text:
Fluctuations in the diffuse X-ray background observed with Ginga
J.A. Butcher, G.C. Stewart, R.S. Warwick, A.C. Fabian, F.J. Carrera, X. Barcons, K. Hayashida , H. Inoue , T. Kii
1. Department of Physics and Astronomy, Leicester University,
University Road, Leicester, LE1 7RH, UK.
2. Institute of Astronomy, Madingley Road, Cambridge CB3 0HA, UK.
3. Instituto de Física de Cantabria (Consejo Superior de Investigaciones Científicas– Universidad de Cantabria), 39005 Santander, Spain.
4. Institute of Space and Astronautical Science, 3-1-1 Yoshinodai, Sagamihara, Kanagawa 229, Japan.
5. Department of Earth and Space Science, Osaka University, Machikaneyama, Toyonaka, Osaka 560, Japan.
We present Ginga measurements of the spatial fluctuations in the diffuse X-ray background. When combined with earlier results, the new data constrain the extragalactic relation in the 2–10 keV energy band to a form close to the Euclidean prediction over the flux range . The normalisation of the 2–10 keV source counts is a factor above that derived in the softer 0.3–3.5 keV band from the Einstein Extended Medium Sensitivity Survey if a spectral conversion is assumed which ignores X-ray absorption intrinsic to the sources. Both this result and the spectral characteristics of the spatial fluctuations are consistent with relatively low-luminosity active galaxies ( i.e. ) dominating the 2–10 keV source counts at intermediate flux levels. We also use the ‘excess variance’ of the fluctuations to constrain possible clustering of the underlying discrete sources.
Keywords: X-rays:general, diffuse radiation - Galaxies:active
Since the discovery of the diffuse X-ray background (XRB) there has been considerable debate as to whether its origin lies solely in the integrated emission of known types of extragalactic X-ray source, such as Seyfert galaxies and QSOs, or whether a significant contribution might come from a hitherto undiscovered population of discrete X-ray sources. The alternative, that much of the XRB might originate in diffuse emission from a putative intergalactic medium, has been effectively rejected through measurements of the microwave background spectrum using the satellite (Mather et al. 1990; Barcons, Fabian & Rees 1991).
In modelling the XRB in terms of discrete sources a continual frustration is the fact that the surface brightness and spectral form of the XRB are well determined only above 3 keV, whereas the most detailed studies of the source populations have been carried out in the soft X-ray band (through the exploitation of the imaging systems on Einstein, EXOSAT and ROSAT). In the 2–10 keV band, which contains a significant fraction of the XRB energy density, our knowledge of the X-ray luminosity and spectra of individual sources is restricted mainly to the relatively bright sources which appear in the all-sky catalogues of Uhuru, Ariel 5 and HEAO-1. However, the statistical properties of sources at much fainter fluxes are accessible through studies of spatial fluctuations in the XRB.
Radio astronomers were the first to recognise that, by studying the beam-to-beam variations in the sky background in directions away from bright catalogued sources, it was possible to derive information on sources too faint to be resolved individually. The theoretical basis for such fluctuation studies is well documented (Scheuer 1974; Condon 1974). Provided source clustering effects can be neglected (see Barcons 1992), the form of the background fluctuations distribution, the so-called distribution, is governed solely by the relation of the discrete sources which produce the fluctuations and by the normalised beam response of the detector. It can be shown that, for simple power-law forms of , the shape of the distribution depends on , whereas the width of the distribution scales as , where is the effective beamsize (see Condon 1974). We use the differential form of the relation, in which the number of sources per steradian, in the flux range from to , is given by:
Here is the normalisation of the differential source counts and the power-law slope; note that corresponds to the Euclidean form of the source counts.
The standard analysis approach is one of model-fitting, in which a predicted curve is computed and compared to the observed distribution. The properties of the underlying relation can then be inferred through the process of minimising the differences between the predicted and observed fluctuation distributions. Although the spatial fluctuations are due to the combined influence of sources over a very wide flux range, in practice most information is extracted at flux levels corresponding to a surface density of about 1 source per beam (Scheuer 1974). It follows that the narrower the detector beam the fainter the flux level reached. An important proviso is, of course, that the fluctuations must be measured with adequate signal-to-noise ratio for useful information to be obtained.
In the present paper we show that measurements of spatial fluctuations by Ginga provide constraints on the 2–10 keV source counts and source clustering at flux levels corresponding to a surface density of extragalactic X-ray sources of object per square degree. Similar levels are encompassed in the Einstein Observatory Extended Medium Sensitivity Survey (EMSS) (Gioia et al. 1990b) and a comparison is made between the source count estimates in the medium energy and soft X-ray regimes ( i.e. the 2–10 keV and 0.3–3.5 keV bands). We also comment on the spectral characteristics of the spatial fluctuations measured by Ginga.
There have been several previous studies of XRB fluctuations as measured in the medium energy X-ray band (e.g. Fabian 1975; Schwartz, Murray & Gursky 1976; Pye & Warwick 1979; Shafer 1983). Of these, the most definitive result is from the HEAO-1 A2 survey in which the XRB data were derived from detectors with collimated fields-of-view of and (Shafer 1983). Here we present measurements of spatial fluctuations in the XRB made with the Large Area Counter (LAC) on Ginga. Since the collimated beam of the LAC is only , the Ginga measurements are potentially more sensitive than those from HEAO-1 A2. Full details of the LAC, which had a total effective area of 4000 cm, several times larger than that of the HEAO-1 A2 experiment, are given in Turner et al. (1989). Preliminary results from this study have been reported by Warwick & Stewart (1989), Hayashida (1990) and Warwick & Butcher (1992). Ginga observations (the same data as used here) have also been used to study the angular autocorrelation function of the X-ray background (Carrera et al. 1991).
