Searching for old neutron stars with ROSAT - I. Soft X-ray sources in molecular clouds at high galactic latitude

Astronomy and Astrophysics Supplement Series, Jul 2018

This is the first in a series of three papers aiming to put strong observational constraints on the number of old accreting neutron stars in the Galaxy. Old neutron stars have been predicted to be visible as soft X-ray sources. The brightest sources are expected where the density of the interstellar medium is high. I present an X-ray survey of a complete sample of molecular clouds at high galactic latitudes based on the ROSAT All-Sky Survey. I detect 89 sources inside the projected contours of the molecular clouds and report on a comprehensive identification program. For all sources I searched astronomical catalogs and created finding charts. I also observed all sources at radio frequencies, most of them at 1.4 GHz and at 8 GHz. For sources with bright counterparts, optical spectra are presented. For fainter sources, optical CCD images are shown. Of all sources, 54 are securely identified and for the majority of the remaining sources likely identifications are given. I find no candidate for an old accreting neutron star in this sample. From this survey I derive an upper limit to the neutron star density of at a ROSAT count rate of .

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Searching for old neutron stars with ROSAT - I. Soft X-ray sources in molecular clouds at high galactic latitude

Astron. Astrophys. Suppl. Ser. Searching for old neutron stars with ROSAT R. Danner 0 1 0 Palomar Observatory, California Institute of Technology , Pasadena, CA 91125 , U.S.A 1 Max-Planck-Institut fu ̈r Extraterrestrische Physik, Giessenbachstra e , 85748 Garching , Germany This is the rst in a series of three papers aiming to put strong observational constraints on the number of old accreting neutron stars in the Galaxy. Old neutron stars have been predicted to be visible as soft X-ray sources. The brightest sources are expected where the density of the interstellar medium is high. I present an X-ray survey of a complete sample of molecular clouds at high galactic latitudes based on the ROSAT All-Sky Survey. I detect 89 sources inside the projected contours of the molecular clouds and report on a comprehensive identication program. For all sources I searched astronomical catalogs and created nding charts. I also observed all sources at radio frequencies, most of them at 1.4 GHz and at 8 GHz. For sources with bright counterparts, optical spectra are presented. For fainter sources, optical CCD images are shown. Of all sources, 54 are securely identied and for the majority of the remaining sources likely identi cations are given. I nd no candidate for an old accreting neutron star in this sample. From this survey I derive an upper limit to the neutron star density of 50 sr−1 at a ROSAT count rate of 0:012 s−1. surveys | stars; neutron; white dwarfs | X-rays; stars | radio continuum; stars 1. Introduction Old isolated neutron stars have sparked the imagination of astronomers since the early days of X-ray astronomy (Ostriker et al. 1970; Helfand et al. 1980) . This quest was reignited by the launch of ROSAT and led to several theory papers estimating the detectability of old neutron stars in the ROSAT All-Sky Survey. A general description ? Fig. 9 and Fig. 10 are only and Table 2 is additionally available in electronic form at the CDS via of the ROSAT satellite is presented in (Tru¨mper 1983; Pfe ermann et al. 1986) and the All-Sky Survey was described by Voges (1992) . Treves & Colpi (1991) were the rst to calculate in detail the probability of detecting old neutron stars with ROSAT. Later Blaes & Madau (1993) published a more extensive study. Both groups arrived at the similar conclusion of a high probability to detect old neutron stars. When preliminary results from the Sky-Survey showed that these estimated were too optimistic, both groups reevaluated their calculations (Madau & Blaes 1994; Colpi et al. 1993) arriving at lower numbers. A comparison of the pulsar birth rate and the number of known pulsars shows that we have strong indications to believe that the vast majority of neutron stars remains undetected, although more than 650 radio pulsars have been discovered. Only a small number of neutron stars, not active as radio pulsars, are detected as high energy sources. Almost all of which are in close binary systems. Where are the missing old isolated neutron stars? At birth, a neutron star starts to cool quickly through neutrino emission. Through this process and continuous cooling through photon emission, most of the initial heat is dissipated after less than a million years. Once