Helper tasks
Table of contents:
- Timestamp
- Event selection
- Multiplicity and centrality selection in O2
- Particle identification (PID)
- Track Selection
- Track Propagation
Timestamp
The timestamp task is needed to fill the table with timestamps. Timestamp contains the time of a bunch crossing since the start of the run. This time is often needed to retrieve objects in the CCDB (see Tutorial CCDB).
Since the Timestamps table has an entry per bunch crossing it can be joined with table BC. The join is defined by o2::aod::BCsWithTimestamps (see list of defined joins and iterators).
Event selection
Table of contents:
- Concept
- Basic usage in user tasks
- Trigger aliases
- Event selection criteria
- Event selection decisions
- Found bunch crossings
- Configurables
- Remarks
Concept
The main purpose of the event selection framework in O2 is to provide tools to select triggered events and reject pileup, beam-gas and poor quality collisions. Event selection in O2 is based on the concept of derived tables created in dedicated tasks from available AOD contents. o2-analysis-event-selection executable produces two in-memory tables described in EventSelection.h:
EvSels
table joinable withCollisions
table. To be used in analyses based on loops overCollisions
, i.e. majority of ALICE analyses.BcSels
table joinable withBCs
table. To be used in analyses based on loops overBCs
table such as muon arm UPCs, luminosity monitoring etc.
The structure of BcSels
and EvSels
tables is kept the same for Run 2 and Run 3. However, there are conceptual differences between Run 2 and Run 3 workflows:
- Run 3 setup is significantly different from Run 2 setup, e. g. V0C detector is not available in Run 3 etc. Therefore Run-2 minimum bias trigger based on V0A & V0C is no longer available and is replaced with FT0A & FT0C requirement in Run 3. Many other selection criteria used in Run 2 are not applicable in Run 3 (e. g. tracklet-vs-cluser correlation cut).
- While in Run 2 there is a unique matching between Collisions and BCs, it is not the case in Run 3. Time resolution for collisions (=primary vertices) is not precise enough to identify corresponding bunch crossing (=25 ns) without ambiguities. The collision time resolution depends on the number of contributed ITS-TPC tracks, availability of TOF-matched tracks and other factors. One of the main goals of event selection task in Run 3 is to find the original bunch crossing for each collision and check for relevant info in forward detectors (FIT, ZDC). Unambiguous association of collisions to bunch crossings might become very nontrivial in high rate environment.
BcSels
and EvSels
tables contain the following information:
- fired trigger aliases, see Trigger aliases section
- offline event selection criteria such as beam-beam and beam-gas decisions from forward detectors (FV0, FT0, FDD, ZDC) and various in-bunch and out-of-bunch pileup checks, see Event selection criteria section
In addition EvSels
table contains additional info:
- event selection decisions (in
EvSels
table only), i.e. logical combinations of various offline event selection criteria, see Event selection decisions section. For example, sel7 is based on beam-beam decisions in V0A and V0C with additional background, pileup and quality checks - indices to found bunch crossings and corresponding FT0 and FV0 entries (in
EvSels
table only), see Found bunch crossings section.
BcSels
and EvSels
tables are produced by BcSelectionTask and EventSelectionTask, respectively, see Common/TableProducer/eventSelection.cxx
.
There are separate process functions for Run 2 and Run 3 in both tasks. One has to use –process-run 2 or –process-run 3 configurables in json files to switch between these process functions, see Configurables section for more details.
Basic usage in user tasks
In general, one has to follow the following steps:
-
add
EventSelection.h
header:#include "Common/DataModel/EventSelection.h""
-
join Collisions and EvSels tables and use corresponding iterator as an argument of the process function:
void process(soa::Join<aod::Collisions, aod::EvSels>::iterator const& col, ...)
-
check if your trigger alias is fired if you run over Run1 or Run2 data (or future triggered Run3 data):
if (!col.alias_bit(kINT7)) { return; }
Bypass this check if you analyse MC or continuous Run3 data.
- apply further offline selection criteria:
-
for Run 2 data and MC:
if (!col.sel7()) { return; }
-
for Run 3 data and MC:
if (!col.sel8()) { return; }
Note that sel8 selection based on FT0A & FT0C requirement is not mandatory in Run 3 pilot beam data. It might be safer to work with unbiased sample.
-
-
run your tasks in stack with timestamp and event-selection tasks:
o2-analysis-timestamp --aod-file AO2D.root -b | o2-analysis-event-selection -b | o2-analysis-user-task -b
This workflow works for Run 2 data. Special settings are required for MC and Run 3 data, see Configurables section.
o2-analysis-timestamp task
Common/TableProducer/timestamp.cxx
is required to create per-event timestamps necessary to access relevant CCDB objects in the event selection task.o2-analysis-zdc-converter and o2-analysis-collision-converter might be also necessary for old datasets to account for changes in the data model.
Trigger aliases
Direct selection on trigger class names in O2 is rather complicated. In contrast to Run 2 AODs, there is no way to get the list of fired classes in a string-like format. Instead one has to check bits corresponding to trigger class ids either in triggerMask
column in BCs
table or triggerMaskNext50
in Run2BCInfos
table (for Run 2 if the trigger class id is larger than 50). This approach is complicated since trigger class ids for the same class vary from run to run.
