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The Arbor Particle Flow Algorithm approach Reconstruction of single particle and overlaid particles Journées Collisionneur Linéaire 2014 - Grenoble Eté Rémi Université Claude Bernard Lyon 1 Institut de Physique Nucléaire de Lyon December 3, 2014 R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 1 / 15

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  • The Arbor Particle Flow Algorithm approachReconstruction of single particle and overlaid particles

    Journées Collisionneur Linéaire 2014 - Grenoble

    Eté Rémi

    Université Claude Bernard Lyon 1Institut de Physique Nucléaire de Lyon

    December 3, 2014

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 1 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryIntroduction

    Particle flow approach is believed to be the most adapted algorithm for Linear Collider Detectors design.The software approach is (rather) simple and works in conjunction with the detector granularity (calorimeters).

    Working principle :

    Identify tracks (Tracker) that can lead to clusters in calorimeters.

    From these tracks, build clusters (ECAL+HCAL) using track momentum→ Charged particlereconstruction

    Remove energy deposition from charged particles

    Build clusters from remaining energy depositions (ECAL+HCAL)→ Neutral particle reconstruction

    The performance of a Particle Flow implementation is mainly characterised by

    Jet Energy Resolution (JER)

    Confusion term (mis-identified energy deposition)

    Performance in physics analysis

    the three characteristics being correlated ...

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 2 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryIntroduction

    Particle flow approach is believed to be the most adapted algorithm for Linear Collider Detectors design.The software approach is (rather) simple and works in conjunction with the detector granularity (calorimeters).

    Working principle :

    Identify tracks (Tracker) that can lead to clusters in calorimeters.

    From these tracks, build clusters (ECAL+HCAL) using track momentum→ Charged particlereconstruction

    Remove energy deposition from charged particles

    Build clusters from remaining energy depositions (ECAL+HCAL)→ Neutral particle reconstruction

    The performance of a Particle Flow implementation is mainly characterised by

    Jet Energy Resolution (JER)

    Confusion term (mis-identified energy deposition)

    Performance in physics analysis

    the three characteristics being correlated ...

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 2 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryIntroduction

    Particle flow approach is believed to be the most adapted algorithm for Linear Collider Detectors design.The software approach is (rather) simple and works in conjunction with the detector granularity (calorimeters).

    Working principle :

    Identify tracks (Tracker) that can lead to clusters in calorimeters.

    From these tracks, build clusters (ECAL+HCAL) using track momentum→ Charged particlereconstruction

    Remove energy deposition from charged particles

    Build clusters from remaining energy depositions (ECAL+HCAL)→ Neutral particle reconstruction

    The performance of a Particle Flow implementation is mainly characterised by

    Jet Energy Resolution (JER)

    Confusion term (mis-identified energy deposition)

    Performance in physics analysis

    the three characteristics being correlated ...

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 2 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryIntroduction

    Particle flow approach is believed to be the most adapted algorithm for Linear Collider Detectors design.The software approach is (rather) simple and works in conjunction with the detector granularity (calorimeters).

    Working principle :

    Identify tracks (Tracker) that can lead to clusters in calorimeters.

    From these tracks, build clusters (ECAL+HCAL) using track momentum→ Charged particlereconstruction

    Remove energy deposition from charged particles

    Build clusters from remaining energy depositions (ECAL+HCAL)→ Neutral particle reconstruction

    The performance of a Particle Flow implementation is mainly characterised by

    Jet Energy Resolution (JER)

    Confusion term (mis-identified energy deposition)

    Performance in physics analysis

    the three characteristics being correlated ...

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 2 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryImplementation

    Many implementations of the Particle Flow Algorithm exist :

    PandoraPFA is currently the one that gives the best performances.The clustering algorithm is a cone-based approach. Also runs multiple clustering algorithm to optimizethe track-cluster association.Designed and tuned with 3x3cm2 Analog HCAL.Adopted by ILC community for physics analysis !