its surface temperature drops below 105 K, a neutron star is undetectable to most instruments. However, the surface of a neutron star might be heated through accretion from the interstellar medium even after the initial thermal energy content is depleted. The resulting surface temperature depends strongly on the accretion geometry but it is generally expected to be on the order of 106 K. Most estimates have assumed that the emergent surface spectrum is a black-body spectrum. Some theorists have speculated that the surface emission might be harder than a black-body spectrum, see e.g. Zampieri et al. (1995) , and have calculated the e ect of this assumption on the X-ray background (Zane et al. 1995) . However, all calculations con rm that the emission spectrum will not deviate more than 40 percent from a blackbody spectrum. Therefore, because of the limited energy resolution available with ROSAT, the spectrum will not be noticeably di erent from a Planck spectrum. For this reason I will use a simple single-temperature Planck spectrum for all my estimates. Based on pulsar birth statistics, the total number of neutron stars in our Galaxy is estimated to be Ntot = 108 − 109. The local neutron star density was derived to be n ' 7:5 10−13Ntot pc−3 with a half density scale height of 280 pc (Madau & Blaes 1994) . A neutron star may be found as close as ten parsecs. Today, only three candidates for old neutron stars accreting from the interstellar medium have been proposed (Stocke et al. 1995; Walter et al. 1996; Haberl et al. 1996) . All three candidates will require further work before they are unambiguously identi ed. A recently published search for old neutron stars (Belloni et al. 1997) has turned up four less well established candidates. Meanwhile, systematic identi cation of ROSAT sources in the galactic plane (Motch et al. 1997a,b) has su ciently progressed to demonstrate that the number of candidate objects for old neutron stars is much smaller than expected earlier. This conflict between the number of old neutron stars predicted and detected motivated me to search the ROSAT All-Sky survey systematically focusing of the regions with the highest expected neutron star densities. The current paper presents the results from a comprehensive identi cation program of X-ray sources in molecular clouds at high galactic latitude. Paper II covers sources in galactic dark clouds. Here, I present the X-ray source sample and its correlation with the astronomical catalogs 2.1. The cloud sample SIMBAD and NED. I include nding charts, optical imaging and spectroscopic observations and the results from One sample of clouds is particularly well suited for radio observations of all sources at the VLA. This paper this search. Magnani, Blitz and Mundy, hereafter MBM, describes the properties of the source sample and the ob- (1985) published a comprehensive survey of the sky servational data. A later, third, paper will discuss in detail the implications of the surveys in Papers I and II. 2. Selection and properties of the X-ray sample Molecular clouds at high galactic latitudes are the most promising hunting grounds for neutron stars accreting from the interstellar medium because: (1) the density of the interstellar medium (ISM) is high (10−100 cm−3 compared to typically 1 cm−3 or less outside) and we therefore expect higher accretion rates and more luminous sources; (2) the increased column density through the cloud screens out background sources; (3) the location of the cloud at galactic latitudes above 20 cuts down the number of chance coincidences with unrelated eld stars. An increased absorption due to the higher column density a ects all sources and their spectra. For a single source population, distributed isotropically within the sampling volume, I therefore expect fewer and less luminous X-ray sources with on average harder spectra inside the projected boundaries of molecular clouds. Accreting compact objects show the opposite behavior because they are directly interacting with the material in the cloud. Prominent soft X-ray sources without bright optical counterparts are for this reason good candidates for accreting objects inside the clouds. However, high absorption due to material in the vicinity of the source can obscure accreting objects deep inside a cloud. These objects will be lost from the sample in the current search technique. For the time being, I assume that their number is small. outside the galactic plane. Areas of apparent optical ex- During the source detection I chose a reduced liketinction at latitudes jbj 20 and declinations greater lihood threshold of 8.0, compared to the standard 10.0 than = −44 on the Palomar Observatory Sky Survey value. Accepting a lower value for the likelihood of exis(POSS) and the White Oak extension were identi ed by tence of a source results in an increased number of spuriMBM through visual inspection. These candidate areas ous sources. These are mere fluctuations of the background were then observed at 115 GHz with the 5 m telescope of and are not real objects on the sky. However, the benethe Millimeter Wave Observatory near Fort Davis, Texas t of this is a higher sensitivity to faint sources close to because emission at the CO (J = 1 − 0) transition fre- the detection limit of the survey. In this manner, I nd quency at 115.2712 GHz is a tracer of molecular clouds. 