To simplify trigger checks, we use trigger alias approach. Fired trigger classes are mapped to trigger alias bits in the alias
array of BcSels
and EvSels
tables. Aliases have at least two advantages:
- several classes based on similar logic can be grouped together into one alias (see kINT7 for example)
- alias bits do not change from run to run in contrast to trigger class ids
The list of available trigger alises can be found in Common/CCDB/TriggerAliases.h
. The mapping between trigger classes (and their indices) and trigger aliases is stored in CCDB
run-by-run in dedicated TriggerAliases objects.
Current mapping can be checked in upload_trigger_aliases.C macro for Run2:
mAliases[kINT7] = "CINT7-B-NOPF-CENT,CINT7-B-NOPF-FAST,CV0L7-B-NOPF-CENT,CINT7-B-NOPF-CENTNOTRD,CINT7ZAC-B-NOPF-CENTNOPMD,CINT7-B-NOPF-ALLNOTRD,CINT7-I-NOPF-ALLNOTRD,CINT7-S-NOPF-ALLNOTRD,CMBAC-B-NOPF-ALL,CMBACS2-B-NOPF-ALLNOTRD,CMBACS2-B-NOPF-ALL";
mAliases[kEMC7] = "CEMC7-B-NOPF-CENTNOPMD,CEMC7-B-NOPF-CENT,CEMC7-B-NOPF-CENTNOTRD,CEMC7-B-NOPF-ALLNOTRD,CEMC7-S-NOPF-ALLNOTRD";
mAliases[kINT7inMUON] = "CINT7-B-NOPF-MUFAST";
mAliases[kMuonSingleLowPt7] = "CMSL7-B-NOPF-MUFAST,CMSL7-B-NOPF-MUON,CMSL7-S-NOPF-MUON,CMSL7-SC-NOPF-MUON,CPBI1MSL-B-NOPF-MUON,CMUS7-B-NOPF-MUON";
mAliases[kMuonUnlikeLowPt7] = "CMUL7-B-NOPF-MUFAST,CMUL7-B-NOPF-MUON,CMUL7-S-NOPF-MUON,CMUL7-S-NOPF-ALLNOTRD,CPBI1MUL-B-NOPF-MUON,CMUU7-B-NOPF-MUON,CMUU7-B-NOPF-ALLNOTRD";
mAliases[kMuonLikeLowPt7] = "CMLL7-B-NOPF-MUFAST,CMLL7-B-NOPF-MUON,CMLL7-S-NOPF-MUON,CPBI1MLL-B-NOPF-MUON";
mAliases[kMuonSingleHighPt7] = "CMSH7-B-NOPF-MUFAST,CMSH7-B-NOPF-MUON,CMSH7-S-NOPF-MUON,CMSH7-S-NOPF-ALLNOTRD,CPBI1MSH-B-NOPF-MUON,CMUSH7-B-NOPF-MUON";
mAliases[kCUP8] = "CCUP8-B-NOPF-CENTNOTRD";
mAliases[kCUP9] = "CCUP9-B-NOPF-CENTNOTRD";
mAliases[kMUP10] = "CMUP10-B-NOPF-MUFAST";
mAliases[kMUP11] = "CMUP11-B-NOPF-MUFAST";
mAliases[kINT1] = "CINT1B-ABCE-NOPF-ALL,CINT1-B-NOPF-ALLNOTRD,CINT1-B-NOPF-ALLNOTRD";
mAliases[kUnbiased] = "CBEAMB-ABCE-NOPF-ALL,CBEAMB-B-NOPF-ALLNOTRD,CTRUE-B-NOPF-ALLNOTRD,CTRUE-S-NOPF-ALLNOTRD,CTRUE-B-NOPF-CENTNOTRD";
mAliases[kDMC7] = "CDMC7-B-NOPF-CENTNOPMD,CDMC7-B-NOPF-CENT,CDMC7-B-NOPF-CENTNOTRD,CDMC7-B-NOPF-ALLNOTRD";
mAliases[kEG1] = "CINT7EG1-B-NOPF-CENTNOPMD,CEMC7EG1-B-NOPF-CENT,CEMC7EG1-B-NOPF-CENTNOTRD,CEMC7EG1-B-NOPF-CENTNOPMD,CEMC7EG1-B-NOPF-ALLNOTRD,CEMC7EGA-B-NOPF-CENTNOTRD,CEMC7EGA-S-NOPF-CENTNOTRD,CEMC7EGA-S-NOPF-ALLNOTRD,CPBI2EGA-B-NOPF-CENTNOTRD";
mAliases[kEJ1] = "CINT7EJ1-B-NOPF-CENTNOTRD,CEMC7EJ1-B-NOPF-CENT,CEMC7EJ1-B-NOPF-CENTNOTRD,CEMC7EJ1-B-NOPF-CENTNOPMD,CEMC7EJ1-B-NOPF-ALLNOTRD,CEMC7EJE-B-NOPF-CENTNOTRD,CEMC7EJE-S-NOPF-CENTNOTRD,CEMC7EJE-S-NOPF-ALLNOTRD,CPBI2EJE-B-NOPF-CENTNOTRD";
mAliases[kEG2] = "CINT7EG2-B-NOPF-CENTNOPMD,CEMC7EG2-B-NOPF-CENT,CEMC7EG2-B-NOPF-CENTNOTRD,CEMC7EG2-B-NOPF-CENTNOPMD,CEMC7EG2-B-NOPF-ALLNOTRD,CEMC7EG2PER-B-NOPF-CENTNOPMD";
mAliases[kEJ2] = "CINT7EJ2-B-NOPF-CENTNOPMD,CEMC7EJ2-B-NOPF-CENT,CEMC7EJ2-B-NOPF-CENTNOTRD,CEMC7EJ2-B-NOPF-CENTNOPMD,CEMC7EJ2-B-NOPF-ALLNOTRD";
mAliases[kDG1] = "CINT7DG1-B-NOPF-CENTNOPMD,CDMC7DG1-B-NOPF-CENT,CDMC7DG1-B-NOPF-CENTNOTRD,CDMC7DG1-B-NOPF-CENTNOPMD";
mAliases[kDJ1] = "CINT7DJ1-B-NOPF-CENTNOPMD,CDMC7DJ1-B-NOPF-CENT,CDMC7DJ1-B-NOPF-CENTNOTRD,CDMC7DJ1-B-NOPF-CENTNOPMD";
mAliases[kDG2] = "CINT7DG2-B-NOPF-CENTNOPMD,CDMC7DG2-B-NOPF-CENT,CDMC7DG2-B-NOPF-CENTNOTRD,CDMC7DG2-B-NOPF-CENTNOPMD,CDMC7DG2PER-B-NOPF-CENTNOPMD";
mAliases[kDJ2] = "CINT7DJ2-B-NOPF-CENTNOPMD,CDMC7DJ2-B-NOPF-CENT,CDMC7DJ2-B-NOPF-CENTNOTRD,CDMC7DJ2-B-NOPF-CENTNOPMD";
and in upload_trigger_aliases_run3.C for Run 3:
mAliases[kTVXinTRD] = "CMTVX-B-NOPF-TRD,minbias_TVX";
mAliases[kTVXinEMC] = "C0TVX-B-NOPF-EMC,minbias_TVX_L0";
