tracking - istituto nazionale di fisica nucleare · development of particle detectors, in...
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Tracking
gianluigi cibinetto
Issue I Lecture 3
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Outline
• Introduction and terminology
• Tracking devices
• Tracking algorithms
• Momentum resolution
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What is Tracking?
• A coordinated system of hardware and software for detecting and measuring charged particles
• A tool to visualize the trajectory of individual stable particles (and their unstable progenitors)
• A connection between the quantum world of particles and the classical world of macroscopic instruments
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History of tracking
• 1992 Nobel Prize, Georges Charpak "for his invention and development of particle detectors, in particular the multiwire proportional chamber"
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• Cloud Chamber 1936 Nobel Prize Carl Anderson "for his discovery of the positron”
• 1968 Nobel Prize, Luis Alvarez, "... hydrogen bubble chamber and data analysis”
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Why Discuss Tracking
• Tracks are the core of (most) analyses
• Charged particle content of final state
• Precise kinematic and vertex information
• Tracks are required for everything else
• Tracks are potential charged particles dEdx, DIRC, e identification, muons, neutrals, ...
• Could also be background, scattering, fakes decays, bad calibration, software bugs,...
• Analysis must take all these into account!
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Tracking Terminology
• Stable charged particles ∈ e, μ, π, K, P
• Trajectory ≡ path of a charged particle (directional 1-D object in 3-space)
• Tracking Detector ≡ highly-segmented detector capable of sensing a charged particle without greatly changing its P
• Hit ≡ position measurement in a single active element of a tracking detector
• Track ≡ collection of hits presumably from one particle, reconstructed to estimate the particle P and trajectory
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A real example
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Why do we need a magnet?
• Magnet + tracking = magnetic spectrometer • momentum ⇒ geometry (curvature) • Requires a ~uniform B-field: solenoid • Approximately constant field inside volume
– Double windings at the end minimize distortions – Iron contains return flux
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B(0,0,L/2) = 0.5×B(0,0,0)
FB = qv×B
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The Drift Chamber
• 5 m3 gas volume
• Al Endplates
• Inner (Be+Al) cylinder
• Outer (CF) cylinder
• Wires – ~32 kNewtons tension – ≤ 200μm sag
• ~1% X0 total (active region)
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Measuring the right time
• Signal time depends on ionization (track) position
• Field irregularities due to shaping wires
• Asymmetric trajectory due to Lorentz force
• Measured using tracking data in-situ. Translate time (TDC) to ‘distance to wire’ using a time to distance (T2D) function
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DCH hits
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dE/dx calibration
• Use: – p from Λ decay (p π-)
– K from D* decay – π from Ks decay
– µ from µµγ events – e from rad BhaBha events
• Bethe Block parametrization
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The Silicon Vertex Detector
• 340 double-sided Si wafers: ~1m2 Si
• 5 layers: independent tracker
• Unique arch in outer layer
• CF support structure 4% X0 total
• ~90% of Ω
• Mounted to the Be beam-pipe.