353 sources within 125 deg2, covering an area substanFigure 1 shows the distribution in galactic coordinates of tially larger than the area covered by the clouds. I then all clouds detected in this survey. The apparent lack of compared the positions in this initial source list with the clouds around b = 300 is due to the declination con- maps published by MBM. straints of the survey. I considered any source found inside the lowest contour Fiftyseven clouds in 35 complexes were detected at level of a cloud as a candidate object and included it in high galactic latitudes, jbj > 25 . Additionally, 66 clouds the identi cation program. The lowest contour in the CO were detected at intermediate latitudes 20 < jbj < 25 . maps of MBM corresponds to an antenna temperature TA Twentythree of the complexes at high galactic latitudes of 0.5 K. For the unmapped clouds, a maximum distance were later mapped to obtain their morphology. These 23 from the position of the cloud according to MBM of 20 complexes cover an area of 33:9 deg2. Including the clouds arcminutes was used as a cut-o . I intentionally set the that have not been mapped raises the area covered by cuts to err on the side of inclusion rather than missing clouds at high galactic latitudes to 48 deg2. The clouds at an interesting candidate. Out of the initial 353 sources 90 intermediate latitudes were not mapped by MBM, there- sources are found inside the projection of an MBM cloud. fore estimating the covered area in this region is more One source out of this sample was later identi ed as a di cult. An upper limit to the area is the area searched double detection leaving me with 89 sources. in the ROSAT All-Sky Survey of 0:25 deg2 per position. The next step was a classi cation of all sources, based The area searched at intermediate latitudes was 16:5 deg2. only on their X-ray characteristics. For faint sources the The total area covered by clouds at high latitudes and at ROSAT Position Sensitive Proportional Counter (PSPC) intermediate latitudes is therefore 64:5 deg2. yields only moderate energy resolution. However, the res MBM derive a range of densities for the mapped clouds olution is su cient to parameterize the spectrum of a of 35 to 500 cm−3 with a mean value of 140 cm−3. The source by a hardness ratio. ROSAT hardness ratios are velocity dispersion of the ensemble is 5:6 1:2 km s−1 and de ned as the number of detected counts in the hard band the mean velocity with respect to the local standard of rest minus the number of counts in the soft band divided by is 0:13 0:11 km s−1. The average distance to the clouds the total number of counts in the two bands. In this way, is 105 pc and the mean radius of a cloud is 1.7 pc. any source spectrum is related to a number between −1 for soft sources and +1 for hard sources. The ROSAT band from 0.1 to 2.0 keV is split into four 2.2. The X-ray sample bands, three of which are independent: A (0:1 − 0:4 keV: 11 − 40), B (0:5 − 2:0 keV: 50 − 200), C(0:5 − 0:9 keV: 50 − 200) and D(0:9 − 2:0 keV: 90 − 200). The numbers after the colon indicate the selected ROSAT PSPC pulse height channels. The gap between 0.4 and 0.5 keV is due to the carbon absorption edge which renders the PSPC entrance window essentially opaque in this energy range. The hardness ratios HR1 and HR2 are then de ned as the ratio of number of detected counts in the respective bands: I searched the ROSAT All-Sky Survey for sources that coincide with the cloud sample of MBM. For clouds where no maps were given by the authors, I used a search radius of 0:5 around the position of the cloud. For the mapped elds, I approximated the often complex shape of the cloud with a mosaic of rectangles. The rectangles were chosen with a generous overlap into empty areas, generally at least 0:5 . All X-ray events detected during the ROSAT All-Sky Survey within the above areas were extracted from the archive. In a second step I binned these event lists into images. On these images, I performed a source detection, following the standard procedures for ROSAT