Simulation for Chandra LETGS (AO-9)

Last modified: February 26, 2007


This thread uses PINTofALE to generate simulated Chandra Low-Energy Transmission Grating Spectrometer (LETGS) spectra. In particular, we will examine the emission of a hot corona along with the contribution to the X-ray emission from an accreting component. The Chandra gRSP files used here were obtained from the LETG Observer Information page. The Chandra Proposal Information page also contains gARFs and gRMFs for various orders and those may also be used. However, note that the formatting of the data in some of those files has been found to be incompatible with IDL's mrdfits() routine, and care must be taken to ensure that the arrays read in correspond to that given in Figure 9.17 of the Proposers' Observatory Guide. We use the gRSP files and set the gARFs to "none" in this thread. If gARF files are used, please ensure that the gRMF files are read in and not the gRSP files, which already include the gARFs.
Update: The HRC-S/LETG gARF files are correct as of 6 Mar 2007.

  1. Initialize some variables
  2. Define a DEM
  3. Rescale to DEM to match ROSAT count rate
  4. Construct spectra
  5. Simulate and plot
All the steps described here are repeated in the .par file: chandra_letg_ao9.par.

1. Initialize some variables

;	NOTE: this thread uses some system variables defined via the script INITALE
;	so, if it hasn't been done already, initialize PINTofALE with:

 .run initale

;	Because some variables will be used repeatedly in the course of this
;	thread, it might be useful to initiate them now. Nailing down these
;	variables now will also allow for something of a checklist for some
;	important quantities/files needed for the task at hand:

;	Source We will characterize our model source by the following:
 !NH           = 3e20			 ; H column density [cm^-2]
 EDENS_c       = 1e10			 ; electron number density [cm^-3]
 EDENS_a       = 1e12			 ; electron number density [cm^-3]
 !ABUND        = getabund('grevesse')    ; elemental abundances (SEE: getabund())
 T_c  	       = [6.5, 7.3]	    	 ; log(T[K]) components in the EM for the corona
 EM_c          = [6.6, 2.2]*1d12	 ; Emission Measure [cm^-3] for the corona
 T_a  	       = [6.3]	    	    	 ; log(T[K]) components in the EM for the accret.
 EM_a          = [3.3]*1d12	    	 ; Emission Measure [cm^-3] for the accret.

;	Observation The observation can be described by:

 EXPTIME   	= 50.			 ; nominal exposure time [ks]
 file_gRMFp	= 'hrcsleg_0411_p1t6.rsp'	; full path name to +ve order grating RMF (or RSP)
 file_gRMFn	= 'hrcsleg_0411_m1t6.rsp'	; full path name to -ve order grating RMF (or RSP)
 file_gARFp	= 'none'	; full path name to +ve order grating ARF (not needed if file_gRMFp includes ARF)
 file_gARFn	= 'none'	; full path name to -ve order grating ARF (not needed if file_gRMFn includes ARF)

 ;	NOTE: we use the 1 thru 6 orders responses combined, and therefore
 ;	do not require the gARFs.  If the gRMFs are downloaded from the
 ;	Chandra PProposal Information page, then the corresponding gARFs
 ;	are necessary.

;	Atomic Database  We have '$CHIANTI','$SPEX','$APED' to choose from:

 !LDBDIR = '$CHIANTI'

 !WMIN         = 1.2           ; minimum wavelength for output spectrum [ang]
 !WMAX         = 45            ; maximum wavelength for output spectrum [ang]
 nwbin         = 400L		; number of bins in theoretical spectrum

2. Define a DEM

;	A Differential Emission Measure (DEM) is required for both components 
;       to estimate the amount of emission at various temperatures. Typically,
;	2-temperature model is used. Here we will use PINTofALE's mk_dem(),
;	which constructs a DEM array given a temperature grid and emission measure
;	components. We use as the temperature grid !LOGT. The emission measure
;	components are T_c and EM_c for the corona and T_a and EM_a for the accreting
;	component as defined above. We choose 'delta' to treat the EM components as
;	delta functions (see mk_dem() or the Chandra/ACIS example for more options)

DEM_c=mk_dem('delta', logT = !LOGT, pardem=T_c, indem=EM_c)

DEM_a=mk_dem('delta', logT = !LOGT, pardem=T_a, indem=EM_a)

; plot the DEMs for illustration
plot,!LOGT,DEM_c,psym=10,xtitle='log!d10!n(T [K])',ytitle='DEM [cm!u-5!n/logK]'
oplot,!LOGT,DEM_a,psym=10,color=2


3. Rescale to DEM to match ROSAT count rate

;	We will assume that a ROSAT/PSPC count rate is available,
;	and that the simulation will match this rate.  We will assume
;	a count rate of 1 ct/s .  Data from other missions such
;	as ASCA, BeppoSAX, etc. can be dealt with in the same manner.

