ACCEPTED BY THE ASTROPHYSICAL JOURNAL SUPPLEMENTPreprint typeset using LATEX style emulateapj v. 08/22/09

THE 22-MONTH Swift-BAT ALL-SKY HARD X-RAY SURVEY

J. TUELLER1 , W. H. BAUMGARTNER1,2,12,18 , C. B. MARKWARDT1,3,12 , G. K. SKINNER1,3,12 , R. F. MUSHOTZKY1 , M. AJELLO4 ,S. BARTHELMY1 , A. BEARDMORE5 , W. N. BRANDT7 , D. BURROWS7 , G. CHINCARINI8 , S. CAMPANA8 , J. CUMMINGS1 ,G. CUSUMANO10 , P. EVANS5 , E. FENIMORE11 , N. GEHRELS1 , O. GODET5 , D. GRUPE7 , S. HOLLAND1,12 , J. KENNEA7 ,

H. A. KRIMM1,12 , M. KOSS3,1,12 , A. MORETTI8 , K. MUKAI1,2,12 , J. P. OSBORNE5 , T. OKAJIMA1,13 , C. PAGANI7 , K. PAGE5 ,D. PALMER11 , A. PARSONS1 , D. P. SCHNEIDER7 , T. SAKAMOTO1,14 , R. SAMBRUNA1 , G. SATO17 , M. STAMATIKOS1,14 , M. STROH7 ,

T.N. UKWATTA1,15 , L. WINTER16

Draft version September 17, 2009

ABSTRACTWe present the catalog of sources detected in the first 22 months of data from the hard X-ray survey (14–

195 keV) conducted with the BAT coded mask imager on the Swift satellite. The catalog contains 461 sourcesdetected above the 4.8σ level with BAT. High angular resolution X-ray data for every source from Swift XRT orarchival data have allowed associations to be made with known counterparts in other wavelength bands for over97% of the detections, including the discovery of ∼ 30 galaxies previously unknown as AGN and several newGalactic sources. A total of 266 of the sources are associated with Seyfert galaxies (median redshift z∼ 0.03) orblazars, with the majority of the remaining sources associated with X-ray binaries in our Galaxy. This ongoingsurvey is the first uniform all sky hard X-ray survey since HEAO-1 in 1977.

Since the publication of the 9-month BAT survey we have increased the number of energy channels from 4to 8 and have substantially increased the number of sources with accurate average spectra. The BAT 22-monthcatalog is the product of the most sensitive all-sky survey in the hard X-ray band, with a detection sensitivity(4.8σ) of 2.2×10−11 erg cm−2 s−1 (1 mCrab) over most of the sky in the 14–195 keV band.Subject headings: Catalogs — Survey: X-rays

1. INTRODUCTIONSurveys of the whole sky which are complete to a well-

defined threshold not only provide a basis for statistical pop-ulation studies but are also a vehicle for the discovery of newphenomena. Compared with lower X-ray energies, where var-ious missions from Uhuru (Forman et al. 1978) to ROSAThave systematically surveyed the sky and where slew surveys

1 NASA/Goddard Space Flight Center, Astrophysics Science Division,Greenbelt, MD 20771

2 Joint Center for Astrophysics, University of Maryland Baltimore County,Baltimore, MD 21250

3 Department of Astronomy, University of Maryland College Park, Col-lege Park, MD 20742

4 SLAC National Laboratory and Kavli Institute for Particle Astrophysicsand Cosmology, 2575 Sand Hill Road, Menlo Park, CA 94025

5 X-Ray and Observational Astronomy Group/ Department of Physics andAstronomy, University of Leicester, Leicester, LE1 7RH, United Kingdom

7 Department of Astronomy & Astrophysics, The Pennsylvania State Uni-versity, 525 Davey Lab, University Park, PA 16802

8 Osservatorio Astronomico di Brera(OAB)/ Istituto Nazionale di As-trofisica (INAF), 20121 Milano, Italy

9 ASDC/ ESA of ESRIN, Via Galileo Galilei, 00044 Frascati (RM), Italy10 IASF-Palermo/ Istituto di Astrofisica Spaziale e Fisica Cosmica di

Palermo/ Istituto Nazionale di Astrofisica (INAF), 90146 Palermo, Italy11 LANL/Los Alamos National Laboratory, Los Alamos, NM 8754512 CRESST/ Center for Research and Exploration in Space Science and

Technology, 10211 Wincopin Circle, Suite 500, Columbia, MD 2104413 Department of Physics & Astronomy, The Johns Hopkins University,

3400 North Charles Street Baltimore, Maryland 2121814 Oak Ridge Associated Universities (ORAU), OAB-44, P.O. Box 117

Oak Ridge, TN 3783115 Department of Physics/ The George Washington University (GWU),

2121 I Street, N.W., Washington, DC 2005216 Center for Astrophysics and Space Astronomy, University of Colorado,

389 UCB, Boulder, CO 8030917 Institute of Space and Astronautical Science, JAXA, Kanagawa 229-

8510, Japan18 Corresponding author: Wayne.Baumgartner@nasa.gov

of later missions have added detail, our knowledge of the skyat hard X-rays (> 10 keV) has been rather patchy and insen-sitive. The sensitivity of the HEAO-A4 13–180 keV survey(Levine et al. 1984) was such that only 77 sources were de-tected.

Recently INTEGRAL-IBIS has provided some observa-tions (Bird et al. 2007; Beckmann et al. 2006, 2009; Krivonoset al. 2007) that are much more sensitive but have concen-trated on certain regions of the sky; the exposure in the latestIBIS ‘all-sky’ catalog varies from one part of the sky to an-other by a factor of a thousand, some regions of the sky hav-ing only a few thousand seconds of observation. The RXTEall-sky slew survey (Revnivtsev et al. 2004) covers much ofthe sky in the 3-20 keV band and detects 294 sources, butthe coverage is not uniform or complete and the sensitivityis weighted to lower energies such that the BAT and RXTEsources are not the same.

A survey in the hard X-ray band is important for severalreasons. Observations below 15 keV can be drastically af-fected by photoelectric absorption in certain sources, givinga false indication of their luminosity. Populations of heav-ily absorbed or Compton-thick Active Galactic Nuclei (AGN)have been hypothesized in order to explain the portion of thespectrum of the diffuse hard X-ray background ascribed tounresolved sources (Gilli et al. 2007), but such objects havenot been found in the necessary numbers, prompting ques-tions as to the composition and evolution of a population ofAGN that could explain its form (Treister et al. 2009). HardX-ray emission is also being discovered from an unexpect-edly large number of previously unknown Galactic sources,notably from certain cataclysmic variables, symbiotic starsand heavily obscured high mass X-ray binaries (Bird et al.2007).

The Burst Alert Telescope (BAT) on Swift (Gehrels et al.

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2004) has a large field of view and is pointed at a large num-ber of different directions which are well distributed over thesky. The resultant survey provides the most uniform hard X-ray survey to date and achieves a sensitivity sufficient to detectvery large numbers of sources, both Galactic and extragalac-tic. Markwardt et al. (2005) have published the results fromthe first three months of BAT data, and Tueller et al. (2008)have published a survey of sources seen in the first 9 monthsof Swift observations, concentrating on the 103 AGN seen atGalactic latitudes greater than 15. We present here a catalogof all sources detected in the first 22 months of operations,(2005 Dec 15 – 2006 Oct 27) increasing the number of AGNto 266 and including all other sources seen across the entiresky.

2. Swift-BATSwift is primarily a mission for the study of gamma-ray

bursts. Swift combines a wide field instrument, BAT, to de-tect and locate gamma-ray bursts (GRBs) with two narrowfield instruments to study the afterglows (the X-ray Telescope(XRT) (Burrows et al. 2005) and the Ultra-Violet/OpticalTelescope (UVOT) (Roming et al. 2005)). Swift-BAT is awide field (∼2 sr) coded aperture instrument with the largestCdZnTe detector array ever fabricated (5243 cm2 consistingof 32,768 4mm detectors on a 4.2mm pitch) (Barthelmy et al.2005). BAT uses a mask constructed of 52,000 5x5x1 mmlead tiles distributed in a half-filled random pattern andmounted in a plane 1m above the detector array.

This configuration results in a large field of view and apoint-spread-function (PSF) that varies between 22′ in thecenter of the field of view (FOV) and ∼14′ in the cornersof the FOV (50off axis). When many snapshot images (asnapshot is the image constructed from a single survey ob-servation of ∼ 5minutes) are mosaicked together the effectivePSF is ∼19.5′.