    ArborPFA which is currently under development.The clustering algorithm is tree-based approach. No use of energy information within the algorithm forthe time being, only topology.Designed for any calorimeter.Currently tuned for 1x1cm2 cell size without any energy readout dependency (AHCAL/DHCAL/SDHCAL).Still under development

    IowaPFA developped for SiD design.Gives similar results to PandoraPFA on physics analysis

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 3 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryImplementation

    Many implementations of the Particle Flow Algorithm exist :

    PandoraPFA is currently the one that gives the best performances.The clustering algorithm is a cone-based approach. Also runs multiple clustering algorithm to optimizethe track-cluster association.Designed and tuned with 3x3cm2 Analog HCAL.Adopted by ILC community for physics analysis !

    ArborPFA which is currently under development.The clustering algorithm is tree-based approach. No use of energy information within the algorithm forthe time being, only topology.Designed for any calorimeter.Currently tuned for 1x1cm2 cell size without any energy readout dependency (AHCAL/DHCAL/SDHCAL).Still under development

    IowaPFA developped for SiD design.Gives similar results to PandoraPFA on physics analysis

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 3 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryImplementation

    Many implementations of the Particle Flow Algorithm exist :

    PandoraPFA is currently the one that gives the best performances.The clustering algorithm is a cone-based approach. Also runs multiple clustering algorithm to optimizethe track-cluster association.Designed and tuned with 3x3cm2 Analog HCAL.Adopted by ILC community for physics analysis !

    ArborPFA which is currently under development.The clustering algorithm is tree-based approach. No use of energy information within the algorithm forthe time being, only topology.Designed for any calorimeter.Currently tuned for 1x1cm2 cell size without any energy readout dependency (AHCAL/DHCAL/SDHCAL).Still under development

    IowaPFA developped for SiD design.Gives similar results to PandoraPFA on physics analysis

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 3 / 15

  • Particle Flow Calorimetry

    Particle Flow CalorimetryImplementation

    Many implementations of the Particle Flow Algorithm exist :

    PandoraPFA is currently the one that gives the best performances.The clustering algorithm is a cone-based approach. Also runs multiple clustering algorithm to optimizethe track-cluster association.Designed and tuned with 3x3cm2 Analog HCAL.Adopted by ILC community for physics analysis !

    ArborPFA which is currently under development.The clustering algorithm is tree-based approach. No use of energy information within the algorithm forthe time being, only topology.Designed for any calorimeter.Currently tuned for 1x1cm2 cell size without any energy readout dependency (AHCAL/DHCAL/SDHCAL).Still under development

    IowaPFA developped for SiD design.Gives similar results to PandoraPFA on physics analysis

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 3 / 15

  • The Arbor algorithm

    The Arbor algorithmPrinciple

    Clustering algorithm that uses connectors between calo hits.Build clusters with an oriented tree topology.

    Key point : The reconstruction follows the underlying physics principle of the shower !

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 4 / 15

  • The Arbor algorithm

    The Arbor algorithmPrinciple

    Clustering algorithm that uses connectors between calo hits.Build clusters with an oriented tree topology.

    Key point : The reconstruction follows the underlying physics principle of the shower !

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 4 / 15

  • The Arbor algorithm

    The Arbor algorithmPrinciple

    Clustering algorithm that uses connectors between calo hits.Build clusters with an oriented tree topology.

    Key point : The reconstruction follows the underlying physics principle of the shower !

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 4 / 15

  • The Arbor algorithm

    The Arbor algorithmPrinciple

    Clustering algorithm that uses connectors between calo hits.Build clusters with an oriented tree topology.

    Key point : The reconstruction follows the underlying physics principle of the shower !

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 4 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Intra-layer clusteringGroup of mip hits and group of isolated hits→ ObjectsOther hits (shower core, larger structures)→ ObjectsEffects in clustering algorithm :

    decrease multiplicity effects

    decrease processing time (Nhit > Nobj )

    Entering 

    Particle

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Tag isolated objects that are not part of :

    the shower core

    mips

    Special treatment in clustering part ...

    Entering 

    Particle

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Look in the forward direction at a maxi-mum distance of ∆max and createmany connections with other objects.

    Δmax

    FIGURE : Single object connection

    Entering 

    Particle

    FIGURE : Calorimeter view after seeding connectors

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Reference direction :

    ~Cref = wfwd .∑f~cf −wbck .∑

    b~cb (1)

    Kappa order parameter :

    κ =(

    θ2π

    )pθ.(

    ∆∆max

    )p∆(2)

    Entering 

    Particle

    FIGURE : Calorimeter view after first connector cleaning

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Starts from cleaned connections.Look in a forward/backward coneof length ∆max ,c of half angle θcand create many connections

    θc

    Δmax, c

    FIGURE : Alignment procedure

    Entering 

    Particle

    FIGURE : Calorimeter view after the second seeding step

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Same cleaning as before ...