;	We will first read in the instrument effective area,
;	then the atomic emissivities from the PINTofALE database,
;	then calculate the predicted PSPC flux for the appropriate
;	DEM and NH, and rescale the input EMs accordingly.

;	First find and read in the ROSAT/PSPC effective area.
;	You will need to know where your local PIMMS installation
;	is to do this.

pimmsdir='/soft/ciao/config/pimms/data'
rosat_pspc_open=get_pimms_file('ROSAT','PSPC','OPEN',pdir=pimmsdir)
rd_pimms_file, rosat_pspc_open, pspc_effar, pspc_wvlar, /wave

;	Make sure that the wavelengths are sorted in increasing order

ae=sort(pspc_wvlar) & pspc_wvlar=pspc_wvlar[ae] & pspc_effar=pspc_effar[ae]

;	The following is similar to the process described in the detailed
;	example thread (see Section 1 and Section 2).
;	For a scripted example with less details, see the companion thread
;	on the low-resolution spectrum generation.


; Read in line cooling emissivities and calculate line intensities ;Read line cooling emissivities from the atomic database. ; To avoid multiple reads, read in the database over the largest ; necessary wavelength range minwave=min(pspc_wvlar) < !WMIN maxwave=max(pspc_wvlar) > !WMAX ; first for the density of the coronal component... !EDENS=EDENS_c lconf_c=rd_line(atom,n_e=!EDENS,wrange=[MINwave,MAXwave],$ dbdir=!LDBDIR,verbose=!VERBOSE,wvl=LWVL,logT=LLOGT,Z=Z,$ ion=ION,jon=JON,fstr=lstr_c) ; ... and next for the density of the accreting component !EDENS=EDENS_a lconf_a=rd_line(atom,n_e=!EDENS,wrange=[MINwave,MAXwave],$ dbdir=!LDBDIR,verbose=!VERBOSE,wvl=LWVL,logT=LLOGT,Z=Z,$ ion=ION,jon=JON,fstr=lstr_a) ;The output of rd_line() will only include level population, ;and not ion balances. We will use fold_ioneq() to fold ion balances. ; NOTE: This step should not be performed if !LDBDIR is set to APED, ; which already includes ion balances and abundances. if strpos(strlowcase(!LDBDIR),'aped',0) lt 0 then lconf_c=$ fold_ioneq(lstr_c.LINE_INT,lstr_c.Z,lstr_c.JON,chidir=!CHIDIR,$ logT=lstr_c.LOGT,eqfile=!IONEQF,verbose=!VERBOSE) if strpos(strlowcase(!LDBDIR),'aped',0) lt 0 then lconf_a=$ fold_ioneq(lstr_a.LINE_INT,lstr_a.Z,lstr_a.JON,chidir=!CHIDIR,$ logT=lstr_a.LOGT,eqfile=!IONEQF,verbose=!VERBOSE) ; NOTE: If !LDBDIR is set to APED, Anders & Grevesse abundances ; are already included in the emissivities. The following removes ; the abundance from the emissivities in such cases. if strpos(strlowcase(!LDBDIR),'aped',0) ge 0 then apedance,lconf_c,lstr_c.Z if strpos(strlowcase(!LDBDIR),'aped',0) ge 0 then apedance,lconf_a,lstr_a.Z ; and now calculate line intensities using lineflx(). linint_c=lineflx(lconf_c,!LOGT,abs(lstr_c.WVL),lstr_c.Z,DEM=DEM_c,abund=!ABUND) ;[ph/s] linint_a=lineflx(lconf_a,!LOGT,abs(lstr_a.WVL),lstr_a.Z,DEM=DEM_a,abund=!ABUND) ;[ph/s]
; Read in continuum emissivities and calculate continuum intensities ;We can read in continuum emissivities usingrd_cont(). ;It is important to note that the output emissivities of rd_cont() ;are in [1e-23 erg cm^3/s/Ang] and not [1e-23 erg cm^3/s] as with rd_line() ; first for the density of the coronal component... !EDENS=EDENS_c cconf_c=rd_cont(!CEROOT,n_e=!EDENS,wrange=[minwave,maxwave],$ dbdir=!CDBDIR,abund=!ABUND,verbose=!VERBOSE,$ wvl=CWW,logT=ClogT,fcstr=cstr_c) ; ... and next for the density of the accreting