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Methods of Experimental Particle Physics. Alexei Safonov Lecture #18. Today Lecture. Presentations : D0 calorimeter by Jeff Trigger. Collisions at LHC. 7.5 m (25 ns). Bunch Crossing 40 million (10 6 ) Hz. Proton Collisions 1 billion (10 9 ) Hz. Parton Collisions.

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today lecture
Today Lecture
  • Presentations:
      • D0 calorimeter by Jeff
  • Trigger
collisions at lhc
Collisions at LHC

7.5 m (25 ns)

Bunch Crossing 40 million (106) Hz

Proton Collisions 1 billion (109) Hz

Parton Collisions

New Particles 1 Hz to 10 micro (10-5) Hz

(Higgs, SUSY, ....)

14 000 x mass of proton (14 TeV) = Collision Energy

Protons fly at 99.999999% of speed of light

2808 = Bunches/Beam

100 billion (1011) = Protons/Bunch

  • Finding anything at a hadron collider requires first getting rid of enormous backgrounds due to QCD multi-jet production
    • Can’t even write all these events on disk, need trigger - will talk later

7 TeV



colliding beams

triggering and qcd
Triggering and QCD
  • There is a reason why QCD is called a strong interaction
  • The cross-sections for strong processes are large
  • Most are “soft” QCD events and are not very interesting:
    • We already know about jets, so now they are more of an obstacle
  • Need a device that allows discarding non-interesting events and keeping interesting ones
    • They may look alike: even though jets and leptons usually look differently, occasionally a jet can look like a lepton.
    • Initial rate is so large that occasional can turn out to be very frequent in absolute terms
making discoveries come faster
Making Discoveries Come Faster
  • Because interesting events are rare, need to make a lot of non-interesting events first
  • Either increase the number of particles per bunch or make more bunches and both create challenges:
    • Many particles per bunch:
      • You end up with a lot of overlapping events (called “pile-up”) within the same crossing, difficult to disentangle things – lower efficiency and less discrimination between signal and background
    • Many bunches:
      • Short time between collisions means that the detector must be able to “recover” from previous collision within a short amount of time and also need to be able to read out your detector very fast
  • Both cause technological limitations on the detector electronics design
    • And also on the computing resources
  • In real life have to pursue both keeping a balance of cost and effectiveness
many bunches
Many Bunches
  • The LHC time between collisions is 25 ns:
    • Detector needs to recover from previous interaction and be ready – else “dead-time”
    • Pressure on the readout:
      • 1 MB of data every 25 ns requires a bandwidth of 320 Terrabit per second, which is an insane number for current technologies
many overlapping events
Many Overlapping Events
  • Very high occupancies of hits and particles per detector granularity
  • Many detector design and performance challenges
    • Even if your detector can “operate”, if the data is not good, you won’t be able to do much when doing analysis
many overlapping events1
Many Overlapping Events
  • Very high occupancies of hits and particles per detector granularity
    • Many challenges:
      • Nice and inexpensive detectors, e.g. as chambers become inefficient due to long drift time
      • Calorimeter measurements become useless as deposits sit on top of each other for low granularity, for high granularity still a problem as you never know which interaction a specific deposit came from
      • The only measurements relatively immune to this are tracking as tracking allows to distinguish which track came from which vertex
  • But you can’t do a physics analysis based on tracks only
    • Or can you?
detectors and pile up
Detectors and Pile-Up
  • An illustration of overlapping signals
    • Can get rid of it by using very “fast” and finely segmented detectors
      • But the cost will skyrocket
triggering basics
Triggering Basics
  • Two paths:
    • Recognize non-interesting events and discard them
      • Not very practical as there are lots of ways how non-interesting events can look like, hard to get all possible modes identified
        • If you don’t, whatever is left can still be way too much
    • Recognize interesting events and keep them
      • More practical as you can build more sophisticated requirements targeting specific topologies
        • Build many “triggers” going after specific types of events, discard events that are not flagged by any of the triggers
        • The more exclusive you go, the less likely it is for a background event to pass your requirements
      • But also dangerous: you may miss a discovery
        • In this approach you must know what you are looking for
        • One has to strike a balance of exclusive and inclusive to not miss something that could be important
boundary conditions
Boundary Conditions
  • On the input:
    • Bunch Crossing rate: 40 MHz
    • Interactions rate: 1-10 GHz (depends on how many overlapping events)
    • Data rate: hundreds of Terrabits per second
  • On the output:
    • Need to write events on disk so that one can analyze the data
    • With some reasonable assumptions on how much you can spend, the likely writing rate is 100-300 crossings per second (100-300 Hz)
      • Multiply by 1 MB event size to get some Gigabits per second

What ‘s in between” ?