data with some adjustments for survey data. The procedure consisted of an initial source detection, the creation of a background model and a renewed source detection. All sources with smaller separation than the point spread function of the telescope were merged and a likelihood value for the existence of the source at that position was calculated. HR1 = B − A B + A ; HR2 = D − C D + C ; When a source is not detected in one of the bands a hardness ratio of −1 (for sources only detected in the soft band) or +1 (for sources detected only in the hard band) is assigned. For some faint sources it is only possible to determine HR1 and not HR2, because the source was detected neither in band C nor D. These sources shown an asterisk in the HR column in Table 2. Two sources are so close to the detection limit that no hardness ratios could be derived. The hardness ratios are generally uncertain in the last digit due to photon statistics. Figure 2 shows the derived X-ray Color-color diagram, comparing all detected sources with the sources that coincide with MBM clouds. The distribution in the harder band, HR2, appears not to be a ected by whether a source is found in front of a cloud or outside the projected boundaries of a cloud. This is not surprising as the column density through the clouds is not su cient to signi cantly attenuate X-ray emission above 0.5 keV. In the softer band, HR1, a signi cant di erence between the two groups of sources is found. The ratio of the hardest sources (HR1 = +1) to the total number of sources is the same for both groups. However, the fraction of soft sources is much higher in the sample coinciding with the clouds than in the sample outside of the clouds. This nding does not match the expectation from the simple single-population source model. A possible interpretation is a two-population model: a soft, local population and a second hard, more distant population. The harder, preferentially fainter sources, fall below the detection limit of the survey due to the additional absorbing column through a molecular cloud. As a result the distribution is dominated by the soft, local component that does not su er from absorption because of the proximity to Earth. The same e ect is seen with much higher statistical signi cance in the sample of sources in galactic dark clouds, see Paper II. 2.3. Modeling the X-ray color-color diagram For bright sources it is often possible to t di erent source models to their X-ray spectra, to derive a goodness of t parameter and then decide on the most appropriate model. However, my sources are in general too faint to derive well constrained parameters and I have to assume a source model. My survey is driven by the idea that the dominant emission from slowly accreting sources will be well described by a black body spectrum. This surface emission has to penetrate intervening material in the immediate vicinity of the source and interstellar material between the source and Earth. These two components can be summarized in a single absorption column to the source. The initial source spectrum plus absorption form the source spectrum arriving at the telescope. This spectrum has to be folded with the energy-dependent vignetting of the imaging system and the detector response matrix. The initial source spectrum, including absorption, can be written as: f (E)dE / e−NHX(E) 2 E3 c2h2 eE=T − 1 dE where NH is the column density in cm−2, X(E) the photoelectric absorption cross section, T the radiation temperature and E the photon energy. This source model was then folded with the detector response matrix and integrated over the four energy bands. The result is a theoretical X-ray Color-Color diagram for di erent source temperatures and absorption columns (see Fig. 3). At the low end of the temperature range, up to 100 eV, even small amounts of absorption will lead to a \hard" value for HR1 because the band between 0.1 and 0.4 keV su ers quickly from even modest absorption. This e ect can easily hide intrinsically soft sources in the hard segment of the diagram. Conversely, HR2 responds much more slowly to absorption due to its higher energy. Therefore HR2 is a better parameter in searches for soft sources beyond the local void of the interstellar medium. 2.4. X-ray to optical flux ratio The most powerful classi cation parameter in the search for compact objects is the ratio of X-ray to optical flux. Previous studies, based on observation made with the EINSTEIN observatory, have pointed out that there is a strong correlation between this ratio and a given class of astronomical objects. Maccararo et al. (1988) order the classes starting with hot B and F stars with log(fX=fopt) −4 through galaxies to AGNs and BL Lac objects with log(fX=fopt) +1:5. They used the following relation to calculate the ratio of X-ray to optical flux (Maccacaro et al. 1988) where the units of the X-ray flux are erg s−1 cm−2 log(fX=fopt) = log fX + mV + 5:37: 2:5 Obtaining CCD photometry on more than 350 sources as an initial screening procedure would require a proFig. 