Physik-Institut
Experimental Methods in Particle Physics
(HS 2015)
Electronics, Data Acquisition and
Trigger
- Trigger Lea Caminada
lea.caminada@physik.uzh.ch
Overview
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Interlude: LHC operation
Data rates at LHC
Trigger overview
Coincidence logic
Pipelines
Higher complexity systems
Important concepts
–  Occupancy
–  Pileup
–  Cross talk
–  Random coincidences
–  Dead time
Interlude: LHC operation
LHC
Proton bunches
•  2808 bunches per
beam
•  1011 protons per
bunch
•  40 MHz bunch
collision rate
•  BX: bunch crossing
LHC Fill
•
An LHC fill usually lasts a
few hours
•
After injection and
acceleration, the beams
are
–  first, focused
–  then, brought into collision
•
LHC then “declares stable
beams” à experiments
start data-taking
•
Luminosity decreases over
the course of the run
•
Divide run into “luminosity
sections” (also called
“luminosity blocks”)
Trigger
Large data volume at the LHC
•  Proton-proton collision rate at LHC is 40 MHz
•  Pixel detector has 66M readout channels out of
which O(104) are hit in an event
•  Data size to be stored for each pixel is 4 byte
à  Data volume of 120 000 TB per day!
•  Offline data analysis would take forever…
•  Therefore:
à  Need to reduce data volume online: Trigger
à  Hardware and/or software trigger select events in
real time based on relevant detector information
Trigger Concepts
•  In collider experiments, events of interest occurs at much
lower rate compared to proton-proton collision rate
Trigger Strategy
•  Good knowledge of detector and signatures is
needed to efficiently select interesting events
–  Relevant detector parts and their performance
–  Needed/desired measurement precision
–  Physical properties of signal and background events
(expected signatures, kinematic distributions, mass
constraints, etc.)
•  In case of multipurpose experiment: Decide which
processes are important…
•  Trigger strategy needs detailed planning and has
physical, technical and political aspects.
Important parameters
•  Timing
–  How long does the trigger need to form decision
–  Need fast processes
–  Need intermediate storage
•  Rate
–  Maximum rate defined by available bandwidth for
permanent storage
–  Usually given by background levels
•  Efficiency
–  Efficiency to select signal events
–  Optimized according to physics needs
Simple Trigger Setup
•  Trigger setup for a sensor producing a signal at a
random time (for example cosmic rays, radioactive
decay)
DET
DELAY
ADC
DISCR
CONVERSION SIGNAL FOR ADC
•  Discriminator is used to form conversion signal
for ADC
•  Signal is passed over delay line
Coincidence Trigger
DET 1
DISCR
DELAY
SCALER
COINCIDENCE
(“AND”)
DET 2
DISCR
DELAY
•  Setup to detect 2-body decay, for example π0 à ϒϒ
Coincidence Trigger
Input 1
Input 2
Output
•  Coincidence triggers if there is some overlap during
time window Δt
•  In order to allow for a true coincidence, both signals
need to have same length signal path à need to
introduce (and adjust) delay lines
Random Coincides
•  Need to take into account probability that coincidence
trigger registers two hits which are not from the same
event:
P = Δt × Z1 × Z2, where
Δt: time window of coincidence
Z1, Z2: count rate of detector 1,2
TRUE CONINCIDENCDE
RANDOM CONINCIDENCDE
Dead time
•  Dead time is the time that the detector and readout
electronics are busy with processing the previous
event and not ready to accept new events
•  Any event that happens during the dead time is lost!
