Particle Flow Calorimetry Technology Requirements and ...
Transcript of Particle Flow Calorimetry Technology Requirements and ...
Particle Flow Calorimetry Technology Requirements and Opportunities
François Corriveau
Institute of Particle Physics of Canada and McGill University (Montréal)
American Workshop for Linear Colliders 2020
October 21st, 2020
2020.10.21 F.Corriveau (IPP/McGill) - AWLC 2020 - Particle Flow Calorimetry 1
Content
• Particle Flow & Calorimetry
• Electromagnetic Calorimeters
• Hadronic Calorimeters
• Particle Flow Algorithms (PFA)
• Case Study
• Summary and Outlook
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Particle Flow - Principle
1) Identify and follow each particle in the detector 2) Optimize the event reconstruction for energy/momentum/position/(time) 3) Use the best available information for each particle, such as:
• tracker information for charged particles • electromagnetic calorimeter for photons • hadronic calorimeter for neutral hadrons • .. and their inter-correlations
This then requires from the detectors:
• accurate tracking with high efficiency • high calorimeter granularity (particle separation) • maximum hermiticity in containing particles
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Identify each leaf, connects it to a branch, etc. down to the tree.
From “Traditional” to “Novel” Detectors
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PFA is actually routinely applied to single particles in most detectors. The technique however hits limitations and breaks down:
• when the particle density saturates the detector granularity, or • in large background events, such as at hadron colliders, or • for hadronic “jets” typical of event final states at LCs
e+e- colliders provide a unique opportunity to exploit the full potential of PFA:
• relatively less background • design of the detectors around PFA techniques • use of the latest reconstruction methods
Content (fluctuations!) and Current Resolutions:
• charged particles ~60% • photons ~29% • neutral hadrons ~10% • neutrinos ~ 1%
ideal resolution: dominated by hadronic resolution
charged photons
neutral hadrons
neutrinos Hadronic Jets
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However, other effects come to play and worsen the achievable resolution:
• tracking and support material in front of the electromagnetic calorimeter • “confusion” term when particle association/separation is ambiguous • tracking efficiency, missing energy, ..
aim for: (σ/E ≤ 2.5% for E>100 GeV)
→ 25-30%
CALICE
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type absorber method active material
Technologies R&D Collaboration
Electromagnetic Calorimeters
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ECAL must be a compact highly granular calorimeter optimized for electron and photon reconstruction, as well as separation from hadrons Main requirements:
• High-Z (Pb or W) absorber needed to keep shower radius small • Cell sizes of the order of 5 × 5 mm2 • There are easily millions of channels: cost and data volume challenges • Readout via silicon pads or scintillator strips (price vs size)
Alternatives?
• Monolithic Active Pixel Sensors (MAPS) technology offers extreme granularity but at a yet prohibitive cost.
24 layers, 30 µm pitch, 4×4×12 cm3, 39 M pixels! Nuclear and Particle Physics Proceedings 273–275 (2016) 1090–1095
CALICE – Si-W ECAL
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new technological prototype with tungsten absorber Si pads: 5 × 5 mm2 (ILD design) 15 Si layers × 1024 channels/layer ≈ 15000 cells
going to test beams again at the end of 2020 components could be installed in a e+e- collider!
Previous: Development of a track-finding algorithm • removal of interaction region: hits ≥ 6 neighboring pads • clusterisation of energy deposits: seeds from downstream • track-like clustering: minimal length and limited curvature
99.7% efficiency for muons, ≤10% agreement between MC and π data Numerous results: energy fraction in core, lateral size, Nclusters, Ntracks, Nhits per track, angle distribution, .. Use secondary (~MIP) tracks for in situ calibration? Insights to be incorporated into PFA optimization.