4. Magnitude calibration of the Digitized Sky-Survey data sets: top: E-Plates: triangles | Landolt standard stars on same POSS I E-plate; dots | stars from Humphreys et al. from three other POSS I E-plates. A single line is t to the data for simplicity. bottom: IIIa-J-Plates: Di erent symbols mark Landolt standard stars from three plates hibitively large amount of telescope time. Fortunately, digitized versions of the Palomar Observatory Sky Survey (POSS) and the UK-Schmidt plates are available. The CDROM set distributed by the Space Science Telescope Institute supplies data with a spatial resolution of 1:700. Most of the northern hemisphere data is based on the red Palomar E-plates and the southern hemisphere data is based on the SERC Southern Sky Survey and the SERC J Equatorial extension. The data from these CDROMs can be related to standard photometric systems. However, the color systems of the ESO R and SERC J surveys (magnitude mr, mj ) are di erent from the BV R system (mB, mV , mR). I use the color transformation from H¨ortnagel et al. (1992) and invert their relations to get: mV = mj − 0:59(mj − mr): For the Palomar northern plates Humphreys et al. (1991) derive the following color transfer function: mE − mR = −0:011 + 0:148(mV − mR)+ +0:058(mV − mR)4: Ignoring all non-linear terms I simplify this to mE = mR − 0:011 + 0:148(mV − mR): I looked for a simple method to apply these relationships to the digitized sky survey data set. I used the standard photometry routine magnitude/circle in the MIDAS (Munich Image Data Analysis System) environment to determine \instrumental magnitudes" from the DSS images and applied the above conversions. The result of this approximation for a set of Landolt standards is shown in Fig. 4. Standard stars on the same survey plate follow closely a linear relation between my derived instrumental magnitudes (mInstr) and the magnitudes calculated from the Johnson BV R system (me, mJ). Because I did not include a correction for di erent exposure times for each plate, a larger scatter was introduced. This is in particular visible in the plot for the J-Plates. For simplicity I ignore these various o sets, which appear to be of lesser importance for the E-Plates, and t one regression line for each plate set: mE = 43:2 + 2:2 mInstr mJ = 42:8 + 2:1 mInstr: This rule of thumb serves my purpose of making an initial estimate of the X-ray to optical flux ratio well, but has to be treated very carefully in individual cases. Large color terms can render the estimate meaningless due to the involved systematics. Notwithstanding the above argument, the derived values are an important tool to classify quickly large numbers of sources without any telescope time. For the future, STScI has announced the completion of a calibration set for each individual survey plate that will take individual o sets into account and will yield much more reliable numbers. Currently only one plate of the POSS survey is included in the DSS for each position on the sky and it is therefore not possible to derive color-information from the DSS. Further assumptions have to be made to estimate the X-ray flux of each source. Most survey sources (with integration times of only 200 − 300 s) did not collect enough photons to extract a meaningful spectrum. In the absence of more information on the source spectrum I apply the rough rule for ROSAT: 1 cnt/sec = 10−11erg s−1cm−2 (ROSAT User Handbook, MPE 1997). As I lack all color information on the optical counterparts, I replace mV with the magnitudes in the photographic pass bands mJ, mE of the survey plates and obtain: log(fX=fopt) = log(count rate) + mopt − 5:63; 2:5 where mopt is replaced with either mE or mJ, whichever is available. The distribution of this ratio is plotted for all 353 detected sources in Fig. 5. The four panels in this gure show the distribution of the X-ray to optical flux ratio for all sources (panel A) and three other sub groups. The distribution of this value does not vary signi cantly for sources found coincident with clouds (panel B), although there might be a hint of fewer sources with high values of log(fX=fopt). The soft source population, where HR1< 0:0, has a strong signature of sources with bright optical counterparts and log(fX=fopt) between −4:5 and −3:5. Finally, the soft sources, HR1< 0:0 that coincide with clouds appear to be completely devoid of sources with high values for this ratio. 