arXiv subjects

C. Lidman

Publications and source records attributed to C. Lidman.

At least 163 records · Page 9Linked to original sources

arXiv2017

Galaxy Merger Candidates in High-Redshift Cluster Environments

We compile a sample of spectroscopically- and photometrically-selected cluster galaxies from four high-redshift galaxy clusters ($1.59 < z < 1.71$) from the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS), and a comparison field sample selected from the UKIDSS Deep Survey. Using near-infrared imaging from the \textit{Hubble Space Telescope} we classify potential mergers involving massive ($M_* \geq 3\times 10^{10}\mathrm{M}_\odot$) cluster members by eye, based on morphological properties such as tidal distortions, double nuclei, and projected near neighbors within 20 kpc. With a catalogue of 23 spectroscopic and 32 photometric massive cluster members across the four clusters and 65 spectroscopic and 26 photometric comparable field galaxies, we find that after taking into account contamination from interlopers, $11.0 ^{+7.0}_{-5.6}\%$ of the cluster members are involved in potential mergers, compared to $24.7^{+5.3}_{-4.6}\%$ of the field galaxies. We see no evidence of merger enhancement in the central cluster environment with respect to the field, suggesting that galaxy-galaxy merging is not a stronger source of galaxy evolution in cluster environments compared to the field at these redshifts.

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arXiv2017

Red but not dead : Unveiling the Star-forming Far-infrared Spectral Energy Distribution of SpARCS Brightest Cluster Galaxies at 0 < z < 1.8

We present the results of a Spitzer/Herschel infrared photometric analysis of the largest (716) and highest-redshift (z=1.8) sample of Brightest Cluster Galaxies (BCGs), those from the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS). Given the tension that exists between model predictions and recent observations of BCGs at z<2, we aim to uncover the dominant physical mechanism(s) guiding the stellar-mass buildup of this special class of galaxies, the most massive in the Universe uniquely residing at the centres of galaxy clusters. Through a comparison of their stacked, broadband, infrared spectral energy distributions (SEDs) to a variety of SED model templates in the literature, we identify the major sources of their infrared energy output, in multiple redshift bins between 0 < z < 1.8. We derive estimates of various BCG physical parameters from the stacked νLν SEDs, from which we infer a star-forming, as opposed to a 'red and dead' population of galaxies, producing tens to hundreds of solar masses per year down to z=0.5. This discovery challenges the accepted belief that BCGs should only passively evolve through a series of gas-poor, minor mergers since z~4 (De Lucia & Blaizot 2007), but agrees with the improved semi-analytic model of hierarchical structure formation of Tonini et al. (2012), which predicts star-forming BCGs throughout the epoch considered. We attribute the star formation inferred from the stacked infrared SEDs to both major and minor 'wet' (gas-rich) mergers, based on a lack of key signatures (to date) of the cluster cooling flows to which BCG star formation is typically attributed, as well as a number of observational and simulation-based studies that support this scenario.

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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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arXiv2016

A Study of Quasar Selection in the Dark Energy Survey Supernova fields

We present a study of quasar selection using the DES supernova fields. We used a quasar catalog from an overlapping portion of the SDSS Stripe 82 region to quantify the completeness and efficiency of selection methods involving color, probabilistic modeling, variability, and combinations of color/probabilistic modeling with variability. We only considered objects that appear as point sources in the DES images. We examine color selection methods based on the WISE mid-IR W1-W2 color, a mixture of WISE and DES colors (g-i and i-W1) and a mixture of VHS and DES colors (g-i and i-K). For probabilistic quasar selection, we used XDQSOz, an algorithm that employs an empirical multi-wavelength flux model of quasars to assign quasar probabilities. Our variability selection uses the multi-band chi2-probability that sources are constant in the DES Year 1 griz-band light curves. The completeness and efficiency are calculated relative to an underlying sample of point sources that are detected in the required selection bands and pass our data quality and photometric error cuts. We conduct our analyses at two magnitude limits, i<19.8 mag and i<22 mag. For sources with W1 and W2 detections, the W1-W2 color or XDQSOz method combined with variability gives the highest completenesses of >85% for both i-band magnitude limits and efficiencies of >80% to the bright limit and >60% to the faint limit; however, the giW1 and giW1+variability methods give the highest quasar surface densities. The XDQSOz method and combinations of W1W2/giW1/XDQSOz with variability are among the better selection methods when both high completeness and high efficiency are desired. We also present the OzDES Quasar Catalog of 1,263 spectroscopically-confirmed quasars taken by the OzDES survey. The catalog includes quasars with redshifts up to z~4 and brighter than i=22 mag, although the catalog is not complete up this magnitude limit.

