Checked eROdays

eROday

Date - Time (UTC)

TSTART

TSTOP

ZZZ

WWW

43068

2019-08-26 T16:59:55

6.201648e8

6.201792e8

43069

2019-08-26 T20:59:55

6.201782e8

6.201936e8

43070

2019-08-27 T00:59:55

6.201936e8

6.202080e8

43071

2019-08-27 T04:59:55

6.202080e8

6.202224e8

43072

2019-08-27 T08:59:55

6.202224e8

6.202368e8

43073

2019-08-27 T12:59:55

6.202368e8

6.202512e8

43074

2019-08-27 T16:59:55

6.202512e8

6.202583e8

43098

2019-08-31 T16:59:55

6.206077e8

6.206112e8

43099

2019-08-31 T20:59:55

6.206112e8

6.206256e8

43100

2019-09-01 T00:59:55

6.206256e8

6.206400e8

43101

2019-09-01 T04:59:55

6.206400e8

6.206544e8

43102

2019-09-01 T08:59:55

6.206544e8

6.206688e8

43103

2019-09-01 T12:59:55

6.206688e8

6.206832e8

43104

2019-09-01 T16:59:55

6.206832e8

6.206904e8

Photon image of the eROdays

Images in the 0.2-10 keV energy band.

TM6 eROdays 43068-43074 TM6 eROdays 43099-43104


Removed / Corrupted data

The items are sorted in order of their frequency (most at top)

  1. We find duplicate Events, defined as having the same RECORDTIME / RAWX / RAWY. These events usually differ only by their PHA value. The number of duplicates can reach numbers in the order of about 25! Typically at least one of these events show a PHA value of more than 16000. (duplicated events)
  2. We typically observe a random distribution of events in the preprocessed eventfile which contain settings, for which the DATASRC and/or TIMESRC are not set to 0, which is the expected setting. In addition most of these events show a subsecond counter of above 120, the maximum we expect is 95. A light curve of subseconds is provided down below. (weird events)
  3. Moreover we find that some data contain information about the env and/or env2 encoding which should also not be the case. These events occur typically twice one where the env/env2 mode is enabled and one it is disabled. (env-mode events)
  4. In rare cases we find that the PHA value is undefined but the PHA1/PHA2 value is set

1st set of eROdays

Duplicated events: ~5%

Weird data *): ~3.5%

env-mode: ~0.7%

2nd set of eROdays

Duplicated events: ~11%

Weird data *): ~7-8%

env-mode: ~1.3%

comments:

  1. during this time the threshold for 1/3 of the detector was changed
  2. a second camera was turned on during this time

Both of these issues could be a reason on why the percentages of corrupted events doubled.

A quick look at the number of corrupted events in a file containing the timespan when the threshold change occurred indicates, that this caused the increased number of corrupted events. Since there were less corrupted data than the average in the 2nd part.

*) time source or data source not equal 0


Record time light curves

Comment / Description

Lightcurves (recordtime) before and after filtering. RecordTime (high resolution creation of the record, calculated from EXT_OTS, INT_OTS, SCTime, SubSec) for more details ask Ingo or see https://erosita.mpe.mpg.de/eROdoc/raw/rawFitsFileFormats_2018-08.html

Open Questions / Items

We find spikes in the lightcurves which are not removed event after the initial filter stage. These spikes are typically only in one frame. And show interesting patterns when investigated in camera coordinates.

Red: unfiltered; Green: filtered. Both histograms are a zoom!

1st set of eROdays

Record time 1st part

Filtering of events does not remove spikes. These are addressed by the pattern task.

2nd set of eROdays

Record time 2nd part

Record time 3nd part

Filtering of events does not remove spikes in the first light curve. But the second light curve shows a bump (620654400) in the light curve which is filtered out. This bump thus seems to be caused by more corrupted events than usual and was longer than one frame. This would need more investigation on what caused more corrupted events than usual.


two examples of RAWX / RAWY distributions of "spikes" in lightcurve

1. example: RAWX vs RAWY 2. example: RAWX vs RAWY

example lightcurves for non timesrc 0 events

We see that timesrc 2 events are constantly created but they also show single frame spikes. These do not necessarily coincide with spikes of the lightcurve of timesrc 0 events. timesrc 1 and timesrc 3 events only appear sporadically and only last for 1 frame.

lightcurve for non timesrc 0 events

env vs Record time

We see events for which the env mode columns contains a value thus indicating that the env mode was enabled. We consider these as corrupted events.

For the unfiltered events.

1st set of eROdays

env vs Record times part 1

2nd set of eROdays

env vs Record times part 2


Subsec vs Record time

We find events for which the subseconds are above 95 and they appear "constantly". These events are typically data which have a non zero timesrc and datasrc and are currently removed after evprep.

For the unfiltered events.

1st set of eROdays

Subsec vs Record times part 1

2nd set of eROdays

Subsec vs Record times part 2


SCtime vs Record time

We would expect that the SCtime (the time info in the frame time in seconds) to increase with recordtime (diagonal) and after it reaches its limit resets. When investigating all received events we find that the SCtime indeed shows a diagonal as expected but also events with a "random" SCtime as well as events with specific values (lines in light curve). When applying the filters for "corrupted" events these are removed and only the diagonal remains.

For the unfiltered events.

1st set of eROdays

SCtime vs Record times part 1

2nd set of eROdays

SCtime vs Record times part 2


PHA/ADU vs Record time

For the unfiltered events.

1st set of eROdays

PHA/AUD vs Record times part 1

2nd set of eROdays

PHA/AUD vs Record times part 2


RAWX and RAWY histograms

For the unfiltered events.

RAWX

RAWX histogram

RAWY

RAWY histogram


Histogram of Frames

Comment / Description

The histograms below are in bins of 1 frame. This should show that we have received frames, which show more events than the expected quota. The current limit of the eventquota was set to 200. The analysed data covered the frames for a total of 3 times. Thus if we find frames with more than 600 events, at least in one of frames we have an excess of events.

We also see that even after removing events (see filter settings) and duplicates the spikes in the histogram remain.

Open Questions / Items

Does the eventquota procedure work as intended? In this dataset we are not ably to answer this question since the eventquota behaviour will only trigger after a certain number of consecutive frames (we think 4) exceed the limits. Here we typically observe a single frame and sometimes a consecutive frame exceeding the limit. This needs further investigation.

What are the spikes? We still do not know yet, but more on the nature of these events in the next section about light curves (recordtime).

Unfiltered events

Unfiltered data

Filtered events

Unfiltered data


Comparison with (some) HK parameters)

HK1

EVTCTR jumps

EVTCR vs Record times


BITERR variation

BITERR vs Record times


LOWHKHI variation

LOWHKHI vs Record times

LOWHKLO shows an even more erratic behaviour.


HK3

Subsec jumps

I1V2 vs Record times


TCCDTD variation

TCCDTD vs Record times


TCCDPT variation

TCCDPT vs Record times


I1V2 variation

TCCDPT vs Record times


HK5

CMFWHM jump

CMFWHM vs Record times


SPLTCT jumps

SPLTCT vs Record times


EVTBMAX match

EVTBMAX vs Record times

EROSITAwiki: eSASS_TM6 (last edited 2019-09-20 09:07:24 by HermannBrunner)