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the evolution of galaxy clustering is a prediction of hierarchical models of galaxy and structure formation ( e.g. , * ? ? ? * ; * ? ? ? * ; * ? ? ? hierarchical models for a concordance cosmology , @xmath11 , @xmath12 , and comoving coordinates . ] predict little or no evolution of the clustering of @xmath13 red galaxies at @xmath14 . precise measurements of galaxy clustering at @xmath4 can therefore test the predictions of these models . extremely red objects ( eros ; * ? ? ? * ; * ? ? ? * ; * ? ? ? * ; * ? ? ? * ) could be the progenitors of local ellipticals ( e.g. , * ? ? ? roughly 80% of @xmath15 eros have spectra with the absorption features of old stellar populations @xcite and @xmath16 of @xmath17 eros have early - type morphologies @xcite . some eros contain super - massive black holes , as @xmath18 of eros contain an obscured active galactic nucleus which can be detected by deep x - ray surveys @xcite . a direct test of the relationship between @xmath4 eros and the most massive local ellipticals is to compare the spatial clustering of the two populations . previous constraints on the spatial correlation function of eros , summarized in table  [ table : prev ] , are provided by pencil - beam surveys with @xmath19 areal coverage each . individual structures comprised of eros can have sizes comparable to the field of view of these surveys ( e.g. , * ? ? ? * ) , and small surveys do not sample representative volumes of the universe for highly clustered objects ( e.g. , * ? ? ? * ) . at @xmath4 , the transverse comoving distance spanned by previous ero studies is @xmath20 , which is much smaller than the size of individual structures observed in the present - day universe . spatial clustering measurements derived from the angular correlation function depend on ero redshift distribution models . previous angular clustering studies were unable to verify their model redshift distributions , as complete spectroscopic samples of eros were unavailable . previous ero spatial clustering measurements have large uncertainties and possibly large ( and sometimes unaccounted for ) systematic errors .    in this paper , we present a measurement of the clustering of eros using @xmath3 imaging of a @xmath2 subset of the noao deep wide - field survey ( ndwfs ) . the large area of our study provides a more representative volume than previous studies . the @xmath3 passbands of the ndwfs allow us to constrain the ero redshift distribution with photometric redshifts and their uncertainties . we also use photometric redshifts to select eros as a function of luminosity and redshift . we use ero spectroscopic redshifts to verify the accuracy of our photometric redshifts and we compare our estimate of the ero redshift distribution with spectroscopic redshift distributions from the literature .    the structure of the paper is as follows . in  [ sec : ndwfs ] we provide a brief description of the ndwfs imaging and catalogs from which the @xmath0 ero sample was selected . we discuss our estimates of ero photometric redshifts , and provide a comparison of ero photometric and spectroscopic redshifts in  [ sec : photoz ] . the selection of the ero sample and ero number counts are discussed in  [ sec : ero ] . in  [ sec : cor ] , we describe the techniques used to measure the angular and spatial correlation functions . the angular and spatial clustering of eros , as a function of apparent magnitude , apparent color , absolute magnitude , and redshift are discussed in  [ sec : clu ] . we discuss the implications of our results in  [ sec : dis ] and summarize the paper in  [ sec : sum ] . the ndwfs is a multiband ( @xmath21 ) survey of two @xmath22 high galactic latitude fields with the ctio @xmath23 , kpno @xmath24 , and kpno @xmath25 telescopes @xcite . a thorough description of the optical and @xmath26-band observing strategy and data reduction will be provided by jannuzi et al . and dey et al . ( both in preparation ) . this paper utilizes @xmath2 of @xmath3 data in the botes field . @xmath27 imaging and catalogs for the entire ndwfs botes field became available from the noao science archive on 22 october 2004 . @xmath26-band imaging and catalogs for approximately half of the botes field are also available from this archive . we generated object catalogs using sextractor @xmath28 @xcite , run in single - image mode in a similar manner to @xcite . at faint magnitudes , detections in the different bands were matched if the centroids were within @xmath29 of each other . at bright magnitudes , detections in the different bands were matched if the centroids were within an ellipse defined using the second order moments of the light distribution of the object , @xmath30 , and @xmath31 . ] . throughout this