•  Measures for dead time:
–  Total dead time d: usually measured in percent as a fraction
of the total measuring time
–  Dead time per event τ: measured in ms (determined by actual
processing time in the electronics circuits)
Dead time:
Events with random time distribution
•  Efficiency is related to total dead time by: ε = 1 - d
•  For a source with actual event rate Rtrue, the events that can
be detected is:
–  Racc = ε Rtrue = (1-d) Rtrue
•  The total dead time is related to the dead time per event:
–  d = Racc τ = (1-d) Rtrue τ
•  The total dead time then becomes: d = (Rtrue τ)/(1+Rtrue τ)
•  And the efficiency becomes: ε = 1/(1+ Rtrueτ)
•  Note that the efficiency decreases with increasing rate
•  Note that there will always be some dead time
Dead time:
Events with fixed occurrence (collider)
•  Events occur at fixed rate with time separation tBX
•  Two possible scenario:
–  τ < tBX à no dead time (used to be the case at LEP)
–  τ >> tBX à need to keep event rate low! à complex trigger
system
From coincidence triggers to higher
complexity
•  Two ways:
1)  Larger number of channels à more complex
combinations
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Usually based on FPGAs (field programmable gate array)
Several hundred inputs
Programmable operations à complex logic combinations
à Need longer delay lines: time for calculation increases with
complexity
2)  Additional computations after digitization
-
For example: π0 àϒϒ: Compute π0- mass from energy of detected
photons , then apply mass window selection
à Second trigger level (can be built from FPGA or fast
processors)
à Need long delay lines and intermediate storage
FPGA
•  Designed to be configured by customer after
manufacturing using hardware description language
(HDL)
•  Contain large number of logic gates and RAM blocks
•  Logic blocks can be configured to perform complex
combinatorial functions
Pipelines
•  Simple delay lines usually not feasible for long delays
–  100ns delay need about 20m cable
•  Pipelines allow for intermediate storage
–  Analog pipelines: built from switch capacitance
–  Digital pipelines: using digital registers
buffer cell
•  Pipelines consist of several buffer cells.
Pipelines
•  R/W pointers are moved by given clock frequency
buffer cell
–  Chosen to match time resolution of detector signal
read pointer
write pointer
Pipelines
•  R/W pointers are moved by given clock frequency
–  Chosen to match time resolution of detector signal
buffer cell
•  Latency: time difference between read and write
pointer
read pointer
latency (<buffer length)
write pointer
Pipelines
•  R/W pointers are moved by given clock frequency
–  Chosen to match time resolution of detector signal
buffer cell
•  Latency: time difference between read and write
pointer
•  Circular buffer: pointer jump back to first cell when
they reach end of buffer
read pointer
latency (<buffer length)
write pointer
Example: Multi-step trigger for π0 à γγ
•  Step 1: Digital signal of photon energy from ADC
•  Step 2: Adding the two values
•  Step 3: Comparing the sum to 2 values (upper
and lower bound of π0-mass window), can be
done in parallel
•  Step 4: Store event if mlow < mϒϒ < mhigh
à  Trigger latency is 4 tBX
à  3 events at the same time in the pipeline
Note: Trigger decision at LHC takes longer than tBX
à trigger decision itself needs to be pipelined
Occupancy
•  Probability to see a signal in a given channel
•  Aim is to have small occupancy (<<1)
•  Probability to create fake matches (for example
hits to tracks) increases with increasing
occupancy
Pileup
•  Electronic pileup:
Signal has too long decay time
à comparator still high when next event arrives
à not possible to record new event
à data loss
Pileup
•  Pileup from additional pp collisions at the LHC
•  At LHC, bunches contain 1011 protons à several
collisions can happen at the same time
•  Hard process (the process of interest which
triggers the readout) overlayed by particles from
other collisions
•  Particles from secondary collisions will need to be
identified offline and subtracted
Pileup in ATLAS
Pileup in CMS
Pileup in Run 1
Peak pileup vs time
Peak luminosity vs time
Pileup in Run 1
Pileup in Run 2
CMS Trigger System
CMS Trigger System
CMS Trigger System: L1 and HLT
•  LHC BX rate: 40 MHz
•  L1:
–  100 kHz rate
–  3.2us latency (128 BX)
•  HLT:
–  ~ 300 Hz rate
–  150ms latency (depends on CPU)
~300 Hz
CMS L1 Trigger
•  Fast readout of the
detector with limited
granularity
•  Only muon system
and calorimeter take
part in decision
•  Implementation using
FPGA and ASICs
•  Synchronous
operation
CMS L1 Trigger Objects
•  Track segments in the
muon system
–  muons
•  Towers of calorimeter
cells in ECAL and
HCAL:
–  Jets, electrons, photons
–  Total energy, missing
energy
–  Isolation
CMS L1 muon trigger
CMS L1 calo trigger
CMS L1 Trigger
CMS L1 Trigger Menu Example (2012)
Trigger
Threshold [GeV]
Single muon
16
Double muon
10, 3.5
Isolated double muon
3, 0
Single e/gamma
22
Isolated single e/gamma
20
Double e/gamma
13, 7
Muon + electron
7, 12
Single jet
128
Ouad jet
4 x 40
Six jet
6 x 45
MET
40
HT
150
L1 rate depends on luminosity
•  Trigger menu needs to be adjusted over the
course of the experiment
Trigger prescales
•  Use prescales to adjust rate of a given trigger
–  Needed at high-luminosity runs for some triggers to
keep system alive
–  Prescale n: Keep only every nth event
(Prescale 1 means no prescale)
•  Dynamic prescales
–  Based on the availability of trigger bandwidth
–  Automatically reduce prescales as the luminosity falls
over the course of the run
•  Note: Needs to be taken into account in offline
physics analysis!