The paper is organised as follows. Section 2 presents the estimates of source counts based on the analysis of the Ginga fluctuations. Upper limits to the excess variance required in the fitting procedure are used to constrain source clustering. The spectrum of the fluctuations is also analyzed. Section 3 is devoted to the discussion of these results and in particular to the comparison of the inferred source counts with the EMSS. Section 4 summarizes our results.
2 The Ginga Measurements
2.1 The observations
The data used in the fluctuation analysis come from two types of observation: dedicated raster scans of the background and observations taken as part of the normal background monitoring programme; in total the dataset comprises 132 independent pointings. The data were all taken in MPC1 mode (Turner et al. 1989) and we use only data from the top layer of the LAC (separation of data from the top and mid layers of the LAC gives an improved signal-to-noise ratio for weak sources). In all of the observations the angle between the LAC pointing direction and the sun was greater than , thus excluding any possibility of contamination of the data by solar X-rays.
Since Ginga had no facility for simultaneous background measurement during a source observation, a typical Ginga observation consisted of one day pointing at the source followed by a further day pointing at a nearby region of ‘blank’ sky. Over the lifetime of the mission there thus accumulated a large database of potentially useful background observations. Here we utilize 70 such observations of independent sky regions made between 1987 June and 1989 August. We selected only observations with . Where there existed multiple pointings in the same direction we chose the one with the largest exposure. The typical exposure of an observation is s. Figure 1 shows the distribution of these observations over the sky. It should be noted that the distribution of these pointings is neither uniform nor random but follows, to first order, the distribution of X-ray sources above the Ginga limiting sensitivity.
The second source of data is from three sets of dedicated background observations performed in 1988 January, 1988 July and 1989 March. In each case a set of independent regions of sky were observed at the rate of one region per satellite orbit giving a typical exposure time per pointing of s. The three areas of sky observed in this way were situated near the north and south galactic poles and the north ecliptic pole.
2.2 Extraction of the background fluctuations
The LAC registered counts from charged particles and other events as well as from cosmic X-rays. Both the count rate and spectrum of the LAC internal background varied with time in a complex manner (see Hayashida et al. 1989). Over a period of hr most of the variation of the background could be explained by the change in cutoff rigidity with satellite altitude and by radioactive decays induced by the passage of the satellite close to the South Atlantic Anomaly (SAA). In addition a 37-day periodicity was present as a result of the precession of the satellite orbit which caused the height of the daily passage through the SAA to vary. There was also a very long term decrease in the background which was related to the gradual decay of the satellite orbit. The internal background of the LAC was modelled using a development of the methods described in Hayashida et al.(1989), although the exact method employed was slightly different for the two different types of data.
Each set of dedicated observations lasted only 1–2 days, so the long term variations could be ignored. For each dataset we fitted a time series model of the form:
where is the LAC count rate as a function of energy channel and time, are five time-dependent parameters derived from LAC housekeeping data and are scaling coefficents which represent the spectral forms of the corresponding background components. More specifically two of the coefficients represent contributions which scale with the SUD (counts Surplus to Upper Discriminator) and with the cutoff rigidity, whereas the other three represent the spectra of induced radioactive decays with empirically-derived e-folding times of 12.5, 1 and 0.5 hours. The time-independent term is the average over the dataset of the cosmic diffuse background plus any residual particle background in the detector. The best fit values of and the five coefficients for each set of dedicated observations were used to create a background model for that dataset. The deflection or fluctuation level was then determined for each individual pointing direction as the difference between the observed count rate and the modelled value.
The equivalent procedure for the observations drawn from the Ginga database was slightly more complicated. As the observations were spread over a longer time period it was necessary to model the variations in internal background caused by the 37-day precession of the satellite orbit (Hayashida et al. 1989). Ideally such modelling requires many observations spread over all phases of the 37-day period. There was also the problem of the long term drift of the internal background induced by the decay of the satellite orbit. The latter proved difficult to incorporate directly in the fitting procedure and, as a first approach to minimising any long term drift whilst attempting to optimise the modelling of the 37 day component, the 70 observations were simply divided into two datasets containing 36 and 34 pointings, each of which spanned roughly 13 months. A background model of the form discussed earlier was then applied to each of these datasets except that the coefficients modelling the induced radioactivity incorporated a (best-fitting) 37-day variation. The fluctuation level for a particular observation was again determined as the difference between the observed count rate and that derived from the background model for the dataset. Finally a check was made for evidence of any obvious trends in the time-ordered fluctuation measurements from each dataset; however, no significant long-term effects were apparent, thus validating the analysis procedure.
2.3 Analysis of the distributions
The distributions measured by Ginga in two energy ranges (2–4 keV and 4–12 keV) are shown in Fig. 2. The rms widths of the distributions correspond to approximately which corresponds to roughly 5 per cent of the predicted count-rate from the XRB in the two bands (using predictions based on the XRB spectrum reported by Marshall et al. 1980).
We fit the observed curves using trial number count relationships of power-law form using standard Fourier transform techniques based on the method of Condon (1974). Full account is taken of the beam profile of the LAC collimators. The relationship is truncated when the integrated intensity exceeds the total background strength, although as explained earlier, the shape of the is not sensitive to fluxes where the curve predicts many sources per beam. The effects of counting statistics and residual errors in the fitting procedure described above are included by convolving the model curve with a Gaussian of standard deviation . This is the appropriate statistical error for the short second scan observations while for the longer pointings the value is dominated by the systematic errors in the background modelling procedure. For the database pointings the value of was estimated by comparing repeated observations of the same region of sky. The results are not sensitive to the exact value of within appropriate limits. (We note that this is the first time that XRB fluctuation measurements have been made where the P(D) noise is several times the statistical error on individual samples.)
