Muon Event FilterStatus Report

Sergio Grancagnolofor the muon EF working

groupINFN Lecce & Salento University

Outline

• Performance in releases 12, 13, 14• Robustness to misalignments• Muon EF wrappers for offline

supertools• Converters• Menus• Muon trigger CSC note status

Muon Slice performanceFrom CSC Note – Muon Rates - Convolution method 12.0.6 trigger swLVL1 emulationmuFast+hypomuComb+hypoTrigMooreMSTrigMooreSATrigMooreCB+hypo

Pythia 6.4 for b,c DPMJET for /K(conservative choice)large theoretical uncertaintiesat pT below 6 GeV

must focus on /K rejection at low pT

mu6 needs prescaling mu20/40 need isolation

or prescaling at 1034

Efficiencies

• a drop of the CB trigger eff. at low pT has been observed in 13.0.30 – recovered in 14.x.0 nightlies – appears related to EFID rather than Muon Algos

• Stable eff. at high pT

12.0.613.0.30.3

TrigMooreCB w.r.t. muCombsingle muons

12.0.613.0.40.214.0.0 nightly

13.0.40.214.0.0 nightly

EFId w.r.t. muCombsingle muons

ZZ

Single muons mc12.*.RDO.* Single muons mc12.*.RDO.* • ATLAS-CSC-01-02-00ATLAS-CSC-01-02-00

– 12.0.612.0.6– 13.0.40.213.0.40.2– 14.X.0 devval, rel_3 (12 Mar 2008)14.X.0 devval, rel_3 (12 Mar 2008)

Resolution 1/pT

12.0.6

13.0.40.2

14.X.0

MuIdSA MuIdCB

MuIdSA performance is more or less constant for all releases

MuIdCB shows slight deterioration in 14.X.0 wrt previously

Resolution and 12.0.6

13.0.40.2

14.X.0

MuIdCBMuIdSA

and resolution stable with releases

MuIdSA MuIdCB

/K rejection

single single

min.bias K

min.bias

K

From the CSC note

with current set of cuts (not extensively optimized)– 75% eff. @ 4GeV for (1-effBG)=35%

– 90% eff. @ 20GeV for (1-effBG)=25%

Inner Detector d0 ≤ 0.15ID n. of pixel hits ≥ 3ID n. of B layer hits ≥ 1ID n. of SCT hits ≥ 6pT (ID) / pT (SA) ≤ 1.25Combined match 2 ≤ 26

present cuts

to be implemented in a new hypo algorithm for 14.x.x

Robustness against misalignments

• RDO reconstruction and AANT/AOD production performed with Athena 13.0.40.2

• Four reconstruction scenarios considered with different knowledge of ID and/or MS alignment:– Aligned ID and aligned MS Aligned ID and aligned MS (perfect correction of misalignments)– Aligned ID and misaligned MSAligned ID and misaligned MS (crude MS misalignments ~1mm)– Misaligned ID and misaligned MS Misaligned ID and misaligned MS (ID as in FDR1 + MS as above)– Misaligned ID and aligned MSMisaligned ID and aligned MS (ID as in FDR1 + perfectly known

MS)

EF_InDet EF_InDet wrt LVL2wrt LVL2 EF_MuidCB EF_MuidCB wrt LVL2wrt LVL2

Dramatic loss of EF algos’ efficiency with misal ID.

Misal MS even worse at high pT

Event-based efficiencies applying lowest muon threshold

Efficiencies

Resolution 1/pT

Standard deviation of pT(Reco) / pT(Gen)

EF EF InDetInDet

EF EF MuidSAMuidSA EF EF MuidCBMuidCB

3%

5%

5%

3%

5%

3%

2%

EF InDet pT reso 2-3 times larger with misal ID

IDal-MSal • IDal-MSmisal • IDmisal-MSal • IDmisal-MSmisal

MuidCB pT reso below 10% with misal ID, out of control at >100 GeV with Misal MS

Resolution

Standard deviation of (Reco) – (Gen)

EF EF InDetInDet

EF EF MuidSAMuidSA EF EF MuidCBMuidCB

3x10-3

5x10-4

2%

3%

5%

5x10-3

3x10-3

2x10-3

2x10-4

3x10-4

5x10-4

MuidCB resolution 2-3 times larger with

misal ID/MS

MuidSA performance unchanged

EF_ID resolution constant with misal

ID

IDal-MSal • IDal-MSmisal • IDmisal-MSal • IDmisal-MSmisal

Resolution:

Standard deviation of (Reco) – (Gen)

