Follow-on Science Instrument

Contract NAS8-01129


Monthly Status Report No. 006

August 2002

HETG Science Theme: Galaxies and Clusters


Prepared in accordance with DR 972MA-002

DPD #972

Prepared for

National Aeronautics and Space Administration

Marshall Space Flight Center, Alabama 35812


Center for Space Research; Massachusetts Institute of Technology; Cambridge, MA 02139



Galaxies and Clusters Research Progress


Introduction to Clusters

X-ray observations of clusters provide unique and important insights into a wide range of astronomical topics. As the largest gravitationally bound objects in the universe, clusters of galaxies are important tracers of the large scale distribution of matter. Cluster mass estimates based on X-ray observations provide strong constraints on various cosmological models and independent checks on masses determined from optical velocity dispersions and gravitational lense studies. In addition, X-ray images and spectra allow determination of the physical state of the intracluster medium(ICM) itself. The temperature and abundance structure of the ICM represents a fossil record of the origin and evolution of the gas in the cluster over its lifetime. While the presence of shocks, cold fronts, mergers, AGN interactions, and other phenomena provide clues to various ongoing physical mechanisms which drive the state of the ICM.


Galaxy clusters frequently have high X-ray surface brightness cores due to thermal emission from dense gas. Absent a substantial and persistent heat source, this high density, relatively low temperature gas should cool on a timescale that is much less than the age of clusters, leading to a so-called ``cooling flow''. The cooling rates reported from the low resolution X-ray observatories that operated throughout the previous two decades were often extraordinally large, and frequently exceeded several hundred to over two thousand solar masses per year. Such large cooling rates posed a dilemma. They imply the presence of enormous sinks of cold gaseous and stellar matter in the cD galaxies found at the centers of cooling flows. Although substantial amounts of cold gas and vigorous star formation are routinely found in cD galaxies centered in cooling flows, they are found in quantities that are much smaller than the cooling rates would imply.


The high spatial resolution imaging provided by Chandra has dramatically changed our view of cooling flow clusters. Images of the cooling flow regions of clusters now show a great deal of structure, including the large cavities or bubbles in the X-ray emission associated with the radio sources harbored by the central cluster galaxies. The strong interactions between the radio sources generated in the nuclei of cD galaxies and the surrounding X-ray emitting gas may reduce the cooling rates and bring them more in line with the star formation rates. Chandra's superb spatial resolution provides the first opportunity to actually map the temperature structure of the keV gas on fine spatial scales, which permits a direct comparison between the sites of star formation seen at optical and ultraviolet wavelengths, and sites of rapid cooling. In essence, we can now reevaluate the proposition that cooling flows are fueling star formation by comparing the cooling and star formation rates on the same spatial scales. In addition, the newly revealed complexity of the gas in cluster cores has sparked a revaluation of several possible heating mechanisms, such as AGN heating, heat conduction from the hoter outer layers of clusters, and supernovae.


Spectroscopically, Chandra and XMM observations of cluster cores are yielding surprising results as well. Naively, one expects that once rapid cooling begins, the gas should rapidly cool below X-ray emitting temperatures as long as no comparable heating source is present. Given this assumption of ``full cooling'', one expects to see X-ray emission lines from gas over the full range of temperatures from that of the hot, ambient medium down to very low temperatures. One can show that the strength of these emission lines is directly proportional to the total cooling rate. Recent XMM RGS observations and the Chandra HETG observations discussed here seem to contradict this simple picture. Neither observatory has yet detected emission lines from cooling cores corresponding to gas temperatures less than about 3 keV. In a way, this eases the earlier dilemma: if the gas is *not* cooling to very low temperatures, the reason why we don't see sufficient cool material in other wavebands becomes clear. Unfortunately, this result raises a deeper problem: why doesn't the gas cool below 3 keV?



Other Introductory material on Galaxies and Clusters is available at:

1) The web page for the course “Astronomy 1120” from the University of Colorado at Boulder:

http://cosmos.colorado.edu/astr1120/lesson10.html .