Point sources are found using a fast Fourier Transform con-volution of the mask pattern with the array of detector rates;this effectively uses the shadow of the mask cast by a sourceonto the detector array to create a sky image.

Over much of the BAT field of view, the mask shadow doesnot cover the whole array. The partial coding fraction is de-fined as the fraction of the array that is used to make the imagein a particular direction and varies across the FOV. The BATfield of view is 0.34, 1.18 and 2.29 sr for areas on the sky withgreater than 95%, 50% and 5% partial coding fractions.

Swift is in low Earth orbit, but because it can slew rapidlyit can avoid looking at the Earth. The narrow field instru-ments cannot be pointed within 45of the Sun, within 30ofthe Earth limb, or within 20of the Moon.

The pointing plan for Swift is optimized to observe GRBs.This strategy produces observations spread out over a fewdays and at nearly random positions in the sky. The BAT FOVis so large that most of the sky is accessible to BAT on anygiven day, but the pointing is deliberately biased toward theanti-Sun direction in order to facilitate ground based opticalfollow-up observations of gamma-ray bursts. Even thoughthe Swift pointing plan is optimized for GRB observations,BAT’s large FOV and Swift’s random observing strategy re-sult in very good sky coverage (50–80% at >20 mCrab in oneday) for transients (Krimm et al. (2006)18). Over a longerterm, this observing strategy produces an even more uniform

18 online at: http://swift.gsfc.nasa.gov/docs/swift/results/transients/

sky coverage (see Figure 1), with an enhanced exposure at theecliptic poles caused by avoiding the Sun and Moon. Thishigh coverage factor means that the BAT survey can providereasonably well sampled light curves and average fluxes com-piled from data taken throughout the period covered by thesurvey.

The effective exposure time of each point in the field ofview is the equivalent on-axis time (partial coding fractiontimes observing time); therefore the observing time for a placeon the sky is generally much larger than is displayed in theeffective exposure map. All of the source count rates from theBAT survey are normalized to this effective exposure.

The observing efficiency of Swift-BAT is high for a satel-lite in low Earth orbit, but observing inefficiencies (passagesthrough the South Atlantic Anomaly (SAA) 16%, slewing16%, down time < 1%) still result in a loss of 33% of thetotal observing time.

The BAT 22-month survey includes data taken between 15Dec 2004 and 27 Oct 2006; there are 39.6 Ms of usable datain the 22 month survey. A typical point on the sky is withinthe BAT FWHM FOV∼ 10% of the time, and the survey datascreening rejects 0.5% of the data (see §3.1). These two ef-fects result in an effective exposure of 3.9 Ms for a typicalpoint on the sky. The histogram of the effective exposure (Fig-ure 2) shows that most of the sky has an effective exposuretime between 1.7 and 4.3 Ms, with a few regions receiving asmuch as 5.6 Ms.

The BAT PSF is determined by the mask tile cell and de-tector cell sizes. For an on-axis source, the PSF is approx-imately Gaussian with a FWHM of 22.5 arcminutes. In thenative Cartesian tangent plane coordinate system of BAT im-ages, the PSF has nearly a constant shape and size through-out the field of view. However, because tangent plane unitsare not spaced at equal celestial angles, the true PSF shapeis compressed for off-axis sources, varying approximately asσPSF = 22.5′/(1 + tan2θ) where θ is the angle of the sourcefrom the pointing axis. When averaged over many pointings,and weighted by partial coding and solid angle, the mean PSFis∼19.5 arcminutes FWHM. We use this 19.5 arcminute PSFwhen analyzing the BAT survey mosaicked skymaps sincethey are composed of many contributing snapshot observa-tions.

3. BAT SURVEY PROCESSINGThe following sections describe the BAT survey analysis

techniques as implemented in the batsurvey software tool.General information on coded mask imaging can be found inSkinner (1995, 2008), Fenimore & Cannon (1981), and Caroliet al. (1986).

3.1. BAT Survey Data Collection and Initial FilteringThe BAT instrument monitors the sky in “survey" mode

when not within a few minutes of responding to a gamma-ray burst. In this mode detected events are binned into his-tograms by the instrument flight software and the histogramcounts are periodically telemetered to the ground (typically ona 5 minute interval). These histograms contain detector (spa-tial) and pulse height (energy) information. On the ground thehistograms are further adjusted to place all detectors on thesame energy scale, and then for the standard survey analysisare re-binned into the eight survey energy bands: 14–20 keV,20–24 keV, 24–35 keV, 35–50 keV, 50–75 keV, 75–100 keV,100–150 keV, and 150–195 keV.

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 3

FIG. 1.— The top panel shows the effective exposure map for the 22-month Swift-BAT survey in a Hammer-Aitoff projection on Galactic coordinates. Theecliptic poles and equator are also shown; the largest exposures are toward the north and south ecliptic poles (the units on the colorbar are Ms). The bottompanel shows the measured 5σ sensitivity across the sky in units of mCrab in the 14–195 keV band. The bright spots at l=344.1, b=-44.0 (GRB060614), l=271.8,b=-27.2 (GRB060729), and l=254.7, b=-1.4 (GRB060428a) are areas of high systematic noise due to very long exposures (> 800 ks) performed early in themission before dithering in roll angle was instituted.

Several quality filters are applied to the BAT survey data.First, the spacecraft must be in stable pointing mode, whichmeans that the attitude control “10 arcmin settled" flag mustbe set. The spacecraft star tracker must be reporting “OK"status, and the boresight direction must be at least 30 abovethe Earth’s limb. Second, BAT must be producing good qual-ity data, which means that the overall array event rate mustnot be too high or low (3000 cts s−1 < rate < 12,000 cts s−1);a count rate lower than 3000 cts s−1 means that the detector isnot operating correctly, and a rate higher than 12,000 cts s−1

only occurs during passages through the SAA. A minimumnumber of detectors must be enabled (> 18,000 detectors outof 32,768), and no histogram bins can be reported as missingdata because of bad telemetry. In addition, histogram time in-tervals that cross the UTC midnight boundary are discardedsince the spacecraft has at times been commanded to make

small maneuvers during that time. These temporal filters pro-duce a set of good time intervals over which the histogramsare summed. The finest time sampling of this survey anal-ysis is approximately a single pointed snapshot (which havedurations of ∼150–2000 s). The good time intervals are fur-ther checked so that the spacecraft pointing does not changeappreciably during the interval (1.5 arcmin in pointing, 5 ar-cmin in roll), and data are excluded if the pointing has varied.Short intervals of 150 seconds or less are discarded in orderto ensure enough counts across the detector for the balancingstage (see §3.2) of the processing to work correctly.

After temporal filtering each pointed snapshot is reducedto a set of eight detector count maps, one for each energyband. Since the systematic noise in the sky images depends onthe quality of individual detectors, significant effort is madein optimizing the spatial filtering of the data (i.e, the mask-ing of undesirable detectors). All detectors disabled by the

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FIG. 2.— Spatial uniformity in the 22-month BAT hard X-ray survey. The left panel is the effective exposure time histogram (bin size = 40 ks), and the rightpanel compares the fraction of sky seen by the BAT and INTEGRAL surveys as a function of effective exposure times.

BAT flight software are masked. In addition the detectorcounts maps are searched for noisy (“hot") detectors using thebathotpix algorithm; any detectors found to be noisy aremasked. Finally, detectors with known noisy properties (i.e.high variance compared to Poisson statistics) are discarded.The “fixed pattern” noise (see §3.3) is also subtracted fromeach map.

3.2. Removal of Bright SourcesBright point sources and the diffuse sky background con-

tribute systematic pattern noise to the entire sky image, at ap-proximately 1% of the source amplitude, due to the codedmask deconvolution technique. By subtracting the contribu-tions of these sources from the detector images, the systematicnoise can be significantly reduced. We used the batcleanalgorithm to remove bright sources and diffuse background atthe snapshot level. The diffuse background is represented asa smooth polynomial in detector coordinates. Bright sourcesare represented by the point source response in the detectorplane. The source responses are generated using ray tracingto determine the shadow patterns. Bright sources are identi-fied by making a trial sky map, and any point source detectedabove 9σ in any energy band is marked for cleaning. In ourexperience–and based on the properties of the BAT mask—nonew bright sources become detectable after the batcleancalculation, so it is not necessary to iterate the process again.In order to preserve the original bright source intensities, weinsert the fluxes from the uncleaned maps into the cleanedmaps around the locations of these sources.

