Processing of 1999 data

1999 L dt = 2.42 pb-1

7.7 × 106 ’s collected

1.1 × 106 KSKL tagged by KS

6.0 × 105 KKtagged by vertex

All data reconstructed at acquisition

Analysis executable:

• CVS source control• Development history• Version-tagged output

0 Short data-taking periods in Aug, Oct, Nov ’99 at acquistion (total ~1 pb-1)

1Main data-taking Dec’99 at acquisition (1.4 pb-1)

Aug, Oct, Nov ’99 data off-line (Feb ’00)

2Changes to algorithms in this report (DC reconst.)

Currently underway for all data

Computing resources

Tape library6 Magstar drives15 MB/sec each40 GB/tape(uncompressed)5500 slots220 TB

GIGASWITCH

Fast Eth,GbitSwitch

OFFLINE FARM 10 Sun Enterprise 450 (4 UltraSPARCII, 400 MHz)700 SpecInt95

Offline farm disk server2 Sun Enterprise 3500

Tapeserver

Tape server

SCSI

SCSI

FDDI

FDDI

Fast Eth

SCSIGbit Eth

ONLINE FARM7 IBM H50 (4 PPC 604e, 330 MHz) 420 SpecInt950.5 TB local disk space (SSA)

0.5 TB RAID

Fast Eth

•All data written to disk in 1 GB files (640 K 1.63 KB evts)

•Reconstruction/streaming performed on dedicated farm

•Production starts on-line and follows acquisition

•Single-CPU job turn-around in 4 hrs

Overview of offline reconstruction

Translation

Cluster reconstruction

Absolute event t0

Background filter

DC hit reconstruction

DC track/vertex recon.

Track-to-cluster assoc.

Event classification

KLKS

Cosmic filter

Rad

K+K Bha

Dedicated

DC hit reconstruction

DC track/vertex recon.

RAW

Track-to-cluster assoc.

Calibration Bhabhas

UFO

datarec “simplified” flow diagram

5 ms/evt

100 ms/evt

Typical data stream composition, Dec ’99

L = ~ 1030 cm-2 s-1 Tot. rate ~1.3 KHz

Unvetoed cosmics ~700 Hz

Prescaled cosmics ~400 Hz

Mach. Bkg + Bhabha < 20° ~200 Hz

Physics ( + Bhabha > 20°) ~15 Hz

Background filters

Cosmic ray and machine background filters use complete EmC reconstruction + number of DC hits

Recent changes to filtering algorithms• increase cosmic ray and MB suppression• decrease inefficiency incurred for physics

channels

Cosmic filter

suppression raised from 84% to 97% with decreasing physics losses

Machine background filter

suppression highly variable depending on run conditions• 40-90% over all KLOE runs• 50-60% for Dec ’99 data

Final stateCosmic filter

MB filter

KSKL 0.02% 0.2%

K+K 2.4% 1.1%

0.07% 0.07%

Neutral

Radiative0.3% <0.01%

0.2% <0.04%

Inefficiency incurred for physics channels

Calorimeter reconstruction

?

Basic clustering algorithm:

• cell readout: {EA, EB, TA, TB}i {E, x, y, z, t}i

• {x, y, z, t}clust from energy weighted avg. over cells

• Missing information systematically underestimate Eclust

New analysis module:

• Uses zclust to get attenuation length correction

• Allows EA and/or EB to be summed into Eclust

Improvements to clustering algorithm Improves measurement of , , masses

Correction of TDC calibration constants

1% error on abs. scale for conversion constants (ps/count)

• ~60 ps error on prompt TOF• Should improve accuracy of neutral vertex reconstruction

ee

Drift chamber reconstruction

•Major effort to understand systematics for momentum reconstruction in DC a priori

•Ad hoc prescription available for some time

Drift chamber geometry

Magnetic field map

Energy loss corrections

p vs , Bhabha events

p(MeV/c)

p (

MeV

/c)

ee

KL

KS

KL lKL l

KL

KL

decay in DCdecay at IP

Many event samples studied

Drift chamber geometry

Stereo angles in reconstruction geometry decreased by ~0.5%

Before correction

After correction

Effect on p vs. , Bhabha events:

p (M

eV/c

)