2) A Power Point presentation from GSFC’s X-Ray Astronomy School:

http://heasarc.gsfc.nasa.gov/docs/xrayschool/Clusters_files/Clusters.ppt .



Summary of Galaxy/Cluster GTO Observations and Activities

There have been 3 galaxies and 3 clusters of galaxies in the HETG GTO program to date as given in the table below. The targets have sufficiently small sizes to give better-than-ACIS resolution with the HETG. However, spatial-spectral complexity, background subtraction, and low signal-to-noise make analysis of these data difficult. To date, these observations have yielded only upper limits which do not place restrictive constraints on the presence of soft X-ray emission lines from cool gas (e.g. OVII and FeXVII).

In parallel, we are doing scientific work on clusters, for example studying cluster evolution in the universe by making use of non-grating imaging observations of clusters that are in the Chandra archive and by making temperature maps of clusters, both described below.









Image size




(, MEG)





NGC 4696


~ 15”


Substructure; cD in Centaurus cluster




NGC 4486 = M87


~ 45”


AGN/Jet; cD in Virgo cluster




NGC 1399


~ 16”


Underexposed; cD in Fornax cluster




ZW 3146


~ 11”






Abell 1835


~ 15”


Bi-modal core




PKS 0745-191


~ 35”














NGC 720


~ 60”


Archival galaxy data (Garmire GTO.) Shows discrete sources.




EMSS 1054.5-



~ 45”


Archival cluster data (Garmire GTO.) High-Z cluster.


HETG Observations of the Clusters ZW 3146, Abell 1835, and PKS 0745-191

The goal of the grating cluster observations is to detect or put upper limits on the strength of low-energy X-ray emission lines from the clusters. Although these objects are extended, the HETG should be able to clearly resolve emission lines of Fe XVII at 15 and 17 and O VIII at 19 and lines of Ne, Mg, and Si at shorter wavelengths --- if they are present and strong.


The flat-fielded, flux image of the 0th order region for PKS 0745-191 is shown at left. The solid circle indicates a radius of 0.5 Mpc; used to estimate the total cluster mass, Hicks et al. (2002). The HEG and MEG extraction regions are shown by the green dashed lines --- dispersed events can be seen extending to the top and bottom of the image.


At right, events in the extraction region are plotted in a “banana plot” which shows the ACIS-measured energy plotted against the dispersion distance. The distinct curved bands are the different diffraction orders.

(Data here are from ZW 3146.)


         Creating a histogram of the dispersion distance of the diffracted events and correcting for the HETGS effective area gives the fluxed spectrum of ZW 3146, below. The location of some of the low-energy emission lines expected from a cool X-ray gas are shown and labeled (green) at what would be their observed wavelength; that is, at a redshift of 0.29. Given the size of the error bars (blue) and some residual background we have no clear detection of lines here but can place upper limits on the emission.


HETG Observation of the Elliptical Galaxy NGC 4696 (in the Centaurus cluster)

The X-ray emission from a galaxy comes from the discrete sources in it (stars, X-ray binaries, supernova remnants), from any central source (like a super-massive blackhole), and from the hot gas which fills the galaxy. The spectrum of a galaxy can therefore be crudely modeled as the sum of a power law component (X-ray binaries, AGN) and a thermal plasma component (stars, supernova remnants.)

The MEG m=-1 order data from the NGC 4696 observation are shown below with a superposed model in purple and slightly (z=0.01) redshifted emission line locations are indicated. Although in crude agreement including a hint of an O VIII line at 19, it’s clear that more modeling effort is needed for these data.

Temperature Map Analysis of Clusters

The combination of Chandra's spectral and spatial resolution allows one to actually map the gas temperature in extended objects whose resolution is limited only by the signal to noise of the data. We have developed a custom module within the ISIS spectral analysis package which automates the process of extracting spectra, generating appropriate ARFs and RMFs, and then fitting a given spectral model. This routine is fully general and can be used to map not only quantities such as the gas temperature in a thermal emission model, but any fit parameter, i.e. abundance, absorption column, or spectral index in a non-thermal, power-law model.