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arXiv2016

The XXL survey XV: Evidence for dry merger driven BCG growth in XXL-100-GC X-ray clusters

The growth of brightest cluster galaxies is closely related to the properties of their host cluster. We present evidence for dry mergers as the dominant source of BCG mass growth at $z\lesssim1$ in the XXL 100 brightest cluster sample. We use the global red sequence, H$α$ emission and mean star formation history to show that BCGs in the sample possess star formation levels comparable to field ellipticals of similar stellar mass and redshift. XXL 100 brightest clusters are less massive on average than those in other X-ray selected samples such as LoCuSS or HIFLUGCS. Few clusters in the sample display high central gas concentration, rendering inefficient the growth of BCGs via star formation resulting from the accretion of cool gas. Using measures of the relaxation state of their host clusters, we show that BCGs grow as relaxation proceeds. We find that the BCG stellar mass corresponds to a relatively constant fraction 1\%\ of the total cluster mass in relaxed systems. We also show that, following a cluster scale merger event, the BCG stellar mass lags behind the expected value from the M$_{cluster}$ - M$_{BCG}$ relation but subsequently accretes stellar mass via dry mergers as the BCG and cluster evolve towards a relaxed state.

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arXiv2016

The redMaPPer Galaxy Cluster Catalog From DES Science Verification Data

We describe updates to the \redmapper{} algorithm, a photometric red-sequence cluster finder specifically designed for large photometric surveys. The updated algorithm is applied to $150\,\mathrm{deg}^2$ of Science Verification (SV) data from the Dark Energy Survey (DES), and to the Sloan Digital Sky Survey (SDSS) DR8 photometric data set. The DES SV catalog is locally volume limited, and contains 786 clusters with richness $λ>20$ (roughly equivalent to $M_{\rm{500c}}\gtrsim10^{14}\,h_{70}^{-1}\,M_{\odot}$) and $0.2<z<0.9$. The DR8 catalog consists of 26311 clusters with $0.08<z<0.6$, with a sharply increasing richness threshold as a function of redshift for $z\gtrsim 0.35$. The photometric redshift performance of both catalogs is shown to be excellent, with photometric redshift uncertainties controlled at the $σ_z/(1+z)\sim 0.01$ level for $z\lesssim0.7$, rising to $\sim0.02$ at $z\sim0.9$ in DES SV. We make use of \emph{Chandra} and \emph{XMM} X-ray and South Pole Telescope Sunyaev-Zeldovich data to show that the centering performance and mass--richness scatter are consistent with expectations based on prior runs of \redmapper{} on SDSS data. We also show how the \redmapper{} \photoz{} and richness estimates are relatively insensitive to imperfect star/galaxy separation and small-scale star masks.

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arXiv2016

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.