6 + 5 + +4 + 3 +1 + 2 In the search for point sources I also discovered a previously undescribed extended feature. The MBM clouds 41 through 44 cast a distinct shadow on the soft X-ray background. The left panel in Fig. 6 shows the ROSAT image in the 0.1 to 0.4 keV range. The right panel shows an image from the IRAS 100 m survey of the same area. Numbered crosses mark corresponding coordinates in the X-ray and the IRAS image. A lighter shade corresponds in both images to a higher intensity. The intensity of areas with reduced di use X-ray emission and outside differs by up to a factor of 2.5. The structure of the di use background as seen with ROSAT has been most recently described by Snowden et al. (1995) . Shadowing structures have been described on several occasions in the past (e.g. Snowden et al. 1993) . However, the complex of clouds 41 to 44 casts one of the cleanest and deepest shadows so far identi ed. The absorption contours in the X-ray image accurately trace the areas of emission on the IRAS image. The IRAS image shows that the apparently isolated peaks of CO emission (Magnani et al. 1985) belong in fact to the same structure. 3. Correlation with existing data bases 3.1. Uncertainty in the X-ray position The e ective point spread function of the ROSAT telescope is signi cantly broader during the All-Sky-Survey than during the pointed observations. This is due to the scanning mode where the PSF is averaged over a wide range of o -axis angles. For most of my sources the number of detected photons is too low to recover this resolution. For consistency I choose a source independent 90 percent error radius r90 of 30 arcsec, regularly used in ROSAT source identi cation (Hasinger priv. com.). Motch et al. (1997a) calculate an upper limit of r90=32 arcsec for their extensive identi cation program and nd that this is a conservative limit. The result of my identi cation program supports this nding, see Fig. 7. 3.2. Catalog search I searched the astronomical catalogs provided by SIMBAD and the NASA Extra Galactic Database (NED) for objects at the X-ray position. In SIMBAD a search radius of 1 arcminute and in NED a search radius of 5 arcminutes was used. Any object within 30 arcsecond of the reported X-ray position was considered a counterpart to the source as long as there was no compelling evidence found to contradict this. Of the 89 sources coinciding with clouds, 11 were readily identi ed with bright (mV < 10:6) stars and 6 others with nearby low mass dwarf stars and one emission line star (mV ; 14:6). Two sources coincide with known quasi-stellar objects (QSOs) and three others with known radio sources. The Abell cluster 0496 was found only 1.5 arcminutes distant from RX J0434:5−1334. Table 2 shows the names of all identi ed SIMBAD sources. 3.3. Finding charts In addition to the DSS images, I created nding charts from data in the Automated Plate Measuring machine catalog. The APM group at Cambridge independently scanned plates from the Palomar Observatory Sky Survey. The signi cant advantage of the APM catalog over the DSS scans is the additional color information as both red (E) and blue (J) plates have been scanned. The detection limits are around 21.5 mag in J and 20 mag in E. The APM data base is an object list, including an automated classi cation into stellar and non-stellar objects, rather than a collection of images. This can cause confusion when large extended structures such as bright emitting clouds are encountered. A comparison between the images from the DSS and the APM scans can then resolve ambiguities in the morphology of the source. I give nding charts for all objects of which spectra have been taken in Fig. 9. 4. Optical and radio identi cation program The majority of sources required further work beyond the catalog searches, either because the objects were too faint or because more information on their optical spectra was required to resolve ambiguities. 4.1. Radio maps I observed all X-ray source positions in a program of short exposures at the Very Large Array Radio Telescope (VLA) in New Mexico. Between 9 September 1995 and 25 October 1995 a total of 20.5 hours were spent in two bands, at 1.425 GHz (L-band) and 8.439 GHz (X-band). I included all source positions in the L-band program and about half of the sources in the X-band observations. Some observations were lost due to technical problems at the telescope and some due to radio interference. In a few cases the detection limit at the source position was strongly limited by side lobes from strong sources outside the primary beam. All observations prior to October 1995 were done in the hybrid AnB con guration resulting in an