mAliases[kTVXinPHOS] = "C0TVX-B-NOPF-PHSCPV,minbias_TVX_L0";
This list of trigger aliases and classes is not complete but it should be enough for tests in various PWGs. New trigger classes and aliases can be added upon request (contact Evgeny Kryshen).
Event selection criteria
Full list of event selection criteria can be found in Common/CCDB/EventSelectionParams.h
enum EventSelectionFlags {
kIsBBV0A = 0, // cell-averaged time in V0A in beam-beam window
kIsBBV0C, // cell-averaged time in V0C in beam-beam window (for Run 2 only)
kIsBBFDA, // cell-averaged time in FDA (or AD in Run2) in beam-beam window
kIsBBFDC, // cell-averaged time in FDC (or AD in Run2) in beam-beam window
kIsBBT0A, // cell-averaged time in T0A in beam-beam window
kIsBBT0C, // cell-averaged time in T0C in beam-beam window
kNoBGV0A, // cell-averaged time in V0A in beam-gas window
kNoBGV0C, // cell-averaged time in V0C in beam-gas window (for Run 2 only)
kNoBGFDA, // cell-averaged time in FDA (AD in Run2) in beam-gas window
kNoBGFDC, // cell-averaged time in FDC (AD in Run2) in beam-gas window
kNoBGT0A, // cell-averaged time in T0A in beam-gas window
kNoBGT0C, // cell-averaged time in T0C in beam-gas window
kIsBBZNA, // time in common ZNA channel in beam-beam window
kIsBBZNC, // time in common ZNC channel in beam-beam window
kIsBBZAC, // time in ZNA and ZNC in beam-beam window - circular cut in ZNA-ZNC plane
kNoBGZNA, // time in common ZNA channel is outside of beam-gas window
kNoBGZNC, // time in common ZNC channel is outside of beam-gas window
kNoV0MOnVsOfPileup, // no out-of-bunch pileup according to online-vs-offline VOM correlation
kNoSPDOnVsOfPileup, // no out-of-bunch pileup according to online-vs-offline SPD correlation
kNoV0Casymmetry, // no beam-gas according to correlation of V0C multiplicities in V0C3 and V0C012
kIsGoodTimeRange, // good time range
kNoIncompleteDAQ, // complete event according to DAQ flags
kNoTPCLaserWarmUp, // no TPC laser warm-up event (used in Run 1)
kNoTPCHVdip, // no TPC HV dip
kNoPileupFromSPD, // no pileup according to SPD vertexer
kNoV0PFPileup, // no out-of-bunch pileup according to V0 past-future info
kNoSPDClsVsTklBG, // no beam-gas according to cluster-vs-tracklet correlation
kNoV0C012vsTklBG, // no beam-gas according to V0C012-vs-tracklet correlation
kNoInconsistentVtx, // no inconsistency in SPD and Track vertices
kNoPileupInMultBins, // no pileup according to multiplicity-differential pileup checks
kNoPileupMV, // no pileup according to multi-vertexer
kNoPileupTPC, // no pileup in TPC
kIsTriggerTVX, // FT0 vertex (acceptable FT0C-FT0A time difference) at trigger level
kIsINT1, // SPDGFO >= 1 || V0A || V0C
kNsel // counter
};
Technically there are three types of criteria:
- based on flags from bc-joinable
aod::Run2BCInfos
table (kIsGoodTimeRange, kNoIncompleteDAQ, kNoTPCLaserWarmUp, kNoTPCHVdip, kNoPileupFromSPD, kNoV0PFPileup) - based on information from FIT and ZDC detectors (kIsBB…, kIsBG…) and/or additional information stored in
aod::Run2BCInfos
table (kNoV0MOnVsOfPileup,kNoSPDOnVsOfPileup) - based on additional information from
aod::Collisions
table
Decisions on inidividual selection criteria are stored in selection array BcSels
and EvSels
tables. E.g. one can check if a given collision passed kIsBBV0A selection:
bool isBBV0Apassed = col.selection_bit(evsel::kIsBBV0A);
Event selection decisions
Offline event selection decisions (e.g. sel7) are constructed based on a subsample of individual checks stored in selection array. The default list of checks may depend on colliding system, specific run conditions and specific analysis requirements. Default set of checks can be found in Common/CCDB/EventSelectionParams.cxx. The default selectionBarrel masks for pp, pA, Ap and AA are summarized below:
- default sel7 selection in pp is based on the requirement of beam-beam timing in V0A and V0C and a number of pileup, beam-gas and othe quality checks
selectionBarrel[kIsBBV0A] = 1;
selectionBarrel[kIsBBV0C] = 1;
selectionBarrel[kNoV0MOnVsOfPileup] = 1;
selectionBarrel[kNoSPDOnVsOfPileup] = 1;
selectionBarrel[kNoV0Casymmetry] = 1;
selectionBarrel[kIsGoodTimeRange] = 1;
selectionBarrel[kNoIncompleteDAQ] = 1;
selectionBarrel[kNoTPCHVdip] = 1;
selectionBarrel[kNoPileupFromSPD] = 1;
selectionBarrel[kNoV0PFPileup] = 1;
selectionBarrel[kNoSPDClsVsTklBG] = 1;
selectionBarrel[kNoV0C012vsTklBG] = 1;
- checks for pA system are similar to pp but in addition they include no beam-gas in ZNA:
selectionBarrel[kNoBGZNA] = 1;
- checks for Ap system are similar to pp but in addition they include no beam-gas in ZNC:
selectionBarrel[kNoBGZNC] = 1;
- default checks for AA are much simpler compared to pp since hadronic pileup is at per-mile level and can be ignored in the first approximation. Default checks include beam-beam timing in V0A, V0C, ZNA and ZNC detectors and a couple of quality checks.
selectionBarrel[kIsBBV0A] = 1;
selectionBarrel[kIsBBV0C] = 1;
selectionBarrel[kIsBBZAC] = 1;
selectionBarrel[kIsGoodTimeRange] = 1;
selectionBarrel[kNoTPCHVdip] = 1;
In addition we define selectionMuonWithPileupCuts and selectionMuonWithoutPileupCuts with reduced set of checks, see Common/CCDB/EventSelectionParams.cxx for more details.
Besides, there are special settings for some run ranges, e.g. we remove checks on out-of-bunch pileup for runs with isolated bunches:
selectionBarrel[kNoV0MOnVsOfPileup] = 0;
selectionBarrel[kNoSPDOnVsOfPileup] = 0;
selectionBarrel[kNoV0Casymmetry] = 0;
selectionBarrel[kNoV0PFPileup] = 0;
These special settings are stored in CCDB. One can find relevant details in upload_event_selection_params.C macro.
Finally, it is worth mentioning that out-of-bunch pileup cuts as well as ZDC timing checks are disabled in MC eventSelection.cxx#L265:
if (isMC) {
applySelection[kIsBBZAC] = 0;
applySelection[kNoV0MOnVsOfPileup] = 0;
applySelection[kNoSPDOnVsOfPileup] = 0;
applySelection[kNoV0Casymmetry] = 0;
applySelection[kNoV0PFPileup] = 0;
}
Selection mask applySelection is obtained from CCDB in eventSelection.cxx:
EventSelectionParams* par = ccdb->getForTimeStamp<EventSelectionParams>("EventSelection/EventSelectionParams", bc.timestamp());
Then sel7 decision is constructed from active checks: Common/TableProducer/eventSelection.cxx
bool sel7 = 1;
for (int i = 0; i < kNsel; i++) {
sel7 &= applySelection[i] ? selection[i] : 1;
}
Found bunch crossings
One of the main goals of the event selection task in Run 3 is to find the original bunch crossing for each collision. The basic approach is to start from estimated collision bc and search for closest BC containing FT0 entries in a +/-4 sigma window where sigma corresponds to the estimated collision time resolution from col.collisionTimeRes()
. Implementation details can be found in eventSelection.cxx#L348.
Users can access found bunch crossings and FT0 entries using foundBC or foundFT0 indices stored in the EvSels table:
if (collision.has_foundBC()) {
auto bc = collision.foundBC();
uint64_t globalBC = bc.globalBC();
}
or
if (collision.has_foundFT0()) {
auto ft0 = collision.foundFT0();
int triggersignals = ft0.triggerMask();
}
If bunch crossing with FT0 entries is not found, foundBC and foundFT0 indices are set to -1 therefore one has to check collision.has_foundBC()
or collision.has_foundFT0()
before accessing corresponding info.