2.4 Constraints on the relation
The observed fluctuation distributions were fitted with model curves, via a process of minimisation. (The results thus obtained were entirely consistent with those produced by an alternative approach, namely the maximum likelihood method - see the next section). This fitting procedure lead to the constraints on the power-law slope, , and normalisation, , of the relation shown in Fig. 3. The parameters of the best-fitting models, for which the predicted P(D) curves are shown in Figure 2, are listed in Table 1, where the quoted errors correspond to 90 per cent confidence for one interesting parameter. Table 1 also gives the best-fitting normalisations for the case, that is a Euclidean slope for the source counts. Finally Table 1 also gives the normalisations converted to 2–10 keV flux units using a conversion factor based on the response of Ginga to a power-law spectrum with an energy index of (we show later that this is an appropriate value for ).
The best-fit slope for both energy ranges are consistent with each other and with the Euclidean value of . The inferred Euclidean 2–10 keV source count normalisations in the two energy bands are also in excellent agreement with each other and with the normalisation of the resolved-source counts reported by Piccinotti et al. (1982).
2.5 Excess variance
So far we have explicitly neglected source clustering in the computation of the model distribution. It is customary (Fabian & Rees 1978; Shafer 1983) to mimic the effects of source clustering by convolving the predicted distribution of fluctuations for unclustered sources with a Gaussian of standard deviation and then to try to measure or constrain this parameter via a comparison with the observational data.
In order to study the allowed range for the excess variance, we have used a maximum likelihood method, since checks revealed that, in this case, binning the data and minimizing the function did appear to give systematically higher values (by up to 20 per cent) of than with the maximum likelihood approach. We have computed the likelihood function in parameter space. We then consider and as non-interesting parameters and for all their values we select the maximum likelihood as a function of only. This function is then normalized to give a measure of probability.
We find that the value of that maximizes the likelihood function is less than ct s, which is of the same order as the errors in the fluctuation measurements. Thus there is no clear evidence for effects arising from source clustering. At the one sigma level ct s and at two sigma confidence ct s. In relative terms those upper limits correspond to per cent and per cent. It must be stressed that the two sigma upper limit corresponds to a situation in which there is a very low surface density source population and most of the width of the curve comes from the excess variance. These results on source clustering are entirely consistent with the results of Carrera et al. (1991) who use the same data reported here to calculate the ACF of the X-ray background and obtain only upper limits.
The two sigma upper limit per cent poses some interesting cosmological constraints. In terms of Poisson fluctuations this limit implies a minimum of 345 sources deg, whereas Shafer (1983) obtained a limit of 2 per cent for a 25 deg beam, thus requiring a minimum of only 100 sources deg. The present measurements pose stringent constraints on any large-scale inhomogeneities of the X-ray Universe (see Fabian & Barcons 1992). This is emphasized in Fig. 4 where the upper bounds to (assuming that X-rays trace mass on large scales) implied by the lack of significant excess variances are shown. It is assumed that the sources that dominate the fluctuations in the LAC are concentrated at a mean redshift of about with a spread , which is very roughly consistent with the EMSS redshift distribution. The present data provide the best direct evidence for the linearity of the fluctuations in the Universe on scales greater than several tens of Mpc at those early redshifts.
2.6 The spectrum of the fluctuations
A further potentially valuable source of information on source properties at relatively faint flux levels is provided by the spectral characteristics of the spatial fluctuations in the XRB. We have extracted the spectral form of the fluctuations by subtracting the average spectrum of “negative” fluctuations from that of “positive” fluctuations. (The spectral parameters are very mildly dependent on the definition of “negative” and “positive” fluctuations).
The resulting spectrum was then analysed by a standard model fitting procedure. We assume a power-law spectral form and initially fit the data over the 2–11 keV range. The fit was formally acceptable and the derived spectral parameters were and (errors are for 2 interesting parameters). Since the fluctuations are dominated by sources with a surface density of roughly one per beam, this reflects the average spectrum of sources producing about 10 per cent of the 2–10 keV XRB. It is notable that the fluctuation spectrum has a power-law slope which is typically of Seyfert 1 galaxies in the 2–10 keV band. Of interest, however, is an extrapolation of the best fitting spectrum to higher energies. This reveals an apparent hardening of the spectrum above 10 keV. Indeed, the simple spectral model described above did not yield a statistically acceptable fit over the 2–18 keV band (). In this case the derived spectral parameters were and but, in view of the bad fit, clearly these should be treated with caution.
The apparent “hard excess” is reminiscent of the features apparent in spectra of Seyfert 1 galaxies, which have been attributed to a Compton reflection bump (e.g., Pounds et al. 1990). In fact the inclusion of a Compton reflection component in the current analysis results in a significant improvement in the 2–18 keV spectral fit (). In this case the spectral parameters were , with the fraction of reprocessed flux being 50%. Figure 5 shows the measured spectrum of the fluctuations and the best fitting model including a reflection component.
3.1 The 2–10 keV X-ray source counts
The 2–10 keV source counts for bright () extragalactic sources have been determined from the Ariel 5, Uhuru and HEAO-1 A2 all-sky surveys (Warwick & Pye 1978; Schwartz 1979; Piccinotti et al. 1982). There is good agreement between the three surveys on the normalisation of the source counts, which is hardly surprising given the fact that the small “statistical samples” derived from each survey (typically sources in each case) overlap to a considerable extent. The derived slope of the bright source counts is marginally steeper than the Euclidean value, but this appears to be due to the chance distribution of a few nearby sources rather than being of direct cosmological significance (Piccinotti et al. 1982). At fainter levels we must rely on spatial fluctuation measurements. This is illustrated in Fig. 6 which shows the form of the 2–10 keV differential source counts derived from the Piccinotti discrete source sample and from both the HEAO-1 A2 (Shafer 1983) and present Ginga fluctuation measurements.
