2.3: Particle Flow ToolsMark Thomson

University of Cambridge

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Overview

Vienna, March 2014

Task 2.3 Work described here from three groups

Cambridge• PandoraPFA framework• algorithm development/optimisation

CERN• extensive validation• performance benchmarking

LLR• algorithm development

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Particle Flow Reminder

Vienna, March 2014

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Traditional Calorimetry

Traditional calorimetric approach: Measure all components of jet energy in ECAL/HCAL ! ~70 % of energy measured in HCAL: Intrinsically “poor” HCAL resolution limits jet energy resolution

In a typical jet : 60 % of jet energy in charged hadrons 30 % in photons (mainly from ) 10 % in neutral hadrons (mainly and )

EJET = EECAL + EHCAL

np+

g

Mark Thomson

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PFlow Paradigm Particle flow approach:

Try and measure energies of individual particles Reduce dependence on intrinsically “poor” HCAL resolution

EJET = ETRACK + Eg + En

Vienna, March 2014 Mark ThomsonMark Thomson

Idealised Particle Flow Calorimetry paradigm: charged particles measured in tracker (essentially perfectly) Photons in ECAL: Neutral hadrons (ONLY) in HCAL Only 10 % of jet energy from HCAL

EJET = EECAL + EHCAL

np+

g

improved jet energy resolution

6

PFlow Paradigm Particle flow approach:

Try and measure energies of individual particles Reduce dependence on intrinsically “poor” HCAL resolution

EJET = ETRACK + Eg + En

Vienna, March 2014 Mark ThomsonMark Thomson

Idealised Particle Flow Calorimetry paradigm: charged particles measured in tracker (essentially perfectly) Photons in ECAL: Neutral hadrons (ONLY) in HCAL Only 10 % of jet energy from HCAL

EJET = EECAL + EHCAL

np+

g

improved jet energy resolution

Complex Pattern Recognition

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PandoraPFA Such high granularity Pflow reconstruction is non-trivial !

PandoraPFA initially developed for “proof of principle” at the ILC

Clustering Topological Association

30 GeV12 GeV

18 GeV

Iterative Reclustering

9 GeV9 GeV

6 GeV

Photon ID Fragment ID

MT, NIM 611 (2009) 24-40 For more details:Vienna, March 2014

ECA

LH

CA

L

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The AIDA Work

Vienna, March 2014

PFlow framework - PandoraPFA PFlow tools

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PandoraPFA

Vienna, March 2014

Pandora Software Originally written in “physicist C++” Then thrown away….

~

Pandora Software Development Kit 6 – 12 months of careful design Robust, fast, optimised container choices, etc. Through AIDA, evolved through new applications

ILC CLIC

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PandoraPFA

Vienna, March 2014

Redesign Implementation GeneralisationSoftware engineering Coding Development through

multiple use cases

Development process Three main steps

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Framework

Vienna, March 2014

The new PandoraPFA framework – detector independent

Create Calo Hits

Create Tracks

Create MC Particles

Register User Content

Clustering Algorithm

Topological Association Algorithms

Statistical Reclustering Algorithm

Photon RecoveryAlgorithm

Fragment Removal Algorithms

Track-cluster Association Algorithms

PFO Construction Algorithm

Pandora

AlgManag

er Calo Hit

Manager

Cluster

Manager

MC Manag

erGeome

try Helper

Pandora

Settings

Track Manag

er

Particle Flow Object Manag

er

Get Particle Flow Objects

Client Application: Pandora Framework, treat as “black box”:

Pandora Algorithms:

Pan

dora

AP

IP

andora Content

AP

I

Highly optimised (CPU/memory footprint) framework User code “Algorithms” separated from Framework code

Generic Aspects Stand-alone library accessed via APIs

“add calorimeter hit” “add track” “return particle flow objects”

Framework Aspects deal with memory management designed to be compact and very fast runs Algorithms supports external plug-ins (via APIs), e.g. algorithms, PID,…