π-
arXiv:1902.06161
integrated front end electronics, compact readout
CALICE – Si-W ECAL
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With relaxed geometrical constraints, 8 modules were used to build a “long slab” typical of what is needed for the ILD barrel. Successful feasibility studies: mechanical structure cosmics electronics tested with sources MIP response DESY beams
arXiv:2004.13791v1
arXiv:1909.04329
Also in the works: development of an ultra-thin PCB called Chip-on-Board (COB) that is equipped with wirebonded ASICs and pixelated silicon wafers to form the basic unit of detection.
long slab: 144 cm × 18 cm
Design configuration: “(20+10)”, i.e. 20 thin W layers (2.5 mm) 10 thick W layers (5.0 mm) 1.25 mm readout gap
Energy leakage of electromagnetic particles estimated by analyzing the patterns in total energy deposition in each layer using neural networks. (18+6) vs (60+0) GEANT4 models, with:
• energies range: 20 – 300 GeV • incidence angles θ = 0° - 45° • azymuthal angles φ = 0° - 30°
Design performance possible with 16+8 configuration:
SiD – Si-W ECAL
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arXiv:2002.05871
+ 30 Si layers
arXiv:1306.8329 - ILC TDR 4: Detectors
6” wafer
CALICE – Scintillator ECAL
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A 32-layer prototype is under construction in China. Option for CEPC and ILC electromagnetic calorimeters.
45×5×2mm3 scintillator strips 2.45×1.9×0.85 mm3 SiPM
assembled layer
Strips could be read at both ends of longer strips to increase accuracy and provide redundancy. CHEF 2019
arXiv:2002.01809v2
Test beams at DESY early 2021
Hadronic Calorimeters
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HCAL must be very large in order to contain extended hadronic showers at LC energies. However the granularity does not need to be as extreme as for electromagnetic calorimeters. Main requirements:
• Traditional approach: Fe or Pb absorbers can be used Scintillator as affordable active medium
• Cell sizes of the order of 30 × 30 mm2 • Readout is now possible via silicon photo-multipliers (SiPM)
advantages: small, tile-integrable, low voltage (~60-100 V) disadvantages: saturation leads to non-linearities (can be handled)
• There are also millions of channels: cost and data volume challenges Several approaches are investigated in analog or digital modes.
SiPM
38 layers 72×72×2.5 cm3 / layer 22,000 tiles SiPM under the tiles for better uniformity and light collection each cell also provides time information with ~1ns resolution a true 5D “pixel” detector: x,y,z,E,t
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CALICE - Analog Hadronic Calorimeter
AHCAL 2018
layer 100 GeV pion
CHEF 2019
CALICE – (Semi-)Digital Hadronic Calorimeters
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DHCAL (ANL+) SDHCAL (Lyon+)
1 m3 1 m3
50 layers, based on cheap/tested resistive plate chamber technology. 96 × 96 channels per layer, i.e. 460,800 1×1 cm2 readout channels. Energies are not measured, but hits are counted → simple, fast readout. Principle demonstrated, still issues.
48 layers × 26 mm, also made of glass RPC. 96 × 96 channels per layer, i.e. 442,368 1×1 cm2 readout channels. Energies are not measured per se, but hits are counted with 3 thresholds coded into 2 bits → pads with few, many or lots of hits. Optimize hadronic shower reconstruction via choice of thresholds. Better linearity response, improved energy resolution.
test beam π± energy resolution
CALICE 2005
CALOR 2016 arXiv:2004.02972
Pandora PFA
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“traditional” “novel” M. Thomson, J.B. Marshall
Cambridge LC Group
However, there might be confusion in particle reconstruction, such as: Hence constraints on both calorimeters and software.