The HEAO-1 A2 fluctuation measurements best define the source counts at flux levels about a factor 6 below the threshold of the Piccinotti sample, whereas the new Ginga results provide additional constraints at flux levels a factor of 30 below the Piccinotti limit, a flux which will only be directly probed by imaging medium energy telescopes.
The discrete source and spatial fluctuation data taken together constrain the relation to a form close to the Euclidean prediction over almost 3 decades of flux. Specifically the 2–10 keV differential counts are consistent with:
over the range (2–10 keV).
We note that although the fluctuation measurements include a contribution from Galactic sources (which are, of course, specifically excluded from the discrete source sample), the net effect of Galactic sources, particularly at the lower flux levels, will be small ( per cent contribution to at ). Similarly the effect of possible large-scale structure in the XRB, for example due to Galactic diffuse emission and the Compton-Getting anisotropy, is unlikely to introduce a significant bias (Shafer 1983; Carrera et al. 1991). As we noted earlier, source clustering might contribute to an overestimate of the source counts, but it would have to be implausibly strong to seriously affect our conclusions (Carrera et al. 1993).
The fact that the extragalactic source counts have a slope close to the Euclidean value necessarily implies some cosmological evolution of the source population, since the effects of relativistic geometry will be quite pronounced even for the modest redshifts which correspond to source luminosities typically in the range .
3.2 Comparison with soft X-ray source counts
The Ginga fluctuation studies extend the 2–10 keV source counts to flux levels encompassed in the 0.3–3.5 keV band by the EMSS (Gioia et al. 1990b) and it is clearly of interest to compare the relations derived in the two spectral regimes.
In principle such a comparison requires knowledge of the spectral properties of the contributing source populations over a wide energy range (0.3–10 keV). However, a convenient simplification (e.g. Boldt 1988) is to define an average spectral conversion factor :
where is the flux measured in the 2–10 keV band and is the corresponding value in the 0.3–3.5 keV band.
If a particular value of applies to the whole source population then the differential source count normalisation in the two bands are related by:
For a source with a power-law spectrum of spectral energy index (the so-called canonical spectral slope for AGN) and negligible low-energy absorption (we actually assume a minimum line-of-sight column density of ), then . Figure 7 shows the effect on of varying the power-law slope and intrinsic absorption. Using , the extragalactic relation from the EMSS (Gioia et al. 1990b) transforms to the dotted line in Fig. 6. Clearly the above assumptions lead to the conclusion that our fluctuation analysis produces a significant ( i.e., a factor ) overestimation of the soft X-ray source counts, as measured by the Einstein Observatory.
To reconcile the EMSS and 2–10 keV source counts requires for the source population as a whole. This implies either a continuum spectrum which is significantly less steep than the canonical form ( i.e., ) or a spectrum which is cut-off at low energies, presumably due to X-ray absorption in relatively cold line-of-sight gas intrinsic to the source. For the canonical spectral slope, implies . This is barely consistent with the upper limit for photoelectric absorption found in the spectrum of the fluctuations (but see below). Nevertheless given the available information on the spectra of extragalactic X-ray sources (e.g. Maccacaro et al. 1988), a solution in terms of absorption would seem to be the more tenable.
The EMSS results (Gioia et al. 1990b; Stocke et al. 1991) confirm that AGN, namely Seyfert galaxies and QSOs, comprise the dominant source population at intermediate flux levels with other classes of source (clusters of galaxies, normal galaxies and BL Lac objects) providing up to a 25 per cent contribution to the extragalactic source counts. Since it is well established that low luminosity AGN preferentially exhibit intrinsic absorption (e.g. Reichert et al. 1985; Turner & Pounds 1989), it would seem reasonable to infer that it is this class of source which is under-represented in the EMSS. The presence of such a spectral selection effect may well account for at least part of the flattening in the luminosity function of AGN below reported in EMSS sample (Maccacaro et al. 1991). Observations of individual Seyfert I galaxies suggest that intrinsic absorption is common in sources with luminosities less than about (Turner & Pounds 1989). Also, it is well known that the more numerous Seyfert 2 galaxies show strong absorption. Absorption by a column density of will strongly suppress the emission in the soft band of the EMSS (0.3 – 3.5 keV) but have little effect on the 4 – 12 keV band of Ginga.
In order to test the above hypothesis we have constructed simple model X-ray source counts. We calculated the cluster contribution taking into account the cluster luminosity function of Edge et al. (1990), the negative evolution shown by the clusters (Edge et al. 1990; Gioia et al. 1990a) and the observed temperature luminosity relation (Edge & Stewart 1991). The residual source counts were then compared to the model predictions for AGN. We used the AGN luminosity function of Piccinotti et al. (1982) and assumed luminosity evolution of the form (see e.g. Maccacaro et al. 1991; Boyle et al. 1992). An energy index of 0.7 is assumed. Intrinsic absorption corresponding to a column density of is applied to all the AGN with luminosities below . An important parameter is the assumed minimum luminosity of the AGN population, , which controls the total contribution of AGN to the X-ray background. In practice we expect there to be a break to a flatter luminosity function but here we simply truncate the luminosity function at .
After searching parameter space we find that , and , give total (AGN plus cluster) source counts which agree with Piccinotti et al. (1982), the source counts derived from the found here and the EMSS counts (see Figure 8).