(deg)

Vertex fit includes new accounting of materials around interaction point

DC wall:650 m CF +50 m Al

Beam pipe at IP:Cylindrical

DC wall:700 m CF +200 m Al

Beam pipe at IP: Spherical

OLD:

NEW:

Effect observed:~ 1.5 MeV step in Mmiss(0) from KL decaying

inside DC (p 400 KeV)

Geometrical adjustments to field mapVarious probe alignment errors detected by detailed analysis of trends in field components in raw map:

• 10-50 Gauss in Br, B

• p(= 20) increased by ~0.7 MeV/c (Bhabha events)

r

r

z

z

r

r

r

z

z

Measurement device:

Cross mounting:

6 Hall probes

Rotating arm with

28 crosses

Alignment errors revealed by study of raw field map:

Global rotation of arm

Misalignment of probes on cross

Gravity-induced torsion on arm

Abs. calib. from NMR probe at

r = 0, z = 0

g

Saturation of field map

Previous reconstruction version: Bz(I = 2660 A) × 2500/2660 Bz(I = 2500 A)

Comparison of maps at 4.5 and 6 KG shows saturation effects depend on (r,) and especially z

Bz(I) from NMR probe (r0, z=0) shows non-linearity:~30 Gauss error in abs. scale of Bz

from extrapolation

Corrections to Bz using NMR data and maps at 4.5 and 6.0 KG reduce p() effect to 1 ppt

Original plan was to run with I = 2660 A Bz = 6 KG

Bz(4

.5) –

0.7

5Bz(6

.0) G

auss

z mm

4.56.0~5.6

Effect of corrections

Bhabha events KS

p (M

eV/c

)

(deg)

±0.5 MeV/c = p/p ~ 0.001

Energy loss corrections

Track/vertex fit includes energy-loss corrections in gas/wall using m = m

2nd pass to re-track identified K+K with m = mK in K+K stream

New materials for dE/dx calculation eliminate step in Mmiss(0) vs. rxy for KL

Event classification

Stream Tagging algorithms/channels Retained Events/nb-1 MB/nb-1

raw raw 762000 1260

kpm KK w/w/o vtx, single K± recon 1000 33

ksl

KS: chg vtx in DC, KL EmC, KL , KL 3

KL: KS , KS

KS lrecon 6700 190

rpi , (prompt chg vtx w/ KS veto) recon 270 6

radneutral radiative decays (prompt neutral energy in EmC)

charged/neutral radiative decaysrecon 720 13

clb , recon 60 1

bhaGolden Bhabhas (5.7 b)

Large-angle Bhabhas (0.75 b)recon 5700 91

flt All events passing FILFO raw 112000 180

afl 1/100 of events rejected by FILFO raw 4200 6

cos 1/10 of prescaled trigger cosmics raw 23000 33

Event streaming1.3 KHz

900 Hz

raw

EmC recon.

DC recon.

DC recon. Evt. Class

bha

kpm

ksl

rpi

rad

clb

flt

afl

190 Hz

7 Hz

Evt. Class

cos

prescaled cosmic

40 Hz

MBcosmic

÷10

÷100

Bhahba 15 Hz

10 Hz

200 Hz

Rates assume typical Dec’99

running conditions

Rates and code optimization

Algorithm

DBV-1 DBV-2

CPU/call (ms)

CPU % of job

CPU/call (ms)

CPU % of job

Overhead

Translation3.1 12.4 2.9 14.2

EmC recon.

Global t01.3 4.9 2.2 10.3

FILFO

Prescale filter0.4 3.3 0.3 3.8

DC track fit 110 67 75 55

Other DC recon. 8.0 4.8 10.4 7.4

Track-to-cluster 8.4 4.9 9.9 7.0

Event classific. 1.5 0.9 2.1 1.6

Diagnostics 3.9 1.6 1.0 0.5

Total Rate 40 Hz 48 Hz

Throughput on 40 CPU offline farm:

Dec ’99 data: 1900 Hz (DBV-2)

L = ~ cm-2 s-1

DC trigger, prescaled cosmics

Aug ’99 data: 2400 Hz (DBV-2)

L = cm-2 s-1

no DC trigger, no prescaled cosmics

Work started on CPU optimization

Changes extensive in online reconstruction (monitoring)

• Throughput increased by factor of 3!