EF EF InDetInDet

EF EF MuidSAMuidSA EF EF MuidCBMuidCB

2%

3%

5x10-3

3x10-3

2x10-4

3x10-4

5x10-4

2x10-3

2x10-3

2x10-4

3x10-4

5x10-4

MuidSA performance unchanged

EF_ID resolution constant with misal

ID

MuidCB worse at high pT with misal MS, resolution ~

mrad with misal ID

IDal-MSal • IDal-MSmisal • IDmisal-MSal • IDmisal-MSmisal

Robustness considerations Tests on muon trigger robustness

performed on (mis)aligned data, running the full Muon Slice shows that With crude non-realistic (~mm) MS

misalignments + realistic ID misalignments (FDR1): EF efficiencies deteriorate significantly EF spatial resolution under control, but pT gets

worse above 50-100 GeV (below 10% with ID misal. only)

Converters – state as today• MuonCnv/MuonByteStream

– bytestream Converter to RDO for Mdt, Rpc, Tgc, Csc– bytestream Converter to Mdt PrepData– bytestream Converter to Rpc PrepData but no

ambiguity/redundancies solving• For trigger technologies online data format very different wrt offline

– no bytestream to PrepData Converter for Tgc, Csc today• MuonCnv/MuonRdoToPrepData

– Conversion Algorithms from RDO to PrepData for all technologies • uniform in general structure among technologies • implemented for the MC: input is the RDO !• can be run on bytestream: when the algorithm retrieve the

RDO, the bytestream to RDO Converters are activated and the RDO become available in memory for further conversion (as in M5)

• converting full event even when working in a region of interest !!

• for RPC the reason is having clean RIO collections – no redundancies/ambiguities

• NEED to preserve the RoI driven data access

New data access schema for New data access schema for RPC (I)RPC (I)

• @ the EF, the algorithm (FeX) requests RPC PRD in a x region (RoI)– get from the region selector a list of data collection hash id (offline) in

the RoI– get from cabling service the corresponding list of pad identifiers– Retrieve from StoreGate the pad container and find (i.e. decode into

RDO) each pad in the selected list output is the RDO for the RoI• i.e. just use the byte-stream to RDO converter

– convert the RDO into PRD by applying the redundancy and ambiguity removal currently implemented in the offline algorithm for RDO PRD

• First implementation of the schema proposed for RPC offline / Event Filter is ready / under test

• in the offline (re-use not duplicate code) MC and DATA– RDO to PRD delegate all the work to the new AlgTool used over the

whole event allow to use the StatusCode + an attached string describing the kind and severity of the problem in data preparation robustness

• The schema can be adopted for all muon technologiesThe schema can be adopted for all muon technologies– uniform way of accessing the data

embed all that into an AlgToolembed all that into an AlgTool

TrigMoore implementation

LVL2 (muFast)LVL2 (muFast)

Moore AlgsMoore Algs

LVL1LVL1

MuIdStandAloneMuIdStandAloneAlgs Algs

TrigMooreTrigMoore

Seeding AlgsSeeding Algs

MuIdCombinedMuIdCombinedAlgs Algs

Hypo AlgHypo Alg

Hypo AlgHypo Alg

Hypo AlgHypo Alg

LVL2 (muComb)LVL2 (muComb)

Inner DetectorInner DetectorAlgs Algs

• Seeding Algorithms assume the seed from LVL1 or LVL2, barrel or endcap

– Reconstruction only in the geometrical regions provided by the RoIs of previous levels

• 3 instances of TrigMoore are called by the steering for:

– Reconstruction in MS– Extrapolation to the IP– Combination with ID tracks

• Each TrigMooreFeature is accessed by TrigMooreHypo to test hypotheses

Follow up with the new Moore style for

14.0.0 • A new package: Trigger/TrigAlgorithms/TrigMuonEF hosts 4

HLTalgorithms: – TrigMuonEFSegmentFinder wrapper for MooSegmentCombinationFinder (offline

tool invoqued with vector of pointers to prd collections) DONE – TrigMuonEFTrackBuilder wrapper for the offline tool MuonCombiTrackMaker

(invoqued with vector of pointers to segment combination) DONE – TrigMuonEFExtrapolator wrapper for MuidBackTracker DONE– TrigMuonEFCombiner wrapper TO BE DONE for the main tool of MuidCB

(COMING SOON ?)