No external dependencies ! 0 % root inside

No internal use of geometry information e.g. hits are now self-defining (size, orientation)

Within AIDA also developed internal event display (CERN)

Designed to be Generic and reusable

“Easily” adaptable to any detector

Vienna, March 2014 Mark Thomson 12

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LC Use case

Vienna, March 2014

PandoraPFA used as workhorse for CLIC CDR (2012) and ILC TDR (2013) All full simulation physics studies based on PandoraPFA reconstruction ! Client applications written for two different detector concepts

+ variants for CLIC

EJETRMS90/EJ

45 GeV 3.6 %100 GeV 2.9 %250 GeV 2.8 %500 GeV 3.0 %1 TeV 3.2 %1.5 TeV 3.2 %

e.g. CLIC CDR

Benchmark studies (Cambridge/CERN) published:“Performance of particle flow calorimetry at CLIC”, J.S. Marshall et al., NIM A 700, 2013, 153-162

Mark Thomson

Beyond the LC

Vienna, March 2014 14

New Pandora software designed to be generic just write the interface (Pandora application)

First non-LC use case… CALICE

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CALICE application

Vienna, March 2014

CERN developed client to PandoraPFA for CALICE test beam e.g. 80 GeV pion test beam

Once client application was written, reco. worked out of the box… Demonstrated “generic” nature, but this is an LC calorimeter prototype…

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AIDA WorkFar beyond the LC

Vienna, March 2014

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Generalisation

Vienna, March 2014

Originally PandoraPFA tied to LC detector studies AIDA re-implementation as a framework

greatly increased flexibility part of AIDA project aims was to utilise this new flexibility

Now have a number of client apps 3 separate “content” libraries of algorithms

Fine Granularity calorimetry – e.g. LC detectors Coarse Granularity calorimetry – e.g. LHC detectors Liquid Argon reconstruction – Neutrino physics

New use cases, drive new features New applications making code more general

e.g. no assumptions about geometry hits can be 2D or 3D (e.g. Liquid Argon TPC) hits can be shared between clusters (e.g. ATLAS)

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Neutrino Physics

Vienna, March 2014

Liquid Argon TPCs likely to form basis of future neutrino oscillation experiments Large volume detectors with ~1mm3 granularity

i.e. Fine Granularity calorimeters Long standing problem

lack of automated reconstruction softwareo non-trivial – large numbers of hitso applications often run into memory/CPU limitations

Need optimised framework… PandoraPFA

PandoraPFA framework applied to this problem improved SDK

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e.g. LArSoft Architecture

Vienna, March 2014

InputGeometry

Hits

Algorithms

PandoraAPIs

OutputReco Particles

LArPandoraInterfaceart::producer

LArPandoraAlgorithms

PandoraPFA

SDK& Monitoring

Inputs:GeometryService

recob::Hits

Outputs:recob::Clusters

LArSoft

PandoraLArSoft

framework

(LArPandoraAlgorithms:housed within LArSoft,

as mirror of SVN).

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Recent Developments

Vienna, March 2014

Many framework improvements Developed for LAr - but wider applications Recent highlights:

templating of all internal objects/managers• easy to expand, e.g. new vertex class

Adding of AlgTools• Plug-ins for algorithms

+ code re-organisation• ease of maintenance

Work in last 6 months focussed on LAr TPC reconstruction

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Eye Candy

Vienna, March 2014

16 GeV ne CC

(a) (b)

27 GeV anti-ne CC

e-

p-

p0

gp+

g

g

p+

p+

e+

p-

p pp-

Now being used for MicroBooNE (data this year) and LBNE

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Eye Candy

Vienna, March 2014

16 GeV ne CC

(a) (b)

27 GeV anti-ne CC

e-

p-

p0

gp+

g

g

p+

p+

e+

p-

p pp-

Now being used for MicroBooNE (data this year) and LBNE

Getting close to full reco chain

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PandoraApplications

c. 2014

Vienna, March 2014

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Pandora Customers

Vienna, March 2014

LC Applications: All ILC physics studies, both ILD and SiD All CLIC physics studies, both CLIC_ILD and CLIC_SiD + Linear Collider Detector optimisation