paper we use sextractor mag_auto magnitudes ( which are similar to kron total magnitudes ; * ? ? ? * ) , due to their small uncertainties and systematic errors at faint magnitudes . our clustering measurements are not particularly sensitive to how we measure ero photometry , and the clustering of eros selected with @xmath32 diameter aperture photometry is only marginally weaker than the clustering of eros selected with mag_auto photometry . we determined the completeness as a function of magnitude by adding artificial objects to copies of the data and recovering them with sextractor . to approximate @xmath4 galaxies , the artificial objects have an intrinsic profile with a full width at half maximum of @xmath33 , which was then convolved with a moffat profile model of the seeing . the @xmath34 completeness limits vary within the sample area in the ranges of @xmath35 , @xmath36 , @xmath37 and @xmath38 . regions surrounding saturated stars were removed from the catalog to exclude ( clustered ) spurious objects detected in the wings of the point spread function . we excluded regions where the root - mean - square of the sky noise in the @xmath26-band data was @xmath39 higher than the mean , as the depth of these regions is significantly less than the mean depth across the field . while it is plausible that smaller variations in the sky noise could alter the measured clustering of the faintest eros , our main conclusions remain unchanged if we exclude @xmath40 eros from the sample . we used sextractor s star - galaxy classifier to remove objects from the galaxy catalog which had a stellarity of @xmath41 in 2 or more bands brighter than @xmath42 , @xmath43 , and @xmath44 . at fainter magnitudes we do not use the star - galaxy classification and correct the angular correlation function for the estimated stellar contamination of the sample . we do not use the @xmath26-band for star - galaxy classification as there are image quality variations across the @xmath26-band image stacks . we estimated stellar contamination of the galaxy sample using the same technique as @xcite , where the stellar number counts were assumed to be a power - law and the distribution of stellar colors does not change with magnitude at @xmath45 . the contamination of the ero sample (  [ sec : ero ] ) by stars is estimated to be @xmath46 , and the conclusions of this paper remain unaltered unless stellar contamination is higher than @xmath47 . photometric redshifts were determined for all objects with @xmath48 and @xmath26-band detections . we provide a brief overview of the photometric redshifts here and refer the reader to our earlier study of @xmath49 red galaxy clustering in the ndwfs @xcite for a more detailed description of the photometric redshift code . to model galaxy spectral energy distributions ( seds ) , we used pegase2 evolutionary synthesis models @xcite with exponentially declining star formation rates ( @xmath50 models ) and @xmath51 ages of @xmath52 ( formation @xmath53 ) . the effect of @xmath54 dust reddening with @xmath55 , comparable to estimates for @xmath56 early - type galaxies @xcite , was included in the @xmath50 models . in @xcite , we used models with solar metallicity at @xmath51 , which resulted in small systematic underestimates of galaxy redshifts . simple solar metallicity @xmath50 models underestimate the uv luminosity of galaxies ( e.g. , * ? ? ? * ) , so in this work we let the metallicity of the models be a function of @xmath50 . this has the effect of slightly increasing the uv flux of the model seds . we verified the accuracy of the photometric redshifts at @xmath8 with 89 @xmath57 galaxies with rest - frame @xmath58 and spectroscopic redshifts . after decreasing the metallicity of the models , the photometric redshifts of these red galaxies did not have significant systematic errors . we note , however , that the uv flux in galaxies can also be increased by the presence of young stars or by altering the properties of the dust extinction ; our approach is merely a proxy for correcting any systematic effects in our photometric redshifts and is not meant to be interpreted as justifying sub - solar metallicities in the red galaxy population . we use these solar and sub - solar @xmath50 models throughout the remainder of the paper . color - tracks for 2 of the models are shown in figure  [ fig : colmod ] . for comparison , we also show two ultra - luminous infrared galaxy ( ulirg ) templates from @xcite , which have bluer @xmath59 colors than the @xmath50 models at @xmath4 . photometric redshifts were estimated by finding the minimum value of @xmath60 as a function of redshift , spectral type ( @xmath50 ) , and luminosity . for objects not detected in the @xmath61 or @xmath62-bands , we estimated the probability of a non - detection