At the batclean stage the maps are also “balanced" sothat systematic count rate offsets between large scale spatialregions on the detector are removed. Sources shining throughthe mask do not produce this kind of coherent structure, there-fore this balancing stage helps to remove systematic noise.This process involves dividing the array into detector modulesides (128 detectors, [= 16×8]), which are separated by gapsof 8.4–12.6 mm from neighboring detector module sides. The

mean counts in both the outer edge detectors (44 detectors),and the inner detectors (84 detectors), are subtracted for eachmodule separately, so that the mean rate is as close as pos-sible to zero. Count rate variations from module to moduleare believed to occur because of variations in the quality ofCZT detector material and because of dead time variations inthe module electronics caused by noisy pixels. Variations be-tween outer edge and inner detectors in each module are dueto cosmic ray scattering and X-ray illumination of detectorsides. The BAT coded mask modulates the count rate of cos-mic sources on essentially detector-to-detector spatial scales,so the subtraction of the mean count rates averaged over manytens of detectors does not affect the coded signal.

Very bright sources which are partially coded will castshadows of the mask support structures on the edges of themask. These shadows are not coded by the mask, are highlyenergy dependent, and thus must be treated carefully. This isdone by masking detectors in regions of the detector plane af-fected by mask-edge regions for bright sources (∼0.3 Crab orbrighter) determined via ray tracing.

After subtracting bright sources and background, detectorswhose counts are more than 4σ from the mean are discardedin order to further remove contributions from noisy detectors.

3.3. Fixed Pattern NoiseNon-uniform detector properties cause variations between

the background count rates measured in different detectors.These spatial differences form a relatively stable pattern overtimescales much longer than a day and are not addressedby the batclean algorithm. These spatial differences alsocomprise a fixed noise in detector coordinates which is trans-formed by the survey processing into unstructured noise inthe sky image. This fixed pattern is determined by construct-ing long term averages of the residual BAT count rates ofeach individual detector, after subtracting the contributions ofbright sources as described above. In this construction, vari-able terms average to zero and only the stable pattern remains.

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 5

This pattern maps are then subtracted from each snapshot de-tector image. The benefit of removing this fixed pattern noiseis that each individual detector is addressed, thereby remov-ing systematic noise on a finer scale than the balancing stagementioned previously.

The contributions of some detectors to this fixed pattern istime dependent as a result of temporal variations in detectorperformance. We address this time dependence in each de-tector by fitting a polynomial to the daily average value. Thefits are done on data spanning weeks to many months, and thepolynomial used has ∼ 1 order per 30 days fit.

This approach (subtracting the long-term average fixed pat-tern noise from the data) avoids removing any legitimate sig-nal from sources since Swift changes its pointing direction onmuch shorter time scales.

In practice, the entire survey processing must be run onceinitially for all of the data, with the pattern contribution set tozero, in order to determine the residual rates mentioned above.Once the pattern maps have been computed, the processing isrun a second time using those values.

3.4. Sky MapsSky maps are produced for each snapshot using the

batfftimage algorithm which cross-correlates the detec-tor count maps with the mask aperture pattern. Sky mapsare sampled at 8.6 arcmin on-axis, which corresponds to halfthe natural element spacing for the coded mask. The natu-ral sky projection for these maps is tangent-plane; thus, thesky-projected grid spacing becomes finer by a factor of ∼2at the extreme edges of the field of view. The angular ex-tent of a sky map from one snapshot covers the region in thesky where the BAT has some non-zero response. This field ofview is approximately 120×60, although the sensitivity ismuch reduced at the edges of the field of view due to projec-tion effects through the mask (foreshortening of the mask andshadowing due to the mask thickness at large off-axis angles)and partial coding.

The snapshot maps are corrected for partial coding, geo-metric projection effects, and the number of active detectors.Thus, they represent the BAT count rate per fully illuminateddetector, corrected approximately to the on-axis response. Anexamination of the measured count rates of the Crab nebula(considered to be a stable point source for the BAT) showssome systematic residual trends as a function of off-axis an-gle and energy. These effects are primarily due to absorptionby passive materials in the field of view, whose absorptionlengths scale approximately as secθ, where θ is the off-axisangle. The absorptions can be as high as 50% at the lowestenergies and largest angles, but are typically smaller. Aftercorrection for these effects, the count rate estimates are accu-rate to within a few percent.

Partial coding and noise maps which represent the partialexposure of each pixel in the sky map are created for eachpointed snapshot. The partial coding maps are further ad-justed to correct for the fact that some parts of the sky areocculted by the Earth during the observation. For each ob-servation, a map of the average Earth occultation is computedshowing the fraction of the observation time each pixel is oc-culted, and the partial coding map is multiplied by this oc-cultation map to account for the reduced effective observingtime. The noise maps are generated by computing the localr.m.s. of the pixel values in an annulus around each position(see §3.6).

Individual pointed snapshot sky maps are discarded if the

differences between the model used in the bright source re-moval and the cleaned, binned detector plane data lead to areduced chi-square value greater than 1.25. This filtering ex-cluded primarily data around the bright X-ray source Sco X-1, which produces such strong count rate modulations thatthey aren’t reduced to zero at the Poisson statistical level bybatclean. This does produce a significant exposure deficitaround Sco X-1 and the Galactic center region.

3.5. MosaickingThe sky images from each snapshot are weighted by inverse

variance (i.e. noise−2) and combined into all-sky maps. Eachsnapshot sky map contributing to the mosaic is trimmed suchthat all areas of the snapshot have greater than 15% partialcoding. The sky is divided into six facets in Galactic coordi-nates, with grid spacing of the pixels 5 arcmin at the center ofeach facet. The Zenithal Equal Area projection was used inorder to minimize distortion far from the center of projection.Each individual sky image is projected and resampled onto theall-sky grids by bilinear interpolation, as are the partial codingand noise maps. The final result is a set of weighted flux maps,propagated noise maps and effective exposure maps for eachenergy band and facet combination, plus an additional one forthe total energy band of 14–195 keV.

This analysis procedure produces a sky image where eachpixel represents the best estimate of the flux for a point sourceat the corresponding position in the sky (see Fenimore & Can-non (1981) for more information on coded mask image recon-struction).

3.6. Source DetectionA “blind" source detection algorithm was used to search

for sources in the mosaicked significance maps using the fullsurvey bandpass of 14–195 keV. The significance map is theratio of the counts map to the local noise map.

The RMS noise map is calculated from the mosaicked skymap using an annulus of radius 30 pixels (2.5) with an innerexclusion radius of 8 pixels (40′). An 8 pixel radius aroundthe position of all known BAT sources is also excluded fromthe regions used for background calculation. We do not at-tempt to fit the PSF of the source for the noise calculation andhence the positions of sources must be eliminated from thiscalculation to get an accurate measure of the underlying noisein the image.

The noise is assumed to be a smooth function of image po-sition and so the value at the center of the annulus is wellapproximated by the average value in the annulus. This calcu-lated noise includes both statistical and systematic noise andis therefore a better estimate of the total noise in the imagethan the noise calculated from a PSF fit. The noise from ev-ery source is distributed over the whole image, just as the sig-nal from the source is distributed over the detector array, sono local enhancement of noise at the position of the source isexpected.

The blind search algorithm first finds all peaks in the mapby searching for pixels that are higher than each of the sur-rounding 8 pixels. If the significance in a peak pixel is greaterthan our detection threshold of 4.8σ (see §4.4), the excessis considered to be a detection in the blind search for newsources.

4. THE Swift-BAT 22-MONTH CATALOGThe catalog of sources detected by Swift-BAT using the first

22 months of data includes sources at all Galactic latitudes.

6 TUELLER ET AL.

TABLE 1COUNTERPART TYPES IN THE Swift-BAT 22-MONTH CATALOG

Class Source Type # in catalog

0 Unidentifieda 191 Galactic b 32 Extragalacticc 173 Galaxy Clusters 74 Seyfert Galaxies 2295 Beamed AGNd 326 CVs / Stars 367 Pulsars / SNR 158 X-ray Binaries 121

a Sources listed as unidentified have an object with unknown physical type asa counterpart. Some of these objects are associated with a source detected atanother wavelength.b Sources classified as galactic are so assigned because of observed transientbehavior in the X-ray band along with insufficient evidence to place them inanother class.c Sources in the extragalactic class are seen as extended in optical or near-IRimagery, but do not have firm evidence (such as an optical spectrum) fromother wavebands confirming whether they harbor an AGN.d Sources classified as “beamed AGN” include blazars, BL Lacs, FSRQs,quasars, and other high redshift AGN.

