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D. Thomas

Publications and source records attributed to D. Thomas.

At least 91 records · Page 5Linked to original sources

Supernova Host Galaxies in the Dark Energy Survey: I. Deep Coadds, Photometry, and Stellar Masses

The five-year Dark Energy Survey supernova programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterising the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimised coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other 4 seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order $\sim 27$ in $g$-band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multi-band photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high mass hosts at high redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects.

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Stellar population properties of individual massive early-type galaxies at 1.4 < z < 2

We analyse publicly available, individual spectra of four, massive ($M>10^{11}M_{\odot}$) early-type galaxies with redshifts in the range 1.4 < z < 2 to determine their stellar content, extending our previous work up to z~2. The wide wavelength range of the VLT/X-Shooter spectroscopic data in the UV-Optical-NIR arms along with the availability of spectro-photometry allows us to explore different techniques to obtain the stellar population properties, namely through age/metallicity sensitive spectral indices, full spectral fitting and broad-band photometric fitting. Moreover, together with the widely used optical Lick indices we consider further indices in the UV rest-frame, and demonstrate that UV indices significantly help the accuracy of the resulting population parameters. We find galaxy ages ranging from 0.2 to 4 Gyr, where the oldest galaxy is found at the lowest redshift, with an excellent agreement between ages determined via indices, full spectral fitting or broad-band colours. These ages are in perfect agreement with ages of local galaxies at the same velocity dispersion when we assume pure passive evolution. Total metallicities derived from indices show some scatter (between less than half-solar to very high values, ([Z/H]~0.6]). We speculate on possible mechanisms explaining these values, but given the sample size and low S/N of the spectra no conclusion can be made. Indices in the UV-rest frame generally lead to similar conclusions as optical indices. For the oldest galaxy (4 Gyr) we show that its UV-indices can only be explained by stellar population models including a UV contribution from old stellar populations, suggesting that old, UV bright populations start to inhabit mature galaxies of a few Gyr of age. This is the highest redshift (z~1.4) detection of the UV-upturn up to date.

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Stellar mass as a galaxy cluster mass proxy: application to the Dark Energy Survey redMaPPer clusters

We introduce a galaxy cluster mass observable, $μ_\star$, based on the stellar masses of cluster members, and we present results for the Dark Energy Survey (DES) Year 1 observations. Stellar masses are computed using a Bayesian Model Averaging method, and are validated for DES data using simulations and COSMOS data. We show that $μ_\star$ works as a promising mass proxy by comparing our predictions to X-ray measurements. We measure the X-ray temperature-$μ_\star$ relation for a total of 150 clusters matched between the wide-field DES Year 1 redMaPPer catalogue, and Chandra and XMM archival observations, spanning the redshift range $0.1<z<0.7$. For a scaling relation which is linear in logarithmic space, we find a slope of $α= 0.488\pm0.043$ and a scatter in the X-ray temperature at fixed $μ_\star$ of $σ_{{\rm ln} T_X|μ_\star}=0.266^{+0.019}_{-0.020}$ for the joint sample. By using the halo mass scaling relations of the X-ray temperature from the Weighing the Giants program, we further derive the $μ_\star$-conditioned scatter in mass, finding $σ_{{\rm ln} M|μ_\star}=0.26^{+ 0.15}_{- 0.10}$. These results are competitive with well-established cluster mass proxies used for cosmological analyses, showing that $μ_\star$ can be used as a reliable and physically motivated mass proxy to derive cosmological constraints.