using the completeness estimates discussed in  [ sec : ndwfs ] . as the model seds do not account for the observed width of the galaxy locus , we increased the photometric uncertainties for the galaxies by @xmath63 magnitudes ( added in quadrature ) . to improve the accuracy of the photometric redshifts , the estimated redshift distribution of galaxies as a function of spectral type and apparent magnitude was introduced as a prior . the 2df galaxy redshift survey ( 2dfgrs ) luminosity functions for different spectral types @xcite , with spectral evolution given by the @xmath50-models , were used to estimate the redshift distributions . we tested the reliability of the photometric redshifts with simulated galaxies and real galaxies with spectroscopic redshifts . simulated galaxies were generated using the pegase2 @xmath50 models . the simulated data consisted of @xmath0 galaxies with @xmath64 in the redshift range @xmath65 and luminosity range @xmath66 . the simulated object photometry was scattered using the estimated uncertainties , thus mimicking what would be present in the real catalogs . we tested the accuracy of the photometric redshifts with a few spectroscopic redshifts and @xmath3 photometry for eros in the ndwfs botes field . a comparison of our photometric and spectroscopic redshifts for eros is shown in figure  [ fig : photoz ] . we discuss the selection criteria for the eros in  [ sec : ero ] . the simulated galaxies in the left panel of figure  [ fig : photoz ] have @xmath67 uncertainties of @xmath68 . for galaxies with seds similar to the pegase2 @xmath50 models , our procedure should yield accurate photometric redshifts . there are 4 ndwfs @xmath0 eros with spectroscopic redshifts . as shown in the right hand panel of figure  [ fig : photoz ] , real eros in the ndwfs exhibit a @xmath67 scatter of @xmath69 between the photometric and spectroscopic redshifts . there are more outliers than would be expected if the @xmath50 models reproduced the variety of ero seds . for comparison , goods obtains ero photometric redshifts with accuracies of @xmath70 @xcite , as they have photometry and upper limits in more bands ( @xmath71 ) . the accuracy of photometric redshifts is a complex function of redshift , sed and apparent magnitude . the accuracy of the ero photometric redshifts could not be extrapolated from @xmath8 red galaxy photometric redshifts , which can have uncertainties of @xmath72 ( e.g. , * ? ? ? the accuracy of ero photometric redshifts can not , and should not , be extrapolated from other samples of galaxies , such as samples selected by apparent magnitude only or from the hubble deep fields ( hdfs ) . though our ero photometric redshifts can only be considered approximations , they provide a good estimate of the ero redshift distribution ( see  [ sec : cor ] ) . we selected eros with the @xmath1 criterion ( e.g. , * ? ? ? * ; * ? ? ? * ; * ? ? ? * ) , though redder color cuts are sometimes used in the literature ( e.g. , * ? ? ? * ; * ? ? ? we have limited the sample to @xmath0 eros , to reduce the effects of completeness variations across the survey area on the measured clustering . as shown in figure  [ fig : colmag ] , the percentage of eros increases from @xmath73 of the total galaxy counts at @xmath74 to @xmath68 at @xmath75 . contamination of the ero sample by other galaxies could significantly alter the measured correlation function . at the magnitude limit of our sample , the uncertainty in the @xmath76 color is @xmath77 magnitudes . for the distribution of galaxy colors shown in figure  [ fig : colmag ] , and assuming gaussian photometric uncertainties , approximately 6% of the @xmath0 ero sample is contamination by @xmath78 galaxies . even if @xmath78 galaxies were completely ( and implausibly ) unclustered , the amplitude of the @xmath1 angular correlation function would only be decreased by 12% . contamination by @xmath79 galaxies could be as high as 22% in the @xmath0 ero sample . this would significantly alter our results if the clustering of galaxies is a very strong function of color at @xmath80 . however , as discussed in [ sec : color ] , we do not see evidence of this within our dataset . @xcite bias does increase the observed number of eros . if we assume the ero number counts in table  [ table : ang ] are a good approximation of the true ero number counts , then the contribution of malmquist bias to the ndwfs counts is @xmath81 . this would alter the measured clustering if ero angular clustering is an extremely strong function of apparent magnitude . we assume the bulk of our sample consists of galaxies with red stellar populations . the colors of dusty starbursts are predicted to differ significantly from galaxies with red stellar populations . as shown in figure  [ fig : colcol ] , 