Configurables
Event selection task supports several configurables:
-
muonSelection allows to activate reduced set of checks for muon analyses
Configurable<int> muonSelection{"muonSelection", 0, "0 - barrel, 1 - muon selection with pileup cuts, 2 - muon selection without pileup cuts"};
-
isMC allows to suppress several checks for Run 2 MC, see Event selection decisions:
Configurable<int> isMC{"isMC", 0, "-1 - autoset, 0 - data, 1 - MC"};
Note that one has to enable isRun2MC flag in the timestamp task in this case:
o2-analysis-timestamp --aod-file AO2D.root -b --isRun2MC 1 | o2-analysis-event-selection -b --isMC 1 | o2-analysis-user-task -b
In the case of Run 3 processing, one has to set processRun2=false
and processRun3=true
flags in bc-selection-task
and event-selection-task
. These configurables cannot be set in the command line. Instead one has to use json files. Typical content of the json file for Run 3 processing:
"bc-selection-task": {
"processRun2": "false",
"processRun3": "true"
},
"event-selection-task": {
"processRun2": "false",
"processRun3": "true"
},
One can set other configurables in the json file. This json file has to be provided using --configuration
option:
o2-analysis-timestamp -b | o2-analysis-event-selection --configuration json://config.json -b
Remarks
- One has to apply offline selections in O2 explicitly in contrast to AliPhysics where these selections were applied together with trigger alias selection.
- EvSel table might be also useful in user tasks relying on beam-beam and beam-gas decisions in forward detectors, e.g. in UPC tasks.
Multiplicity and centrality selection in O2
Multiplicity selection concept
The multiplicity and centrality selection in O2 is based on the concept of derived tables created in dedicated tasks from available AOD contents:
- o2-analysis-multiplicity-table task
Common/TableProducer/multiplicityTable.cxx
stores relevant multiplicity values (V0A, V0C, ZNA, ZNC) and their dynamic sums (V0M) inMults
table joinable with Collisions table. - o2-analysis-multiplicity-qa task
Common/Tasks/multiplicityQa.cxx
creates multiplicity distributions in minimum bias triggers necessary for centrality calibration. - o2-analysis-centrality-table task
Common/TableProducer/centralityTable.cxx
takes multiplicity values from theMults
table and stores centrality values inCents
table joinable with Collisions table. Relevant cumulative multiplicity distributions are stored in CCDB. The centrality calibration relies on 90% anchor points in Pb-Pb. - o2-analysis-centrality-qa task
Common/Tasks/centralityQa.cxx
creates centrality distributions for minimum bias triggers and can be used for control and QA purposes.
Note that o2-analysis-multiplicity-qa and o2-analysis-centrality-qa tasks rely on the minimum bias trigger selection therefore one has to run event selection in stack with these tasks.
Multiplicity selection usage in user tasks
One can check o2-analysis-centrality-qa task for example usage: Common/Tasks/centralityQa.cxx
. Usually, analysers perform event selection before the centrality selection therefore one has to consider the following steps:
-
add
EventSelection.h
andCentrality.h
headers:#include "Common/DataModel/EventSelection.h" #include "Common/DataModel/Centrality.h"
-
join Collisions, EvSels and Cents tables and use corresponding iterator as an argument of the process function:
void process(soa::Join<aod::Collisions, aod::EvSels, aod::Cents>::iterator const& col, ...)
-
check if your trigger alias is fired if you run over Run1 or Run2 data (or future triggered Run3 data):
if (!col.alias_bit(kINT7)) return;
Bypass this check if you analyse MC or future continuous Run3 data.
-
apply further offline selection criteria:
if (!col.sel7()) return;
-
apply centrality selection, for example:
// analyse 0-20% central events if (col.centV0M()>20) return;
-
run your tasks in stack with timestamp, event-selection, multiplicity and centrality tasks:
o2-analysis-timestamp --aod-file AO2D.root -b | o2-analysis-event-selection -b | o2-analysis-mulitplicity-table -b | o2-analysis-centrality-table -b | o2-analysis-user-task -b
o2-analysis-timestamp task is required to create per-event timestamps necessary to access relevant CCDB objects in the event selection and/or centrality tasks.
o2-analysis-zdc-converter and o2-analysis-collision-converter might be also necessary for old datasets to account for changes in the data model.
Particle identification (PID)
Table of contents:
- Introduction
- Usage in user tasks
- Task for TOF and TPC PID
- Example of tasks that use the PID tables (and how to run them)
Here are described the working principles of Particle Identification (PID) in O2 and how to get PID information (expected values, nSigma separation et cetera) in your analysis tasks if you plan to identify particles.
Introduction
PID is handled in analysis by filling helper tables that can be joined to tracks (propagated or not).
The parameterization of the expected detector response (e.g. signal, resolution, separation) is used in the PID tasks to fill the PID tables.
These parameterizations are detector specific and handled by the detector experts; usually, they are shipped to the PID helper tasks from the CCDB to match the data-taking conditions.
The interface between the detector and the Analysis Framework (i.e. your tracks) is fully enclosed in PIDResponse.h
.
Here are the defined tables for the PID information for all the detectors.
The filling of the PID tables is delegated to dedicated tasks in Common/TableProducer/PID/
Examples of these tasks can be found in pidTOF.cxx
and pidTPC.cxx
for TOF and TPC tables, respectively.
Usage in user tasks
Tables for PID values in O2 are defined in PIDResponse.h
.
You can include it in your task with:
#include "Common/DataModel/PIDResponse.h"
...
In the process functions, you can join the table to add the PID (per particle mass hypothesis) information to the track.
In this case, we are using the mass hypothesis of the electron, but tables for nine (9) stable particle species are produced (El
, Mu
, Pi
, Ka
, Pr
, De
, Tr
, He
, Al
).