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Dark Energy Survey Year 3 results: cosmology with moments of weak lensing mass maps -- validation on simulations

We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The analysis is geared towards the third year (Y3) data from the Dark Energy Survey (DES), but the methodology can be applied to other weak lensing data sets. The second moment, or variances, of the convergence as a function of smoothing scale contains information similar to standard shear 2-point statistics. The third moment, or the skewness, contains additional non-Gaussian information. We present the formalism for obtaining the convergence maps from the measured shear and for obtaining the second and third moments of these maps given partial sky coverage. We estimate the covariance matrix from a large suite of numerical simulations. We test our pipeline through a simulated likelihood analyses varying 5 cosmological parameters and 10 nuisance parameters. Our forecast shows that the combination of second and third moments provides a 1.5 percent constraint on $S_8 \equiv σ_8 (Ω_{\rm m}/0.3)^{0.5}$ for DES Y3 data. This is 20 percent better than an analysis using a simulated DES Y3 shear 2-point statistics, owing to the non-Gaussian information captured by the inclusion of higher-order statistics. The methodology developed here can be applied to current and future weak lensing datasets to make use of information from non-Gaussianity in the cosmic density field and to improve constraints on cosmological parameters.

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Dark Energy Survey Year 1 results: The relationship between mass and light around cosmic voids

What are the mass and galaxy profiles of cosmic voids? In this paper we use two methods to extract voids in the Dark Energy Survey (DES) Year 1 redMaGiC galaxy sample to address this question. We use either 2D slices in projection, or the 3D distribution of galaxies based on photometric redshifts to identify voids. For the mass profile, we measure the tangential shear profiles of background galaxies to infer the excess surface mass density. The signal-to-noise ratio for our lensing measurement ranges between 10.7 and 14.0 for the two void samples. We infer their 3D density profiles by fitting models based on N-body simulations and find good agreement for void radii in the range 15-85 Mpc. Comparison with their galaxy profiles then allows us to test the relation between mass and light at the 10%-level, the most stringent test to date. We find very similar shapes for the two profiles, consistent with a linear relationship between mass and light both within and outside the void radius. We validate our analysis with the help of simulated mock catalogues and estimate the impact of photometric redshift uncertainties on the measurement. Our methodology can be used for cosmological applications, including tests of gravity with voids. This is especially promising when the lensing profiles are combined with spectroscopic measurements of void dynamics via redshift-space distortions.

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Observation and Confirmation of Nine Strong Lensing Systems in Dark Energy Survey Year 1 Data

We describe the observation and confirmation of \nbconfirmtext\ new strong gravitational lenses discovered in Year 1 data from the Dark Energy Survey (DES). We created candidate lists based on a) galaxy group and cluster samples and b) photometrically selected galaxy samples. We selected 46 candidates through visual inspection and then used the Gemini Multi-Object Spectrograph (GMOS) at the Gemini South telescope to acquire spectroscopic follow-up of 21 of these candidates. Through analysis of this spectroscopic follow-up data, we confirmed nine new lensing systems and rejected 2 candidates, but the analysis was inconclusive on 10 candidates. For each of the confirmed systems, we report measured spectroscopic properties, estimated \einsteinradiussub, and estimated enclosed masses. The sources that we targeted have an i-band surface brightness range of iSB ~ 22 - 24 mag arcsec^2 and a spectroscopic redshift range of zspec ~0.8 - 2.6. The lens galaxies have a photometric redshift range of zlens ~ 0.3 - 0.7. The lensing systems range in image-lens separation 2 - 9 arcsec and in enclosed mass 10^12 - 10^13 Msol.

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Dark Energy Survey Year 1 Results: Constraints on Intrinsic Alignments and their Colour Dependence from Galaxy Clustering and Weak Lensing