The 22-month catalog and associated data in electronic formcan be found online at the Swift website.19

Figure 3 shows the distribution of sources on the sky colorcoded by source type, with the symbol size proportional tothe source flux in the 14–195 keV band. Table 1 gives thedistribution of objects according to their source type. Sourcesclassified as “unidentified” are those where the physical typeof the underlying object (e.g., AGN, CV, XRB, etc) is un-known. These sources have a primary name derived from theBAT position. Some unidentified BAT sources are associatedwith sources in the X-ray or gamma-ray bands (with posi-tions unable to sufficiently determine an optical counterpart orphysical source type), and these sources can be distinguishedby having a name in the catalog derived from the observa-tion in the other waveband. The few sources classified onlyas “Galactic” generally lie in the plane and have shown sometransient behavior which indicates a Galactic source, but noother information is available that would allow further clas-sification. “Extragalactic” sources are detected as extendedsources in optical or near-IR imaging, but do not have otherindications of being an AGN. The “Beamed AGN” categoryincludes BL Lacs, blazars, and FSRQs.

Table 5 is the listing of all the sources detected above the4.8σ level in a blind search of the 22-month Swift-BAT surveymaps. The first column is the source number in the 22-monthcatalog. The second column of the table is the BAT name,constructed from the BAT source position given in columnsthree and four. In cases where the source has been previouslypublished with a BAT name corresponding to a slightly differ-ent location (e.g., a source position from a previous BAT cata-log with less data), we have used the first published name buthave given the correct 22-month BAT coordinates in columnstwo and three. The fifth column is the significance of the blindBAT source detection in sigma units. Instances where morethan one possible counterpart to a single BAT source is likelyare indicated with ditto marks in columns 2–5.

The sixth column gives the name of the identified counter-part to the BAT hard X-ray source with the most preciselyknown position. These are often optical galaxies, or 2MASS

19 http://swift.gsfc.nasa.gov/docs/swift/results/bs22mon/

sources, and are associated with a source detected in themedium-energy X-ray band (3–10 keV) in Chandra, XMM-Newton, or XRT images. Counterpart determination is dis-cussed in §4.2. The seventh column gives an alternate namefor the counterpart. We have preferred to list a well knownname (e.g., Sco X-1) or a name from a hard X-ray instrumentor high energy detection. The best available coordinates of thecounterpart (J2000) are given in the table in columns 8 and 9.

The 10th and 11th columns give the 14–195 keV flux of theBAT source (in units of 10−11 ergs sec−1 cm−2) and its 1σ error.The BAT flux for each counterpart is extracted from the hardX-ray map at the location of the counterpart given in columns8 and 9. The flux determination method is described in §4.5.

The 12th column indicates whether there is source confu-sion: there is source confusion either if there is more than onepossible XRT counterpart or if two likely hard X-ray sourceslie close enough together to make a proper extraction of theflux not possible with the standard method. The treatment ofconfused sources is discussed in more detail in §4.3. We de-fine two classes of source confusion: “confused” sources, and“confusing” sources. A source is “confusing” for the purposesof this column if a fit to the map indicates that the source con-tributes to the hard X-ray flux of a neighboring source. A“confused” source has received more than 2% of its flux froma neighboring source. A confused source is labeled with an“A” in this column, and a confusing source with a “B” (thecase of a very bright source next to a weak one would resultin the bright source labeled with a “B” and the weak sourcewith an “A”). A source that is both confused and confusing(e.g., the case where there are two similar strength sourcesclose to each other, such as when there are two possible XRTcounterparts to a single BAT source) is labeled with an “AB”.

When a source has an entry in column 12, a best estimate ofthe counterpart flux is listed in column 10 from a simultaneousfit of all the counterparts in the region to the BAT map. Whenthe entry is “A” or “AB” in column 12 (indicating a confusedsource), the error on the flux is not well defined, and column11 is left blank. (See §4.5).

The 13th and 14th columns list the source hard X-ray hard-ness ratio and its error computed as described in §4.7. Thehardness ratio is defined here as the ratio of the count ratein the 35–150 keV band divided by the count rate in the 14–150 keV band.

The 15th and 16th columns give the redshift and BAT lu-minosity of the counterpart if it is associated with a galaxyor AGN. The source luminosity (with units log[ergs s−1]in the 14–195 keV band) is computed using the redshiftand flux listed in the table and a cosmology where H0 =70 km s−1 Mpc−1, Ωm = 0.30, and ΩΛ = 0.70.

The 17th column lists a source type with a short verbal de-scription of the counterpart.

4.1. Source Positions and UncertaintiesThe BAT position is determined by using the BAT public

software tool batcelldetect to fit the peak in the map tothe BAT PSF (a two dimensional Gaussian with a FWHM of19.5 arcminutes). The batcelldetect program performsa least-square fit using the local rms noise to weight the pixelsin the input map. These fit positions were used to generate theBAT positions in the catalog and the names of newly detectedBAT sources.

The PSF fit using batcelldetect also reports a formalposition uncertainty based on the least-square covariance ma-

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 7

FIG. 3.— All sky map showing classification of the BAT 22-month survey sources. The figure uses a Hammer-Aitoff projection in Galactic coordinates; theflux of the source is proportional to the size of the circle. The source type is encoded by the color of the circle.

trix. However, because neighboring pixels in the coded maskimages are inherently correlated, the formal uncertainty re-ported by this technique will not be representative of the trueuncertainty. Therefore we choose to use the offset betweenthe fit position and the counterpart position as an indicator ofthe BAT position error.

The batcelldetect program also has the option of fit-ting source locations using an input catalog of starting po-sitions. We have used this capability to test the stability ofthe source positions found by batcelldetect by using aninput catalog where all the starting positions have been off-set by 8 arcminutes in a random direction from the sourceposition found in the blind search. We have performed thistest with several different offsets and find that the fit con-verges to within 1 arcminute of the counterpart position forBAT sources that are not confused. For a few sources, the fitsometimes converges onto a side peak instead of the primarypeak, but this error is not repeated in additional tests startingfrom other randomized positions. This type of systematic er-ror in the position determination does not occur in the blindsearch (§3.6) since we use the maximum pixel to start the fitinstead of a randomized spot 8 arcminutes from the blind po-sition. Anomalous offsets in the source position are identifiedby examination of the image and refitting.

In order to judge the accuracy of the BAT positions, weplot in Figure 4 the angular separation between the BAT po-sition and the counterpart position against the significance ofthe BAT source detection. The accuracy of the BAT posi-tion improves as the significance of the detection becomesstronger. There are 461 BAT sources in Table 5 with detec-tion significances greater than 4.8σ; there are 479 possiblecounterparts, and of these 25 are located grater than 5 arcmin-utes from the BAT position. Therefore, there is only a ∼ 5%chance of a BAT-detected source (> 4.8σ) having a counter-

FIG. 4.— The BAT position error as a function of the BAT detection signifi-cance. The angular separation between the counterpart position and the fittedBAT position is used to determine a measured position error for each source.This measured position error is plotted as a function of BAT detection signif-icance. The dashed line in the plot shows the 96% error radius as a functionof BAT source detection significance. Sources with large position errors arealmost always low galactic latitude sources falling in regions of high sourcedensity and locally higher noise.

8 TUELLER ET AL.

part farther away than 5 arcminutes.In Figure 4 we also plot a line showing our estimate of the

BAT position error for a given source significance. This es-timate for the error radius (in arcminutes) can be representedwith the function

BAT error radius =

√√√√( 30(S/N − 1

))2

+ (0.25)2, (1)

where S/N is the BAT detection significance. This empiricalfunction includes a systematic error of 0.25 arcmin deducedfrom the position errors of very significant sources. This errorradius includes 96% of the sources that are greater than 5from the Galactic plane and 15 from the Galactic center. Theerror radius encloses 85% of sources in the Galactic plane.Sources known to be confused are not included in the plot.