Some optimizations propagated back to offline reconstruction (work in progress)

• DC track fit 46% faster Reconstruction chain 20% faster

OFFLINE

root hist. server

Trigger monitortrigger performancebackground rateluminosity estimate

Offline monitoring: W, , p

L3 spies

Bhabha, CosmicMIP

EMC monitort()E(Bhabha)MIP

DC monitorcell effic.residualsIP, p monitor

root browserillumination

Event display

raw

L3

Calibration

DANE

DANE

Online calibration and monitoring

SWITCH

BUILDER

KID

Drift chamber online calibration

EmC recon

selective filterraw

DC tracking

residuals

DC CALIBGO

STOP

DC CHECK • starts automatically every run • integrates 300K cosmics (3 hr)• histograms track-hit residuals• 50 m residual tolerance 8%

100% = 400 Hz

selcos raw32 Hz

HepDB

DC CALIB• reconstructs selected evts using

residuals (45 evt/sec, ~2hr)• fits s-t relations • stores new calibrations in DB

along with DC conditions

Implemented at script level

All reconstruction proceeds with residuals < 50 m for upcoming data taking

DC CHECKOK

Calorimeter online calibrationMIP-cosmic run

vfib, t0, t0, MIP response

24 hrs, every 30-60 daysPrescaled cosmics

monitor t0

online, every run

eventsmonitor gbl t0, update DB

online, every run

STOP

eventsfine t0 adj by column0.5 hr, every 100 nb-1

Bhabha eventsfine equalization by col.update HepDB, online

eventsAbs energy scale

update HepDB, online

GO

100 nb-1100 nb-1

t0 shift

Timing Energy

no

yes

Online reconstruction monitor

Fast versions of reconstruction algorithms run on-line for monitoring

Bhabha tracks extrapolated to z-axis measure:• position () and size (L) of luminous region• machine boost (p)

Values written to DB, available for analysis

L3 Bhabha(+)

L3 cosmic

EMC monitorEtot, Ecl

Tcl, TclR/c, TclL/vE

EmC vs. EDC

for ee

DC monitorcell efficienciestrack-hit residualsIP and boost: , L, p

EmC + DC reconstruction

EmC + DC reconstruction

65 Hz

Reconstruction and quality controlRejected rates:

MB, cosmics, Bhabhas

Bhabha rate:

L dt, L

Event rates, :

KS , , KL EmC, , KK

Bhabha:

W, p, Etot, E/p, TL/c

KS:

Minv, pK, 2(dN/dcos)

KK:

Minv, p(K), p(K)

Many variables continuously monitored during data processing

Web interface

Graphical history interface

Monte Carlo productionPlan to generate and reconstruct ~11M events

Production environment similar to that used for reconstruction:

• Same executable used for official reconstruction • Output files are version-tagged, have DB entries

MC production runs on offline farm, or on new Linux farm (to be acquired soon)

Work to be completed:Not conditioned on data:

• precise reconciliation of EmC and DC geometry• introduction of new generators

• BABAYAGA (Pavia): Bhabha generator with radiative corrections

• EVA (Karlsruhe): ee generator with ISR+FSR

Conditioned on data:• new field map if next run at IB = 2300 A• finalization of physics program

Event type Request

all 5.0M

KSKL

KS ; KL

KS ; KL charged

KS ,e

1.9M

KK

K ,e0.5M

radiative channels,,fa

ee

3.1M

calibration channelseeee

ee

cosmic rays

0.3M

Total ~11 M

Conclusions

• KLOE reconstruction has been thoroughly proven on all fronts:

algorithms, procedures, environment, and monitoring.

• Emphasis while waiting for luminosity is on refinements.

• New online calibration procedures for upcoming data-taking.

• Next step:

Monte Carlo production for studies of efficiencies and systematicsdriven by requests from analysis groups.