SAG+SASWG Meeting Potsdam /15 PN Tasks – Status Report (update since Leicester) Hermann Brunner - MPE  epframes:  The dark quadrant problem   in small number of observations event time vector stops while exposure vector continues => one or several `dark´ image quadrants not correctly represented in exposure maps machine-dependent: ok on Tru64 (32/64 bit issue ?) workarounds: - keyword OBT_WARN to identify affected exposures ( InvalidObtValue warning) - task parameter withallobtgti to adjust GTI to make images and exposure maps consistent - check for NaNs in „all good AUX1 entries“ loop

SAG+SASWG Meeting Potsdam /15 do i = 1, ngaux1-1 if (aux1Gtime(i).EQ. aux1Gttime(i) ) then... consistency with hardware where the problem did not occure ?? task uploads should be made by the task author or with the consent of the task author Question on version numbers patch level uploads should not contain interface changes for DEPEND mechanism to work (?) (counter-)example: oal > oal new feature: OAL_hasconfIPPV( )

SAG+SASWG Meeting Potsdam /15 merge:  now merges both STDGTI and GTI to permit merging of individual flare screened event sets permit merging of arbitrary numbers of event files (current version merges two event files) CAUTION: merged event files don‘t work with all SAS tasks ! epatplot: missing axis labels on some arcitectures but not on others (different pgplot libraries ? – ongoing analysis) epchain: corrected error when running epchain for specific exposures in odfacess=oal mode (SPR closed)

SAG+SASWG Meeting Potsdam /15  epreject - ongoing activities: - define new pn event flags BELOW_THRESH flag bit 26 LOEN_NOISE flag bit 27 and include in EPN_REJECTION_MASK purpose: - exclude events shifted below threshold from pattern recognition ( BELOW_THRESH ) - replacement for NOISE column ( LOEN_NOISE ) discussed with CG – SCR to ssclib issued

- replace noise screening method with different method current method: noise properties derived from calclosed obervations - problems: may cause discontinuities in soft spectrum of weak sources new method: remove noisy frames (more than one event per frame below 31 ADU) and perform statistical noise flagging based on observation itself (calclosed noise-maps not needed anymore) - problem: spectral analysis – interface to arfgen new event table extension: noise ratio image/vector ?? SAG+SASWG Meeting Potsdam /15

23.2 ks closed FF application of the original method (implemented in the SAS task epreject) Konrad Dennerl, EPIC Cal meeting, Mallorca, ct. 2006

EPIC-pn detector noise (LW) 2050 adu 99% suppression Original method (“method 1”): Suppression of events below 50 adu according to a reference noise distribution deduced from long calclosed exposures Shown in blue is the result of this method applied to a (long) calclosed exposure, to illustrate the effect on a very faint X-ray source

SNR 1E 0102, rev 803, LW, thick, 30 ks =+ singles, 20 – 30 adu, all frames singles, 20 – 30 adu, frames with more than 1 event below 31 adu per frame and CCD singles, 20 – 30 adu, frames with 1 event below 31 adu per frame and CCD

number of frames removed original number of frames percentage of frames removed removing frames with more than 1 event below 31 adu per CCD and frame: SNR 1E 0102, rev 803, LW, thick, 30 ks

singles, keV mask for source regions to be avoided for noise determination source region mask SNR 1E 0102, rev 803, LW, thick, 30 ks In order to determine the noise properties, some areas have to be ignored:

common fit (for all CCDs) between 40 and 100 adu Deriving the general properties of the detector noise from closed exposures

SNR 1E 0102, rev 803, LW, thick, 30 ks, source regions included red: data set to be corrected, blue: closed exposure

average adu flux SNR 1E 0102, rev 803, LW, thick, 30 ks, source regions excluded

extrapolated flux at 20 adu averaged between all CCDs SNR 1E 0102, rev 803, LW, thick, 30 ks, source regions excluded

spectrum before/after noise suppression, source regions excluded SNR 1E 0102, rev 803, LW, thick, 30 ks, source regions excluded

unfiltered data singles, 25 adu after noisy frame removal SNR 1E 0102, rev 803, LW, thick, 30 ks

after noisy frame removal singles, 25 adu after spatially uniform noise suppression

SNR 1E 0102, rev 803, LW, thick, 30 ks after noisy frame removal singles, 25 adu after spatially variable noise suppression

unfiltered data singles, 30 adu after noisy frame removal SNR 1E 0102, rev 803, LW, thick, 30 ks

after spatially uniform noise suppression singles, 30 adu after spatially variable noise suppression SNR 1E 0102, rev 803, LW, thick, 30 ks

singles, eV original data after noisy frame removal and spatially uniform noise suppression after noisy frame removal and spatially variable noise suppression

SNR 1E 0102, rev 803, LW, thick, 30 ks singles, eV original data after noisy frame removal and spatially uniform noise suppression after noisy frame removal and spatially variable noise suppression

SNR 1E 0102, rev 803, LW, thick, 30 ks singles, eV original data after noisy frame removal and spatially uniform noise suppression after noisy frame removal and spatially variable noise suppression

SNR 1E 0102, rev 803, LW, thick, 30 ks singles, eV original data after noisy frame removal and spatially uniform noise suppression after noisy frame removal and spatially variable noise suppression

SNR 1E 0102, rev 803, LW, thick, 30 ks singles, eV original data after noisy frame removal and spatially uniform noise suppression after noisy frame removal and spatially variable noise suppression

Todo list:  epreject: new treatment of noise screening, possibly split in separate tasks for offset correction and noise screeing  epframes/epevents: internal interface change after solution of OAL time jump problem  epexposure: randomisation of event times (after solution of OAL time jump problem)  calpnalgo: implement/calibrate mode dependent temperature gain corrections – may require calpnalgo/CCF changes SSC Consortium Meeting Potsdam