• Running with release 14.0.0 - producing standalone EF muons propagated to the interaction point

• Most work is just in configuration– requires dedicated configuration of the tools for running in trigger

• The new chain (up to the available implementation) will be in 14.1.0 – defined temporary extra muon trigger sequences to be run concurrently with

the standard EF (TrigMoore)– needs to revise the trigger AOD for the EF

New EF wrappers

LVL2 (muFast)LVL2 (muFast)

TrigMuonEFTrackBuilderTrigMuonEFTrackBuilder

LVL1LVL1

TrigMuonEFExtrapolatorTrigMuonEFExtrapolatorTrigMuonEFTrigMuonEF

TrigMuonEFSegmentFinderTrigMuonEFSegmentFinder

TrigMuonEFCombinerTrigMuonEFCombiner

Hypo AlgHypo Alg

Hypo AlgHypo Alg

Hypo AlgHypo Alg

LVL2 (muComb)LVL2 (muComb)

Inner DetectorInner DetectorAlgs Algs

MooSegmentCombinationFinder

MuonCombiTrackMaker

New implementation schema of muon EF code (to be implemented for 14.1.0)With wrappers for offline tools

MuidBackTracker

Hypo AlgHypo Alg

Combination tool

In red: to be implemented

The slow particle trigger TrigMuGirl will be also included in 14.1.0 or 14.2.0

Revision of muon EF trigger AOD

• The separate step of segment finding allow for another early hypothesis algo– As an example if the number of segments in

inner/middle/outer MS layers is stored– Fit 2 could be saved at different track building

steps• To implement hypo algos for /K rejection

– At least combined match 2 fit must be stored• Link to the ID track used in combination

– Use of ElementLink if ID info is already stored in AOD

– Store ID info if missing (21 bytes)• Proposal made @ last Muon Slice Trigger

Software (3 Apr) for a new schema– Possibility under study

Muon Trigger Menus

• A lot of effort has been put in cross checking the trigger rate estimated with the convolution method and with the counting method (on min. bias Pythia 6.4 samples)– a basic agreement is observed taking into account the

different theory input for /K rates– full details can be found in reports at Nov. Trigger and

Physics week and at Dec.2007 TDAQ week• Based on estimated trigger rates the muon trigger menus

have been defined for 1031 and 1032 assuming standard muon slice algorithms (no isolation yet, no /K rejection strategies)

• first though for 1033 based on extrapolation of 1032

– Need to account for minimum bias pile-up – Reliable samples needed – implications of 1033 luminosity at 75 ns bunch

crossing spacing

PHYSICS MENU -13.0.40.4 (PHYSICS MENU -13.0.40.4 (TriggerMenuPython-00-00-47-34TriggerMenuPython-00-00-47-34) + rates) + rates

SIGNATURESSIGNATURES E32E32

LVL1LVL1 LVL2LVL2 EFEF RATES (Hz)RATES (Hz)

PSPS PTPT PSPS PTPT PS PS ratesrates

PT PT ratesrates

Total Total ratesrates

mu4 1 5*10 400*10 300 0 0.2 0 0.2

mu6 1 1*10 200*10 30 0 3.5 0.1 3.6

mu10 1 1 100*10 1*10 0 18 1 19

mu15 1 1 20*10 1*10 0 5.7 0.2 5.9

mu20 1 1 0 1 0 19 0 19

mu40 1 1 1*10 1 0 1 14 15

mu20_passHLT 1 1000 20*10 1 0 0.02 ~0.2 0.22

2mu4 1 1*10 5*10 1 0 2.4 1.3 3.7

2mu6 1 1 1*10 1 0 7 10 17

mu4_mu6 1 1 1*10 1 0 14 33 47

2mu10 1 1 0 1 0 1 0 1

2mu20 1 1 1 1 0 0 2 2

3mu6 1 1 1 1 0 0 0 0

Menus (13.0.40.4) & Rates for of 10Menus (13.0.40.4) & Rates for of 1032 32 (13 (13th th February)February)

PHYSICS MENU -13.0.40.4 + ratesPHYSICS MENU -13.0.40.4 + rates

SIGNATURESSIGNATURES E32E32

LVL1LVL1 LVL2LVL2 EFEF RATES (Hz)RATES (Hz)

PSPS PTPT PSPS PTPT PS PS ratesrates

PT PT ratesrates

Total Total ratesrates

mu4 1 5*10 400*10 300 0 0.2 0 0.2

mu6 1 1*10 200*10 30 0 3.5 0.1 3.6

mu10 1 10 100*10 1*10 0 1.8 <1 <2.8

mu15 1 1 20*10 1*10 0 5.7 0.2 5..9

mu20 1 1 0 1 0 19 0 19

mu40 1 1 100 1 0 1 1.4 2.4

mu20_passHLT 1 1000 20*10 1 0 0.02 ~0.2 0.22

2mu4 1 1*10 5*10 1 0 2.4 1.3 3.7

2mu6 1 1 100 1 0 7 1 8

mu4_mu6 1 10 200 1 0 1.4 <1.5 <2.9

2mu10 1 1 0 1 0 1 0 1

2mu20 1 1 1 1 0 0 2 2

3mu6 1 1 1 1 0 0 0 0

mu20i mu20i 1 1 0 1 0 5 0 5new

PROPOSAL FOR OPTIMIZATION OF 10PROPOSAL FOR OPTIMIZATION OF 103232

Very fast estimate of the cumulative rate gives : Very fast estimate of the cumulative rate gives : ~50 Hz (against 112 as before)~50 Hz (against 112 as before)