We perform a joint analysis of intrinsic alignments and cosmology using tomographic weak lensing, galaxy clustering and galaxy-galaxy lensing measurements from Year 1 (Y1) of the Dark Energy Survey. We define early- and late-type subsamples, which are found to pass a series of systematics tests, including for spurious photometric redshift error and point spread function correlations. We analyse these split data alongside the fiducial mixed Y1 sample using a range of intrinsic alignment models. In a fiducial Nonlinear Alignment Model (NLA) analysis, assuming a flat \lcdm~cosmology, we find a significant difference in intrinsic alignment amplitude, with early-type galaxies favouring $A_\mathrm{IA} = 2.38^{+0.32}_{-0.31}$ and late-type galaxies consistent with no intrinsic alignments at $0.05^{+0.10}_{-0.09}$. We find weak evidence of a diminishing alignment amplitude at higher redshifts in the early-type sample. The analysis is repeated using a number of extended model spaces, including a physically motivated model that includes both tidal torquing and tidal alignment mechanisms. In multiprobe likelihood chains in which cosmology, intrinsic alignments in both galaxy samples and all other relevant systematics are varied simultaneously, we find the tidal alignment and tidal torquing parts of the intrinsic alignment signal have amplitudes $A_1 = 2.66 ^{+0.67}_{-0.66}$, $A_2=-2.94^{+1.94}_{-1.83}$, respectively, for early-type galaxies and $A_1 = 0.62 ^{+0.41}_{-0.41}$, $A_2 = -2.26^{+1.30}_{-1.16}$ for late-type galaxies. In the full (mixed) Y1 sample the best constraints are $A_1 = 0.70 ^{+0.41}_{-0.38}$, $A_2 = -1.36 ^{+1.08}_{-1.41}$. For all galaxy splits and IA models considered, we report cosmological parameter constraints that are consistent with the results of Troxel et al. (2017) and Dark Energy Survey Collaboration (2017).

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Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogs from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multi-band deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalog created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of $σ_{Δz} = 0.007$, which is a 60% improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.

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Dark Energy Survey Year 1 Results: The effect of intracluster light on photometric redshifts for weak gravitational lensing

We study the effect of diffuse intracluster light on the critical surface mass density estimated from photometric redshifts of lensing source galaxies, and the resulting bias in a weak lensing measurement of galaxy cluster mass. Under conservative assumptions, we find the bias to be negligible for imaging surveys like the Dark Energy Survey (DES) with a recommended scale cut of >=200 kpc distance from cluster centers. For significantly deeper source catalogs from present and future surveys like the Large Synoptic Survey Telescope (LSST) program, more conservative scale and source magnitude cuts or a correction of the effect may be necessary to achieve per-cent level lensing measurement accuracy, especially at the massive end of the cluster population.

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Superluminous Supernovae from the Dark Energy Survey

We present a sample of 21 hydrogen-free superluminous supernovae (SLSNe-I), and one hydrogen-rich SLSN (SLSN-II) detected during the five-year Dark Energy Survey (DES). These SNe, located in the redshift range 0.220<z<1.998, represent the largest homogeneously-selected sample of SLSN events at high redshift. We present the observed g,r, i, z light curves for these SNe, which we interpolate using Gaussian Processes. The resulting light curves are analysed to determine the luminosity function of SLSN-I, and their evolutionary timescales. The DES SLSN-I sample significantly broadens the distribution of SLSN-I light curve properties when combined with existing samples from the literature. We fit a magnetar model to our SLSNe, and find that this model alone is unable to replicate the behaviour of many of the bolometric light curves. We search the DES SLSN-I light curves for the presence of initial peaks prior to the main light-curve peak. Using a shock breakout model, our Monte Carlo search finds that 3 of our 14 events with pre-max data display such initial peaks. However, 10 events show no evidence for such peaks, in some cases down to an absolute magnitude of <-16, suggesting that such features are not ubiquitous to all SLSN-I events. We also identify a red pre-peak feature within the light curve of one SLSN, which is comparable to that observed within SN2018bsz.