4.2. CounterpartsCounterparts to the BAT sources were primarily discovered

by examining X-ray images taken with instruments with goodangular resolution. Chandra resolution is sometimes requiredon the plane, otherwise XMM-Newton, Suzaku or ASCA im-ages were examined. ROSAT images and source catalogswere of relatively low importance for counterpart identifica-tion because of ROSAT’s lack of effective area in the hardX-ray band, because of the poor correlation between ROSATflux and the BAT hard X-ray flux (see Tueller et al. (2008),Figure 7), and because of the high chance probability of find-ing a ROSAT source in the BAT error circle.

If no archival X-ray images existed for the location of aBAT source, we requested Swift-XRT followup observationsof the field containing the BAT source. A 10 ks obser-vation with XRT is deep enough to detect almost all BATsources. BAT extragalactic sources are usually AGN con-tained in bright (J ∼ 13), nearby galaxies at redshift z < 0.1and are easily identified in an XRT observation.

The X-ray counterpart to an unabsorbed BAT source is avery bright XRT source, which is easily detected with a 2 ksXRT observation. However, most of the new BAT sources areheavily absorbed in the X-ray band and were not detected byROSAT. We have found empirically that XRT can detect es-sentially all of the BAT sources (including the absorbed ones)in a 10 ks observation.

We require consistency of the BAT and the X-ray spectrum(> 3 keV) when simultaneously fit with an absorbed powerlaw allowing only a renormalization between BAT and XRTto account for variability. This consistency of the spectra isrequired for all sources not previously known to be hard X-rayemitters, except transients and sources known to have highlyvariable spectra where the BAT spectrum averaged over yearscannot be directly compared to the XRT measurement from asingle observation.

A small fraction of XRT follow-up observations in the 5–10 ks range detected multiple sources consistent with the BATposition. In these cases the counterpart to the BAT source wasalmost always identified by limiting the bandpass of the X-rayimage to the higher energy 3–10 keV band. This bandpassfiltering usually reduced the number of sources in the field toa single hard source.

In the few cases where two or more hard sources still remainafter bandpass filtering, all are considered possible counter-parts to the BAT source and listed in the catalog with a flag in-dicating that the counterpart identification suffers from source

confusion. There are 18 more possible counterparts in Table 5than there are blind BAT sources (461) because of the 15 caseswhere there are one or more possible counterparts to a singleBAT source.

Because the counterpart identification requires an X-raypoint source with a small error radius (∼ 4 arcsec), a posi-tional coincidence with a known source or bright galaxy, andan X-ray spectrum consistent with the BAT flux, we believethat the counterpart misidentification rate is extremely small.All of the identified counterparts listed in Table 5 are hardX-ray sources.

4.3. Confused SourcesSources are labeled as confused in our table when the high-

est pixel associated with the BAT source in the mosaickedmaps (the “central pixel” value) has a significant contribu-tion from adjacent sources. This includes the cases when twopossible X-ray counterparts lie within a single BAT pixel andwhen two BAT sources are close enough that each contributesflux to the location of the adjacent source.

Using the positions of the X-ray counterparts as an inputcatalog, we calculated the fractional contribution of each BATsource to its neighbors. We used the significance measuredin the blind search and the 19.5 arcminute FWHM GaussianBAT PSF to calculate the intensity of each source at the po-sition of its neighbors. The central pixel value for each BATsource was assumed to be the sum of the source plus all thecontributions from its neighbors. This creates a set of linearequations that can be solved for the true significance of eachsource. We solved these equations with the constraint thatsources were not allowed to have negative significance. Thisprocedure was devised to determine cases where the BAT sig-nificance is altered because of the presence of a very strongnearby source.

If we found that the resulting fit S/N from the technique thataccounted for contributions from neighbors was lower thanthe central pixel S/N from the blind search by 2%, we labeledit as confused.

4.4. Detection Significances and LimitsThe detection significance for the BAT sources in the cat-

alog is extracted from the mosaicked significance map at theBAT position (see §3.6). The significance is taken from thehighest pixel value in the blind search.

Figure 5 shows the distribution of individual pixel signifi-cances from the mosaicked map of the entire sky. As is usualfor a coded mask imager, the noise distribution is a Gaussianfunction centered at zero significance, with a width of σ = 1and a total integrated area equal to the number of pixels inthe map. The large tail at positive significance is due to realastrophysical sources present in the map.

The distribution of the pixel significances in Figure 5closely follows a Gaussian distribution for the negative sig-nificances. The positive side of the distribution also follows aGaussian, but with the addition of pixels with enhanced sig-nificances because of the presence of real sources in the map.

Examination of the negative fluctuations provides a goodmeasure of the underlying noise distribution. There is only1 negative pixel in the entire map with a magnitude greaterthan 5σ. We therefore choose our detection limit to be 4.8σ.This detection limit is also the same as used in the 9-monthversion of the Swift-BAT catalog. While it is clear that thereare several real sources with significances somewhat smaller

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 9

FIG. 5.— Histogram showing the significances of the pixels in the 22-monthsurvey. The gray line is not a fit to the data; it is a Gaussian distribution withσ = 1 and normalized to the peak of the observed distribution.

FIG. 6.— The integral distribution of sky coverage versus sensitivityachieved in the survey. The 1 mCrab sensitivity limit (for 50% sky cover-age) corresponds to a flux of 2.3× 10−11 ergs cm−2 s−1 in the 14–195 keVband.

than 4.8σ, we choose this value in order to minimize falsesources caused by random fluctuations. We expect randomfluctuations to account for 1.54 sources at the 4.8σ level inour sky map of 1.99×106 independent pixels.

Figure 6 shows the integral distribution of sky coverage ver-sus sensitivity achieved in the survey. We achieve a sensitivityof better than 1 mCrab for half the sky, which corresponds toa flux of < 2.3×10−11 ergs cm−2 s−1 in the 14–195 keV band.

4.5. Counterpart Fluxes

Fluxes of the counterparts to BAT sources were extractedfrom the mosaicked maps using the pixel containing the posi-tion of the identified counterpart. For sources where a coun-terpart is not known, we use the fitted BAT position to deter-mine the flux.

We have chosen to normalize source fluxes in the 8 surveybands to the Crab because the systematic uncertainties in thesurvey averaged Crab spectrum are smaller than the uncer-tainties in the BAT survey response matrix. The source fluxesin each band were computed by comparing the source countrate to the measured rate of the Crab Nebula in each band:

BAT source flux =(

BAT source count rateCrab count rate

)Crab flux, (2)

where the Crab flux in each band is given by

Crab flux =∫ b

aE F(E) dE, (3)

where a and b are the lower and upper BAT band edges and Ethe energy in keV.

We take the Crab counts spectrum to be

F(E) = 10.17 E−2.15(

photonscm2 sec keV

), (4)

determined by fitting a power-law model to BAT on-axis cal-ibration observations taken early in the Swift mission. Thesevalues are consistent with characterizations of the Crab spec-trum using data from Integral/SPI (Jourdain & Roques 2008),Integral/IBIS (Jourdain et al. 2008), HETE/FREGATE (Oliveet al. 2003), SAX/PDS (Fiore et al. 1999), and GRIS (Bartlett1994).

The total Crab flux is then

Crab flux =∫ 195 keV

14 keVE F(E) dE = 2.44×10−8

( ergscm2 sec

).

(5)Sources with a spectral index very different from the Crab

can have a small but significant residual systematic error inthe fluxes determined with this method.

In order to gauge this error we generated counts spectra fordifferent models in the eight survey bands using the BAT on-axis spectral response matrix. The Crab comparison flux de-termination method described above was used to obtain themodel fluxes in each of the eight survey bands. The flux er-rors between the computed fluxes and the model fluxes in theindividual bands were always < 10% for a range of modelspectral indices between 1 and 3 and so we deem this tech-nique acceptable for producing the source fluxes in each ofthe survey bands.

We fit the 8-channel spectra with a power law model inorder to produce an overall hard X-ray flux for each BATsource. We used XSPEC and a diagonal matrix to fit the 8-channel spectra with the pegpwrlw model over the entire14–195 keV BAT survey energy range in order to extract thesource flux in this band. This approach was selected becauseit weights the energy bands by their individual uncertainties;a simple sum of the bands would produce a very large errordue to the high weight it assigns to the noisiest bands at thehighest energies.