component !EDENS=EDENS_a cconf_a=rd_cont(!CEROOT,n_e=!EDENS,wrange=[minwave,maxwave],$ dbdir=!CDBDIR,abund=!ABUND,verbose=!VERBOSE,$ wvl=CWW,logT=ClogT,fcstr=cstr_a) ;The continuum intensities per angstrom can be calculated again using ;lineflx(). Note that cstr.WVL contains the wavelength bin boundaries ;for the emissivity array. conint_c=lineflx(cconf_c,!LOGT,cstr_c.midWVL,DEM=DEM_c) ;[ph/s/Ang] conint_a=lineflx(cconf_a,!LOGT,cstr_a.midWVL,DEM=DEM_a) ;[ph/s/Ang] ;Now to get just continuum intensity, we must multiply by an array ;containing the bin widths. If we define this array simply with ;CDW=cstr.WVL[1:*]-cstr.WVL, we will get an ugly 'saw-toothed' figure ;due to numerical issues having to do with subtracting regularly spaced ;floating point numbers. To work around this, we use the mid-bin values ;cstr.midWVL, and mid2bound(), which gives intelligent bin-boundary ;values given the mid-bin values: CWB=mid2bound(cstr_c.midWVL) & CDW=CWB[1:*]-CWB conint_c=conint_c*CDW ;[ph/s/Ang]*[Ang] CWB=mid2bound(cstr_a.midWVL) & CDW=CWB[1:*]-CWB conint_a=conint_a*CDW ;[ph/s/Ang]*[Ang]
; Correct for inter-stellar absorption ;Derive ISM absorptions using ismtau() ltau=ismtau(abs(lstr_c.WVL),NH=!NH,fH2=!fH2,He1=!He1,HeII=!HeII,$ Fano=Fano,wam=wam,/bam,abund=!ABUND,verbose=!VERBOSE) ctau=ismtau(cstr_c.midWVL,NH=!NH,fH2=!fH2,He1=!He1,HeII=!HeII,$ Fano=Fano,wam=wam,/bam,abund=!ABUND,verbose=!VERBOSE) ltrans=exp(-ltau) & ctrans=exp(-ctau) ; NOTE: lstr_c.WVL and lstr_a.WVL are identical, so there is no ; need to repeat these calculations for both components ;Derive theoretical line fluxes linflx_c = linint_c * ltrans ;[ph/s/cm^2] linflx_a = linint_a * ltrans ;[ph/s/cm^2] ;Derive theoretical continuum fluxes conflx_c = conint_c * ctrans ;[ph/s/cm^2] conflx_a = conint_a * ctrans ;[ph/s/cm^2]
; Bin spectra and fold in effective area ;make input theoretical spectrum grid dwvl=float((MAX(pspc_wvlar)-MIN(pspc_wvlar))/nwbin) wgrid=findgen(nwbin+1L)*dwvl+MIN(pspc_wvlar) ;Rebin to form theoretical line spectrum using hastrogram() linspc_c = hastogram(abs(lstr_c.WVL),wgrid,wts=linflx_c) ;[ph/s/cm^2/bin] linspc_a = hastogram(abs(lstr_a.WVL),wgrid,wts=linflx_a) ;[ph/s/cm^2/bin] ;Rebin to form theoretical continuum spectrum using rebinw() conspc_c = rebinw(conflx_c,cstr_c.WVL,wgrid,/perbin) ;[ph/s/cm^2/bin] conspc_a = rebinw(conflx_a,cstr_a.WVL,wgrid,/perbin) ;[ph/s/cm^2/bin] ;Derive predicted flux spectrum. WVLS=0.5*(WGRID[1:*]+WGRID) newEffAr=(interpol(pspc_effar,pspc_wvlar,WVLS) > 0) < (max(pspc_effar)) flxspc_c = (linspc_c + conspc_c) * newEffAr flxspc_a = (linspc_a + conspc_a) * newEffAr ;Derive predicted counts spectrum by combining contributions from both ;the coronal and the accretion components flxspc=(flxspc_c+flxspc_a)*EXPTIME*1e3 ;[ct/bin] ;plot the predicted ROSAT/PSPC spectrum for illustration ;(note that the RMF blurring has not been applied to this) plot,wvls,flxspc/dwvl,psym=10,xtitle='!4k!X ['+!AA+']',ytitle='[counts/'+!AA+']'
; Renormalize the DEMs ;Now get the total count rate and renormalize the DEM to the ;observed rate of 1.0 ct/s. obs_rate = 1.0 ;[ct/s] pred_rate = total(flxspc/EXPTIME/1e3) ;[ct/s] print,'normalization factor: ',obs_rate/pred_rate ;normalization factor: 0.038552682 DEM_c = DEM_c * obs_rate/pred_rate DEM_a = DEM_a * obs_rate/pred_rate