-
For the TOF PID as:
void process(soa::Join<aod::Tracks, aod::pidTOFEl>::iterator const& track) { track.tofNSigmaEl(); }
-
For the TPC PID as:
void process(soa::Join<aod::Tracks, aod::pidTPCEl>::iterator const& track) { track.tpcNSigmaEl(); }
-
For both TOF and TPC PID information as:
void process(soa::Join<aod::Tracks, aod::pidTOFEl, aod::pidTPCEl>::iterator const& track) { const float combNSigmaEl = std::sqrt( track.tofNSigmaEl() * track.tofNSigmaEl() + track.tpcNSigmaEl() * track.tpcNSigmaEl()); }
Task for TOF and TPC PID
In short: O2 tasks dedicated to the filling of the PID tables are called with
-
Filling TOF PID Table
o2-analysis-pid-tof
This requires a helper class for the building of the event time information
o2-analysis-pid-tof-base
These tasks can be configured according to the needs specified by the detector experts. If you are in doubt, you can contact them or take the configuration of the Hyperloop as a reference.
-
Filling the TPC PID Table
o2-analysis-pid-tpc
o2-analysis-pid-tpc-base
These tasks can be configured according to the needs specified by the detector experts. If you are in doubt, you can contact them or take the configuration of the Hyperloop as a reference.
Example of tasks that use the PID tables (and how to run them)
-
TOF PID task
pidTOF.cxx
You can run the TOF spectra task with:o2-analysis-pid-tof-qa --aod-file AO2D.root -b | o2-analysis-pid-tof -b | o2-analysis-pid-tof-base -b
-
TPC PID task
pidTPC.cxx
You can run the TPC spectra task with:o2-analysis-pid-tpc-qa --aod-file AO2D.root -b | o2-analysis-pid-tpc -b | o2-analysis-pid-tpc-base -b
Enabling QA histograms
-
QA histograms should come with the PID tasks; they can be enabled by including the QA tasks in your workflow when running locally or with the corresponding QA tasks as in:
For the TOF QA plots
... | o2-analysis-pid-tof-qa | ...
For the TPC QA plots
... | o2-analysis-pid-tpc-qa | ...
Where by
...
we mean the other tasks in your workflow.
Track Selection
The track selection in the O2 analysis framework is provided in form of a stand-alone workflow that you can run in front of your analysis:
o2-analysis-trackselection | o2-analysis-myTask
Based on a set of track quality criteria, the track selection workflow produces a flag.
Provided that the user uses the standard supported o2-analysis-trackselection
track tables can be filtered, e.g. by requiring global tracks (with cuts on pT and eta), in the following manner:
#include "Analysis/TrackSelectionTables.h"
...
// NB: this only works provided that you use the supported task o2-analysis-trackselection to perform the track selection
Filter filter1 = requireTrackCutInFilter(TrackSelectionFlags::kTPCNCls); // General filter, defined using flags
Filter filter2 = requireQualityTracksInFilter(); // Predefined filter, for kQualityTracks tracks
Filter filter3 = requirePrimaryTracksInFilter(); // Predefined filter, for kPrimaryTracks tracks
Filter filter4 = requireInAcceptanceTracksInFilter(); // Predefined filter, for kInAcceptanceTracks tracks
Filter filter5 = requireGlobalTrackInFilter(); // Predefined filter, for kGlobalTrack tracks
Filter filter6 = requireGlobalTrackWoPtEtaInFilter(); // Predefined filter, for kGlobalTrackWoPtEta tracks
Filter filter7 = requireGlobalTrackWoDCAInFilter(); // Predefined filter, for kGlobalTrackWoDCA tracks
Filter filter8 = requireTrackWithinBeamPipe(); // Tracks starting from within the beam pipe
void process(soa::Filtered<soa::Join<aod::Tracks, aod::TrackSelection>>::iterator const& track)
{
...
}
In general it is advised to use the filter decisions only in the filter expressions, so the framework can optimize the processing. However, if really needed you can also access the filtering decisions in the following way:
#include "Analysis/TrackSelectionTables.h"
...
void process(soa::Join<aod::Tracks, aod::TrackSelection>::iterator const& track)
{
// Check single cuts
track.passedTrackType(); // Passed the track cut: kTrackType
track.passedPtRange(); // Passed the track cut: kPtRange
track.passedEtaRange(); // Passed the track cut: kEtaRange
track.passedTPCNCls(); // Passed the track cut: kTPCNCls
track.passedTPCCrossedRows(); // Passed the track cut: kTPCCrossedRows
track.passedTPCCrossedRowsOverNCls();// Passed the track cut: kTPCCrossedRowsOverNCls
track.passedTPCChi2NDF(); // Passed the track cut: kTPCChi2NDF
track.passedTPCRefit(); // Passed the track cut: kTPCRefit
track.passedITSNCls(); // Passed the track cut: kITSNCls
track.passedITSChi2NDF(); // Passed the track cut: kITSChi2NDF
track.passedITSRefit(); // Passed the track cut: kITSRefit
track.passedITSHits(); // Passed the track cut: kITSHits
track.passedGoldenChi2(); // Passed the track cut: kGoldenChi2
track.passedDCAxy(); // Passed the track cut: kDCAxy
track.passedDCAz(); // Passed the track cut: kDCAz
// Check combiation of cuts (filterbit like)
track.isQualityTrack(); // Passed the combined track cut: kQualityTracks
track.isPrimaryTrack(); // Passed the combined track cut: kPrimaryTracks
track.isInAcceptanceTrack(); // Passed the combined track cut: kInAcceptanceTracks
track.isGlobalTrack(); // Passed the combined track cut: kGlobalTrack
track.isGlobalTrackWoPtEta(); // Passed the combined track cut: kGlobalTrackWoPtEta
track.isGlobalTrackWoDCA(); // Passed the combined track cut: kGlobalTrackWoDCA
}
Some of the track parameters used in the track selection require additional calculation effort and are then stored in a table called TracksExtended
which is produced by either the o2-analysis-trackextension
task (Run 2) or o2-analysis-track-propagation
(Run 3).