The 1σ error in the overall flux was determined by using theerror function in XSPEC and is given in Table 5. For the high-est significance BAT sources (> 100 sigma), this proceduredoes not produce a good fit (reduced χ2 1), but this is to be

10 TUELLER ET AL.

expected from the very high significances of each point andthe coarse energy binning. To evaluate the systematic error inthe fitting we performed fits to our model spectra generatedfrom the response matrix. For power law spectra, the system-atic error in the flux is dominated by the error in the individualdata points as calculated above. Sources with hardness ratiosless than 0.1 are not well fit with a power law, and the system-atic uncertainty in the flux can be significantly larger.

The fluxes for sources marked as confused were calculatedin a slightly different way. Instead of using the count rateextracted from the map at the counterpart position, we per-formed a simultaneous fit to find the fluxes of all the sources inthe confused region as described in §4.3. For these sources wedo not quote an error on the flux estimate because the behav-ior of the errors with this fitting technique is not well known.Any source with a confused flag should be considered as de-tected by BAT but the flux should be considered as an upperlimit.

4.6. Sensitivity and Systematic ErrorsIn this section, we compare the expected statistical errors

with the actual measured statistical noise in the final mosaicmaps. From the perspective of pure Poisson counting statis-tics, the uncertainties are governed primarily by the propertiesof the coded mask and the background (see Skinner (2008)for details). The expected 5σ noise level can be expressed as(adapting from Skinner (2008) Eqn. 23 and 25):

5σPoisson = 5

√2b

αNdet T, (6)

where b is the per-detector rate, including background andpoint sources in the field of view; Ndet is the number of activedetectors (Ndet ≤ 32768); T is the effective on-axis exposuretime; and α is a coefficient dependent on the mask pattern anddetector pixel size (α = 0.733 for BAT). The partial coding,p, enters the expression through the “effective on-axis expo-sure” time, T = pTo, where To is the actual exposure time. Us-ing nominal values (b = 0.262 cts s−1 detector−1; Ndet = 23500(the exposure-weighted mean number of enabled detectors);and Crab rate = 4.59× 10−2 cts s−1 detector−1), we find theestimated Poisson 5σ noise flux level to be

f5σ = 0.99 mCrab(

T1 Ms

)−1/2

. (7)

We consider this to be a lower limit to the expected Poissonnoise level for a given effective exposure. In reality, the back-ground rate b may be higher than the nominal value by upto 50% depending on the particle environment of the space-craft. Also, along the Galactic plane the contributions ofbright sources such as the Crab, Sco X-1 and Cyg X-1, arenot strictly negligible, and will raise the overall level of b byup to ∼10%. All of these adjustments would cause a Poissonnoise level larger than given by equation 7, by an amount thatdepends on the specific satellite conditions during the survey.We estimate that, averaged over the entire survey duration, thetrue Poisson noise level may be 5–15% higher than the lowerlimit quoted above.

Figure 7 compares the measured noise and expected noiseversus effective on-axis exposure. We see that both noisemeasures are decreasing approximately as T −1/2, which sug-gests that the dominant errors are uncorrelated over time. Italso suggests that pointing strategies such as roll-angle dither-

FIG. 7.— Measured 5σ BAT sensitivity limit for pixels in the all-sky map,as a function of effective exposure time, T , for the 3-month (red; Markwardtet al. (2005)), 9-month (green; Tueller et al. (2008)) and 22-month (blue;this work) survey analyses. The contours indicate the number of pixels witha given sensitivity and effective exposure. The contour levels are linearlyspaced. The red dashed line represents the original T −1/2 sensitivity curvequoted in Markwardt et al. (2005). The black dashed line represents a lowerlimit to the expected Poisson noise level (see §4.6). The measured noise isapproximately 30–45% higher than the expected Poisson noise.

ing have been successful in reducing pointing-related system-atic errors. However, the measured noise is still higher thanthe expected Poisson noise by ∼30–45%, and we take this tobe a measure of the unmodeled systematic variations on thedetector plane.

The largest likely contributors to systematic variations areimproper subtractions of diffuse background, and of brightsources. BAT count rates are background-dominated — thebackground rate is equivalent to ∼6–9 Crab units — so thecoded mask analysis is particularly sensitive to imperfect sub-traction of spatial background variations. While the patternmap method and the functions fitted during the cleaning stageproduce a good model of the detector background, some im-perfections remain. One effect is that detector-to-detector sen-sitivity differences, coupled with varying exposures to the X-ray background, can lead to excess residuals.

For similar reasons, bright sources may also contribute sys-tematic noise. The brightest sources are clustered along theGalactic plane, and thus contribute noise in those preferredlocations. Indeed, we note that the measured noise is ∼50%higher in the Galactic center region, where there is a concen-tration of bright point sources. This is a larger factor thancan be accounted for by a larger count rate. Modeling ofpoint sources may be imperfect for the same reasons as forthe background. Also, there may be other effects such as sideillumination of detectors that may contribute additional noise.Here, “side illumination” refers to the facets of the individualCdZnTe detectors which do not face the pointing direction,but are still sensitive to X-rays. Off-axis sources will shinethrough the mask and illuminate the sides, producing an addi-tional (although fainter) coded signal. At the moment, illumi-

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 11

nation of the sides of detectors is not modeled at the imagingor cleaning steps, and thus there will be an additional noisedue to the effect.

Proper modeling of these systematic error contributors willbe the subject of future work. At this stage we do not havean in-depth analysis of the quantitative contributions of eacheffect to the systematic noise, and in some cases the analysismay be prohibitively difficult. Still, at the current exposurelevels, the noise level seems to be decreasing with exposure,and we do not appear to be reaching an ultimate systematiclimit in this analysis.

4.7. Spectral AnalysisIn §4.5 we use a simple power-law fit to the data to esti-

mate the source flux. However, because the catalog containssources with various different physical natures and spectralshapes, we choose to use the more robust characterizationgiven by a hardness ratio to describe the BAT spectra.

Hardness ratios for the Swift-BAT sources were calculatedby taking the sum of the count rate in the 35–150 keV bandand dividing by the count rate in the 14–150 keV band. Errorson the hardness ratio were calculated by propagating the er-rors on the count rates in the individual 8 bands except whenthe source is listed as confused. Figure 8 shows a map of thesource positions on the sky, with the source flux representedby the size of the point and the source hardness by the color(red is softer and blue is harder). Figure 9 shows the hardnessratios of the 22-month BAT sources by source class.

A mapping can be made between hardness ratio and power-law index for sources that have spectral shapes well describedby a simple power-law model (e.g., the majority of AGN inour catalog). This mapping is well represented by

Γ = 3.73 − 4.52 HR, (8)

where Γ is the power-law index and HR is the hardness ra-tio as defined above. Figure 10 shows the correlation be-tween power-law index and hardness ratio for the BAT surveysources. The correlation holds well for sources with hard-nesses above about 0.15, but begins to break down for softersources. An illustration of this problem is the soft BAT spec-tra of clusters of galaxies, which have thermal spectra withtemperatures ∼ 10 keV and are usually detected only in thelowest energy BAT band and are not well fit by a power-lawmodel. We leave to a later paper a more careful spectral anal-ysis using models appropriate to the physical nature of thesources.

5. Swift-BAT SURVEY SOURCESAlthough it is for extragalactic astronomy that the present

survey represents the greatest step forward, a comparison ofthe results for Galactic sources with earlier work also has in-teresting implications.

Of the 479 sources in Table 5, 97% have reasonably firmassociations either with objects known in other wavebands orwith previously known X-ray or gamma-ray sources. Morethan 60% of the associations are with extragalactic objects.At high Galactic latitudes (|b|> 10) the density of identifiedextragalactic sources is 22.6 sr−1, and it is only only slightlyreduced at low latitudes to 19.2 sr−1. This suggests that only∼ 7 extragalactic sources in the plane are missed through re-duced sensitivity, lack of information in other wavebands, orconfusion, and illustrates the uniformity of the survey.

153 BAT AGN were previously reported in the BAT 9-month AGN survey (Tueller et al. 2008). Winter et al. (2009)

provide X-ray spectral fits for these sources and provide mea-sures of the luminosity, nH , etc. for the sources in the 9-monthcatalog. Most of the sources in the 9-month catalog also ap-pear here in the 22-month catalog; however, variability in thesources has caused 11 sources to drop out of the 22-month listthat were in the 9-month catalog.