The summed spectrum of the sources brighter than is shown in Fig. 9. It is seen that it is well fit over the 3–12 keV band by a power law with , the softer spectra of the clusters having steepened the total spectrum slightly. It is in reasonable agreement with the observed 2–10 keV spectral fluctuations. Significant deviations from a power law are only clear below 3 keV, where the absorption from the low-luminosity AGN becomes effective. The total AGN contribution at 4 keV, extrapolating the best fit model to low fluxes and integrating to a maximum redshift of 2.5, amounts to 63 per cent of the observed background intensity. The uncertainty on this figure is difficult to quantify - it depends on , and other parameters not constrained by the Ginga fluctuation results. While the uncertainty could, in principle, be per cent, the model would then have the wrong spectral shape at 4 keV. Smaller values of do not give enough difference between the and the EMSS counts. Larger values, or the same value extending to a higher , start to affect the predicted fluctuation spectrum significantly. In reality we expect that there are distributions of , and , so that not all low luminosity sources are affected in the same way. Without much better samples of AGN spectra to constrain so many variables, we cannot be more specific about the details at the present time. We require simply that the appropriately weighted means of these distributions influence the spectra and counts in the same manner as the results quoted above.
Note that the effects of redshift and absorption mean that the apparent luminosity evolution of sources in our model appears steeper in soft X-rays than in harder X-rays. Current estimates of the luminosity evolution of AGN based upon soft X-ray luminosity functions are overestimated if some correction for luminosity-dependent, intrinsic absorption is required and not made. This means that X-ray evolution, which without such corrections is slower than at optical wavelengths, is even slower than previously assumed. Whether there are similar corrections to be applied to reddened Seyfert 2 galaxies, for example, in the optical band remains to be seen.
The main conclusions from our analysis of the spatial fluctuations in the XRB measured by Ginga are as follows:
1. The relation in the 2–10 keV band follows the form, , down to . The surface density of extragalactic X-ray sources at this flux limit is object per square degree at which point approximately 10 per cent of the 2–10 keV XRB intensity is directly accounted for in terms of discrete sources.
2. The excess variance technique provides a tight upper limit to the inhomogeneities in the source distribution and direct evidence for the large scale isotropy of the Universe out to redshifts .
3. The spectral properties of the XRB fluctuations are consistent with the average 2–10 keV source having a spectral slope close to the canonical AGN value. Tentative evidence for high energy hardening is found which might be interpreted in terms of a reflection bump present in the sources that dominate the fluctuations. The softer spectra of clusters contributing to the fluctuations may partly mask the absorption in the AGN component.
4. The normalisation of 2–10 keV source counts is a factor of 2 – 3 above that derived from the EMSS if a spectral conversion is assumed which ignores absorption effects. It is proposed that the EMSS under-estimates the number of low-luminosity AGN as a result of intrinsic absorption. The revised estimate of the surface density of extragalactic sources is of particular importance when considering the confusion limit of imaging systems operating above keV. For an X-ray mission with with an effective resolution of , the confusion limit will be reached at a flux of about .
The work described in this paper was completed in late 1994 but due to a number of unfortunate compounding factors its publication has been subject to protracted delay. In the interim there have been major developments in the field stemming from the source counts measured by ROSAT and ASCA. The ROSAT source counts reach unprecedently faint levels in the soft X-ray (0.5–2 keV) band revealing a high density of sources ( at ) which contribute over half of the X-ray background in this band (Hasinger et al. 1993; Branduardi-Raymont et al. 1994; Georgantopoulos et al. 1996). However, in the relevant flux range, the ROSAT source counts are fully consistent with the earlier EMSS results; thus our detailed comparison of the Ginga results with those from EMSS is still valid. In the medium energy 2–10 keV X-ray band to which our fluctuation measurements apply, estimates have recently become available of the discrete source detection rate in deep ASCA observations. These preliminary results from ASCA, albeit based on limited source statistics (e.g. Inoue et al 1996; Georgantopoulos et al. 1997), appear to be in very good agreement with the Ginga measurements in terms of the normalisation of the log N - log S curve at a flux of . The existence of a major X-ray source population characterised by either intrinsically flat or absorbed spectra is thus confirmed. For a review of other recent developments relating to our understanding of the wide-band X-ray to Gamma-ray extragalactic background, see Hasinger (1997).
We thank Rees Williams for his help in modelling the Ginga background during the early stages of this work. JAB acknowledges the receipt of a PPARC Research Studentship. ACF thanks the Royal Society for Support. Partial financial support to FJC and XB was provided by the DGES under project PB95-0122. This work made use of the STARLINK node at Leicester which is funded by PPARC.
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LABEL:Stocke J.T., Morris S.L., Gioia I.M., Maccacaro T., Schild R., Fleming T.A., Henry J.P., 1991, ApJS, 76, 813
LABEL:Turner, M.J.L. et al., 1989, PASJ, 41, 345
LABEL:Turner T.J., Pounds K.A., 1989, MNRAS, 240, 833
LABEL:Warwick R.S., Pye J.P., 1978, MNRAS, 183, 169
LABEL:Warwick R.S., Stewart G.C., 1989, In: X-Ray Astronomy, 2. AGN and the X-ray Background, Eds. Hunt J., Battrick B., ESA SP-296, Noordwijk, 727
LABEL:Warwick R.S., Butcher J.A., 1992, In: Frontiers of X-ray Astronomy, Eds. Koyama K., Tanaka Y., Univ. Acad. Press, Tokyo, 641
5 Figure Captions
Figure 1. The distribution of background observations obtained from the Ginga database shown in galactic coordinates. The concentration in the bottom right hand corner corresponds to background observations made during the regular monitoring of SN 1987A.
Figure 2. The measured histograms (a) in the 2–4 keV band and (b) 4–12 keV band, together with the best fit model predictions (filled circles).
Figure 3. One sigma and 90 per cent contours in the parameter space for (a) the 2–4 keV band and (b) the 4–12 keV band. is in units of (LAC ct.
Figure 4. Upper bounds to inhomogeneities as a function of comoving scale based on the two-sigma upper limits to the excess fluctuations from HEAO–1 A2 and Ginga. It is assumed that fluctuations come from a redshift range around .