Maps are generated using a grid of adaptively sized extraction regions selected to contain a given minimum number of counts. For clusters, the drop off in surface brightness with increasing radius results in an increase in the size of the extraction regions with radius. Consequently, sharp spatial features are not well resolved in the outer parts of the maps. In the cores, however, the extraction regions range in size and can approach the size of the PSF for long exposures with high signal to noise.


The temperature map for the cluster ZW 3146 is shown at left with contours of X-ray flux superposed. Note the small near-central region with temperatures as low as 2 keV --- could gas at even lower temperatures of 0.5 to 1 keV be present? These CCD data are unable to tell hence our use of the HETG to look for low-T gas emission (above.)


Archival Research on Cluster Morphology

Using Chandra archival data, we are starting to quantify the evolution of cluster morphology with redshift. Recent ROSAT surveys have discovered tens of clusters with z>0.8 which are now being followed up with Chandra. At right is an image from the Chandra observation of the cluster MS 1054 at z=0.83 showing a complex internal structure.

With this sample the dynamical "age" of clusters at high-z can be compared to those at low-z. Clusters’ formation and evolution are highly sensitive to the mean matter density of the universe. We are quantifing cluster morphology and dynamical state using the power ratio method of Buote and Tsai (1996). These ratios are constructed from moments of the 2D potential and are capable of distinguishing a large range of cluster morphologies. We will also compare our results to simulated X-ray clusters (with help from Greg Bryan.)

Analysis Issues for HETG data of Clusters and Galaxies

Analysis of HETG spectra for significantly extended sources presents a number of unique problems. The current analysis is founded on a number of assumptions specific to point sources. These assumptions begin to break down for sources much larger than the PSF. We list some of the key issues here:

Wavelength Scale --- The mapping between dispersion angle relative to the 0th order position and photon energy assumes a single 0th order location can be defined. For a cluster, we cannot simply define a single 0th order position. Even in the absence of significant substructure in the object, photons from various position in the cluster (different radii for example) will each have a wavelength scale different from neighboring regions in the object. Using the current extraction region paradigm tied to a single 0th position guarantees that photons from positions in the cluster far from the center will have incorrect energies. Clusters represent the extreme case of overlapping spectra from multiple sources.


Contrast or Background Definition --- For point sources, the background is essentially negligible and is typically ignored during analysis. For extended objects, the definition of "background" is somewhat different. In the case of clusters, where we are interested in detecting soft emission lines from cool gas at the cores, the "background" is not the usual detector background but rather the spectrum of the hotter surrounding cluster gas. This conceptual issue is exacerbated by the fact that the CIAO software does not currently scale the extracted background spectrum according to area correctly for non-standard (non-point source) size extraction regions.


We note that cooling flow clusters are optimal targets for making this separation between source and extended background due to the large temperature difference between the two gas components. In the cores, gas is seen down to temperatures of ~2 keV while the more extended cluster gas typically has temperatures of 5-9 keV. The greater the contrast between the two components, the better.


Projection effects --- Since clusters are 3D objects, even photons dispersed from the same focal plane position actually sample many different points in the cluster and consequently many potentially different spectral distributions. The spectrum from any point in the cluster actually represents the superposition of a wide range of gas temperatures and densities. This projection effects imaging analysis as well as dispersed spectra and is not treated at all by current analysis software.


Galaxies and Clusters Plans and Further Work



-       Clusters PKS 0745-191, A1835, and Zw3146:

       Improve background subtraction

       Produce combined +/-1st order spectra


-       Galaxies NGC 4696, and '4486 and '1399:

       Investigate appropriate galaxy models to fit the data.

       Better background estimation/subtraction is needed for the HETG dispersed data.


-       Cluster archival morphology project:

       Continue modeling the spatial non-uniformity of the background to subtract from cluster images;

       Create “power ratios” software to evaluate cluster image morphology.


-       Algorithms and software:

       Implement 0th order based RMF profile routine in ISIS.

       Evaluate/implement Monte-Carlo and other techniques for fitting spatially varying spectral models to HETG data of extended sources.



MIT Accessibility