Neutrino Applications: Strong candidate for MicroBooNE reconstruction Being developed for LBNE physics studies + studies for LBNO (Warwick)

LHC/HL-LHC Applications CMS now have a Pandora application (Athens) Being investigated for CMS upgrade studies (see later) + discussions with ATLAS groups

AIDA: Pandora generic/reusable framework

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Algorithm Development at

LLR

Vienna, March 2014

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In Period P1 (reminder)– Development of photon finder: GARLIC

– JINST: D. Jeans, J. Brient, and M. Reinhard, “GARLIC: GAmma Reconstruction at a LInear Collider experiment,” JINST 7 (2012) P06003, arXiv:1203.0774 [physics.ins-det].

– development of an event display for PFA (DRUID)– ACAT'11: M. Ruan, “Druid, displaying root module used for linear collider detectors,” in

Proceedings ACAT’2011, vol. 368, p. 012040. September, 2011. http://indico.cern.ch/event/93877/

– Fractal dimension of showers as ParticleID and Energy estimators:– ACAT'11: M. Ruan, V. Boudry, J. Brient, D. Jeans, and H. Videau, “Fractal dimension

analysis in a highly granular calorimeter,” in Proceedings ACAT’2011, vol. 368, p. 012038. September, 2011. http://indico.cern.ch/event/93877/

In period P2:– PRL: M. Ruan, D. Jeans, V. Boudry, J.-C. Brient, and H. Videau, “Fractal Dimension of

Particle Showers Measured in a Highly Granular Calorimeter,” Phys. Rev. Lett. 112 (Jan, 2014) 012001, arXiv:1312.7662 [physics.ins-det]. http://link.aps.org/doi/10.1103/PhysRevLett.112.012001.

– A tree like clustering algorithm for PFA (ARBOR)– CHEF'13 M. Ruan, “ARBOR, a new approach of the Particle Flow Algorithm,” in

Proceedings, International Conference on Calorimetry for the High Energy Frontier (CHEF 2013), J.-C. Brient, ed. April, 2013. arxiv.org:1403.4784 [physics.ins-det]. http://llr.in2p3.fr/chef2013/index.php

Papers: Reco. Tools

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ARBORTopological clustering by connection of hits (cells) & cleaning

– Every branch is created (backwards)• Only longest ones are kept

– Link branches to trees according to spatial distances• Branch information is kept

track finder e.g. for fitting⇒

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ARBORExcellent agreement for track length:e.g. single gun event at ILD RPC HCAL, compare length:• Charged MCParticle: spatial

distance between start & end points• Arbor branch: sum of distance

between neighbouring cells

Separation:overlay showers

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Fractal Dimensions New way of classifying showers for PiD based on fractal dimension

published in PRL

MCSDHCAL test beam

Looks promising

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LLR Algorithms

Very promising ideas Now need to:

integrate into repository Integrate into PandoraPFA

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CMS-HGCAL Studies

SHASHLIK (LYSO) or SILICON –Tungsten

High Granularity Si-W ECAL for the CMS endcap upgrade Application of PandoraPFA, GARLIC and ARBOR foreseen this year (part of MS15) Work has started, e.g.

pp min-bias 140 pile-up: display with DRUID

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Conclusions

Vienna, March 2014

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Conclusions AIDA funded Particle Flow Calorimetry work is progressing well

PandoraPFA framework, LC reimplementation, Neutrino physics, real LHC interest

LC benchmarking, visualisation, CALICE application

e.g. Arbor algorithm + fractal dimensions

Milestones & Deliverables: MS10: month 10 : “Application of prototype PFA for LC” D2.5 : month 12 : “Software design for PFA” D2.9 : month 38 : “Particle flow software tools” MS15: month 44 : “Application of PFA tools to sLHC detectors”

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