jet-met november-7-2002 g. bernardi lpnhe - paris run selection for p11 data -august-october =...

Jet-MetNovember-7-2002

G. Bernardi LPNHE - Paris

Run Selection for p11 data

-August-October = Post-Mixing Data, -Runs 161972 to 166782 , p11.11, p11.12 , p11.13

-Studies of the data are presented,

Store by Store,

Run by Run

File by File (i.e. root file by root file)

Data, from mid-August to end of October



We start after the fix of Calo bunch mixing.

Run 161972, and go up to October 25th:

Run 166782 39 stores

During this period: 395 Lumi runs / 64 Millions evt

Studied 15945 Files (root-tuples) about 1-few Lumi-block each (2500 evts each).

33.9 Million Events / 203 Reconstructed runs

Corresponding to a delivered LUMI: 17.7 pb-1

recorded 13.2 pb-1

Live fraction 76.0%

The rest is not reconstructed with p11.

Info presented on 214 runs: 33.3 Mevts / 12.3 pb-1

p11.11/12 Data, mid-August to end October



Overview: MET, Hot cells, SET

MET: 1 entry per file. August to October.

Hot cells sometimes correlated to high MET

39 stores, visible in mean scalar ET

also in RMS



Overview: MET-x , MET-y

Rms(MET-x) : 1 entry per file. Relatively stable

<MET-x>: huge variations +/- 5 GeV

Same story for MET-y



Overview: MET-x , MET-y

How to select runs?

No clear separation on RMS (MET-x) or y

Anisotropy of the calo response due to warm zones creates strong x-y offsets.

Offset can be removed “by hand” (cf W x-sec kado/zitoun), but how to keep the event consistent???




A closer look : MET, Hot cells

4 stores in October (1828, 30, 32, 34)

Hot cells: 1.5/event

Compared to

4 stores at end of August (1686, 87, 89, 91)



A closer look : MET-x


Compared to




A closer look : Scalar ET


We see the changes of prescales, not the direct influence of lumi decrease




A closer look : MET-x


Not only the shapes are different, but the rms is also larger when there is a shaky behaviour.

(also true in Met-y)




Good Run definitionOnly Runs with >= 1000 events are considered.

(203 runs to start with)

Define MET-xy = sqrt [ (MET-x)2 +(MET-y)2 ]

GOOD RUN:

1) require MET-xy < 3 GeV in at least 75% of the events of the run, and all events must have MET-xy < 5 GeV

2) Require mean scalar ET between 90 and 150 GeV

We keep 123 good runs ( 60% of the total statistics, about 8.5 pb-1)

Possibility to reject on a file by file base, since each file is lumi-block consistent only 20% rejected.




Good Runs: MET, Hot cells, SET

MET: 1 entry per file. August to October.

Hot cells sometimes correlated to high MET

39 stores, more regular, still visible in mean scalar ET

also in RMS



Good Runs: MET, Hot cells, SET

MET:

1 entry per run:

123 runs selected August to October.

Regularity improves with time.



Good runs: MET-x , MET-y1 entry per file.

Rms(MET-x) : Relatively stable

<MET-x>: variations have been reduced




Good runs: MET-x , MET-y1 entry per run

Rms(MET-x) : Relatively stable

<MET-x>: systematically shifted by about +1-2 GeV

<MET-y> closer to 0.

Sometimes correlation between large offset and large RMS



Good runs : MET-x , MET-y

1 entry per file (9127 files for the 123 good runs)

bumps are removed by the run selection criteria.

Shift in x worse than in y. RMS also larger in x than in y.



Good runs : MET, SET

Dispersion in MET and SET diminished.

Same story for rms.



Conclusions“Warm zones” create problems to the missing ET, rendering the run selection delicate. Problem is amplified with the “soft” 2.5 sigma cut (let alone the famous 1.5 sigma…), so situation will naturally become easier with the “hard 2.5” of p13.

To save Lumi, it is possible to provide in addition to the current Run selection, a file by file selection (one file = one lumi block in stable conditions).

Currently we have 8.5 pb-1 of data which can be used w/o further correction. The additional 4 pb-1

have a MET offset too large to be used w/o a “recentering” function.

jet-met november-7-2002 g. bernardi lpnhe - paris run selection for p11 data -august-october =...

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