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arXiv2016

The XXL Survey: VI. The 1000 brightest X-ray point sources

X-ray extragalactic surveys are ideal laboratories for the study of the evolution and clustering of active galactic nuclei (AGN). The XXL Survey spans two fields of a combined 50 $deg^2$ observed for more than 6Ms with XMM-Newton, occupying the parameter space between deep surveys and very wide area surveys; at the same time it benefits from a wealth of ancillary data. This paper marks the first release of the XXL point source catalogue selected in the 2-10 keV energy band with limiting flux $F_{2-10keV}=4.8\cdot10^{-14}\rm{erg\,s^{-1}\,cm^{-2}}$. We use both public and proprietary data sets to identify the counterparts of the X-ray point-like sources and improved upon the photometric redshift determination for AGN by applying a Random Forest classification trained to identify for each object the optimal photometric redshift model library. We also assign a probability to each source to be a star or an outlier. We model with Bayesian analysis the X-ray spectra assuming a power-law model with the presence of an absorbing medium. We find an average unabsorbed photon index of $Γ=1.85$ and average hydrogen column density $\log{N_{H}}=21.07 cm^{-2}$. We find no trend of $Γ$ or $N_H$ with redshift and a fraction of 26% absorbed sources ($\log N_{H}>22$). We show that the XXL-1000-AGN number counts extended the number counts of the COSMOS survey to higher fluxes and are fully consistent with the Euclidean expectation. We constrain the intrinsic luminosity function of AGN in the 2-10 keV energy band where the unabsorbed X-ray flux is estimated from the X-ray spectral fit up to z=3. Finally, we demonstrate the presence of a supercluster size structure at redshift 0.14, identified by means of percolation analysis of the XXL-1000-AGN sample. The XXL survey, reaching a medium flux limit and covering a wide area is a stepping stone between current deep fields and planned wide area surveys.

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arXiv2016

The Accelerated Build-up of the Red Sequence in High Redshift Galaxy Clusters

We analyse the evolution of the red sequence in a sample of galaxy clusters at redshifts $0.8 11.5$) red sequence galaxies in the WINGS clusters, which do not include only the brightest cluster galaxies and which are not present in the HCS clusters, suggesting that they formed at epochs later than $z=0.8$. The comparison with the luminosity distribution of a sample of passive red sequence galaxies drawn from the COSMOS/UltraVISTA field in the photometric redshift range $0.8<z_{phot}<1.5$ shows that the red sequence in clusters is more developed at the faint end, suggesting that halo mass plays an important role in setting the time-scales for the build-up of the red sequence.

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arXiv2016

DES14X3taz: A Type I Superluminous Supernova Showing a Luminous, Rapidly Cooling Initial Pre-Peak Bump

We present DES14X3taz, a new hydrogen-poor super luminous supernova (SLSN-I) discovered by the Dark Energy Survey (DES) supernova program, with additional photometric data provided by the Survey Using DECam for Superluminous Supernovae (SUDSS). Spectra obtained using OSIRIS on the Gran Telescopio CANARIAS (GTC) show DES14X3taz is a SLSN-I at z=0.608. Multi-color photometry reveals a double-peaked light curve: a blue and relatively bright initial peak that fades rapidly prior to the slower rise of the main light curve. Our multi-color photometry allows us, for the first time, to show that the initial peak cools from 22,000K to 8,000K over 15 rest-frame days, and is faster and brighter than any published core-collapse supernova, reaching 30% of the bolometric luminosity of the main peak. No physical Nickel powered model can fit this initial peak. We show that a shock-cooling model followed by a magnetar driving the second phase of the light curve can adequately explain the entire light curve of DES14X3taz. Models involving the shock-cooling of extended circumstellar material at a distance of ~400 solar radii are preferred over the cooling of shock-heated surface layers of a stellar envelope. We compare DES14X3taz to the few double-peaked SLSN-I events in the literature. Although the rise-times and characteristics of these initial peaks differ, there exists the tantalizing possibility that they can be explained by one physical interpretation.

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arXiv2015

The XXL Survey X: K-band luminosity - weak-lensing mass relation for groups and clusters of galaxies