Figure 5. The spectrum of the fluctuations (top panel) and the residuals (bottom panel) after fitting a model including a reflection component.
Figure 6. The differential source counts in the 2–10 keV band normalized to . Points are from Piccinotti et al. (1982), the dashed contour is the 90 per cent contour from HEAO–1 A2 fluctuations (Shafer 1983) and the solid curve is the 90 per cent contour from the present fluctuation analysis. The dotted line shows the EMSS prediction assuming (see text). The dash-dotted line to the left represents the boundary of the region where a particular power-law extrapolation completely produces the XRB.
Figure 7. Curves of constant for values of photon spectral index, , and absorbing column, , typical of AGN.
Figure 8. The integrated source counts from the AGN model described in the text. The upper solid line represents the fiducial model in the 2–10 keV band after subtracting the cluster contribution. The lower solid line corresponds to the EMSS measurement. The dashed and dotted lines correspond to the integrated counts from AGN in the hard and soft bands respectively. The flux units are for the hard source counts and for the soft counts.
Figure 9. The cumulative contribution (lower solid line) of AGN (dotted line) and clusters (dashed line) brighter than a 2–10 keV flux of is compared with the intensity of the XRB obtained from Gruber’s (1992) formula (upper solid curve). The best-fitting power-law in the range 3–12 keV to the AGN contribution is shown by the dash-dotted line. It has an energy index of 0.76, slightly steeper than that of the underlying AGN spectra of index 0.70.
Table 1. The parameters of the best-fitting source-count models. The normalisation values are quoted in both count rate and flux units.
|2–4 keV Band||4-11 keV Band|
in units of .
in units of .


And our preference for sporty models will see Lexus put its performance-oriented F Sport models.
The F Sport vehicles represent almost half of IS350 sales and around a quarter of IS250s.
“Lexus is committed to growing its performance portfolio – with two more F Sport models destined for launch next year,” chief executive Tony Cramb said.
The growth in F Sport model sales is also reflected in Lexus Australia doubling its order of LFA vehicles from an initial allocation of five to 10 of the limited-build $700,000 supercars.
The $700,000 LFA is made from carbon fibre and exotic alloys and is powered by a 4.8 litre V8 with 412kW and 480Nm. That power is fed through a six-speed automatic transmission and gives the lightweight car a 0-100km/h time of 3.9 seconds.
“Australia is viewed as a yardstick for the rest of the world, and our increased allocation of LFAs demonstrates the strength of the brand locally and the importance we hold in the global Lexus market,” Lexus Australia chief executive Tony Cramb said.


text:
by Gregg Meadows
Coach Todd McLoughlin’s Tri-Valley boys basketball team didn’t get caught looking ahead to a hoped for shot at No. 1 seed Meadowbrook, as the Dawgs took care of business Wednesday night at the Eastern District Division II district semi-final at Cambridge High School, dispatching seventh-seeded St. Clairsville by a 69-48 count.
With the win, Tri-Valley – now 19-5 – advances to Saturday night’s district final vs the top seeded Colts (22-3), who dismantled Claymont 66-26 to reach the title game, which will be played at Muskingum University with a 7:00 p.m. tip-off.
In the St. Clairsville win, the Red Devils provided some stiff competition for the Scotties in the early going, with several lead changes between the two teams in the first quarter, before the Scotties took a slim 15-14 lead ahead to the second period. Scottie sophomore Luke Lyall’s trey and baseline jumper for five points led TV in the first frame, while Ty Smith converted a pair of layups for four points, Keaton Williams a traditional three-point play, and senior leading scorer Skye Bryan a trey as well.
Second stanza action saw scrappy St. Clairsville edge ahead of the Dawgs in the first few minutes of the period, as the Red Devils owned a brief 18-15 lead before Tri-Valley got going in a big way, as Scottie guards Ty Smith and Skye Bryan took control of the game – on both ends of the floor – leading a 10-0 run and combining for 13 of the team’s 16 second period points, while turning up the pressure on defense as well to create Red Devil turnovers into points. Smith struck for nine points in the quarter and Smith four, helping the black and gold to a 31-23 halftime lead.
The Scotties couldn’t quite shake completely loose from St. Clairsville in the third quarter of district semi-final action, and despite seven Skye Bryan counters and three points each from Jalen Goins-Chandler, Keaton Williams, and Jack Lyall, took a less than commanding 49-39 lead into the fourth quarter.
But as the saying goes, the Scotties ‘put the pedal to the metal’ in the final eight minutes of play, outscoring the Red Devils 20-9 in the fourth quarter, to win going away, 69-48.
Keaton Williams and Skye Bryan led the fourth frame fireworks for the Dawgs, scoring eight points apiece with Jack Lyall adding his final four counters as well.
Skye Bryan led the winners in scoring with a game-high 22-point effort, getting double-figure help from Keaton Williams with 17, and Ty Smith with 15. Will Balgo’s 11 points and ten from Drew Sefsick led St. Clairsville, who exited the tournament trail with a 13-11 record on their season.
Tri-Valley and Meadowbrook share common opponent wins over Zanesville, John Glenn and Philo for the 2019-20 regular season. Scottie head coach Todd McLoughlin knows the highly-touted and top-seeded Colts will be a huge challenge for his team, noting their size, good guard play, and experience; Meadowbrook was a final four contestant just two seasons ago.

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Democrats have also spoken out and theirs is the voice of reason and common sense. If you too can see through all this hot air and fallacies then email: firstname.lastname@example.org on the representation form, which can be down loaded at http://fenland.newgrove.com/App/DiscussIt/Content/CoreStrategy/Proposedsubmsn%20Representation%20Form.pdf.


