiency vs. signal to noise ratio) based on 10,000 fake SN light curves whose fluxes were overlaid on images and processed with our analysis pipelines. The quality of the simulation is illustrated by predicting distributions observed in the data. Averaging within redshift bins, we find distance modulus biases up to 0.05~mag over the redshift ranges of the low-z and DES-SN samples. For individual events, particularly those with extreme red or blue color, distance biases can reach 0.4~mag. Therefore, accurately determining bias corrections is critical for precision measurements of cosmological parameters. Files used to make these corrections are available at https://des.ncsa.illinois.edu/releases/sn.

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arXiv2019

Steve: A hierarchical Bayesian model for Supernova Cosmology

We present a new Bayesian hierarchical model (BHM) named Steve for performing type Ia supernova (SNIa) cosmology fits. This advances previous works by including an improved treatment of Malmquist bias, accounting for additional sources of systematic uncertainty, and increasing numerical efficiency. Given light curve fit parameters, redshifts, and host-galaxy masses, we fit Steve simultaneously for parameters describing cosmology, SNIa populations, and systematic uncertainties. Selection effects are characterised using Monte-Carlo simulations. We demonstrate its implementation by fitting realisations of SNIa datasets where the SNIa model closely follows that used in Steve. Next, we validate on more realistic SNANA simulations of SNIa samples from the Dark Energy Survey and low-redshift surveys. These simulated datasets contain more than $60\,000$ SNeIa, which we use to evaluate biases in the recovery of cosmological parameters, specifically the equation-of-state of dark energy, $w$. This is the most rigorous test of a BHM method applied to SNIa cosmology fitting, and reveals small $w$-biases that depend on the simulated SNIa properties, in particular the intrinsic SNIa scatter model. This $w$-bias is less than $0.03$ on average, less than half the statistical uncertainty on $w$.These simulation test results are a concern for BHM cosmology fitting applications on large upcoming surveys, and therefore future development will focus on minimising the sensitivity of Steve to the SNIa intrinsic scatter model.

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arXiv2019

A Fast Radio Burst with frequency-dependent polarization detected during Breakthrough Listen observations

Here, we report on the detection and verification of Fast Radio Burst FRB 180301, which occurred on UTC 2018 March 1 during the Breakthrough Listen observations with the Parkes telescope. Full-polarization voltage data of the detection were captured--a first for non-repeating FRBs--allowing for coherent de-dispersion and additional verification tests. The coherently de-dispersed dynamic spectrum of FRB 180301 shows complex, polarized frequency structure over a small fractional bandwidth. As FRB 180301 was detected close to the geosynchronous satellite band during a time of known 1-2 GHz satellite transmissions, we consider whether the burst was due to radio interference emitted or reflected from an orbiting object. Based on the preponderance of our verification tests, we find that FRB 180301 is likely of astrophysical origin, but caution that anthropogenic sources cannot conclusively be ruled out.

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arXiv2018

First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Survey Overview and Supernova Spectroscopy

We present spectroscopy from the first three seasons of the Dark Energy Survey Supernova Program (DES-SN). We describe the supernova spectroscopic program in full: strategy, observations, data reduction, and classification. We have spectroscopically confirmed 307 supernovae, including 251 type Ia supernovae (SNe Ia) over a redshift range of $0.017 < z < 0.85$. We determine the effective spectroscopic selection function for our sample, and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. We also provide a full overview of the strategy, observations, and data products of DES-SN, which has discovered 12,015 likely supernovae during these first three seasons. The data presented here are used for the first cosmology analysis by DES-SN ('DES-SN3YR'), the results of which are given in DES Collaboration (2018a).

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arXiv2018

First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Effects of Chromatic Corrections to Supernova Photometry on Measurements of Cosmological Parameters

Calibration uncertainties have been the leading systematic uncertainty in recent analyses using type Ia Supernovae (SNe Ia) to measure cosmological parameters. To improve the calibration, we present the application of Spectral Energy Distribution (SED)-dependent "chromatic corrections" to the supernova light-curve photometry from the Dark Energy Survey (DES). These corrections depend on the combined atmospheric and instrumental transmission function for each exposure, and they affect photometry at the 0.01 mag (1%) level, comparable to systematic uncertainties in calibration and photometry. Fitting our combined DES and low-z SN Ia sample with Baryon Acoustic Oscillation (BAO) and Cosmic Microwave Background (CMB) priors for the cosmological parameters $Ω_{\rm m}$ (the fraction of the critical density of the universe comprised of matter) and w (the dark energy equation of state parameter), we compare those parameters before and after applying the corrections. We find the change in w and $Ω_{\rm m}$ due to not including chromatic corrections are -0.002 and 0.000, respectively, for the DES-SN3YR sample with BAO and CMB priors, consistent with a larger DES-SN3YR-like simulation, which has a w-change of 0.0005 with an uncertainty of 0.008 and an $Ω_{\rm m}$ change of 0.000 with an uncertainty of 0.002 . However, when considering samples on individual CCDs we find large redshift-dependent biases (approximately 0.02 in distance modulus) for supernova distances.