astro-ph.HE↗

Producing a BOSS-CMASS sample with DES imaging

We present a sample of galaxies with the Dark Energy Survey (DES) photometry that replicates the properties of the BOSS CMASS sample. The CMASS galaxy sample has been well characterized by the Sloan Digital Sky Survey (SDSS) collaboration and was used to obtain the most powerful redshift-space galaxy clustering measurements to date. A joint analysis of redshift-space distortions (such as those probed by CMASS from SDSS) and a galaxy-galaxy lensing measurement for an equivalent sample from DES can provide powerful cosmological constraints. Unfortunately, the DES and SDSS-BOSS footprints have only minimal overlap, primarily on the celestial equator near the SDSS Stripe 82 region. Using this overlap, we build a robust Bayesian model to select CMASS-like galaxies in the remainder of the DES footprint. The newly defined DES-CMASS (DMASS) sample consists of 117,293 effective galaxies covering $1,244 {\rm deg}^2$. Through various validation tests, we show that the DMASS sample selected by this model matches well with the BOSS CMASS sample, specifically in the South Galactic cap (SGC) region that includes Stripe 82. Combining measurements of the angular correlation function and the clustering-z distribution of DMASS, we constrain the difference in mean galaxy bias and mean redshift between the BOSS CMASS and DMASS samples to be $Δb = 0.010^{+0.045}_{-0.052}$ and $Δz = \left( 3.46^{+5.48}_{-5.55} \right) \times 10^{-3}$ for the SGC portion of CMASS, and $Δb = 0.044^{+0.044}_{-0.043} $ and $Δz= ( 3.51^{+4.93}_{-5.91}) \times 10^{-3}$ for the full CMASS sample. These values indicate that the mean bias of galaxies and mean redshift in the DMASS sample is consistent with both CMASS samples within $1σ$.

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Dark Energy Survey Year 1 Results: Calibration of Cluster Mis-centering in the redMaPPer Catalogs

The center determination of a galaxy cluster from an optical cluster finding algorithm can be offset from theoretical prescriptions or $N$-body definitions of its host halo center. These offsets impact the recovered cluster statistics, affecting both richness measurements and the weak lensing shear profile around the clusters. This paper models the centering performance of the \RM~cluster finding algorithm using archival X-ray observations of \RM-selected clusters. Assuming the X-ray emission peaks as the fiducial halo centers, and through analyzing their offsets to the \RM~centers, we find that $\sim 75\pm 8 \%$ of the \RM~clusters are well centered and the mis-centered offset follows a Gamma distribution in normalized, projected distance. These mis-centering offsets cause a systematic underestimation of cluster richness relative to the well-centered clusters, for which we propose a descriptive model. Our results enable the DES Y1 cluster cosmology analysis by characterizing the necessary corrections to both the weak lensing and richness abundance functions of the DES Y1 redMaPPer cluster catalog.

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First Cosmology Results Using Type Ia Supernovae From the Dark Energy Survey: Photometric Pipeline and Light Curve Data Release

We present griz light curves of 251 Type Ia Supernovae (SNe Ia) from the first 3 years of the Dark Energy Survey Supernova Program's (DES-SN) spectroscopically classified sample. The photometric pipeline described in this paper produces the calibrated fluxes and associated uncertainties used in the cosmological parameter analysis (Brout et al. 2018-SYS, DES Collaboration et al. 2018) by employing a scene modeling approach that simultaneously forward models a variable transient flux and temporally constant host galaxy. We inject artificial point sources onto DECam images to test the accuracy of our photometric method. Upon comparison of input and measured artificial supernova fluxes, we find flux biases peak at 3 mmag. We require corrections to our photometric uncertainties as a function of host galaxy surface brightness at the transient location, similar to that seen by the DES Difference Imaging Pipeline used to discover transients. The public release of the light curves can be found at https://des.ncsa.illinois.edu/releases/sn.

astro-ph.IM↗

Identification of RR Lyrae stars in multiband, sparsely-sampled data from the Dark Energy Survey using template fitting and Random Forest classification

Many studies have shown that RR Lyrae variable stars (RRL) are powerful stellar tracers of Galactic halo structure and satellite galaxies. The Dark Energy Survey (DES), with its deep and wide coverage (g ~ 23.5 mag) in a single exposure; over 5000 deg$^{2}$) provides a rich opportunity to search for substructures out to the edge of the Milky Way halo. However, the sparse and unevenly sampled multiband light curves from the DES wide-field survey (median 4 observations in each of grizY over the first three years) pose a challenge for traditional techniques used to detect RRL. We present an empirically motivated and computationally efficient template fitting method to identify these variable stars using three years of DES data. When tested on DES light curves of previously classified objects in SDSS stripe 82, our algorithm recovers 89% of RRL periods to within 1% of their true value with 85% purity and 76% completeness. Using this method, we identify 5783 RRL candidates, ~31% of which are previously undiscovered. This method will be useful for identifying RRL in other sparse multiband data sets.