The trigger!

how to build a trigger
How to Build a Trigger
  • Need to bring the rate closer to something manageable but can’t lose data:
    • Solution is to delay full readout until you know the event is interesting
    • Make “pipelines” in the front-end electronics holding the data and “go parallel”
      • Can do if electronics is very segmented (each piece serves some small portion of the coverage of a specific detector system
        • Like one muon chamber
      • Unless you go nuts on segmenting your readout (which will be very expensive), rates are still too high for any kind of commercial computers, need to use fast electronics
    • Can use a fraction of data (say reduce granularity to reduce the rate) or make a more elaborate electronics system
trigger designs
Trigger Designs
  • Conventional trigger systems use 3 levels:
    • Ultra fast electronics (ASICs/FPGAs) and fast connections
    • Slower but smarter electronics (or super-fast processors)
    • Conventional computer farm
algorithmic considerations
Algorithmic Considerations
  • The idea is always the same:
    • Do something fast and dirty first to quickly recognize “junk” (if you do, stop processing)
    • More intelligent (and thus slower) algorithms go later
      • The rate is already reduced by “fast and dirty”, so you can spend more time per event without creating a bottle-neck leading to dead-time
    • The deeper the storage pipe-lines, the more time you have to make a decision
      • But your system becomes more and more expensive
        • Need to strike a balance
  • Tree-like structure of decision making:
level 1
  • CMS and ATLAS do not have tracking in Level-1
    • Nothing to be proud of: we can kind of survive now, but won’t last long. The only reason we do it is we can’t handle the rates of the current tracker
cms level 1 and daq
CMS Level-1 and DAQ
  • Current system design:
general hlt sequence
General HLT Sequence:
  • Conditionally it’s broken into L2 – L2.5 and L3:
    • L2: repeat L1 algorithms at full segmentation
      • Fast and can eliminate easy to eliminate events
    • L2.5: add only limited tracking information:
      • Pixel detector hits or (later within L2.5) tracks and vertices
      • Not as fast but allows large rejections (although limited tracking capabilities – reduced resolution, potential efficiency losses)
    • L3: add full tracking and particle flow
      • Slow, but hopefully the number of events coming is already small enough to allow it to work
trigger table
Trigger Table
  • A typical experiment has hundreds of what’s called trigger paths
    • Each path is a sequence of requirements at Level-1 and HLT
      • Essentially you are looking for some specific object (very energetic electron) or a topology (3 muons with high pt), but you can use earlier paths as bricks in building your trigger path
      • Each path has it’s “owners” who maintain them and continuously improve their trigger
      • An analysis usually uses one or few of these trigger paths
    • A special group usually deals with allocating available bandwidth among trigger paths
      • Reviews proposed triggers and physics motivation, suggests modifications (say to improve background rejection or to make trigger usable for more than one purpose)
      • Allocates available bandwidth to specific paths based on physics priorities
      • The result of such allocation is a “Trigger Table”
        • Dynamic as needs change, different triggers have different growth terms in their rates, needing frequent rebalancing
data storage
Data Storage
  • Once the trigger has made a decision to keep the event, the data is written on disk
    • The data is sent in several streams based on the type of objects and physics
      • This way you can only filter events from one stream for your analysis instead of looping over 10 times more events
  • Then the data gets manipulated before it becomes available for analysis
    • Within a few days these events move around
      • From Tier-0 to Tier-1 and further as full event reconstruction is performed
        • Various “standard” formats:
          • Some information that s rarely used gets dropped to make events smaller in size, but a full event record is kept somewhere (one of Tier-1 centers)
      • Eventually data in one of the light format moves to Tier-2 where it can be accessed by analyzers
next time
Next time
  • Monte Carlo event generators
  • Detector emulation
  • This lecture had a lot of slides borrowed from one of the lectures about triggers by Wesley Smith (UW-Madison)