elliptical beam that varies with the elevation of the object. The remaining observations were conducted in the more extended B con guration, with a more circular beam. Table 1 summarizes all elds with detected radio sources detected close enough to the X-ray position to serve as plausible radio counterparts. Table 2 shows in Col. B if a source position has a successfully reduced radio map associated with it. A successful radio map is one in which the observation is free from major radio interference, was successfully calibrated and cleaned to an acceptable level. The typical root mean square noise level is between 250 and 350 Jy at L-band and 150 to 200 Jy at X-band. These values are a factor 2-3 higher than the expected theoretical thermal noise. The reasons for the high noise levels are mostly large zenith angles, the increased background in areas close to the galactic plane and confusing sources. Cleaning the images beyond the current noise level proved to be prohibitively expensive in terms of time and was not justi ed by the objective to nd strong isolated sources. All VLA data were reduced and calibrated within the AIPS software packet distributed by the National Radio Astronomy Observatory. 4.2. Optical observations I took optical spectra and CCD images of most sources during 15 observing nights at Mt. Palomar between 28 June 1995 and 27 December 1995. For low resolution spectra of stars brighter than mV = 16 I used the Echelle spectrograph in the long slit mode at the Palomar 60-inch telescope. For spectra of fainter objects, down to mV 18, I used primarily the Double Spectrograph at the Cassegrain focus of the 200-inch Hale telescope. For some elds I also used the COSMIC prime focus instrument at the Hale telescope. The optical data were reduced using standard routines in the IRAF software suite. 5. Identi cation and statistics My identi cation strategy was to search the X-ray error circle for a counterpart until a plausible counterpart was found. Plausible means an object with either a characteristic signature (color, spectrum) for a counterpart to an X-ray source or where the X-ray to optical flux ratio was within the typical ratio for a given source type. AGN spectra, broad Balmer lines and forbidden [OIII] emission were always taken as a strong indicator for the X-ray counterpart, regardless of the presence of radio emission. M dwarf spectra with or without H emission were also strong counterpart candidates. In a few cases bright stars are found just outside the error circle. These are quite likely the counterparts to the X-ray sources, as other identi cation programs have shown. The analysis of the X-ray data and the multiwavelength follow-up program led to the identi cation of the majority of sources in my sample. Out of 89 sources 54 have rm identi cations; for the remaining 34 sources the current status of the identi cation process is presented. More spectroscopic data would be required to resolve the ambiguous cases with several optical counterparts inside the error box. However, in most cases the most likely counterpart has already been identi ed. Table 2 summarizes the results of this program. Previously known objects are listed with their names. In many cases optical spectra were required to resolve ambiguities, see Fig. 8. I created nding charts for all objects that I took spectra of, see Fig. 9. Arrows on the nding charts mark the objects. These nding charts are based on the APM scans of the POSS I plates. CCD frames are reproduced for all elds where no good APM or DSS nding chart was available, Fig. 10. The APM nding charts, the CCD frames and the identication spectra are all referenced to Table 2 through their internal ID number which is easier to handle than the full X-ray position. Table 3 nally lists remarks on the rationale for each individual identi cation. Figure 7 presents the distribution of the separation between the X-ray source and the identi ed counterpart for my sample. The distribution is shown rst as the number of identi cations as a function of the separation. A second panel shows the same distribution but normalized by the radius. In this normalization the increasing sampling area for each radius bin has been removed from the distribution. The distribution con rms my initial assumption that most sources will have counterparts within 30 arcseconds of the X-ray source position. In a few cases very bright stars that burn out the point spread function are nominally found at larger distances. Of the 54 rm identi cations which are cataloged objects or objects with optical identi cation spectra, 34 are stars and 20 are extragalactic objects. Of the remaining sources, all but two have several counterparts in their