77% of the ndwfs ero sample has @xmath82 , which is redder than the @xcite non - evolving ulirg templates shown in figure  [ fig : colmod ] . our assumption that most @xmath0 eros have red stellar populations is also consistent with the conclusions of @xcite , who find 86% of @xmath83 eros have the absorption features of old stellar populations . the final sample consists of 671 objects , of which 318 are detected in the @xmath62-band and 635 are detected in the @xmath61-band . the @xmath84 eros have photometric redshifts in the range @xmath85 , with the median of the distribution at @xmath86 . only 5 of the 671 @xmath84 eros have photometric redshifts of @xmath87 . ero number counts as a function of @xmath26-band limiting magnitude are provided in table  [ table : ang ] and figure  [ fig : counts ] , along with results from previous surveys . we evaluated the uncertainties of the sky surface density , for the ndwfs and previous work , using the method discussed by @xcite , which includes the contribution of large - scale structure . the contribution of clustering to the uncertainties is typically several times larger than uncertainties determined by poisson statistics . for our @xmath84 ero sample , accounting for the clustering increases the @xmath67 uncertainty from 5% to 20% ! we note that the uncertainties quoted by some studies do not include this contribution ( e.g. , * ? ? ? * ; * ? ? ? * ; * ? ? ? the distribution of the ero sample on the plane of the sky is shown in figure  [ fig : dist ] . ero surveys of @xmath88 often have individual structures with sizes comparable to the field of view ( e.g. , * ? ? ? while clustering and voids are evident in figure  [ fig : dist ] , there are no obvious @xmath89 structures or gradients in the distribution of eros in our sample . we determined the angular correlation function using the @xcite estimator : @xmath90 where @xmath91 , @xmath92 , and @xmath93 are the number of galaxy - galaxy , galaxy - random and random - random pairs at angular separation @xmath94 . the pair counts were determined in logarithmically spaced bins between @xmath95 and @xmath96 . we employed the same methodology as @xcite to generate random object catalogs , correct for the integral constraint @xcite , and estimate the covariance of the @xmath97 bins ( using the technique of * ? ? ? * ) . the random object catalog contains 100 times the number of objects as the ero catalog , so @xmath92 and @xmath93 are renormalized accordingly . the angular correlation function was assumed to be a power - law given by @xmath98 where @xmath99 is a constant . this is a good approximation of the observed galaxy spatial correlation function from the 2dfgrs and sloan digital sky survey ( sdss ) on scales of @xmath100 @xcite . throughout this paper we assume @xmath101 , the approximate value of @xmath99 for @xmath102 red galaxies from the 2dfgrs and sdss surveys . for a @xmath101 power - law , the integral constraint for this study was approximately @xmath103 of the amplitude of the correlation function at @xmath104 . pair counts and the estimate of the angular correlation function ( including the integral constraint correction ) for @xmath105 and @xmath106 eros are presented in table  [ table : pairs ] . the spatial correlation function was obtained using the @xcite equation ; @xmath107 dz \left/ \left ( \int^\infty_0 \frac{dn}{dz } dz \right)^2 \right.\ ] ] where @xmath108 is the redshift distribution without clustering , @xmath109 is the spatial correlation function and @xmath110 is the comoving distance between two objects at redshifts @xmath111 and @xmath112 separated by angle @xmath113 on the sky . the spatial correlation function was assumed to be a power law given by @xmath114^{-\gamma}. \label{eq : spa}\ ] ] we estimated the redshift distribution for the sample by summing the redshift likelihood distributions of the individual galaxies in each subsample . model redshift distributions for subsamples selected by apparent magnitude and photometric redshift are shown in figure  [ fig : dndz ] . while the individual photometric redshifts are not especially accurate , they do include information provided by the observed ero photometry and are likely to provide a fair approximation of the ero redshift distribution . redshift distribution models which only reproduce the apparent ero number counts and local galaxy luminosity functions ( e.g. , * ? ? ? * ; * ? ? ? * ; * ? ? ? * ) have fewer constraints and may have larger systematic errors . the estimated median redshift of the @xmath0 eros is 1.18 , which is almost identical to the spectroscopic median redshift of 24 @xmath15 eros from @xcite . the median redshift is also similar to @xmath115 eros in the k20 spectroscopic sample ( * ? ? ? * a. cimatti 2003 , private communication ) . we measured the angular and spatial correlation functions for a series of apparent magnitude , apparent color , absolute magnitude , and redshift bins . a power - law of the form @xmath116 was fitted to the data with @xmath99 fixed to @xmath117 . much larger imaging surveys , including the completed ndwfs botes and cetus fields , will have sufficient area to accurately measure @xmath99 . when parameterizing the power - law fits , we use @xmath118 instead of @xmath119 as it depends less on the assumed value of @xmath99 . using @xmath120 instead of @xmath101 increases @xmath118 by @xmath121 and @xmath119 by @xmath122 . the best - fit values of @xmath123 do depend on the assumed value of @xmath99 , but for the ndwfs ero sample , changing @xmath99 from @xmath117 to @xmath124 increases @xmath123 by only @xmath121 . measurements of @xmath118 for eros as a function of @xmath26-band limiting magnitude from our study and the literature are summarized in table  [ table : ang ] . angular correlation functions for apparent magnitude limited samples are also plotted in figure  [ fig : ang ] . estimates of @xmath118 and @xmath123 for each of the ndwfs subsamples are presented in table  [ table : r0 ] and discussed in  [ sec : app ] to  [ sec : foz ] . the amplitude of the angular correlation function for a series of apparent magnitude limited samples is presented in figure  [ fig : omegak ] and table  [ table : ang ] , along with estimates from the literature . while our @xmath84 sample has a larger volume and more objects than previous studies , our uncertainties are comparable to the published uncertainties of many previous studies . this is due to our inclusion of the covariance when fitting a power - law to the data . our estimates of the amplitude of the angular correlation function are @xmath125 lower than the smaller @xmath126 ero samples from @xcite . within our sample we do not see a significant change in the angular clustering amplitude with apparent magnitude , but this is not unexpected as we span a small range of apparent magnitudes . the first section of table  [ table : r0 ] provides an estimate of @xmath123 for eros as a function of apparent limiting magnitude . while the ndwfs @xmath123 values are accurate to @xmath18 , each apparent magnitude bin spans a large range of redshift and absolute magnitude . as @xmath123 is correlated with luminosity in other galaxy samples ( e.g. , * ? ? ? * ; * ? ? ? * ; * ? ? ? * ; * ? ? ? * ) , a correlation between @xmath123 and apparent magnitude might be expected . we do not observe a significant correlation within the ndwfs , but our uncertainties are too large to rule out such a correlation .    combining published ero samples provides spatial clustering measurements over a broad magnitude range . however , it is not possible to directly compare the published @xmath123 measurements of different ero samples ( table  [ table : prev ] ) , as different authors use different models of the ero redshift distribution . different studies also estimate the uncertainties of the angular correlation function and @xmath123 using different techniques . in table [ table : pairs ] , we present the ndwfs pair counts for the @xmath105 and @xmath106 @xmath0 ero angular correlation functions , so other researchers can apply their techniques for estimating the correlation function to our data . poisson statistics underestimate the uncertainties of the correlation function on large - scales , where object pair counts are high and the uncertainties of the correlation function are dominated by large - scale structure . the uncertainties of clustering measurements from deep pencil - beam surveys should be larger than those of the ndwfs , and the large scatter of @xmath127 ero clustering measurements shown in figure  [ fig : omegak ] may reflect this . if we assume the published best - fit values of the amplitude of the angular correlation are correct , then the angular clustering of eros does decrease with increasing limiting magnitude . we find @xmath5 for @xmath0 eros while @xcite find @xmath128 for @xmath129 eros . unless the redshift distribution of faint eros is very broad , the spatial clustering of eros is decreasing with increasing apparent magnitude . several studies to measure @xmath130 for faint eros @xcite , but their model redshift distributions contain more high redshift objects than the goods @xmath131 ero photometric redshift distribution @xcite . if @xmath132 for faint eros and the goods photometric redshifts are accurate , then @xmath123 decreases from @xmath133 for @xmath0 to @xmath10 for @xmath134 eros . red galaxies at @xmath8 have a comparable range of @xmath123 values ( e.g. , * ? ? ? * ; * ? ? ? * ; * ? ? ? * ) and their spatial clustering is correlated with absolute magnitude . the