The quantities contained in this table can also be directly used in the analysis.
For instance if you require the distance of closest approach (dca) to the primary vertex, you do not need to (and should not!) re-calculate it in your task.
You can simply obtain it by extending the Tracks
table in the following way and then access it directly as a property of the track:
void process(soa::Filtered<soa::Join<aod::Tracks, aod::TrackSelection, aod::TracksDCA>>::iterator const& track)
{
track.dcaXY();
track.dcaZ();
}
Both the definition of TrackSelection
and the TracksDCA
tables can be found here: TrackSelectionTables
.
If you want to have a look at the track parameters after the selection, you can use the o2-analysis-qa-event-track
task:
o2-analysis-trackselection | o2-analysis-qa-event-track | ...
At the moment there are two ‘FilterBits' available in the TrackSelection table, which are defined as follows:
Cuts | globalTrack | globalTrackSDD |
---|---|---|
min number of crossed rows TPC | 70 | 70 |
min ratio of crossed rows over findable clusters TPC | 0.8 | 0.8 |
max chi2 per cluster TPC | 4.0 | 4.0 |
max chi2 per cluster ITS | 36.0 | 36.0 |
require TPC refit | true | true |
require ITS refit | true | true |
max DCA to vertex z | 2.0 | 2.0 |
max DCA to vertex xy | 0.0105 * 0.035 / pT1.1 | 0.0105 * 0.035 / pT1.1 |
cluster requirement ITS | Run 2 (Run 3): at least one hit in SPD (in 3 innermost ITS layers) [*] | no hit in SPD and hit in first SDD layer |
pT range | 0.1 - 1e10 | 0.1 - 1e10 |
η range | -0.8 - 0.8 | -0.8 - 0.8 |
[*]
RUN2 data/MC analyses (isRun3 == false
)The default set of global-track selections requires at least 1 hit between the two innermost ITS layers (function getGlobalTrackSelection
in TrackSelectionDefaults.h
).This is a Run 1, 2 refuse when the SPD was equipped, and currently this is enabled ONLY for analyses on Run2 converted data (isRun3 == false
).
RUN3 data/MC analyses (isRun3 == true
)The same set of global-track selections, but with different ITS requirements for Run3 data are available in trackselection.cxx
. This is possible thanks to the getGlobalTrackSelectionITSMatch
in TrackSelectionDefaults.h
, which can be enabled with different ITS requirements via the integer configurable itsMatching
in trackselection.cxx
. The available configurations are the following:
itsMatching == 0
: at least one hit between the two innermost ITS layers (default forisRun3 == false
). IMPORTANT: in caseisRun3 == true
, thenitsMatching == 0
enablesitsMatching == 1
automatically (a WARNING is dumped at runtime);itsMatching == 1
: at least one hit among the three innermost ITS layers (Run3ITSibAny
, default forisRun3 == true
);itsMatching == 2
: at least one hit among all the ITS layers (Run3ITSallAny
);itsMatching == 3
: one hit on all the ITS layers (Run3ITSall7Layers
);
The goal of the track selection task is to provide the most common selections for all analyses.
If you really require a completely different set of tracks not covered by the standard filter bits, you can create your own TrackSelection object (see TrackSelectionTables.h
and trackselection.cxx
) :
TrackSelection myTrackSelection()
{
TrackSelection selectedTracks;
selectedTracks.SetTrackType(aod::track::Run2GlobalTrack);
selectedTracks.SetPtRange(0.1f, 1e10f);
selectedTracks.SetEtaRange(-0.8f, 0.8f);
selectedTracks.SetRequireITSRefit(true);
selectedTracks.SetRequireTPCRefit(true);
selectedTracks.SetRequireGoldenChi2(true);
selectedTracks.SetMinNCrossedRowsTPC(70);
selectedTracks.SetMinNCrossedRowsOverFindableClustersTPC(0.8f);
selectedTracks.SetMaxChi2PerClusterTPC(4.f);
selectedTracks.SetRequireHitsInITSLayers(1, {0, 1}); // one hit in any SPD layer
selectedTracks.SetMaxChi2PerClusterITS(36.f);
selectedTracks.SetMaxDcaXYPtDep([](float pt) { return 0.0105f + 0.0350f / pow(pt, 1.1f); });
selectedTracks.SetMaxDcaZ(2.f);
...
return selectedTracks;
}
...
// member of analysis task
TrackSelection mySelection;
...
// in init()
mySelection = myTrackSelection();
...
// in process()
bool isSelected = mySelection.IsSelected(track)
Remarks on track selection
Please note that this documentation only represents the status quo of the track selection implementation and many things can and will change. In particular the cut values will most likely change with the ‘new' detector in Run 3 and some of the legacy cuts will be removed or only available for converted Run 2 data. In case of questions or suggestions don't hesitate to contact us.