A PFA is a set of algorithms for pattern recognition and particle reconstruction.
arXiv:1308.4537
Pandora PFA - Approach
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“Implement a large number of ‘decoupled’ pattern-recognition algorithms, each of which looks to reconstruct specific particle topologies, whilst carefully avoiding causing confusion”
working outwards topological merging tracker-calorimeter improve match neutral vs charged particle flow objects particle identification CLIC Workshop 2013
Pandora PFA - Performance
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ILC: Tested with ILD-model Monte-Carlo Z’→jj events produced at rest at 4 energies
(θ = polar angle)
100-250 GeV jets: resolution ~constant (barrel) 45 GeV jets: limited by intrinsic term high energy jets: limited by confusion term PFA robust wrt shower parameters
CLIC (higher energies and larger backgrounds): e.g. W vs Z separation (pT, PID) “traditional” “novel” e+e-→WW→µνqq
e+e-→ZZ→ννqq W/Z energies: 125-1000 GeV overlaid γγ→hadrons background (BX=beam crossing) 2σ separation without background ~1.7σ with 60BX background
/
[GeV]
arXiv:1308.4537
CLIC Workshop 2013
Arbor PFA
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Shower development topology in an imaging calorimeter reminds of a tree structure. Backward approach, from leaf to branches to tree with seeds often in the last layers
April APRIL ≈ Arbor PFA with modified cluster merging for SDHCAL
Garlic Gamma reconstruction at a Linear Collider arXiv:1203.0774
→ extra slides
→ extra slides
Other examples:
CMS - High Granularity Calorimeter Upgrade
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High luminosity LHC will have radiation background conditions such that the current CMS endcap calorimeter will no longer be efficient: an upgrade opportunity to reach for new physics with the HGCAL. High granularity to distinguish very narrow VBF jets + Timing for an effective pile-up rejection → complex and ambitious new detector
TICL – The Iterative Clustering
modular framework for particle reconstruction
1) pattern recognition: from hits to tracksters 2) GPU-friendly 2D clustering 3) NN → Particle ID score and energy regression
CHEF 2019
Summary and Outlook
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Future detectors need high granularity and novel techniques such as Particle Flow Algorithms to reach for new physics:
Calorimeters are becoming imaging devices of unprecedented precision, including time info, with numerous new challenges.
PFAs exploit these capabilities with new approaches, which might/will include Neural Networks and Machine Learning.
The ILC is the perfect opportunity for this symbiosis.
Extra Slides
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CALICE Collaboration
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~340 physicists and engineers 58 institutes 18 countries 4 regions
R&D international collaboration towards highly granular calorimetry optimized for particle flow event reconstruction for future detectors focusing on ILC and CLIC
several technologies are studied prototypes tested in particle beams investigate performances in details
https://twiki.cern.ch/twiki//bin/view/CALICE
Pandora PFA - Particle Identification
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Arbor PFA
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Shower development topology in an imaging calorimeter reminds of a tree structure. Step 1: initial hit cleaning if necessary (e.g. noise) close pairs of hits are connected a connector is the outgoing vector between them Step 2: a reference direction calculated from a hit position and the directions of its outgoing connectors the most likely incoming connector is kept → tree structure this structure can be iterated. Tree means no loop. Step 3: some hits are seeds (no ingoing connector) or leafs (no outgoing connector) tracing from leaf to seed → branches → tree ideal case, a tree = a particle shower intuitive, effective is separating nearby showers
The algorithm is next applied to jets Reconstructed energy for e.g. Higgs decay events Jet energy resolution comparable to Pandora’s
arXiv:1403.4784
APRIL: Algorithm for Particle Reconstruction at ILC from Lyon
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APRIL ≈ Arbor PFA with modified cluster merging for SDHCAL
(Pandora PFA assumes linear responses as in AHCAL case) SDHCAL energy reconstruction: Ereco = α1N1 + α2N2 + α3N3 where Ni are the number of hits for each threshold
CHEF 2019
APRIL
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Tracks: 1) clustering done by Arbor with parameters set to avoid big clusters 2) remaining hits merged by efficient Nearest Neighbour clustering (mlpack) 3) keep only one backward connection per hit (minimal angles × distance) Clusters: 1) cluster merging similar to above hit clustering 2) function of cluster orientations and distances 3) (work in progress, e.g. splitting/reclustering) Results: jet energy resolution in barrel at MZ APRIL: 4.2% → competitive with Pandora (<60 GeV) Pandora: 4.1% “ideal PFA”: 3.3% CHEF 2019