L1 muon triggers
L1 jet triggers
CMS High-Level Trigger (HLT)
•  Events that are
accepted by L1 are
passed to HLT
•  Full readout of the
detector at 100 kHz
•  Implemented as
software algorithms
running on large cluster
of commercial
processors (event filter
farm)
~15k cores (30k processors or threads)
The challenge
CMS High-Level Trigger (HLT)
•  Form regions of
interest to speed up
reconstruction
–  i.e. if there is a L1
muon or calo tower à
perform local
reconstruction
surrounding detectors
•  Reject events as
early as possible to
free CPUs
CMS HLT Objects
•  Muons
–  Tracker and muon system
•  Electrons and photons
–  Tracker and calorimeter
•  Taus
–  Tracker and calorimeter
•  Jets, MET, HT
–  Tracker and calorimeter
•  B-tagging (secondary
vertices)
–  Tracker
•  Other more complex
variables
HLT muons
•  Muons
•  Track segment in muon system
•  Matched to track in tracking detector
•  Isolation requirement based on calorimeter
HLT electrons and photons
•  Tower in
electromagnetic
calorimeter
•  Matched track in
tracking detector?
–  yes: electron,
no: photon
•  Isolation requirement
based on calorimeter
HLT taus
•  Leptonic tau decays
(e,mu) usign e/mu
triggers
•  Hadronic tau decays: 1prong or 3-prong decays
•  Calo cluster matched to
tracks in tracker detector
•  Isolation requirement
based on calorimeter
detector
HLT b-tagging
•  Calo cluster with
associated tracks in the
tracker detector
•  B-tagging based on long
lifetime of b-quark and its
large mass
•  Form secondary vertex
from tracks in jet
HLT menu
CMS HLT Trigger Menu Example (2012)
Trigger
Threshold [GeV]
Single muon
40
Single isolated muon
24
Double muon
17, 8
Single electron
80
Isolated single electron
27
Single photon
150
Double photon
36, 22
Muon + electron
8, 17
Single jet
320
Ouad jet
4 x 80
Six jet
6 x 45
MET
120
HT
750
CMS HLT Config Browser
CMS HLT Config Browser
Prescales for
different luminosities
L1 condition
HLT rate depends on luminosity
•  Different HLT paths have different allocated rates
HLT muon efficiency
•  Measured efficiency compared to simulated
efficiency
•  Reasonable agreement between data and simulation
•  Note: Need to have ways of measuring trigger
efficiency
Measurement of trigger efficiency
•  Knowledge of trigger efficiency needed for
physics analysis
•  Strategy for measuring trigger efficiency needs to
be thought of from the very beginning
•  Events that are rejected on trigger level are lost,
i.e. not available for efficiency calculation!
à need backup trigger with looser selection
à can be prescaled
Measurement of trigger efficiency
•  Example: Measurement of efficiency of QuadJet50
•  Efficiency measured wrt reconstructed events
–  8 jets pT > 30 GeV, leading 4 jets pT > 50 GeV
Efficiency
•  Use EightJet30 as backup trigger à need to take
bias into account
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Data
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MC (HLT_8j30)
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jet p [GeV]
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Summary
•  Triggers are needed to reduce data volume and
allow for permanent storage
•  Trigger strategy has physical, technical and
political aspects and needs careful planning
•  Parameters to consider are timing, rate and
signal efficiency
•  Discussed trigger concepts ranging from simple
coincidence triggers to multi-level trigger system
as used at the LHC