    Entering 

    Particle

    FIGURE : Calorimeter view of the final tree structure

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Entering 

    Particle

    FIGURE : Calorimeter view of the final tree structure

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Project the track entering point on the calorimeter front face and find alltree starting points (seeds) within a distance ∆track . Create an associa-tion between the cluster (tree) and the track.

    Δ track

    FIGURE : Topological track association view

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Dedicated algorithm for neutral particles.Merge trees in a single one when their seeds are close to each others

    within the same layer.

    FIGURE : Neutral tree merging view

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Merging of small structures into bigger ones (closest barycenter)

    Entering 

    Particle

    FIGURE : Small neutral fragment merging view

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • The Arbor algorithm

    The Arbor algorithmArbor algorithms

    Object Creation

    Isolation TaggingConnector ClusteringAlgorithm

    Connector IterationAlgorithms

    Connector Seeding 1Connector Cleaning 1Connector Seeding 2Connector Cleaning 2

    Tree BuildingAssociation Algorithms

    Topological TrackAssociationNeutral Tree MergingSmall Neutral Merging

    Pfo Creation

    Create Particle Flow Objects from reconstructed trees and tracks.

    NEUTRALPARTICLE

    CHARGEDPARTICLE

    FIGURE : Final output Pfos of ArborPFA

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 5 / 15

  • Pfo analysis

    Pfo analysisData set

    Using Semi-Digital HCAL (3 thresholds) data set of pi− with

    Standalone Geant4 simulation (A. Steen)

    Test beam data (AUG-SEPT 2012, CERN SPS)

    Selection cuts applied on both TB and simulation data (see CAN-037).

    Studying :

    Single particle reconstruction from 10 up to 80 GeV :EfficiencyReconstructed energyNumber of pfos

    Overlaid particles for 10 and 30 GeV neutral pi and 30 GeV charged pi− and for a separation distancefrom 5 up to 30 cm

    EfficiencyPurityReconstructed energiesNumber of Pfos

    Running ArborPFA (v01-03-00) and PandoraPFA (v00-12) with only a HCAL (SDHCAL) and a set a generatedtracks in front of the calorimeter for charged particles

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 6 / 15

  • Pfo analysis

    Pfo analysisSingle particle study

    E [GeV]

    10 20 30 40 50 60 70 80

    pfo

    #N

    0

    0.5

    1

    1.5

    2

    2.5

    3

    PandoraPFA - Simulation

    PandoraPFA - Test Beam

    ArborPFA - Simulation

    ArborPFA - Test Beam

    PRELIMINARY

    E [GeV]

    10 20 30 40 50 60 70 80

    Effi

    cien

    cy

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PandoraPFA - Simulation

    PandoraPFA - Test Beam

    ArborPFA - Simulation

    ArborPFA - Test Beam

    PRELIMINARY

    E [GeV]

    10 20 30 40 50 60 70 80

    Rec

    onst

    ruct

    ed e

    nerg

    y

    0

    10

    20

    30

    40

    50

    60

    70

    80

    90

    PandoraPFA - Simulation

    PandoraPFA - Test Beam

    ArborPFA - Simulation

    ArborPFA - Test Beam

    PRELIMINARY

    Less splitting of single showers for ArborPFA.

    But the efficiency and the reconstructed energy shows similar performance.

