time of the DAQ while also increasing the portion of recorded events corresponding to the coherent peak. The change had the indirect advantage for this analysis of
increasing the percentage of recorded events coming from 2π0 decays. The two data
sets were analysed together after checks were made on their compatibility.
The cluster multiplicity from CB and TAPS was set to have a lower limit of three
which accounted for decay products of π0 photoproduction off the proton; the two
decay photons from a π0 and the recoiling proton. Every fourth event detected
which consisted of two clusters was also accepted, so that events where one of the decay particles was not detected could be quantified. The clustering method used by the DAQ is not as involved as that used in later analysis in order that the number of clusters can be determined quickly.
If the logic conditions were not met, the DAQ was reset, dumping the stored signals and preparing for the next event.
4.3
A2 Simulation
Simulation of detector systems and the underlying physics becomes more important as the complexity of experiments increases. A Monte Carlo simulation of the A2 setup [93] has been developed using Geant4 libraries [94, 95]. The simulation is designed to directly match the geometry of the experimental setup with physics li- braries which best describe the scintillation showers and other detected signals. The main components of the A2 simulation are the CB and TAPS, shown respec- tively in figures 4.15(b) and 4.20(b). Models of the other detectors are also included and the setup allows any additional detectors to be added to the setup.
The simulation is fed events with the decay particles from a particular reaction channel. Signals produced in the simulated detectors are recorded in the same way as real experimental data.
4.3. A2 Simulation 68 reaction channels expected to contribute to the signal and background. The shape of the missing mass from each channel has been used as a Probability Density Function (PDF) to fit the experimental missing mass distribution, the implementation of this is discussed in 6.4.2, showing the simulated distributions in figures 6.14 and 6.15.
Chapter 5
Calibration
All of the detector systems were calibrated carefully before the recorded data were used to extract meaningful and accurate measurements. As each research group specialised in different detectors, the calibration work was shared amongst the col- laboration for each experimental run. The complexity of the calibration varied from detector to detector with some cross reliance between detectors.
For this experimental run most of the calibration has been carried out by others, a summary of the process for a selection of detectors is given in this chapter. A more detailed discussion has been included on the calibration and determination of the degree of linear polarisation; work carried out by myself.
Producing accurate, reliable calibration of the detectors is of great importance in producing physical results with minimal systematic uncertainties.
5.1
Timing Calibration
Modern hadron physics experiments require timing precision of the order of 10−9 s
to separate potentially overlapping reactions. Detector elements and electronics on this scale have inherent timing resolution and delays which differ between elements of identical design. Signals from an event registering in multiple detector elements will reach the DAQ system at different times. In order to account for these effects
5.1. Timing Calibration 70 a number of complementary approaches were applied to align the time of signals within and between detectors.
A preliminary calibration was achieved in the hardware by testing detector electron- ics in order to quantify timing profiles for each component. Signals were brought into alignment to arrive at time to digital converters (TDCs) within a narrow time window by adjusting cable lengths.
Fine timing calibration was achieved offline after the experimental run. Peaks in coincidence times relating to triggered events were identified for each detector ele- ment and aligned with each other. The timing alignment of the tagger is presented as an example in figure 5.1. Time (ns) 40 60 80 Tagger Channel 0 100 200 Time (ns) 40 60 80 Tagger Channel 0 100 200
Figure 5.1: Coincidence peaks of every tagger channel were aligned to the same arbitrary time. Left - Before alignment. Right - After alignment.
Timing calibration only aligns peaks from detectors and detector elements to the same value relative to the initial trigger. The relative time between signals detected in, for example, TAPS and the CB, was more difficult to determine but is not
necessary for this analysis, as very loose timing cuts ∼100 ns were applied.
It was possible to use TAPS for time-of-flight particle identification as its position is far enough down stream from the target. Signals from TAPS arrived with multi- ple timing peaks each associated with different particles, the earliest peak was the photon peak, which was used for the alignment of the detector elements.
5.1. Timing Calibration 71
5.1.1
CB Time Walk Correction
The calibration of coincidence time from a peak of all the recorded signals in a detector is not necessarily the whole picture. The response time of a detector relates to how quickly a signal passes the trigger threshold energy, detected particles of lower energy have a longer response time, this is called a time walk. If the time walk is not accounted for, the timing coincidence peak is widened, increasing the uncertainty in the energies detected through identification of the tagger prompt photon. The time walk calibration is made by examining the relationship between the energy and recorded time of highest energy cluster detected in the CB (Figure 5.2).
Figure 5.2: Effects of cluster time walk corrections. Left - Trigger time against highest CB energy cluster time. Right - Trigger time against CB Cluster energy.
5.2. Energy Calibrations 72