We present the K-band luminosity-halo mass relation, $L_{K,500}-M_{500,WL}$, for a subsample of 20 of the 100 brightest clusters in the XXL Survey observed with WIRCam at the Canada-France-Hawaii Telescope (CFHT). For the first time, we have measured this relation via weak-lensing analysis down to $M_{500,WL} =3.5 \times 10^{13}\,M_\odot$. This allows us to investigate whether the slope of the $L_K-M$ relation is different for groups and clusters, as seen in other works. The clusters in our sample span a wide range in mass, $M_{500,WL} =0.35-12.10 \times 10^{14}\,M_\odot$, at $0<z<0.6$. The K-band luminosity scales as $\log_{10}(L_{K,500}/10^{12}L_\odot) \propto βlog_{10}(M_{500,WL}/10^{14}M_\odot)$ with $β= 0.85^{+0.35}_{-0.27}$ and an intrinsic scatter of $σ_{lnL_K|M} =0.37^{+0.19}_{-0.17}$. Combining our sample with some clusters in the Local Cluster Substructure Survey (LoCuSS) present in the literature, we obtain a slope of $1.05^{+0.16}_{-0.14}$ and an intrinsic scatter of $0.14^{+0.09}_{-0.07}$. The flattening in the $L_K-M$ seen in previous works is not seen here and might be a result of a bias in the mass measurement due to assumptions on the dynamical state of the systems. We also study the richness-mass relation and find that group-sized halos have more galaxies per unit halo mass than massive clusters. However, the brightest cluster galaxy (BCG) in low-mass systems contributes a greater fraction to the total cluster light than BCGs do in massive clusters; the luminosity gap between the two brightest galaxies is more prominent for group-sized halos. This result is a natural outcome of the hierarchical growth of structures, where massive galaxies form and gain mass within low-mass groups and are ultimately accreted into more massive clusters to become either part of the BCG or one of the brighter galaxies. [Abridged]

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arXiv2015

The XXL survey XIV. AAOmega redshifts for the southern XXL field

We present a catalogue containing the redshifts of 3,660 X-ray selected targets in the XXL southern field. The redshifts were obtained with the AAOmega spectrograph and 2dF fibre positioner on the Anglo-Australian Telescope. The catalogue contains 1,515 broad line AGN, 528 stars, and redshifts for 41 out of the 49 brightest X-ray selected clusters in the XXL southern field.

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arXiv2015

The XXL Survey: I. Scientific motivations - XMM-Newton observing plan - Follow-up observations and simulation programme

We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms to date and involving an international consortium of roughly 100 members. The XXL Survey covers two extragalactic areas of 25 deg2 each at a point-source sensitivity of ~ 5E-15 erg/sec/cm2 in the [0.5-2] keV band (completeness limit). The survey's main goals are to provide constraints on the dark energy equation of state from the space-time distribution of clusters of galaxies and to serve as a pathfinder for future, wide-area X-ray missions. We review science objectives, including cluster studies, AGN evolution, and large-scale structure, that are being conducted with the support of approximately 30 follow-up programmes. We describe the 542 XMM observations along with the associated multi-lambda and numerical simulation programmes. We give a detailed account of the X-ray processing steps and describe innovative tools being developed for the cosmological analysis. The paper provides a thorough evaluation of the X-ray data, including quality controls, photon statistics, exposure and background maps, and sky coverage. Source catalogue construction and multi-lambda associations are briefly described. This material will be the basis for the calculation of the cluster and AGN selection functions, critical elements of the cosmological and science analyses. The XXL multi-lambda data set will have a unique lasting legacy value for cosmological and extragalactic studies and will serve as a calibration resource for future dark energy studies with clusters and other X-ray selected sources. With the present article, we release the XMM XXL photon and smoothed images along with the corresponding exposure maps. The XMM XXL observation list (Table B.1) is available in electronic form at the CDS. The present paper is the first in a series reporting results of the XXL-XMM survey.

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arXiv2015

The XXL Survey. II. The bright cluster sample: catalogue and luminosity function

Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. Aims. This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of $3\times 10^{-14}\,\mathrm{erg \,s^{-1}cm^{-2}}$ on the source flux within a 1$^{\prime}$ aperture. Methods. The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results. The bright cluster sample consists of systems with masses between $M_{500}=7\times 10^{13}$ and $3\times 10^{14} M_\odot$, mostly located between $z=0.1$ and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the predictions from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of $σ_8$ and/or $Ω_m$ appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to $z\sim1$. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters.

