1. High Energy Physics experiments.
Application of the Cluster Counting and Timing techniques to improve the performance of high transparency Drift Chambers for modern
High Energy Physics experiments.
G. Chiarello(a,b), C. Chiri (a) ,G. Cocciolo(a,b), A. Corvaglia(a),F. Grancagnolo(a), M. Panareo(a,b),
A. Pepino(a,b), F. Renga(c) ,G.F. Tassielli(a,b), C. Voena(c)
Istituto Nazionale di Fisica Nucleare, Lecce, Italy,
Dipartimento Matematica e Fisica Ennio De Giorgi, Università del Salento, Via Arnesano LECCE (Italy)
Istituto Nazionale di Fisica Nucleare, Roma1, Italy,
ABSTRACT
Ultra-low mass and high granularity Drift Chambers, using the Cluster Counting and Timing techniques, fulfill the requirements of tracking systems for modern High Energy Physics experiment. We present how, in Helium based gas mixtures, by counting and measuring the arrival times of each individual ionization cluster and by using statistical tools, it is possible to reconstruct a bias free estimate of the impact parameter and a more discriminant Particle Identification.
Drift chamber operation
Cluster Finder Approach
A charged particle, passing through the gas of a drift chamber, creates ion-electron pairs along its path. Depending on the released energy, for each ionization act, the particle creates one or more ion-electron pairs, indicated as clusters. The distance between two consecutive clusters follows an exponential distribution with average λ, the value of which depends on the gas nature, pressure and temperature. The time separation between consecutive ionization acts, in helium based gas mixture is of few ns, near the sense wire, to tens of ns, far away.
A simple peak finder algorithm, based on the first and second derivative of the digitized signal function f, is defined for each time bin i, Δb being the number of bins (signal rise time) over which the average value of f is calculated:
ionizing
track
drift tube
sense
wire
drift distance
impact parameter b
ionization
act 
electron
clusters
A peak (assumed to be an ionization electron) is found when Δf, f' and f" are above a threshold level, defined according to the r.m.s. noise of the signal function f, and when the time difference with a contiguous peak is larger than the time bin resolution. 50
100
150
200
250 mV ns
PID and spatial resolution
expected PID performance comparison with dE/dx for a track length of L=3m
Assuming a C.C. efficiency ε = 80%
σ dNcl/dx /(dNcl/dx) = 1/(ε×L×12.5/cm) = 1.8%
Total charge
Nr e- recogn
Nr of peaks
mean
14.86
12.37
10.52
= 85%
ε =
The association of electrons in clusters is based on the time difference between consecutive electrons. Electrons belonging to same cluster are separated by time differences which are compatible with single electron diffusion.
Cluster counting outperforms dE/dx by at least a factor 2.
First Cluster
λ/2
MPS
Time separation between consecutive ionization clusters, for a helium-based gas mixture, goes from a few nanoseconds to a few tens of nanoseconds. Experimental results indicate clear improvements of the cluster counting technique over chaege integration (dE/dx) by a factor 2 in π/μ separation at p=200MeV/c, limited only by the cluster recognition performance [NIM A386 (1997) ].
tcut
Cls gen
Cls recogn
Cls found
mean
9.66
8.77
9.11
RMS
4.04
3.83
4.13
Time difference between MC generated cluster and reconstructed cluster
In a conventional drift chamber, only the time of the first cluster is used to estimate the track impact parameter, resulting in a systematic biased overestimate. Cluster timing technique use statistical tools in order to improve the bias estimate by using the information of different clusters. ns
The algorithm has been implemented on a Virtex6 FPGA, interfaced with a 12 bit ADC (AD9625 – 2.0 GSa/s).
The algorithm:
identifies, in the digitized signal, the peaks corresponding to the different
ionization clusters;
stores each peak amplitude and time in an internal memory;
sends the data stored to an external device when specific trigger signals occur.
Waveform generation
Using PSpice software, we simulated the single cluster signal propagation along the drift cells convoluted with FE transient function.
The convoluted signal is parameterized as follows:
Signal waveforms are generated according to:
Cylindrical cell geometry with 9.75 mm radius
He-iC4H10 = at 4· 105 gas gain
Number of clusters from Poisson distribution with mean = 12 cls/cm
Single electron diffusion as function of drift time
Single avalanche gain fluctuations
Front End response with a BW of 800MHz and gain of 10
very consistent results obtained
with the offline version
of the algorithm mV μs
In modern High Energy Physics Experiments it is possible to perform an online analysis of all cells waveforms to extract and store only the relevant data thanks to a sizeable data suppression algorithm.
The CC/CT technique is mature to be used on a full scale detector.
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