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arXiv2018

A nearby superluminous supernova with a long pre-maximum 'plateau' and strong CII features

Super-luminous supernovae (SLSNe) are rare events defined as being significantly more luminous than normal terminal stellar explosions. The source of the extra powering needed to achieve such luminosities is still unclear. Discoveries in the local Universe (i.e. $z<0.1$) are scarce, but afford dense multi-wavelength observations. Additional low-redshift objects are therefore extremely valuable. We present early-time observations of the type I SLSN ASASSN-18km/SN~2018bsz. These data are used to characterise the event and compare to literature SLSNe and spectral models. Host galaxy properties are also analysed. Optical and near-IR photometry and spectroscopy were analysed. Early-time ATLAS photometry was used to constrain the rising light curve. We identified a number of spectral features in optical-wavelength spectra and tracked their time evolution. Finally, we used archival host galaxy photometry together with HII region spectra to constrain the host environment. ASASSN-18km/SN~2018bsz is found to be a type I SLSN in a galaxy at a redshift of 0.0267 (111 Mpc), making it the lowest-redshift event discovered to date. Strong CII lines are identified in the spectra. Spectral models produced by exploding a Wolf-Rayet progenitor and injecting a magnetar power source are shown to be qualitatively similar to ASASSN-18km/SN~2018bsz, contrary to most SLSNe-I that display weak/non-existent CII lines. ASASSN-18km/SN~2018bsz displays a long, slowly rising, red 'plateau' of $>$26 days, before a steeper, faster rise to maximum. The host has an absolute magnitude of --19.8 mag ($r$), a mass of M$_{*}$ = 1.5$^{+0.08}_{-0.33}$ $\times$10$^{9}$ M$_{\odot}$ , and a star formation rate of = 0.50$^{+2.22}_{-0.19}$ M$_{\odot}$ yr$^{-1}$. A nearby HII region has an oxygen abundance (O3N2) of 8.31$\pm$0.01 dex.

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arXiv2018

Rapidly evolving transients in the Dark Energy Survey

We present the results of a search for rapidly evolving transients in the Dark Energy Survey Supernova Programme. These events are characterized by fast light curve evolution (rise to peak in $\lesssim 10$ d and exponential decline in $\lesssim30$ d after peak). We discovered 72 events, including 37 transients with a spectroscopic redshift from host galaxy spectral features. The 37 events increase the total number of rapid optical transients by more than factor of two. They are found at a wide range of redshifts ($0.05 M_\mathrm{g}>-22.25$). The multiband photometry is well fit by a blackbody up to few weeks after peak. The events appear to be hot ($T\approx10000-30000$ K) and large ($R\approx 10^{14}-2\cdot10^{15}$ cm) at peak, and generally expand and cool in time, though some events show evidence for a receding photosphere with roughly constant temperature. Spectra taken around peak are dominated by a blue featureless continuum consistent with hot, optically thick ejecta. We compare our events with a previously suggested physical scenario involving shock breakout in an optically thick wind surrounding a core-collapse supernova (CCSNe), we conclude that current models for such a scenario might need an additional power source to describe the exponential decline. We find these transients tend to favor star-forming host galaxies, which could be consistent with a core-collapse origin. However, more detailed modeling of the light curves is necessary to determine their physical origin.

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arXiv2018

Dark Energy Survey Year 1 Results: Redshift distributions of the weak lensing source galaxies

We describe the derivation and validation of redshift distribution estimates and their uncertainties for the galaxies used as weak lensing sources in the Dark Energy Survey (DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (BPZ) code is used to assign galaxies to four redshift bins between z=0.2 and 1.3, and to produce initial estimates of the lensing-weighted redshift distributions $n^i_{PZ}(z)$ for bin i. Accurate determination of cosmological parameters depends critically on knowledge of $n^i$ but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts $n^i(z)=n^i_{PZ}(z-Δz^i)$ to correct the mean redshift of $n^i(z)$ for biases in $n^i_{\rm PZ}$. The $Δz^i$ are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the COSMOS field to BPZ estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the $Δz^i$ are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15<z<0.9. This paper details the BPZ and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the $n^i(z)$ beyond the choice of $Δz^i$. The clustering and COSMOS validation methods produce consistent estimates of $Δz^i$, with combined uncertainties of $σ_{Δz^i}=$0.015, 0.013, 0.011, and 0.022 in the four bins. We marginalize over these in all analyses to follow, which does not diminish the constraining power significantly. Repeating the photo-z procedure using the Directional Neighborhood Fitting (DNF) algorithm instead of BPZ, or using the $n^i(z)$ directly estimated from COSMOS, yields no discernible difference in cosmological inferences.

