This file gives a detailed account of how the ACIS spectra 
and response files were derived from archived Chandra data.  
The ACIS-S observation of Abell 1795 (ObsId 6160) is used
as an example.

1) Extract the data from the Chandra archive.

2) Start up CIAO and re-process the Level 1 event list with the 
latest calibration products. The example below corrects the data 
for the affects of CTI, applies the appropriate temperature and 
time-dependent gain correction and applies the VF mode background 
filtering. 

ciao
punlearn acis_process_events
pset acis_process_events mtlfile=acisf06160_000N002_mtl1.fits
pset acis_process_events infile=acisf06160_000N002_evt1.fits
pset acis_process_events outfile=acis_new_evt1.fits
pset acis_process_events acaofffile=pcadf227708740N002_asol1.fits
pset acis_process_events eventdef=")stdlev1"
pset acis_process_events check_vf_pha=yes
pset acis_process_events apply_cti=yes
pset acis_process_events apply_tgain=yes
acis_process_events

3) Filter out bad grades and remove events flagged as background
by the VF mode filtering.

dmcopy "acis_new_evt1.fits[events][grade=0,2,3,4,6,status=0]" acis_evt2.fits

4) Filter the data for background flares.  For observations
on ACIS-S3 (a BI chip), light curves were generated from the 
S1 chip (a BI chip). For observations on ACIS-I3 (a FI chip), 
light curves were generated from the S2 chip (a FI chip).
All intervals with 2.5-7.0~keV counts rates exceeding 20%
of the mean count rate were excluded from further analysis.

dmcopy "acis_evt2.fits[@good.gti.fits]" acis_clean_evt2.fits

4) Find the appropriate blank field background file from the
Chandra calibration data base

acis_bkgrnd_lookup acis_evt2.fits
/soft/ciao-4.3/CALDB/data/chandra/acis/bkgrnd/acis2sD2000-12-01bkgrnd_ctiN0005.fits
/soft/ciao-4.3/CALDB/data/chandra/acis/bkgrnd/acis3sD2000-12-01bkgrnd_ctiN0005.fits
/soft/ciao-4.3/CALDB/data/chandra/acis/bkgrnd/acis5sD2000-12-01bkgrnd_ctiN0001.fits
/soft/ciao-4.3/CALDB/data/chandra/acis/bkgrnd/acis6sD2000-12-01bkgrnd_ctiN0005.fits
/soft/ciao-4.3/CALDB/data/chandra/acis/bkgrnd/acis7sD2000-12-01bkgrnd_ctiN0001.fits

5) Since this is an ACIS-S3 observation make a link with the S3 file (CCD_ID=7).

ln -s /soft/ciao-4.3/CALDB/data/chandra/acis/bkgrnd/acis7sD2000-12-01bkgrnd_ctiN0001.fits

6) Remove events flagged as background by the VF mode filtering.

dmcopy "acis7sD2000-12-01bkgrnd_ctiN0001.fits[status=0]" bg_evt2.fits

7) Re-project the background image onto the sky using the aspect
solution for the source image.

punlearn reproject_events
pset reproject_events infile="bg_evt2.fits[cols -time]"
pset reproject_events outfile=bg_reproj_evt2.fits
pset reproject_events aspect=pcadf227708740N002_asol1.fits.fits
pset reproject_events match=acis_clean_evt2.fits
pset reproject_events random=0
reproject_events

8) Adjust the EXPOSURE and LIVETIME in the background file to
yield the same 9-12 keV count rate as in the source file.

dmhedit bg_reproj_evt2.fits filelist=none operation=add key=LIVETIME value=1.58E6 datatype=indef
dmhedit bg_reproj_evt2.fits filelist=none operation=add key=LIVTIME7 value=1.58E6 datatype=indef
dmhedit bg_reproj_evt2.fits filelist=none operation=add key=EXPOSURE value=1.58E6 datatype=indef
dmhedit bg_reproj_evt2.fits filelist=none operation=add key=EXPOSUR7 value=1.58E6 datatype=indef

9) Extract spectra and generate response files

punlearn ardlib
punlearn specextract

pset ardlib AXAF_ACIS7_BADPIX_FILE="acisf06160_000N002_bpix1.fits[BADPIX7]"

dmhedit bg_reproj_evt2.fits filelist=none operation=add key=OBS_ID value=6160 datatype=string

specextract "acis_clean_evt2.fits[sky=region(a1795.reg)]" weight=yes correct=no asp=asphist.fits combine=no pbkfile=acisf227709923N002_pbk0.fits mskfile=acisf06160_000N002_msk1.fits dafile=CALDB outroot=a1795_6160_CALDB_4.4.3 bkgfile="bg_reproj_evt2.fits[sky=region(a1795.reg)]" bkgresp=no grouptype=NUM_CTS binspec=50