current measurements of ero clustering are consistent with eros being the progenitors of local red galaxies . we present the clustering of @xmath105 and @xmath106 eros in figure  [ fig : omegak ] and table  [ table : r0 ] . we find the angular and spatial clustering of @xmath106 galaxies does not differ significantly from the remainder of the sample . low redshift galaxies may have a bimodal distribution of clustering properties as a function of color @xcite . this could be due to the bimodal distribution of galaxy colors at low redshift , or a bimodality of the clustering properties of galaxies as a function of star formation rate . if the clustering is bimodal at all redshifts , we would not expect a correlation between clustering and color within a red galaxy sample . we do not see a correlation of clustering with color but a larger sample with improved photometric redshifts is required so accurate spatial clustering measurements can be performed as a function of rest - frame color . the clustering of eros as a function of absolute magnitude is presented in table  [ table : r0 ] . we have determined the absolute magnitudes ( without evolution corrections ) of the eros using the best - fit @xmath50-model sed . as shown in figure  [ fig : photoz ] , ero photometric redshifts can have large uncertainties and our ero absolute magnitudes are , at best , approximations . the two absolute magnitude bins are approximately volume limited samples with the same photometric redshift range . both absolute magnitude bins are extremely luminous , and contain eros approximately 4 times brighter than the local value of @xmath135 ( @xmath136 ; * ? ? ? we do not see a significant correlation between luminosity and @xmath123 within the sample . the correlation between galaxy luminosity and clustering is only seen unambiguously in @xmath8 samples ( e.g. , 2dfgrs and sdss ) which contain a factor of @xmath137 more galaxies than the ndwfs ero sample . a strong correlation between ero luminosity and spatial clustering remains plausible , and may be detected with an analysis of the complete ndwfs . we measured the clustering of eros within the sample with two photometric redshift bins , @xmath138 and @xmath139 . we exclude eros beyond these redshift ranges , as they contribute less than @xmath140 of the total @xmath0 ero number counts . the results are presented in table  [ table : r0 ] and figure  [ fig : r0z ] . we do not observe significant evolution of @xmath123 with redshift within the ero sample . however , our uncertainties are large and the redshift distributions of the two samples overlap , so they are not entirely independent . the clustering of @xmath141 , @xmath0 eros is well approximated by a power law with @xmath142 and @xmath99 fixed at @xmath117 . as eros are thought to be the progenitors of local ellipticals , it is useful to compare the clustering measurements of these populations . in the 2dfgrs , the spatial correlation function increases from @xmath143 for @xmath144 red galaxies to @xmath145 for @xmath146 red galaxies @xcite . other @xmath8 surveys , including the ndwfs , measure comparable spatial clustering for red galaxies ( e.g. , * ? ? ? * ; * ? ? ? * ; * ? ? ? it is not unreasonable to assume the brightest eros are the progenitors of the @xmath146 red galaxies in the local universe , as the comoving spatial clustering of the two populations is comparable . however , this assumes models predicting little or no evolution of the @xmath13 galaxy correlation function ( e.g. , * ? ? ? * ; * ? ? ? * ) are valid .    if @xmath0 eros are the progenitors of the most luminous local red galaxies , fainter eros could the progenitors of @xmath147 red galaxies . several previous studies of fainter eros find they are very strongly clustered , with @xmath148 @xcite . this is much stronger than the clustering of local @xmath135 red galaxies , where @xmath149 @xcite . however , the ero spatial clustering measurements could be subject to large , and possibly systematic , errors . several of these measurements use model redshift distributions which are primarily constrained by the local galaxy luminosity function and faint galaxy number counts @xcite . other model redshift distributions use unverified photometric redshifts @xcite or redshifts which could only be verified with galaxies other than eros @xcite . as shown in figure  [ fig : omegak ] , the angular clustering of eros does decrease with increasing apparent magnitude . unless the redshift distribution of @xmath9 eros is very broad , the spatial clustering of @xmath9 eros is weaker than the spatial clustering of @xmath150 eros . while @xmath0 eros may be the progenitors of most luminous local ellipticals , our spatial clustering measurement should be treated with some caution . our ero