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 7 / 15

  • Pfo analysis

    Pfo analysisOverlay study. 10 GeV neutral pi + 10 GeV charged pi-

    Distance between showers [cm]

    5 10 15 20 25 30

    pfo

    #N

    0

    0.5

    1

    1.5

    2

    2.5

    3

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Cha

    rged

    par

    ticle

    pur

    ity

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Cha

    rged

    par

    ticle

    effi

    cien

    cy

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Neu

    tral

    par

    ticle

    pur

    ity

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Neu

    tral

    par

    ticle

    effi

    cien

    cy

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 8 / 15

  • Pfo analysis

    Pfo analysisOverlay study. 10 GeV neutral pi + 10 GeV charged pi-

    Distance between showers [cm]

    5 10 15 20 25 30

    Mea

    n of

    rec

    onst

    ruct

    ed c

    harg

    ed e

    nerg

    y [G

    eV]

    0

    2

    4

    6

    8

    10

    12

    14

    16

    18

    20

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Mea

    n of

    rec

    onst

    ruct

    ed n

    eutr

    al e

    nerg

    y [G

    eV]

    0

    2

    4

    6

    8

    10

    12

    14

    16

    18

    20

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    /E o

    f rec

    onst

    ruct

    ed c

    harg

    ed e

    nerg

    yEσ

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    /E o

    f rec

    onst

    ruct

    ed n

    eutr

    al e

    nerg

    yEσ

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 9 / 15

  • Pfo analysis

    Pfo analysisOverlay study. 10 GeV neutral pi + 30 GeV charged pi-

    Distance between showers [cm]

    5 10 15 20 25 30

    pfo

    #N

    0

    0.5

    1

    1.5

    2

    2.5

    3

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Cha

    rged

    par

    ticle

    pur

    ity

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Cha

    rged

    par

    ticle

    effi

    cien

    cy

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Neu

    tral

    par

    ticle

    pur

    ity

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Neu

    tral

    par

    ticle

    effi

    cien

    cy

    0

    0.1

    0.2

    0.3

    0.4

    0.5

    0.6

    0.7

    0.8

    0.9

    1

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 10 / 15

  • Pfo analysis

    Pfo analysisOverlay study. 10 GeV neutral pi + 30 GeV charged pi-

    Distance between showers [cm]

    5 10 15 20 25 30

    Mea

    n of

    rec

    onst

    ruct

    ed c

    harg

    ed e

    nerg

    y [G

    eV]

    20

    22

    24

    26

    28

    30

    32

    34

    36

    38

    40

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    Mea

    n of

    rec

    onst

    ruct

    ed n

    eutr

    al e

    nerg

    y [G

    eV]

    -20

    -15

    -10

    -5

    0

    5

    10

    15

    20

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    /E o

    f rec

    onst

    ruct

    ed c

    harg

    ed e

    nerg

    yEσ

    0

    0.05

    0.1

    0.15

    0.2

    0.25

    0.3

    0.35

    0.4

    0.45

    0.5

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    Distance between showers [cm]

    5 10 15 20 25 30

    /E o

    f rec

    onst

    ruct

    ed n

    eutr

    al e

    nerg

    yEσ

    0

    0.2

    0.4

    0.6

    0.8

    1

    1.2

    1.4

    1.6

    PRELIMINARY

    ArborPFA - Simulation

    PandoraPFA - Simulation

    ArborPFA - Test Beam

    PandoraPFA - Test Beam

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 11 / 15

  • Pfo analysis

    Conclusions and plans

    Conclusions :

    ArborPFA and PandoraPFA have both good results for single particle reconstruction in terms of efficiencyand reconstructed energy.

    The overlay shower study shows very different behaviors for the 2 algorithms but are able to recovercorrectly the shower energy until 10 cm separation distance.

    PandoraPFA shows for both single particle and overlaid showers studies a high number of unphysicalPFOs ...

    Plans :

    Run PFAs on new test beam data (currently running at CERN SPS ,)Prepare a working version for ILD studies and extract general PFA performances plots.

    Include photon and electron clustering in the ECAL (GARLIC ?)Manage hadronic shower part in the ECAL.Implement a dedicated algorithm for ECAL-HCAL gap region (cluster connection)Muon clustering (Arbor standalone ? Pandora ? New tracking tools ?)

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 12 / 15

  • Pfo analysis

    Thank you for your attention !

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 13 / 15

  • Backup

    Event display

    Neutral π of 30 GeV overlaid with a charged π− of 50 GeV at 5 cm distance.

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 14 / 15

  • Backup

    Shower structure

    Neutral π of 30 GeV overlaid with a charged π− of 50 GeV at 10 cm distance.

    R. Eté (UCBL - IPNL) Arbor PFA December 3, 2014 15 / 15

    Particle Flow CalorimetryThe Arbor algorithmPfo analysis