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modern astronomical data often consists of 2 high - resolution dimensions : e.g. , \{@xmath0 } for 2d sky images , \{@xmath1 } for spectral images as from a long - slit ( or slitless ) spectrometer , and \{@xmath2 } for time - resolved spectroscopy .
there is also a growing body of 3d or 4d data sets , \{@xmath3 $ ] } , being produced by instruments across the spectrum ( emsellem 2008 ) .
here we focus on the needs of the high - energy transmission grating ( hetg ) spectrometer on _ chandra _ ( canizares et al . 2005 ) : a slitless dispersive imaging spectrometer operating in the x - ray range of 0.3 to 8 kev , although the techniques and software ( s / w ) described here are applicable to other instruments as well .    for extended sources observed with the hetg ,
the dispersed data are 2d and combine spatial and spectral information ( dewey 2002 ) . a block diagram of the event-2d system used to analyze these data is shown in figure  [ pa.11-fig-1 ] .
some key ingredients are : the ability to model the 3d geometric - spectral properties of the source , appropriate instrument simulation to generate modeled 2d events from the source photons , the management and viewing of multiple 2d data sets , and a flexible and quantitative comparison of the real and modeled data .
event-2d is written in s - lang ( ) , a high - performance interpreted language which is also used in our general x - ray analysis system , isis ( houck & denicola 2000 ) .
s - lang / isis allows us to import ( interface to ) a wide variety of external modules ( gsl , volpack , etc . ) in order to extend available functionality ( noble & nowak 2008 ) .
this hetg s / w falls under the large umbrella of the hydra ( ) project at mit .
the following sections summarize the status of the main components of the current event-2d system .
the source-3d s / w allows models to be created as a combination of geometric components each having their own 3d geometry , spectral emission , and velocity properties .
examples of some of the geometric primitives provided by the v3d library are shown in figure  [ pa.11-fig-2 ] .
the v3d routines generate 3d arrays ( data cubes ) of values which can be combined , e.g. , through union and intersection , to produce more complex geometries .
the emission spectra associated with each component can be defined by the usual isis function specifications and `` .par '' files .
velocity properties including `` hubble - like '' expansion and orbital rotation can be included in the components ; these source motions are very important for the spectral imprints they leave via doppler shifts .
the user specification of a source model is most conveniently done through a custom s - lang script file which includes definition of the model parameters and rules for updating the model based on the parameters .
while this does require some `` programming '' on the users part , it is relatively simple and gives complete control of the model definition to the user : e.g. , direct access to the structures that define the spectral and the geometric components .
the source can include a foreground absorption component which is applied in the observer s rest frame , along with an optional instrument effective area ( or first approximation thereof ) allowing the photon monte carlo ( mc ) generation and subsequent detection to be more efficient . besides useful model visualizations ,
the main output of the model is the mc generation of `` photons '' with \{@xmath4 } values ; these can also be used outside of event-2d for other applications , e.g. , as input to an observatory s simulator .
data are loaded from _ chandra
_ fits event files into internal structures by specifying the 2 desired event tags , e.g. , \{skyx , skyy } or \{@xmath5,tg_d}. here also , it is convenient to create a user script to load the data sets .
several structures keep track of the instrument properties , the event data , and the viewing and binning parameters for each of the loaded data sets . since these structures are user accessible , custom analyses are facilitated .
x - ray instrument simulation is done by mc ray - tracing of appropriate fidelity .
the instrument knowledge is coarse but useful : an arf specifies effective area vs energy , a 2-gaussian approximates the on - axis psf , and the detector intrinsic energy resolution is specified by a simple equation , @xmath6 .
grating simulation includes period variation and cross - dispersion blurs .
the appropriate 2 simulated tags are then loaded into the model events for comparison with the data events , figure  [ pa.11-fig-1 ] .
the data and model can be compared by binning the events in a regular 2d grid ( image ) and calculating the usual @xmath7 of the residuals between them as shown for two cases in figure  [ pa.11-fig-3 ] .    the specific feature of the model that is being fit often guides the range and binning size for the comparison .
an important aspect of the fitting here is that the mc model itself contains `` noise '' : re - evaluation with the same input parameters does not give the identical model result .
this mc noise can be reduced below scientific relevance by `` over simulating '' , generating more events than in the data and scaling appropriately .
even so , the fitting has to be noise - aware and noise - tolerant .
a modified conjugate gradient fitting method and a markov chain mc method are available ; each of these requires user guidance in the form of providing a `` should make a noticeable difference '' size scale for each of the fitted parameters .
canizares , c.r .
2005 , , 117 , 1144 .
dewey , d.  2002 , in _ high resolution x - ray spectroscopy with xmm - newton and chandra _ , ed .
g.  branduardi - raymont , 14 .
emsellem , e.  2008 , talk at `` gas and stars in galaxies '' , + http://www.eso.org/sci/meetings/gal3d2008/program.html houck , j.c .
& denicola , l.a .
2000 , , 591 . noble , m.s .  & nowak , m.a .
2008 , , 120 , 821 .
astronomical data generally consists of 2 or more high - resolution axes , e.g. , x , y position on the sky or wavelength and position - along - one - axis ( long - slit spectrometer ) . analyzing these multi - dimension observations 
 requires combining 3d source models ( including velocity effects ) , instrument models , and multi - dimensional data comparison and fitting . 
 a prototype of such a `` beyond xspec '' ( noble & nowak , 2008 ) system is presented here using _ 
 chandra _ imaging and dispersed hetg grating data . 
 techniques used include : monte carlo event generation , chi - squared comparison , conjugate gradient fitting adapted to the monte carlo characteristics , and informative visualizations at each step . 
 these simple baby steps of progress only scratch the surface of the computational potential that is available these days for astronomical analysis .