4. Construct the Spectra

;	The construction of the simulated spectra is largely a
;	repetition of the steps carried out to rescale the DEM.
;	It is in fact different only in three aspects: we will use
;	Chandra's instrumental response files and account for
;	differences in plus/minus orders.  Also, we will convolve
;	the resulting spectrum with an RMF (for the DEM normalization,
;	only the total counts was important). 

;	NOTE: We have already read in the line and continuum emissivities
;	in  section 3 above. We will use these to compute the corresponding
;	line and continuum intensities for the accreting and the coronal components.

	;first for the accreting comp.

        linint_accret=lineflx(lconf_a,!LOGT,abs(lstr_a.WVL),lstr_a.Z,DEM=DEM_a,abund=!ABUND) ;[ph/s]
        conint_accret=lineflx(cconf_a,!LOGT,cstr_a.midWVL,DEM=DEM_a)       ;[ph/s/Ang]
        CWB=mid2bound(cstr_a.WVL) & CDW=CWB[1:*]-CWB
        conint_accret=conint_accret*CDW	;[ph/s/Ang]*[Ang]

        ;now for the corona

        linint_corona=lineflx(lconf_c,!LOGT,abs(lstr_c.WVL),lstr_c.Z,DEM=DEM_c,abund=!ABUND) ;[ph/s]
        conint_corona=lineflx(cconf_c,!LOGT,cstr_c.midWVL,DEM=DEM_c)       ;[ph/s/Ang]
        CWB=mid2bound(cstr_a.WVL) & CDW=CWB[1:*]-CWB
        conint_corona=conint_corona*CDW	;[ph/s/Ang]*[Ang]