5.1. New sourcesDuring the survey BAT has detected a number of new

sources that are transients or other Galactic objects not pre-viously reported as hard X-ray sources. Some of these havebeen reported in Astronomer’s Telegrams or elsewhere, othersappear for the first time in this compilation. For conveniencethese are summarized in Table 2.

In Table 3 we note other sources that are detected in thissurvey and where XRT follow-up has provided additional in-formation, but where a unique optical, IR, or radio counter-part is still lacking, or where there is only a BAT detection.Some of these are almost certainly Galactic objects as may bejudged from their proximity to the Galactic plane.

Table 4 list the new AGN discovered in the 22-month Swift-BAT survey. Table 4 lists those objects discovered with BATwhose AGN nature could be confirmed with an optical spec-trum. In column 3 of the table we list the source of the opticaldata, and columns 4 and 5 list our own typing of the spectrumand the redshift. The optical spectra are mostly obtained fromdata in the public domain such as SDSS or 6df, but in a fewcases we have obtained data from our own observations takenat the 2.1m telescope on Kitt Peak.

5.2. Extragalactic SourcesMost of the extragalactic identifications are with relatively

nearby Seyfert galaxies and many of the remainder are withbeamed AGN (blazars, BL Lac, FSRQ, etc) sources at muchhigher z.

Figure 11 shows some typical BAT source host galaxy im-ages from the Palomar digital sky survey. The field of viewis 2 arcmin across for each subimage. The figure was pro-duced by dividing the hardness-luminosity plane into 70 binsand randomly choosing a BAT source from that category todisplay. Of note are the high fraction of spiral galaxy hosts(as opposed to ellipticals), and the high number of interactinggalaxies.

The 234 sources that have an identification with a well es-tablished Seyfert galaxy more than double the number in anyprevious hard X-ray survey. The distribution of column densi-ties, spectral indices, and luminosities for the survey sourceswill be presented in a separate paper. As elsewhere in this pa-per, we emphasize that this catalog is based on mean flux lev-els over the entire 22 month period. The detections of sourceswith significant temporal variability over the survey periodand the implications of such variability will be discussed else-where (Skinner et al., in preparation).

Figure 12 shows a histogram of the redshifts of all the AGNfound in the 22-month catalog. The distribution of the Seyfertgalaxy redshifts from the 22-month survey (left panel of Fig-ure 12) is highly biased towards low redshifts (z∼ 0.03) witha tail extending out to z ∼ 0.1 and a few more distant objectsout to z∼ 0.3. The right panel of Figure 12 shows the redshiftdistribution of the beamed AGN. This distribution is quite dif-ferent from the Seyfert galaxies in the left panel, with redshiftsthat extend to z∼ 4 and with no objects at z< 0.033. Since wehave no selection biases with respect to these beamed AGN

12 TUELLER ET AL.

TABLE 2NEW HIGH ENERGY SOURCES IN THE 22-MONTH CATALOG THAT ARE GALACTIC, OR PROBABLY GALACTIC, AND

WERE FIRST DETECTED AS HARD X-RAY SOURCES BY Swift-BAT

Source First Notesreported

SWIFT J0026.1+0508 Here Of several sources in an XRT follow-up observation, only one is hard and it istaken to be the counterpart. It could be a CV.

SWIFT J0732.5−1331 ATel 697 CV of subtype DQ Her. ATels 757, 760, 763.SWIFT J1010.1-5747 ATel 684 = CD−57 3057. ATel 669 gives XRT position for BAT source SWIFT J1011.1-

5748 = IGRJ 10109-5746 associated with Symbiotic star CD-57 3057 (ATel715).

SWIFT J1515.2+1223 Here In a 7400 s XRT follow-up, only one source is detected in the hard band at(α,δ) = (151447, + 122244). No known counterparts at this position.

SWIFT J1546.3+6928 Here The BAT source is confused. There are TWO hard (>3 keV) sources in theXRT image, 1RXS J154534.5+692925 AND 2MASS J15462424+6929102.There are some indications that the ROSAT source is extended, perhaps an in-teracting pair (making a possible third source). The 2MASS object is extendedand clearly a galaxy.

SWIFT J1559.6+2554 ATel 668/9 = T CrB. The Swift source is identified with this symbiotic star in XRT follow-up.

SWIFT J1626.9−5156 ATel 678 Peculiar (HMXB?) transient. 15.37 s pulsations. Optical counterpart2MASS16263652−5156305. Short (100–1000s) flares (Reig et al. 2008).

SWIFT J1753.5−0130 ATel 546 Short period (3.2 hr; ATel 1130) BH LMXB transient observed with manyother instruments following BAT detection.

SWIFT J1907.3-2050 Here = V1082 Sgr. XRT follow-up shows a strong hard source coincident with thepulsating variable star. Steiner et al. (1988) have found that this star in itshard state has properties similar to a CV of subtype DQ Her. Thorstensen etal. (2009) has determined an orbital period of 20.821 hr for this object whichclassifies it as a long period CV.

SWIFT J1922.7−1717 ATel 669 Transient observed with RXTE and Integral after BAT detection (Falanga etal. 2006)

SWIFT J1942.8+3220 Here = V2491 Cyg. We find a weak hard X-ray source whose position is consistentwith V2491 Cyg in data taken before its eruption as Nova Cyg 2008b. (seealso Ibarra et al. (2009), ATel 1478)

SWIFT J2037.2+4151 ATel 853 Transient; later seen with Integral (ATel 967)SWIFT J231930.4+261517 ATel 1309 XRT data show that this source is the same as 1RXS J231930.9+261525, re-

ported and identified as a CV of subtype AM Her in ATel 1309. Mkn 322 andUGC 12515 may also contribute to the BAT counts

SWIFT J2327.6+0629 Here There is no clear source in the XRT field.

TABLE 3UNIDENTIFIED NEW SOURCES

Source la () b () Notes

SWIFT J0826.2−7033 284.21 −18.09 = 1ES 0826−703, 1RXS J082623.5−703142. The 4.1" radius XRT position is1.2" from T Tau star 2MASS J08262350−7031431.

SWIFT J1515.2+1223 16.44 +53.28 Nearest XRT source is a weak one 7.8’ away, just outside the 5’ radius BATerror circle.

SWIFT J1546.3+6928 104.27 40.74 Two hard XRT sources lie within the BAT error circle. One is associated with1RXS J154534.5+692925, about which nothing is known, the other is coinci-dent with the extended source 2MASX J15462424+6929102, which is identi-fied with LEDA 2730634, a side-on spiral galaxy.

SWIFT J1706.6−6146 328.72 −12.40 = IGRJ17062−6143. Bright XRT counterpart gives precise position but no ap-parent optical/IR/Radio counterpart.

SWIFT J1709.8−3627 349.55 2.07 = IGR J17098−3628. IGR J17091−3624 is only 8.5’ away. XRT provides posi-tions for both (ATel 1140). The BAT position corresponds to IGR J17098−3628,but the XRT error circle contains a complex of IR sources and a radio sourceand it is not clear which are counterparts.

NOTE. — These sources have new information but no firm identification with an optical/IR/Radio object.a Galactic coordinates are given as an indication of whether the sources is likely to be Galactic.

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 13

FIG. 8.— All sky map showing spectral hardness of BAT 22-month survey sources. The figure uses a Hammer-Aitoff projection in Galactic coordinates; thesize of the circle is proportional to the flux of the source. Blue sources are harder, and red sources are softer.

TABLE 4NEW AGN DETECTED IN THE Swift-BAT 22-MONTH SURVEY WITH OPTICAL SPECTROSCOPIC

CONFIRMATION

BAT Name Host Galaxy Optical Spectruma Galaxy Type redshift

SWIFT J0100.9-4750 2MASX J01003490-4752033 6df Sy1.8SWIFT J0623.8-3215 ESO 426- G 002 6df Sy2SWIFT J0923.9-3143 2MASX J09235371-3141305 6df Sy1.8SWIFT J1513.8-8125 2MASX J15144217-8123377 6df Sy1.8

SWIFT J0249.1+2627 2MASX J02485937+2630391 KP XBONGb 0.058SWIFT J0353.7+3711 2MASX J03534246+3714077 KP Sy2 0.01828SWIFT J0543.9-2749 MCG -05-14-012 KP XBONG 0.0099SWIFT J0544.4+5909 2MASX J05442257+5907361 KP Sy1.9 0.06597SWIFT J1246.6+5435 NGC 4686 KP XBONG 0.0167SWIFT J1621.2+8104 CGCG 367-009 KP Sy2 0.0274SWIFT J1830.8+0928 2MASX J18305065+0928414 KP Sy2 0.019SWIFT J2118.9+3336 2MASX J21192912+3332566 KP Sy1 0.0507SWIFT J2341.8+3033 UGC 12741 KP Sy2 0.0174

a The optical spectra sources are as follows: 6df = Six degree field galaxy survey, SDSS = Sloan DigitalSky Survey, KP = 2.1 m at Kitt Peak.b XBONG = (hard) X-ray Bright, Optically Normal Galaxy

14 TUELLER ET AL.

FIG. 9.— Hardness ratios of BAT 22-month sources by source class.