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Tactical charging handle has an oversized lever on the left side that folds against the receiver to present a slim, no-snag profile during carry or storage. Opens instantly to give you a larger grasping surface than the standard-issue handle, so you can find it and cycle it faster. Deeply serrated front face ensures non-slip hand contact for positive operation on the first attempt in all conditions. Lever angles down slightly when retracted, so it won't interfere with a scope or sight mounted on the receiver rail. Drop-in ready for a mil-spec AR-15/M16 upper receiver; no gunsmithing required. Machined from billet 7075 T6 aluminum-the same material USGI receivers are made fromMfg: Brownells SPECS: 7075 T6 aluminum, hardcoat anodized, black. 2 1/2"" (6.35cm) wide open, 15/16"" (3.4cm) wide folded.
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Brownells Ar-15/M16 Para-Trooper Charging HandleTactical charging handle has an oversized lever on the left side that folds against the receiver to present a slim, no-snag profile during carry or storage. Opens instantly to give you a larger grasping surface than the standard-issue handle, so you can find it and cycle it faster. Deeply serrated front face ensures non-slip hand contact for positive operation on the first attempt in all conditions. Lever angles down slightly when retracted, so it won't interfere with a scope or sight mounted on the receiver rail. Drop-in ready for a mil-spec AR-15/M16 upper receiver; no gunsmithing required. Machined from billet 7075 T6 aluminum-the same material USGI receivers are made fromMfg: Brownells SPECS: 7075 T6 aluminum, hardcoat anodized, black. 2 1/2"" (6.35cm) wide open, 15/16"" (3.4cm) wide folded.
Badger Ordnance Ar-15/M16 Gen 3 Ambidextrous Charging HandleThe 5.56 Gen 3 Ambidextrous Charging Handles from Badger Ordnance have an oversized design to provide easier manipulations. These charging handles allow for use of either the finger and thumb grip or the palm of the hand to be used to charge the rifle on both the strong and support side. Mfg: Badger Ordnance
Brownells Ar-15/M16 Oversized Charging Handle LatchTactical charging handle latch has an extra-large, deeply grooved finger pad for positive contact that helps you charge the weapon quickly under stress. Pad angles out 90deg from the receiver so you can slap at the latch and get a secure grasp even with gloves on. Made from extra-strong 4340 chrome-moly steel hardened to Rc 38-45, with a tough manganese phosphate Parkerized finish for added surface strength and corrosion resistance. Fits mil-spec AR-15/M16 charging handle (not included) . Mfg: Brownells SPECS: 4340 chrome-moly steel, Parkerized, matte black. Finger pad is 5/8"" x 5/8"". 0.4 oz. (11.3g) weight.
Brownells Ar-15/M16 M&A Ambidextrous Latch Charging Handle KitEasy-to-build kits contain all the components needed to assemble a tactical charging handle that aids in fast action drills, efficient jam clearing, and smooth operation. All kits are built around a stripped DPMS factory charging handle machined to stringent mil-spec standards for proper fit and dependable function. Each kit also comes with latch spring and roll pin. Badger kit features an oversized latch that's easy to find and operate with the left hand. M&A Ambidextrous kit includes a large, extended latch lever that's easy to grab and allows rapid operation of the handle with either hand. Mfg: Brownells SPECS: Aluminum charging handle, matte black finish. M&A Ambidextrous Aluminum latch, matte black. Latch approx. 23/8"" (6cm) long.
Precision Reflex, Inc. Ar-15/M16 Tactical Charging Handle LatchesMilitary Latch has smooth latch face with round edges that is easy on your fingers, less painful during lengthy firing sessions. Mfg: Precision Reflex, Inc. SPECS: Aluminum, hardcoat anodized, matte black.
Badger Ordnance Ar-15/M16 Left-Hand Charging HandleMachined aluminum charging handle has an extended latch on the right side to enable fast, positive operation by left-handers. Gives both left- and right-handed shooters a tactical advantage in combat or competition to clear jams quickly, and operate the handle even if one hand becomes incapacitated. Extended right-side latch is machined from ordnance-grade steel and features a large, 5/8"" square contact pad that projects 3/4"" from the handle. It's easy to find under stress and provides extra leverage to release the latch and cycle the handle quickly. Also useful on a rifle with a large scope that limits access to the standard charging handle. Mfg: Badger Ordnance SPECS: Aluminum, hardcoat anodized, matte black finish. Extended Latch - Steel, black oxide finish. Fits mil-spec AR-15/M16/M4 and clones.
Dpms Ar-15/M16 Charging Handle SpringAR-15/M16 CHARGING HANDLE SPRING Mfg: Dpms
Wmd Guns Ar-15/M16 Nib-X? Charging HandleReplacement charging handle offers a quick reliability upgrade to your AR. Lightweight aluminum construction keeps weight to a minimum, while the super-slick, self-lubricating NiB-X nickel-boron surface coating ensures smooth cycling and gives nothing for fouling or grit to adhere to, so it facilitates quick, easy cleaning, too. Mfg: Wmd Guns SPECS: Aluminum, NiB-X nickel boron coating, silver-gray finish. 6 3/4"" (17.1cm) long. 2"" (5cm) wide gasping surface. Fits mil-spec AR-15/M16 upper receivers.