error box. A few of the sources at the faint flux limit are expected to be spurious detections due to the lower likelihood threshold that I used in the source detection process. No unidenti ed source shows the X-ray characteristics that I expect from a soft thermal source nor is any of them luminous enough to indicate an unusual X-ray to optical flux ratio in the presence of the counterparts inside the error box. The only soft and bright source in the entire 89 source sample, 49, stands out in its X-ray characteristics and was readily identi ed with a DC white dwarf star (see identi cation spectrum). A considerably larger amount of telescope time would have to be invested to resolve all ambiguities at the end of which I expect that most of the suggested candidates would be con rmed. 6. Summary A detailed discussion of this survey, together with the results from Paper II, will be published as a later paper. Here, I will only briefly summarize the results of the current survey. I found one white dwarf, several late type stars, M stars with and without emission lines and a large population of AGNs. I identi ed no candidate for an accreting neutron star over the sample area of 64.5 deg2. Because of the reduced detection threshold for X-ray sources I expect to be complete to the 99 percent level at a count rate of 0.012 s−1. This implies that at most one of the 89 sources might have not been detected in the X-ray survey. An upper limit of one source in the 64.5 deg2 survey area translates to 50 such sources per steradian (50 sr−1). This upper limit to the number of old accreting neutron stars, assuming 108 neutron stars, is a factor of 1.6 lower than the lowest value of the prediction for isotropic accretion, and more than a factor of 35 lower than we expect for polar-cap accretion (Blaes & Madau 1993) . Acknowledgements. This article is based on research conducted during my three year visit to the California Institute of Technology. I want to thank Prof. S.R. Kulkarni for his hospitality, support and countless discussions during this time. I am indebted to J. Tru¨mper for his support of this project and many fruitful suggestions. The ROSAT project is supported by the German Bundesministerium fu¨r Bildung und Wissenschaft (BMBW/DARA) and the Max-Planck-Society. This research has made use of the NASA/IPAC extragalactic database NED) which is operated by the Jet Propulsion Laboratory, Caltech, under contract with the National Aeronautics and Space Administration, and of the SIMBAD database, operated at CDS, Strasbourg, France. The Digitized Sky Survey (DSS) was produced at the Space Telescope Science Institute under U.S. Government grant NAG W-2166. The National Radio Astronomy Observatory (NRAO) is operated by Associated Universities, Incorporated, under cooperative agreement with the National Science Foundation. ID ID Remark bright star bright SIMBAD object, low mass star bright star 2 faint (B and C) objects in CCD frame bright star bright star bright star 1 blue object within error box, DC white dwarf A is just outside the error circle, bluish B is red, likely extragalactic 2 objects, brighter (A) is K0III, fainter (B) is K3, claim A as counterpart several red objects, no blue object bright star A shows AGN spectrum and is counterpart, B is a serendipitously detected carbon star CCD frames shows red object (B) coincident with radio position, A is 20 arcseconds o from radio source no obvious counterpart A is detected in B, V , R, and I A is brightest object, E is a galaxy A is brightest object, AGN POSS object, galaxy spectrum with break? no radio source down to 615 Jy bright SAO star. A is brightest object. no object on 300 s 60-inch frame. star S is close. 2 objects, A is late type star, B is AGN @ z = 0:214 bright star, M dwarf bright star, M dwarf K3-5 star (just outside error box) radio source coincides with A binary system unresolved on APM chart, each component shows strong H lines bright star 2 objects, brighter is late type star, fainter object, closer to X-ray position coincides with radio source bright M-dwarf A is brightest object A is brightest object and is red 2 objects. brighter shows AGN lines. z = 0:14 AGN @ z = 0:47 A is brightest object. bright star emission line star A is bright G star, B is faint late type star, Abell cluster 0496 is 1.5 arcminutes o 1 POSS object bright star A is brightest object crowded eld bright star bright star bright star too far south too far south. 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R. Danner. Searching for old neutron stars with ROSAT - I. Soft X-ray sources in molecular clouds at high galactic latitude, Astronomy and Astrophysics Supplement Series, 331-348, DOI: 10.1051/aas:1998383