; Correct for inter-stellar absorption ;NOTE: the ISM transmission factors have been calculated in ;section 3 above and we reuse those here. linflx_accret = linint_accret * ltrans ;[ph/s/cm^2] conflx_accret = conint_accret * ctrans ;[ph/s/cm^2] linflx_corona = linint_corona * ltrans ;[ph/s/cm^2] conflx_corona = conint_corona * ctrans ;[ph/s/cm^2]
; Bin spectra dwvl=float((!WMAX-!WMIN)/nwbin) & wgrid=findgen(nwbin+1L)*dwvl+!WMIN & WVLS=0.5*(WGRID[1:*]+WGRID) linspc_accret = hastogram(abs(lstr_a.WVL),wgrid,wts=linflx_accret) ;[ph/s/cm^2/bin] conspc_accret = rebinw(conflx_accret,cstr_a.WVL,wgrid,/perbin) ;[ph/s/cm^2/bin] linspc_corona = hastogram(abs(lstr_c.WVL),wgrid,wts=linflx_corona) ;[ph/s/cm^2/bin] conspc_corona = rebinw(conflx_corona,cstr_c.WVL,wgrid,/perbin) ;[ph/s/cm^2/bin]
; Read the effective area ;read in the effective areas if given and the wavelength grid over which ;they are defined (use the RSPs if the ARFs are not defined) ; for the +ve order if strpos(strlowcase(file_gARFp),'none') ge 0 then begin & $ grsp_p=rd_ogip_rmf(file_gRMFp,effar=effar_p,verbose=!VERBOSE) & $ wvlar_p = !fundae.KEVANG/(0.5*(grsp_p.ELO+grsp_p.EHI)) & $ newEffArP=0.*WVLS+1. & $ endif else begin & $ effar_p=rdarf(file_ARFp,ARSTRp) & $ wvlar_p=!fundae.KEVANG/(0.5*(ARSTRp.ELO+ARSTRp.EHI)) & $ newEffArP=(interpol(EFFAR_p,WVLAR_p,WVLS) > 0) < (max(EFFAR_p)) & $ endelse ; for the -ve order if strpos(strlowcase(file_gARFn),'none') ge 0 then begin & $ grsp_n=rd_ogip_rmf(file_gRMFn,effar=effar_n,verbose=!VERBOSE) & $ wvlar_n = !fundae.KEVANG/(0.5*(grsp_n.ELO+grsp_n.EHI)) & $ newEffArN=0.*WVLS+1. & $ endif else begin & $ effar_n=rdarf(file_ARFn,ARSTRm) & $ wvlar_n=!fundae.KEVANG/(0.5*(ARSTRn.ELO+ARSTRn.EHI)) & $ newEffArN=(interpol(EFFAR_N,WVLAR_n,WVLS) > 0) < (max(EFFAR_n)) & $ endelse ;[ct/s/bin] (if DEM is [cm-5]: [ct/s/cm2/bin]) flxspcP_accret = (linspc_accret + conspc_accret) * newEffArP flxspcN_accret = (linspc_accret + conspc_accret) * newEffArN flxspcP_corona = (linspc_corona + conspc_corona) * newEffArP flxspcN_corona = (linspc_corona + conspc_corona) * newEffArN ;Derive predicted counts spectrum for +ve and -ve orders flxspcP_accret=flxspcP_accret*EXPTIME*1e3 ;[ct/bin] flxspcN_accret=flxspcN_accret*EXPTIME*1e3 ;[ct/bin] flxspcP_corona=flxspcP_corona*EXPTIME*1e3 ;[ct/bin] flxspcN_corona=flxspcN_corona*EXPTIME*1e3 ;[ct/bin] EGRID=!fundae.KEVANG/WGRID
; Convolve with RMF or RSP conv_rmf,EGRID,flxspcP_accret,CHANP,CTSPCP_accret,file_gRMFp,rmfstr=grsp_p conv_rmf,EGRID,flxspcN_accret,CHANN,CTSPCN_accret,file_gRMFn,rmfstr=grsp_n conv_rmf,EGRID,flxspcP_corona,CHANP,CTSPCP_corona,grsp_p conv_rmf,EGRID,flxspcN_corona,CHANN,CTSPCN_corona,grsp_n
; Combine the positive and negative orders to get a co-added spectrum. CHAN_accret=CHANP ;[keV] cts_accret=ctspcP_accret+ctspcN_accret ;[ct/bin] CHAN_corona=CHANP ;[keV] cts_corona=ctspcP_corona+ctspcN_corona ;[ct/bin] ;combine the components to get the total spectrum CHAN=CHANP ;[keV] cts = cts_corona + cts_accret ;[ct/bin] ;Note that the output energy grid of the spectra will be ;the energy grid defined by the RMF. However, the spectrum ;will only show lines and continuum between the selected ;wavelength range [!WMIN,!WMAX]

5. Obtain Poisson deviates and plot

;	The final step is a simulation of counts based on the spectrum
;	predicted above

nbin = n_elements(cts_accret)
CTSIM_accret=intarr(nbin) & CTSIM_corona=intarr(nbin)
for i=0L,nbin-1L do if cts_accret[i] gt 0 then $
    CTSIM_accret[i]=randomu(seed,poisson=cts_accret[i])
for i=0L,nbin-1L do if cts_corona[i] gt 0 then $
    CTSIM_corona[i]=randomu(seed,poisson=cts_corona[i])

	;here is an example plot showing the effects of the different
	;components for, e.g., the O VII triplet.

plot, !fundae.KEVANG/CHAN, CTSIM_corona+CTSIM_accret, psym=10, xrange=[21.5,22.4],$
	xtitle='!4k!X ['+!AA+']',ytitle='[counts/bin]',title='LETGS+HRC-S spectrum'
oplot, !fundae.KEVANG/CHAN, CTSIM_corona, psym=10, color=2
oplot, !fundae.KEVANG/CHAN, CTSIM_accret, psym=10, color=3
xyouts, !x.CRANGE[1], !y.CRANGE[1]-0.1*(!y.CRANGE[1]-!y.CRANGE[0]), 'TOTAL',align=1.1
xyouts, !x.CRANGE[1], !y.CRANGE[1]-0.2*(!y.CRANGE[1]-!y.CRANGE[0]), 'CORONAL',align=1.1,color=2
xyouts, !x.CRANGE[1], !y.CRANGE[1]-0.3*(!y.CRANGE[1]-!y.CRANGE[0]), 'ACCRETION',align=1.1,color=3
stample
 

pintofale()head.cfa.harvard.edu (MM/VK)