12 Triggering and High-Level Data Selection
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piece of individual data processing can take more than this time. This prohibits the
use of iterative algorithms, such as jet finding based on finding a seed tower and then
adding the surrounding towers to make a jet energy sum. This pipelined structure
means that each step in the L1T logic must be completed within the time of the
crossing frequency and the results output so that this step in the logic is available
to process the data from the next crossing. The L1T logic therefore consists of a
number of pipelined steps equal to the processing time multiplied by the crossing
frequency.
The tight timing structure of the L1T presents a couple of challenges. Generally,
the detector calorimeters have long pulse shapes that exceed the time between
beam-crossings. This implies that particles produced in different bunch crossings
can produce significant pulse-height in the bunch crossing of interest. Therefore,
the detector systems that calculate the input information for the trigger need to
correctly identify the energy associated with the correct bunch crossing, usually
against a background of additional energy deposits from other bunch crossings.
Typically, these systems use peak-finding algorithms and finite input response filters
to perform this determination. The gaseous tracking detectors used in the muon
systems can also have drift times or pulse widths exceeding the time between bunch
crossings. These systems are also required to not only detect the passage of the
charged track but also to identify the crossing that produced the track. Often this is
resolved by combining and comparing the hits found in adjacent planes of chambers.
Another challenge is that the physical extent of large HEP detectors produces times
of flight to traverse them that exceed the time between bunch crossings. Therefore,
at any particular point in time, the particles from interactions of more than one bunch
crossing are present in the detector at different locations. This requires tight timing
and synchronization of the detector trigger and readout systems.
The trigger is the start of the physics event selection process. A decision to
retain an event for further consideration has to be made at the crossing frequency.
This decision is based on the event’s suitability for inclusion in one of the various
data sets to be used for analysis. The data sets to be taken are determined by
the experiment’s physics priorities as a whole. Examples of data sets used in
LHC experiments include di-lepton and multi-lepton data sets for top and Higgs
studies, lepton plus jet data sets for top physics, and inclusive electron data sets
for calorimeter calibrations. In addition, other samples are necessary for measuring
efficiencies in event selection and studying backgrounds. The trigger has to select
these samples in real time along with the main data samples.
The L1T is based on the identification of physics objects such as muons,
electrons, photons, jets, taus and missing transverse energy. Each of these objects
is typically tested against several p T or E T thresholds. The efficiency of a trigger is
determined by dividing the number of events that pass the trigger by the number of
actual events that would populate the final physics results plots if all of them passed
the trigger. The trigger must have a sufficiently high and understood efficiency at a
sufficiently low threshold to ensure a high yield of events in the final physics plots
to provide enough statistics and a high enough efficiency for these events so that the
correction for this efficiency does not add appreciably to the systematic error of the
535
piece of individual data processing can take more than this time. This prohibits the
use of iterative algorithms, such as jet finding based on finding a seed tower and then
adding the surrounding towers to make a jet energy sum. This pipelined structure
means that each step in the L1T logic must be completed within the time of the
crossing frequency and the results output so that this step in the logic is available
to process the data from the next crossing. The L1T logic therefore consists of a
number of pipelined steps equal to the processing time multiplied by the crossing
frequency.
The tight timing structure of the L1T presents a couple of challenges. Generally,
the detector calorimeters have long pulse shapes that exceed the time between
beam-crossings. This implies that particles produced in different bunch crossings
can produce significant pulse-height in the bunch crossing of interest. Therefore,
the detector systems that calculate the input information for the trigger need to
correctly identify the energy associated with the correct bunch crossing, usually
against a background of additional energy deposits from other bunch crossings.
Typically, these systems use peak-finding algorithms and finite input response filters
to perform this determination. The gaseous tracking detectors used in the muon
systems can also have drift times or pulse widths exceeding the time between bunch
crossings. These systems are also required to not only detect the passage of the
charged track but also to identify the crossing that produced the track. Often this is
resolved by combining and comparing the hits found in adjacent planes of chambers.
Another challenge is that the physical extent of large HEP detectors produces times
of flight to traverse them that exceed the time between bunch crossings. Therefore,
at any particular point in time, the particles from interactions of more than one bunch
crossing are present in the detector at different locations. This requires tight timing
and synchronization of the detector trigger and readout systems.
The trigger is the start of the physics event selection process. A decision to
retain an event for further consideration has to be made at the crossing frequency.
This decision is based on the event’s suitability for inclusion in one of the various
data sets to be used for analysis. The data sets to be taken are determined by
the experiment’s physics priorities as a whole. Examples of data sets used in
LHC experiments include di-lepton and multi-lepton data sets for top and Higgs
studies, lepton plus jet data sets for top physics, and inclusive electron data sets
for calorimeter calibrations. In addition, other samples are necessary for measuring
efficiencies in event selection and studying backgrounds. The trigger has to select
these samples in real time along with the main data samples.
The L1T is based on the identification of physics objects such as muons,
electrons, photons, jets, taus and missing transverse energy. Each of these objects
is typically tested against several p T or E T thresholds. The efficiency of a trigger is
determined by dividing the number of events that pass the trigger by the number of
actual events that would populate the final physics results plots if all of them passed
the trigger. The trigger must have a sufficiently high and understood efficiency at a
sufficiently low threshold to ensure a high yield of events in the final physics plots
to provide enough statistics and a high enough efficiency for these events so that the
correction for this efficiency does not add appreciably to the systematic error of the