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 15

FIG. 10.— The correlation between power law index and hardness ratio forthe BAT survey sources.

(as opposed to optical searches for blazars) these different red-shift distributions are a fundamental property of these classesand are directly related to their luminosity functions and evo-lution (Ajello et al. 2009).

Figure 13 is a histogram of the luminosities of the Seyfertgalaxies detected in the BAT 22-month survey. The luminos-ity distribution of the Seyfert galaxies continues to show a dif-ference between the type Is and type IIs as noted in Winter etal. (2008). This indicates that the true luminosity distributionis indeed different for these two classes, which is inconsistentwith the unified model of AGN. A K-S test of these two lumi-nosity distributions shows that they are drawn from the sameparent distribution with a probability of only 0.30.

As in earlier hard X-ray surveys, the second most commoncategory of extragalactic sources are beamed AGN, which in-clude types such as blazars, BL Lacs, FSRQs, etc. Thereare 32 objects in this category. The highest redshift is forQSO J0539−2839 at z = 3.104.

We have detected 10 clusters of galaxies at> 4.8σ; Perseus,Coma, Ophiuchus, Cygnus A, Abell 2319, Abell 754,Abell 3266, Abell 2142, Abell 3571, and Triangulum Aus-tralis. The BAT spectra of Cygnus A and Abell 2142 inthe 14–100 keV band are dominated by the AGN componentin or around the clusters. The other 8 clusters are all hot(kT ∼10 keV); their BAT spectra are consistent with an ex-tension of the thermal emission modeled with ASCA/XMM-Newton/Chandra archival data in the 2–10 keV band and donot require any additional component for a good fit. In otherwords, there is no evidence of a non-thermal diffuse compo-nent in these clusters. We estimated the upper limit of the non-thermal emission by adding a power-law model to the spectralfit for the 10 detected clusters. The upper limit is ∼ 6×10−12

ergs cm−2 s−1 on average and the lower limit for the magneticfield B ranges from ∼ 0.2–1 µG, assuming inverse Comptonscattering of Cosmic Microwave Background photons by rel-ativistic electrons in the cluster. More details are describedin the papers by Ajello et al. (2009) and Okajima et al. (ApJ,

submitted).Some 20 sources are clearly identified, largely through

follow-up Swift-XRT observations, with galaxies from whichno sign of nuclear activity has yet been reported in other wave-bands. Their mean luminosity is only slightly lower thanthat of those classed as Seyferts on the basis of optical spec-tra (1043.53 compared with 1043.75 erg s−1). These are prob-ably low-z counterparts to the X-ray bright, optically nor-mal (XBONG) sources discovered in the Chandra and XMM-Newton deep fields (Barger et al. 2005; Comastri et al. 2002).

5.3. Galactic Sources5.3.1. X-ray Binaries

As can be seen from Table 5, approximately two-thirds ofthe Galactic sources are X-ray binaries. Of those whose na-ture is known, about 40% are high mass X-ray binaries, whichreflects the BAT’s sensitivity to hard-spectrum X-ray sources.60% are low mass X-ray binaries, which typically have softerspectra but can have a higher total flux. The low mass X-ray binary population is concentrated near the Galactic planeand bulge, whereas the high mass X-ray binary population ismore distributed, including significant contributions from theMagellanic clouds.

The sensitivity of the survey is such that high luminositysources (> Lx ∼ 1036 erg s−1) are detectable anywhere in theGalaxy and the catalog is complete for sources that emit con-tinuously at this level. However, since many X-ray binariesare transient it is likely that there are a significant number ofadditional X-ray binaries that are not seen in the present anal-ysis (which is based on fluxes averaged over 22 months), butthat can be detected in specific shorter intervals. This will bethe subject of further work. The detection of outbursts fromtransients that do not repeat, or that repeat only on timescalesof several years, should scale approximately linearly with thelength of the survey.

5.3.2. CVs and Other Accreting White Dwarf Systems

Accreting white dwarf binaries constitute the second mostcommon category of Galactic sources. Of these, 31 have beenidentified as cataclysmic variables (CVs) or CV candidates.Of the 31 CVs detected with BAT, 14 are in the Barlow etal. (2006) (INTEGRAL) list, while 17 are new detections inhard X-ray surveys. Because the INTEGRAL catalog goesdeeper near the Galactic plane but the BAT catalog is moresensitive at higher latitude, the lists of CVs in the two catalogsare complementary. With the expanded list, we confirm thatthe hard X-ray selected CVs are dominated by magnetic CVsof the intermediate polar (IP) subtype, also known as DQ Hertype stars (see also Brunschweiger et al. (2009)).

In addition, 4 hard X-ray bright symbiotic stars have beendetected by BAT, as summarized by Kennea et al. (2007), andthere is now a candidate to be the fifth member of the class. Fi-nally, BAT has also detected one Be star, gam Cas, for whichan accreting white dwarf companion is one of three possibili-ties proposed as the origin of the X-ray emission (Kubo et al.1998).

5.3.3. SNRs and Non-Accretion Powered Pulsars

We detect hard X-ray emission from 8 pulsars and/or theirassociated Pulsar Wind Nebula (PWN) or supernova rem-nants (SNRs). Our upper limit on PSR J1846−0258 is con-sistent with the flux level at which it was detected in along INTEGRAL-IBIS observation and reported in Bird et al.

16 TUELLER ET AL.

FIG. 11.— Typical host galaxies of BAT detected Seyfert galaxies. The individual images are taken from the Palomar Digital Sky Survey, and are 2′ on a side.The BAT hardness-luminosity plane is divided into 70 bins, and a BAT source from that bin randomly selected to display.

FIG. 12.— Histograms showing the redshift distribution of the AGN in the 22-month survey. The left panel shows the Seyfert distribution, and the right panelshows the beamed AGN distribution. The beamed AGN panel has redshift bins that are 0.5 units wide.

SWIFT-BAT 22 MONTH HARD X-RAY SURVEY 17

FIG. 13.— The distribution of Seyfert galaxy luminosities in the BAT 22-month survey.

(2007). In the case of HESS J1813−178 it appears that weare detecting emission that is from the point source seen atlower energies (Funk et al. (2007)) rather than directly relatedto the slightly extended VHE gamma-ray emission. The onlySNR-related source that is not associated with a PWN is CasA.

5.3.4. The Galactic Center

Because of the limited resolution of the BAT instrumentthe emission reported as from Sgr A* should be regarded asthe net emission from a region of ∼ 6′ radius centered on theGalactic center. It is possible that a number of sources con-tribute.

6. CONCLUSIONSThe 22 month BAT catalog reinforces and enhances the re-

sults from the 3 month (Markwardt et al. 2005) and 9 month(Tueller et al. 2008) catalogs and shows that the BAT surveycontinues to increase in sensitivity roughly as the square rootof time and is far from being confusion or systematics lim-ited. Future papers will discuss the X-ray spectral and tim-ing properties of these sources as well as the nature of theoptical identifications, in a manner similar to that of Winteret al. (2008, 2009). We have also obtained extensive opticalimaging and spectroscopy of the AGN population (Koss, inpreparation; Winter et al. (2009)), more detailed X-ray obser-vations as well as Spitzer IR spectroscopy (Melendez et al.2009) and radio data which will be presented in future publi-cations. These results will allow the first large scale catego-rization of the AGN phenomenon from a large uniform andunbiased sample as well as a detailed comparison with resultsobtained with other selection techniques.

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349.

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0.22

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349.

7359

0.24

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700.

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1.5

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TJ2

319.

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235

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470

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J232

3.3+

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0.85

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780.

320.

190.

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J232

5.5−

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2.41

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2006

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2008

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2009

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2002

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1994

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