Track Propagation
The Run 3 AO2D stores the tracks at the point of innermost update. For a track with ITS this is the innermost (or second innermost) ITS layer. For a track without ITS, this is the TPC inner wall or for loopers in the TPC even a radius beyond that. In the AO2D.root the trees are therefore called O2tracks_IU and O2tracksCov_IU (IU = innermost update). The corresponding O2 data model tables are TracksIU and TracksCovIU, respectively. If your task needs tracks at the collision vertex it will fail because it looks for O2tracks and O2tracksCov.
In order to propagate the tracks to the collision vertex, include the task o2-analysis-track-propagation
into your workflow.
This task produces the tables Tracks and TracksCov (in order to get the latter, please enable processCovariance
through the json configuration).
This task also produces the TrackExtended
table needed for o2-analysis-track-selection
, therefore o2-analysis-trackextension
does not need to be added to the workflow at the same time.
This task is not needed for Run 2 converted data where the tracks are already propagated to the collision vertex.
The overall table flow is illustrated here:
TrackTuner
The TrackTuner
class (Common/Tools/TrackTuner.h) allows to smear the reconstructed track parameters.
Such tool is primarely conceived to smear the parameters of tracks reconstructed in MC simulations according to the discrepancy between data and MC of the dcaXY and dcaZ.
This task was called improver-task
in the Run 2 jargon
The smearing is done on the y
, z
parameters of each reconstructed track in MC evaluated at the associated particle production point. The smearing is based on the discrepancy between resolution, mean and pull ratio of dcaXY, dcaZ w.r.t. primary vertex measured in data and MC.
The performance of such parameters is evaluated vs. global-track pt and stored into .root
files, which can be read from CCDB at runtime.
An instance of the TrackTuner
class is present as data-member in the trackPropagation
workflow, and it can be enabled via
Configurable<bool> useTrackTuner{"useTrackTuner", false, "Apply Improver/DCA corrections to MC"};
The TrackTuner
can be enabled only if the processCovarianceMc
process function in the trackPropagation
workflow is used
This object can be configured through the Configurable<std::string> trackTunerParams
in the trackPropagation
workflow. This configuration std::string
must define the following parameters:
bool debugInfo
: flag to switch on/off some debug outputsbool updateTrackDCAs
: flag to switch on/off the smearing of the dcaXY, dcaZbool updateTrackCovMat
: flag to enable the update of the track covariance matrix, propagating the scaling on the dca resolutionbool updatePulls
: flag to enable the update of the track covariance matrix updating also the pulls (ifupdateTrackCovMat == true
)std::string pathInputFile
: path to browse to find the correction file for the dca smearingstd::string nameInputFile
: name of the correction file for the dca smearingbool isInputFileFromCCDB
: thepathInputFile/nameInputFile
is searched in CCDB if this flag istrue
, otherwise in the local file system (debug purposes)bool usePvRefitCorrections
: if this flag istrue
, the track smearing is performed using mean, resolution and pulls parametrizations vs. pt of dcaXY, dcaZ calculated w.r.t. primary collision vertex refitted w/o the current track, if this was originally a PV contributorNoteIn pp collisions, one should use
usePvRefitCorrections == true
This is not relevant in Pb-Pb collisions.std::string pathFileQoverPt
: path to browse to find the correction file for theq/pt
smearingstd::string nameFileQoverPt
: name of the correction file for theq/pt
smearingbool updateCurvature
: flag to enable the update of the track curvature, i.e.q/pt
, at the particle production pointbool updateCurvatureIU
: flag to enable the update of the track curvature, i.e.q/pt
, at the innermost update (IU) pointfloat oneOverPtMC
(MC) andfloat oneOverPtData
(data): the ratiooneOverPtData/oneOverPtMC
defines the scaling factor to theq/pt
residual to smear the track ptfillTrackTunerTable
: flag to enable the filling of a new table containing for each track the smearedq/pt
at the IU point
- The
TrackTuner
allows also to smear theq/pt
if only one betweenupdateCurvature
andupdateCurvatureIU
istrue
- By default, the variables
oneOverPtData
andoneOverPtMC
are initialized to-1
- If at least one between
qOverPtMCq
andOverPtData
is negative, theq/pt
correction is done wuering the file from CCDB. Otherwise, the input values ofqOverPtMC
andqOverPtData
are used to defined the factoroneOverPtData/oneOverPtMC
, which is a constant factor flat in transverse momentum.
The string trackTunerParams
must follow the format: <variable_name>=<value>|<variable_name>=<value>
(see the default configuration here as reference).
The dcaXY, dcaZ parametrization currently available are the following:
- proxy for pp @ 13.6 TeV: trackTuner_DataLHC23fPass1_McLHC23k4b_run535085.root Data: LHC23f apass1, run 535085. MC: LHC23k4b, run 535085. Slides here.
- [NEW] proxy for pp @ 13.6 TeV: trackTuner_DataLHC23hPass4_McLHC23k4g.root Data: LHC23h apass4. MC: LHC23k4g. Slides here.
- proxy for Pb-Pb @ 5.36 TeV: trackTuner_DataLHC22sPass5_McLHC22l1b2_run529397.root Data: LHC22s apass5, run 529397. MC: LHC22l1b2, run 529397. Slides here.