sample spans broad ranges of redshift and absolute magnitude ( @xmath151 ) . the luminosity and density evolution of eros and red galaxies at @xmath8 has not been accurately determined . the pegase @xmath50 models predict @xmath152 magnitudes of luminosity evolution at @xmath8 , so eros would be the progenitors to @xmath144 red galaxies . if this were the case , the spatial correlation function would be decreasing with decreasing redshift , which is unphysical . the uncertain luminosity and density evolution of eros limits the use of @xmath153 eros to measure the evolution of the galaxy spatial correlation function . current ero spatial clustering measurements , including our study , have large uncertainties and may be subject to systematic errors . we will significantly reduce the random uncertainties of ero clustering measurements when we analyze the entire ndwfs botes field . the uncertainties and systematic errors of our photometric redshifts will be accurately determined as we obtain more spectroscopic redshifts . we will also improve the photometric redshifts for eros by using ndwfs , flamingos @xcite , and _ space telescope data . we will then be able to accurately measure the spatial clustering of eros as a function of luminosity , color , and redshift . we have measured the clustering of 671 @xmath0 eros with @xmath2 subset of the ndwfs . this study covers an area nearly 5 times larger and has twice the sample size of any previous ero clustering study . the angular clustering of @xmath0 , @xmath105 eros is well described by a power - law with @xmath5 and @xmath101 . using a model of the ero redshift distribution derived from photometric redshifts , we find the spatial clustering of @xmath0 eros is given by @xmath154 comoving . within our study , we detect no significant correlations between ero clustering and apparent magnitude , apparent color , absolute magnitude , or redshift . however , our uncertainties are large and such correlations may exist . when combined with data from other studies , there is evidence of the angular clustering of eros decreasing with increasing apparent magnitude . unless the redshift distribution of @xmath9 eros is very broad , the spatial clustering of eros decreases with increasing apparent magnitude . as the uncertainties and systematic errors of current ero spatial clustering measurements are large , they do not yet provide strong tests of models of structure evolution and galaxy formation . this research was supported by the national optical astronomy observatory which is operated by the association of universities for research in astronomy ( aura ) , inc . under a cooperative agreement with the national science foundation . we thank our colleagues on the ndwfs team and the kpno and ctio observing support staff . we are grateful to frank valdes , lindsey davis and the iraf team for the packages used to reduce the imaging data . we thank alyson ford , chris greer , heather gross , lissa miller , and erin ryan , for helping reduce kpno mosaic-1 and onis imaging data used for our work . while working on this paper , the authors had many useful discussions about galaxy clustering with tod lauer and daniel eisenstein . jannuzi , b. t. , & dey , a. , 1999 , in asp conf . 191 , photometric redshifts and high redshift galaxies , ed . r. j. weymann , l. j. storrie - lombardi , m. sawicki , & r. j. brunner ( san francisco : asp ) , 111                                                ccccccccccc ndwfs & 3529 & 671 & @xmath156 & @xmath1 & & @xmath157 & photz & @xmath158 & 1.87 +   + k20 & 52 & 18 & @xmath159 & @xmath1 & dusty sf sed & @xmath160 & spectra & @xmath161 & 1.8 + k20 & 52 & 15 & @xmath159 & @xmath1 & old stellar sed & @xmath162 & spectra & 5.5 to 16 & 1.8 + ntt - wht & 701 & 400 & @xmath159 & @xmath1 & & @xmath163 & pe & @xmath164 & 1.8 + lcirs & 744 & 337 & @xmath165 & @xmath166 & & @xmath167 & photz & @xmath168 & 1.8 + lcirs & 407 & 312 & @xmath169 & @xmath166 & & @xmath167 & photz & @xmath170 & 1.8 + subaru & 114 & 134 & @xmath171 & @xmath172 & dusty sf sed & @xmath173 & photz & @xmath174 & 1.8 + subaru & 114 & 143 & @xmath171 & @xmath172 & old stellar sed & @xmath173 & photz & @xmath175 & 1.8 + elais n2 & 81.5 & 158 & @xmath176 & @xmath1 & & @xmath177 & m - de & @xmath178 & 1.8 + elais n2 & 81.5 & 158 & @xmath176 & @xmath1 & & @xmath177 & ne & @xmath179 & 1.8 + cdf - s & 50.4 & 198 & @xmath180 & @xmath181 & & @xmath177 & m - de & @xmath182 & 1.8 + hdf - s & 4 & 18 & @xmath183 & @xmath184 & & & photz & @xmath185 & 1.8 + hdf - s & 4 & 39 & @xmath183 & @xmath186 & & & photz & @xmath187 & 1.8 + hdf - s & 4 & 23 & @xmath183 & @xmath186 & @xmath188 & @xmath163 & photz & @xmath189 & 1.8 +    cccccccc ndwfs & 3529 & 256 & @xmath190 & @xmath191 & @xmath105 & @xmath192 & 1.87 + ndwfs & 3529 & 421 & @xmath193 & @xmath194 & @xmath105 & @xmath195 & 1.87 + ndwfs & 3529 & 671 & @xmath196 & @xmath0 & @xmath105 & @xmath197 & 1.87 + ntt - wht & 701 & 58 & @xmath198 & @xmath199 & @xmath200 & @xmath201 & 1.8 + ntt - wht & 701 & 106 & @xmath202 & @xmath203 & @xmath200 & @xmath204 & 1.8 + ntt - wht & 701 & 158 & @xmath205 & @xmath206 & @xmath200 & @xmath207 & 1.8 + ntt - wht & 701 & 279 & @xmath208 & @xmath209 & @xmath200 & @xmath210 & 1.8 + lcirs & 744 & 337 & @xmath211 & @xmath212 & @xmath213 & @xmath214 & 1.8 + lcirs & 744 & 201 & @xmath215 & @xmath212 & @xmath216 & @xmath217 & 1.8 + ntt - wht & 447.5 & 281 & @xmath218 & @xmath219 & @xmath200 & @xmath220 & 1.8 + subaru & 114 & 111 & @xmath221 & @xmath222 & @xmath200 & @xmath223 & 1.8 + lcirs & 407 & 312 & @xmath224 & @xmath225 & @xmath213 & @xmath226 & 1.8 + lcirs & 407 & 170 & @xmath227 & @xmath225 & @xmath216 & @xmath228 & 1.8 + elais n2 & 81.5 & 73 & @xmath229 & @xmath230 & @xmath105 & @xmath231 & 1.8 + elais n2 & 81.5 & 93 & @xmath232 & @xmath233 & @xmath105 & @xmath234 & 1.8 + elais n2 & 81.5 & 112 & @xmath235 & @xmath236 & @xmath105 & @xmath237 & 1.8 + elais n2 & 38.7 & 63 & @xmath238 & @xmath239 & @xmath105 & @xmath240 & 1.8 + cdf - s & 50.4 & 137 & @xmath241 & @xmath242 & @xmath181 & @xmath243 & 1.8 + cdf - s & 50.4 & 179 & @xmath244 & @xmath245 & @xmath181 & @xmath246 & 1.8 + cdf - s & 50.4 & 198 & @xmath247 & @xmath248 & @xmath181 & @xmath249 & 1.8 + hdf - s & 4 & 18 & @xmath250 & @xmath251 & @xmath184 & @xmath252 & 1.8 +    cccccc @xmath105 & @xmath253 to @xmath254 & @xmath255 & 88 & 5515 & 558532 + @xmath105 & @xmath254 to @xmath256 & @xmath257 & 424 & 33602 & 3346550 + @xmath105 & @xmath256 to @xmath258 & @xmath259 & 2274 & 192715 & 19207198 + @xmath105 & @xmath258 to @xmath260 & @xmath261 & 12084 & 1115798 & 107760586 + @xmath105 & @xmath260 to @xmath262 & @xmath263 & 60806 & 5811770 & 555035500 + @xmath105 & @xmath262 to @xmath264 & @xmath265 & 244670 & 23592613 & 2273794800 +   + @xmath106 & @xmath253 to @xmath254 & @xmath266 & 20 & 1193 & 122608 + @xmath106 & @xmath254 to @xmath256 & @xmath267 & 80 & 7502 & 733626 + @xmath106 & @xmath256 to @xmath258 & @xmath268 & 510 & 41951 & 4199066 + @xmath106 & @xmath258 to @xmath260 & @xmath269 & 2546 & 242766 & 23547906 + @xmath106 & @xmath260 to @xmath262 & @xmath270 & 13240 & 1269134 & 121503332 + @xmath106 & @xmath262 to @xmath264 & @xmath271 & 53148 & 5137427 & 497077474 +   +    cccccccc @xmath105 & 0.80 - 3.00 & @xmath272 & @xmath273 & 256 & @xmath274 & 1.17 & @xmath275 + @xmath105 & 0.80 - 3.00 & @xmath276 & @xmath277 & 421 & @xmath278 & 1.17 & @xmath279 + @xmath105 & 0.80 - 3.00 & @xmath280 & @xmath281 & 671 & @xmath282 & 1.18 & @xmath283 + @xmath106 & 0.80 - 3.00 & @xmath284 & @xmath273 & 96 & @xmath285 & 1.22 & @xmath286 + @xmath106 & 0.80 - 3.00 & @xmath287 & @xmath277 & 180 & @xmath288 & 1.22 & @xmath289 + @xmath106 & 0.80 - 3.00 & @xmath290 & @xmath281 & 314 & @xmath291 & 1.24 & @xmath292 + @xmath105 & 0.80 - 1.25 & @xmath293 & @xmath294 & 108 & @xmath295 & 1.16 & @xmath296 + @xmath105 & 0.80 - 1.25 & @xmath297 & @xmath298 & 208 & @xmath299 & 1.11 & @xmath300 + @xmath105 & 0.80 - 1.15 & @xmath301 & @xmath302 & 318 & @xmath303 & 1.04 & @xmath304 + @xmath105 & 1.15 - 1.40 & @xmath305 & @xmath306 & 292 & @xmath307 & 1.28 & @xmath308 + @xmath105 & 0.80 - 1.40 & @xmath309 & @xmath306 & 610 & @xmath310 & 1.15 & @xmath311 +
we have measured the angular and spatial clustering of 671 @xmath0 , @xmath1 extremely red objects ( eros ) from a @xmath2 sub - region of the noao deep wide - field survey ( ndwfs ) . 
 our study covers nearly 5 times the area and has twice the sample size of any previous ero clustering study . 
 the wide field of view and @xmath3 passbands of the ndwfs allow us to place improved constraints on the clustering of @xmath4 eros . 
 we find the angular clustering of eros is slightly weaker than in previous measurements , and @xmath5 for @xmath0 eros . 
 we find no significant correlation of ero spatial clustering with redshift , apparent color or absolute magnitude , although given the uncertainties , such correlations remain plausible . 
 we find the spatial clustering of @xmath0 , @xmath1 eros is well approximated by a power - law , with @xmath6 in comoving coordinates . 
 this is comparable to the clustering of @xmath7 early - type galaxies at @xmath8 , and is consistent with the brightest eros being the progenitors of the most massive ellipticals . 
 there is evidence of the angular clustering of eros decreasing with increasing apparent magnitude , when ndwfs measurements of ero clustering are combined with those from the literature . 
 unless the redshift distribution of @xmath9 eros is very broad , the spatial clustering of eros decreases from @xmath6 for @xmath0 to @xmath10 for @xmath9 eros .