FDR-2 Release13.0.40.4 ( FDR-2 Release13.0.40.4 ( tag 00-00-47-33tag 00-00-47-33))

SIGNATURESSIGNATURES LVL1LVL1 E32E32 E33E33

E32E32 E33E33 LVL2LVL2 EFEF LVL2LVL2 EFEF

PSPS PTPT PSPS PTPT PSPS PTPT PSPS PTPT

mu10 100 100 * 10 1 0 1 0 1 0 1 0

mu20i/ mu20i_tight ( for1033)

1 1 1 0 1 0 1 0 1 0

mu40 / mu40_tight (for 1033)

1 1 1 0 1 0 1 0 1 0

2mu4 (E32) 10 No 1 0 1 0 No No No No

2mu6 1 1 * 10 1 0 1 0 1 0 1 0

2mu10 (E32) 1 No 1 0 1 0 No No No No

2mu15 (E33) No 1 No No No No 1 0 1 0

Not yet inside the menu definition

Status of Muon Trigger CSC Note

• Comments received from referees before Easter– Almost all comments have been implemented

and the remaining ones are going to be finalized

• Mainly editorial work– Figures to be uniformed in style

• New draft sent to referees for further comments

Conclusions • Muon EF performs satisfactory in releases 13 and

14• Several studies of robustness against misalignment

– Need to better understand how much realistic are the considered scenarios

– effort on-going for having realistic (day 0) MS misalignments for FDR2 (~100 microns)

• Muon EF wrappers for offline supertools planned to enter in release 14.1.0– Muon EF AOD under study

• Reenginering of Converters: common effort for different technologies

• Muon trigger menus @ 1032 under optimization– first thoughs for 1033

• Muon trigger CSC note in final shape

Backup

pT(Reco) / pT(Gen) distributions 6 GeV Single Muons Resolution : pT

MuIdCB

12.0.6 13.0.40.2

14.X.0

pT(Reco) / pT(Gen) distributions

19 GeV Single Muons Resolution : pT

MuIdCB

12.0.6 13.0.40.2

14.X.0

Systematic underestimate for release 12.0.6 . This problem seems overcome in the subsequent releases

pT(Reco) / pT(Gen) distributions

100 GeV Single Muons Resolution : pT

MuIdCB

12.0.6 13.0.40.2

14.X.0

pT resolution looks stable wrt releases at high transverse momentum

Mean of pT(Reco) / pT(Gen) gaussian fit

Mean 1/pT : EF MuidSA & MuidCB

12.0.6

13.0.40.2

14.X.0

MuIdSA MuIdCB

No offset appear in reconstructed EF pT

Beam halo

• Samples by A. Stradling:– /castor/cern.ch/user/s/stradlin/PileupNM/

misal1_mc12.007499.singlepart_empty/halo

The Muon Trigger seems unaffected by muons in beam halo (statistical significance to be evaluated according to the luminosity of the simulated sample)

54294 generated events 0 at LVL1 & HLT

ge

n

pT gen (MeV)

pT gen (MeV) gen (rad)

RPC Raw Data and Prep Raw Data

On-line: RDO

Offline: PrepRawData

on-line hits different from off-line hits h.w. duplicated hits due to cabling overlap s.w duplicated hits due to wired-or and logical-or 3 types of trigger hits in the readout

We have to deal with a very different structure of the online and offline data model

Current path to RPC PrepData @ EF

• RPC bytestreamRDOprep data i.e. running the offline algorithm for RDOPRD conversion which, as first step, activates the converter bytestreamRDO– run before the steering (not trigger driven!!!)– converting full event even when working in a region of interest

• inefficient – the reason is having clean PRD collections

• no redundancies /ambiguities– current byte-stream to PRD converter does not solve

overlaps/ambiguities because it scans sequentially the byte-stream and output a PRD for each relevant CM hit

– data clean-up requires to apply some logic on top of raw hits (which must necessarily be organized and stored in some format)

– the most natural and well tested format for that is the RDO