astro-ph.SR↗

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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Dark Energy Survey Year 1 results: Detection of Intra-cluster Light at Redshift $\sim$ 0.25

Using data collected by the Dark Energy Survey (DES), we report the detection of intracluster light (ICL) with $\sim300$ galaxy clusters in the redshift range of 0.2-0.3. We design methods to mask detected galaxies and stars in the images and stack the cluster light profiles, while accounting for several systematic effects (sky subtraction, instrumental point-spread function, cluster selection effects and residual light in the ICL raw detection from background and cluster galaxies). The methods allow us to acquire high signal-to-noise measurements of the ICL and central galaxies (CGs), which we separate with radial cuts. The ICL appears as faint and diffuse light extending to at least 1 Mpc from the cluster center, reaching a surface brightness level of 30 mag arcsec$^{-2}$. The ICL and the cluster CG contribute to $44\%\pm17$\% of the total cluster stellar luminosity within 1 Mpc. The ICL color is overall consistent with that of the cluster red sequence galaxies, but displays the trend of becoming bluer with increasing radius. The ICL demonstrates an interesting self-similarity feature -- for clusters in different richness ranges, their ICL radial profiles are similar after scaling with cluster $R_\mathrm{200m}$, and the ICL brightness appears to be a good tracer of the cluster radial mass distribution. These analyses are based on the DES redMaPPer cluster sample identified in the first year of observations.

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A Search for Optical Emission from Binary-Black-Hole Merger GW170814 with the Dark Energy Camera

Binary black hole (BBH) mergers found by the LIGO and Virgo detectors are of immense scientific interest to the astrophysics community, but are considered unlikely to be sources of electromagnetic emission. To test whether they have rapidly fading optical counterparts, we used the Dark Energy Camera to perform an $i$-band search for the BBH merger GW170814, the first gravitational wave detected by three interferometers. The 87-deg$^2$ localization region (at 90\% confidence) centered in the Dark Energy Survey (DES) footprint enabled us to image 86\% of the probable sky area to a depth of $i\sim 23$ mag and provide the most comprehensive dataset to search for EM emission from BBH mergers. To identify candidates, we perform difference imaging with our search images and with templates from pre-existing DES images. The analysis strategy and selection requirements were designed to remove supernovae and to identify transients that decline in the first two epochs. We find two candidates, each of which is spatially coincident with a star or a high-redshift galaxy in the DES catalogs, and they are thus unlikely to be associated with GW170814. Our search finds no candidates associated with GW170814, disfavoring rapidly declining optical emission from BBH mergers brighter than $i\sim 23$ mag ($L_{\rm optical} \sim 5\times10^{41}$ erg/s) 1-2 days after coalescence. In terms of GW sky map coverage, this is the most complete search for optical counterparts to BBH mergers to date

astro-ph.HE↗

Mass Variance from Archival X-ray Properties of Dark Energy Survey Year-1 Galaxy Clusters

Using archival X-ray observations and a log-normal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behavior of X-ray temperatures, $T_X$, with optical richness, $λ_{RM}$, for clusters in the redshift range $0.2 50\%$ complete for clusters with $λ_{RM} > 130$. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, $σ_{\ln Tx | λ} = 0.275 \pm 0.019$. Joined with constraints for $T_X$ scaling with halo mass from the Weighing the Giants program and richness--temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, $σ_{\ln M | λ} = 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rm sys})}$, at an optical richness of approximately 70. Uncertainties in external parameters, particularly the slope and variance of the $T_X$--mass relation and the covariance of $T_X$ and $λ_{RM}$ at fixed mass, dominate the systematic error. The $95\%$ confidence region from joint sample analysis is relatively broad, $σ_{\ln M | λ} \in [0.14, \, 0.55]$, or a factor ten in variance.

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