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arXiv2018

FRB microstructure revealed by the real-time detection of FRB170827

We report a new Fast Radio Burst (FRB) discovered in real-time as part of the UTMOST project at the Molonglo Observatory Synthesis Radio Telescope (MOST). FRB170827 is the first detected with our low-latency ($< 24$ s), machine-learning-based FRB detection system. The FRB discovery was accompanied by the capture of voltage data at the native time and frequency resolution of the observing system, enabling coherent dedispersion and detailed off-line analysis, which have unveiled fine temporal and frequency structure. The dispersion measure (DM) of 176.80 $\pm$ 0.04 pc cm$^{-3}$, is the lowest of the FRB population. The Milky Way contribution along the line of sight is $\sim$ 40 pc cm$^{-3}$, leaving an excess DM of $\sim$ 145 pc cm$^{-3}$. The FRB has a fluence $>$ 20 $\pm$ 7 Jy ms, and is narrow, with a width of $\sim$ 400 $μ$s at 10$\%$ of its maximum amplitude. However, the burst shows three temporal components, the narrowest of which is $\sim$ 30 $μ$s, and a scattering timescale of $4.1 \pm 2.7$ $μ$s. The FRB shows spectral modulations on frequency scales of 1.5 MHz and 0.1 MHz. Both are prominent in the dynamic spectrum, which shows a very bright region of emission between 841 and 843 MHz, and weaker, patchy emission across the entire band. We show the fine spectral structure could arise in the FRB host galaxy, or its immediate vicinity.

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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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arXiv2017

Follow up of GW170817 and its electromagnetic counterpart by Australian-led observing programs

The discovery of the first electromagnetic counterpart to a gravitational wave signal has generated follow-up observations by over 50 facilities world-wide, ushering in the new era of multi-messenger astronomy. In this paper, we present follow-up observations of the gravitational wave event GW170817 and its electromagnetic counterpart SSS17a/DLT17ck (IAU label AT2017gfo) by 14 Australian telescopes and partner observatories as part of Australian-based and Australian-led research programs. We report early- to late-time multi-wavelength observations, including optical imaging and spectroscopy, mid-infrared imaging, radio imaging, and searches for fast radio bursts. Our optical spectra reveal that the transient source afterglow cooled from approximately 6400K to 2100K over a 7-day period and produced no significant optical emission lines. The spectral profiles, cooling rate, and photometric light curves are consistent with the expected outburst and subsequent processes of a binary neutron star merger. Star formation in the host galaxy probably ceased at least a Gyr ago, although there is evidence for a galaxy merger. Binary pulsars with short (100 Myr) decay times are therefore unlikely progenitors, but pulsars like PSR B1534+12 with its 2.7 Gyr coalescence time could produce such a merger. The displacement (about 2.2 kpc) of the binary star system from the centre of the main galaxy is not unusual for stars in the host galaxy or stars originating in the merging galaxy, and therefore any constraints on the kick velocity imparted to the progenitor are poor.

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arXiv2017

How Many Kilonovae Can Be Found in Past, Present, and Future Survey Datasets?

The discovery of a kilonova (KN) associated with the Advanced LIGO (aLIGO)/Virgo event GW170817 opens up new avenues of multi-messenger astrophysics. Here, using realistic simulations, we provide estimates of the number of KNe that could be found in data from past, present and future surveys without a gravitational-wave trigger. For the simulation, we construct a spectral time-series model based on the DES-GW multi-band light-curve from the single known KN event, and we use an average of BNS rates from past studies of $10^3 \rm{Gpc}^{-3}/\rm{year}$, consistent with the $1$ event found so far. Examining past and current datasets from transient surveys, the number of KNe we expect to find for ASAS-SN, SDSS, PS1, SNLS, DES, and SMT is between 0 and $0.3$. We predict the number of detections per future survey to be: 8.3 from ATLAS, 10.6 from ZTF, 5.5/69 from LSST (the Deep Drilling / Wide Fast Deep), and 16.0 from WFIRST. The maximum redshift of KNe discovered for each survey is z = 0.8 for WFIRST, z = 0.25 for LSST and z = 0.04 for ZTF and ATLAS. For the LSST survey, we also provide contamination estimates from Type Ia and Core-collapse supernovae: after light-curve and template-matching requirements, we estimate a background of just 2 events. More broadly, we stress that future transient surveys should consider how to optimize their search strategies to improve their detection efficiency, and to consider similar analyses for GW follow-up programs.

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arXiv2017

Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-$z$ methods applied to the same source galaxy sample. We apply the method to three photo-$z$ codes run in our simulated data: Bayesian Photometric Redshift (BPZ), Directional Neighborhood Fitting (DNF), and Random Forest-based photo-$z$ (RF). We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering vs photo-$z$'s. The systematic uncertainty in the mean redshift bias of the source galaxy sample is $Δz \lesssim 0.02$, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.

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arXiv2017

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.

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arXiv2016

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.

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arXiv2015

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.

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arXiv2014

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↗