Dpms Ar-15/M16 Stripped Charging HandleMfg: Dpms
Dpms Ar-15/M16 Charging Handle Roll PinAR-15/M16 CHARGING HANDLE ROLL PIN Mfg: Dpms
|Kundenrezensent||Ehrenzeichen||Zuletzt erreicht||Rezensionen insgesamt||Hilfreiche Stimmen|
Hall of Fame in 9 verschiedenen Jahren erreicht
Hall of Fame in 8 verschiedenen Jahren erreicht
|Fuchs Werner Dr||2012||3.543||39.519|
Hall of Fame in 7 verschiedenen Jahren erreicht
Hall of Fame in 6 verschiedenen Jahren erreicht
|Christian von Montfort||2010||1.003||14.122|
Hall of Fame in 5 verschiedenen Jahren erreicht
|Dr. R. Manthey||2014||1.607||31.730|
Hall of Fame in 4 verschiedenen Jahren erreicht
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Hall of Fame in 2 verschiedenen Jahren erreicht
|Mark Andreas Giesecke||2003||191||2.822|
In die Hall of Fame aufgenommen
|My Hits for Family & Kids||2016||2.282||8.845|
|Andreas & Simeon||2012||698||7.130|
|Joe "Gratias ago"||2016||1.063||5.955|


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text:
Here’s Enimems new song “We Made You”. I’m looking forward to his new album “Relapse 2”, which should be out next month :)
This video seems to be following the same formula as his first song from the last few albums i.e. making fun of celebrities and politicians. It’s getting a little bit repetative but the songs ok. Most of my favourite songs from his albums were not released as singles anyways so I think the album will be good.

domain: artistic


text:
Government Is 'Handcuffing' Private-Sector Health Care Innovation
Instead of interfering in private innovation, Washington needs to let new ideas thrive.
Washington can take important steps now to fix one of the biggest problems in our health care system: Medicare's broken fee-for-service structure. This method of payment encourages providers to see as many patients and prescribe as many treatments as possible. The program does nothing to reward providers who keep patients healthy. These misaligned incentives drive up costs and hurt patient care. The new health care law unfortunately did nothing to address these problems.
The most important thing that Washington needs to understand is that there is no single solution for every family or every patient. Unfortunately, when we mandate funds for a specific purpose like health insurance, many people are confronted with the reality of fewer choices and higher costs.
There are a number of steps that can be taken to address this growing problem. Value-based insurance would help realign the incentive structures for delivering health care services by reducing copays for high-value services and increasing copays for low-value or excessive services. Shifting the health care delivery system from one that pays and delivers services based on volume to one that pays and delivers services based on value is an idea that unites both Republicans and Democrats. Consumer-directed health plans provide another avenue for linking financial and delivery system incentives, and have the potential to reduce health care spending by $57 billion per year. Bundled payments will support more efficient and integrated care. All of these options have already been utilized by a number of private sector firms with great success.
Our nation has made great strides in improving the quality of life for all Americans, and every major legislative initiative that has helped transform our country was forged in the spirit of compromise and cooperation. These qualities are essential to the success and longevity of crucial programs such as Medicare and Medicaid. But when it comes to health care decisions being made in Washington lately, the only thing the government is doing well is increasing partisanship and legislative gridlock.
We still need health care reform, but it has to be done the right way. The federal government should be willing to support viable reforms where it is needed, but also refrain from handcuffing innovative private sector designs with excessive regulations or narrow political interests. Providing Americans with access to high quality, affordable health care is something I am confident both Democrats and Republicans should be able to agree upon.


- This event has passed.
A Tale of Two Brians: Brian Wolfe and Brian Larney
November 6 @ 7:00 pm - 9:00 pm
- 07:00 pm
- The Buttonwood Tree
BEPW (Brian Ebin Parker Wolfe) has been writing and performing original music on acoustic and electric guitar since the late Sixties. His earliest gigs at The Exit Coffeehouse shaped his ambition to do little more than hang out on the New Haven Green for most of his young adult life. Little has changed since then, beyond the weight of time. BEPW is a solo effort, though he is often joined on stage and in the studio by his wife Rose on vocals and their compatriot Bobo Lavorgna on bass—the nucleus of the Ebin-Rose Trio. Brian Larney is an eclectic, non-stop music making machine. The Connecticut native splits his time performing as a solo acoustic act and as the front-man of the Brian Larney Band.
The Buttonwood Tree set will include Rose and Bobo was guests. The songs will be from BEPW’s debut EP “Passage” and it’s follow up EP “Second Hand World”.
Passage – “The act or process of moving through, under, over, or past something on the way from one place to another”.
The Passage EP is five songs, ten minutes long in total. It’s perfect for our times or lack of time. “I’ve Moved On” was written for a movie soundtrack coming out next year.
“Passage,” The electric & acoustic instrumentals that bookend the EP, were recorded directly into my iPhone, and cleaned up at The Coffeehouse Recording Studio.
“Hide Away” – “If there was ever just one song that totally represented the 1967 NY/SF vibe, this could be it. Started out like Santana, morphed into Pearls Before Swine and then went straight to early Jefferson Airplane”. – Ed Maxin (No Depression/ The Real Easy Ed).
“Station Man” – is about listening to DJs play the music all night long while trying to fall asleep. It is inspired by my earliest Rock & Roll memories as a young kid in the early Sixties, playing the radio at night in bed with an earphone in the dark so my parents would not know, and how the DJs were spirit guides.


text:
For the woman who wants an edgy, non-conformist look and who needs a hairstyle to counter overly-soft babyish features - with angles and edges - this short style fits the bill. The buttery-blonde hair is cut with a randomized, almost organic sense of balance. The haircut is haphazard, but only on the surface.
The layers are meant to appear choppy and almost accidental, but they give texture and interest to a short hairstyle that takes it from a "typical" look to one that's guaranteed to make people take notice.
Recreate the styling using a blow dryer with a sculpting paste and direct the hair forward slightly in the back and at the sides.
Collection: New York
Hair: BIBA Creative Team Australia
Hairstyles for short hair
Choppy short bob with varying lengths
Feisty short haircut with peaks and flips


text:
Location And Contact
Cape D'Aguilar Road, Cape D'Aguilar, Hong Kong SAR, China.
To Get There
Start Walk from the Cape D'Aguilar, Cape D'Aguilar Road Bus Station
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domain: geography