Analysis@FCC

FCCAnalyses framework

Juraj Smieško

CERN

PyHEP.dev 2023

Princeton, 27 July 2023

Introduction

CERN

  • FCCSW
  • FCCAnalyses
  • Phoenix/Web tools

Charles Uni.

  • LAr Calorimeter for FCC-ee
  • TileCal operations
  • TileCal offline DQ tools
  • Pileup mitigation

Comenius Uni.

  • Photon + c-jet / Intrinsic Charm
  • TileCal offline DQ tools
Juraj Smiesko (kjvbrt)

Pronunciation: You-rye

Institute: CERN

Alma Mater: Comenius University, SK

Future Circular Collider

Energy and luminosity upgrade in integrated program

  • FCC-ee (Z, W, H, tt):
    Highest luminosities at Z, W, ZH among
    proposed Higgs and EW factories with
    indirect discovery potential up to ~ 70 TeV
  • FCC-hh (~100 TeV):
    Direct exploration of next energy frontier (~ x10 LHC) and unparalleled measurements
  • Feasibility Status Report in 2025
FCC Placement
FCC Integrated program

See latest FCC Week in London

FCC Detectors

FCC Detectors

See: M. Salvaggi's presentation

FCCAnalyses Scope

Goal of the framework is to aid the users in obtaining the desired results not only from the reconstructed physics objects

Requirements:

  • Efficiency — Make quick turn-around possible
  • Flexibility — Allow heavy customization
  • Ease of use — Should not be hard to start using
  • Scalable — Seamlessly handle from small to large datasets

Key4hep

  • Set of common software packages, tools, and standards for different Detector concepts
  • Common for FCC, CLIC/ILC, CEPC, EIC, …
  • Individual participants can mix and match their stack
  • Main ingredients:
    • Data processing framework: Gaudi
    • Event data model: EDM4hep
    • Detector description: DD4hep
    • Software distribution: Spack

EDM4hep I.

Describes event data with the set of standard objects.

  • Specification in a single YAML file
  • Strives to be minimal
  • Generated with the help of Podio

EDM4hep II.

Example object: 

#-------------  CalorimeterHit
edm4hep::CalorimeterHit:
  Description: "Calorimeter hit"
  Author : "F.Gaede, DESY"
  Members:
    - uint64_t cellID            //detector specific (geometrical) cell id.
    - float energy               //energy of the hit in [GeV].
    - float energyError          //error of the hit energy in [GeV].
    - float time                 //time of the hit in [ns].
    - edm4hep::Vector3f position //position of the hit in world coordinates in [mm].
    - int32_t type               //type of hit. Mapping of integer types to names via collection parameters "CalorimeterHitTypeNames" and "CalorimeterHitTypeValues".
  • Current version: v0.8.0
  • Objects can be extended / new created
  • Bi-weekly discussion: Indico

ROOT RDataFrame

  • Describes processing of data as actions on table columns
    • Defines of new columns
    • Filter rules
    • Result definitions (histogram, graph)
  • The actions are lazily evaluated
  • Multi threading is available out of the box
  • Optimized for bulk processing

Integration with Existing Tools

  • Boundary between reconstruction and analysis blurred
    • Especially for full-sim
    • Plan: Develop algorithm on analysis side, then move to reconstruction
  • Many C++ tools/libraries created over the years
    • Most are integrated into the Key4hep stack
    • At the moment we have:
      • ROOT — together with RDataFrame
      • ACTS — track reconstruction tools
      • ONNX — neural network exchange format
      • FastJet — jet finding package
      • DD4hep — detector description
      • Delphes — fast simulations

Distribution

FCCAnalyses latest release v0.7.0 can be found:

  • As a package in the stable Key4hep stack
    • Allows to quickly put together small analysis
    • Limited options for customization

Latest/development version of the FCCAnalyses can be found:

  • As a package in the nightlies Key4hep stack
    • Might easily break
  • By checking out master branch
    • Allows greater customization
    • Requires discipline

Platforms: CentOS 7, AlmaLinux 9, Ubuntu 22.04

Analysis Architecture

One can write and run an analysis in several ways:

  • Managed mode: fccanalysis run my_ana.py
    • The RDataFrame frame is managed by the framework
    • Analysis script has to contain compulsory attributes
    • Libraries are loaded automatically
    • Dataset metadata are loaded from remote location — CVMFS/HTTP server
    • Batch submission on HTCondor
    • Customization: Possible at the level of analyzer functions
    • Intend for: Quick analysis, no advanced analyzer functions
  • Standalone mode: python my_ana.py
    • The RDataFrame frame is managed by the user
    • Can leverage the FCCAnalyses library of analyzer functions
  • Ntupleizer style

Writing an analyzer function

  • Typically an analyzer is a struct which operates on an EDM4hep object
  • ROOT RDataFrame needs to be aware of the analyzer function
    • Provided as a string
    • A file loaded and JITed by the ROOT.gInterpreter
    • Compiled in the library

Documentation

Several documentation types

Questions

  • Interaction of the C++ analyzer functions with the Python in the context of RDataFrame
  • Efficient work with the Podio and EDM4hep data format
  • Ways to distribute of analyzer functions among the users
  • Large scale management of the pre-generated input samples
  • Integration of facilities needed to support full simulation studies
  • Non CLI based modes of interaction with the analysis code