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arXiv2015

Simulations of the OzDES AGN Reverberation Mapping Project

As part of the OzDES spectroscopic survey we are carrying out a large scale reverberation mapping study of $\sim$500 quasars over five years in the 30 deg$^2$ area of the Dark Energy Survey (DES) supernova fields. These quasars have redshifts ranging up to 4 and have apparent AB magnitudes between $16.8<r<22.5$ mag. The aim of the survey is to measure time lags between fluctuations in the quasar continuum and broad emission line fluxes of individual objects in order to measure black hole masses for a broad range of AGN and constrain the radius-luminosity ($R-L$) relationship. Here we investigate the expected efficiency of the OzDES reverberation mapping campaign and its possible extensions. We expect to recover lags for $\sim$35-45\% of the quasars. AGN with shorter lags and greater variability are more likely to yield a lag, and objects with lags $\lesssim$6 months or $\sim$1 year are expected be recovered the most accurately. The baseline OzDES reverberation mapping campaign is predicted to produce an unbiased measurement of the $R-L$ relationship parameters for H$β$, Mg II $λ$2798, and C IV $λ$1549. However, extending the baseline survey by either increasing the spectroscopic cadence, extending the survey season, or improving the emission line flux measurement accuracy will significantly improve the $R-L$ parameter constraints for all broad emission lines.

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arXiv2015

Redshift distributions of galaxies in the DES Science Verification shear catalogue and implications for weak lensing

We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods -- ANNZ2, BPZ calibrated against BCC-Ufig simulations, SkyNet, and TPZ -- are analysed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-zs. From the galaxies in the DES SV shear catalogue, which have mean redshift $0.72\pm0.01$ over the range $0.3<z<1.3$, we construct three tomographic bins with means of $z=\{0.45, 0.67, 1.00\}$. These bins each have systematic uncertainties $δz \lesssim 0.05$ in the mean of the fiducial SkyNet photo-z $n(z)$. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of $σ_8$ of approx. 3%. This shift is within the one sigma statistical errors on $σ_8$ for the DES SV shear catalog. We further study the potential impact of systematic differences on the critical surface density, $Σ_{\mathrm{crit}}$, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of $n(z)$ of width $0.05$ for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis.

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arXiv2015

redMaGiC: Selecting Luminous Red Galaxies from the DES Science Verification Data

We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the color-cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photozs are very nearly as accurate as the best machine-learning based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalog sampling the redshift range $z\in[0.2,0.8]$. Our fiducial sample has a comoving space density of $10^{-3}\ (h^{-1} Mpc)^{-3}$, and a median photoz bias ($z_{spec}-z_{photo}$) and scatter $(σ_z/(1+z))$ of 0.005 and 0.017 respectively. The corresponding $5σ$ outlier fraction is 1.4%. We also test our algorithm with Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8) and Stripe 82 data, and discuss how spectroscopic training can be used to control photoz biases at the 0.1% level.

astro-ph.IM↗

arXiv2015

OzDES multi-fibre spectroscopy for the Dark Energy Survey: first-year operation and results

OzDES is a five-year, 100-night, spectroscopic survey on the Anglo-Australian Telescope, whose primary aim is to measure redshifts of approximately 2,500 Type Ia supernovae host galaxies over the redshift range 0.1 < z < 1.2, and derive reverberation-mapped black hole masses for approximately 500 active galactic nuclei and quasars over 0.3 < z < 4.5. This treasure trove of data forms a major part of the spectroscopic follow-up for the Dark Energy Survey for which we are also targeting cluster galaxies, radio galaxies, strong lenses, and unidentified transients, as well as measuring luminous red galaxies and emission line galaxies to help calibrate photometric redshifts. Here we present an overview of the OzDES program and our first-year results. Between Dec 2012 and Dec 2013, we observed over 10,000 objects and measured more than 6,000 redshifts. Our strategy of retargeting faint objects across many observing runs has allowed us to measure redshifts for galaxies as faint as m_r=25 mag. We outline our target selection and observing strategy, quantify the redshift success rate for different types of targets, and discuss the implications for our main science goals. Finally, we highlight a few interesting objects as examples of the fortuitous yet not totally unexpected discoveries that can come from such a large spectroscopic survey.

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