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Silicon detectors are diodes
• Doped bulk, Implants creates diode
• Reverse-bias depletes conduction carriers from the bulk
• Tracks ionize bulk – electron-hole pairs
collected at implants – charge collection and
amplification
• Diode separation allows spatial signal – resolution given by pitch,
charge sharing
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The Success of Si Vertex Detectors
• Standard industrial manufacturing
• <1μm precision features on cm-scale wafers
• Signals from both charge carriers
• Charge drift distance ~ 100μm
– geometric position reconstruction
• Compatibility with IC electronics
• Disadvantage: material (0.3 mm Si, 0.5% X0)
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SVT readout and resolution
• AToM (“A Time Over threshold Machine”) chip measures when signal is over threshold and how long (time over threshold)
• Adjacent strips above threshold are clustered • Cluster position from charge distribution
– Diffusion + capacitive coupling allow interpolation: better resolution than pitch/√12
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Tracking algorithms
• Track Finding
• Track Fitting
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Track Finding
• Track Finding = pattern recognition – Associate all hits from a single particle
• Requirements – maximally efficient at finding tracks: some lost hits is OK
– Low mis-association rate: single wrong hit can spoil resolution
• Computationally affordable: combinatoric problem
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Tracks looks obvious
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But not at first
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A common tracking strategy
• Find tracks in Dch first – Fewer background hits (especially outer layers) – More redundancy (40 vs 5 layers) – only tracks with Pt > 150 MeV
• Add Svt hits to Dch tracks – Improve impact parameter and angle resolution
• Find Svt (low-Pt) tracks with remains
• Add Dch hits to tracks found in Svt – Improve momentum resolution
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Issues with tracks reconstruction
• Material effects – Multiple scattering ~14MeV/P √X0 – dE/dx (energy loss)
• B field inhomogeneity
• Trajectory needs more params – 2 angles + 1 curvature for materials: ~100 total - Equal number of
extra constraint – Changes from track to track
• Standard multi-variable fit is a poor match to the problem
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Kalman Track Fitting
• Progressive least-squares fit – Start with an initial estimate – Add measurements one-at-a-time, in order
– Add (process) noise (= scattering, dE/dx) – Account for B Field inhomogeneities
• Final result piecewise helix – position and momentum along track
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Other uses of Kalman Fit
• Track extrapolation (to IP and other detectors)
• Pattern recognition
• Add Svt (Dch) hits to Dch (Svt) tracks
• Vertexing – Consider each track as a decay ‘hit’ – Combine tracks using Kalman formalism – Can fit an entire decay chain at once
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Question
• Which particle emits the most synchrotron radiation light when bent in a magnetic field? (Proton, muon electron).
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Question
• Which particle emits the most synchrotron radiation light when bent in a magnetic field? (Proton, muon electron).
• Kalman filter can be used also for bremsstrahlung recovery algorithms.
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Momentum resolution
• Typical collider experiment: solenoid magnet (field lines parallel to beam axis)barrel and endcap detectors
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• Typical fixed-target experiment: dipole magnet (field lines orthogonal to beam axis) planar detection layers
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Momentum measurement
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Using sagitta • Bending of elementary charge in a magnetic field
– large radius -> weak bending -> large momentum
– typically see only a small portion of the circle
– measurement of momentum is equivalent to a measurement of the sagitta.
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( ) )4/(7203.0)(
2
.
+⋅
⋅= N
BLpx
pp T
meas
T
T σσfor N equidistant measurements, one obtains (R.L. Gluckstern, NIM 24 (1963) 381)
( )T
T
TT
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BpqBp
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σσσσσσ231
2xxxs +
−=
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Multiple scattering effect
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What is the contribution of multiple scattering to ?
Tpp)(σ
0
1045.0)(LXBp
pMS
T
=σ
TT
pxpp
⋅∝ )()(σ
σ
px MS 1)( 0 ∝∝θσ
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constant)(=
MS
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More precisely:
, i.e. independent of p !
σ (p)/p
σ (p)/p
σ (p)/p
p
MS
meas. total error
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Problem
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Example:
pt = 1 GeV/c, L = 1m, B = 1 T, N = 10
σ(x) = 200 µm:
Assume detector (L = 1m) to be filled with 1 atm. Argon gas (X0 = 110m),
€
σ(p)pT
MS
≈
€
σ pT( )pT
meas.
≈
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Bibliography " Text books (a selection)
– C. Grupen, Particle Detectors, Cambridge University Press, 1996
– G. Knoll, Radiation Detection and Measurement, 3rd ed. Wiley, 2000
– W. R. Leo, Techniques for Nuclear and Particle Physics Experiments, Springer, 1994
– R.S. Gilmore, Single particle detection and measurement, Taylor&Francis, 1992
– W. Blum, L. Rolandi, Particle Detection with Drift Chambers, Springer, 1994
– G. Lutz, Semiconductor Radiation Detectors, Springer, 1999
" Review Articles – Experimental techniques in high energy physics, T. Ferbel (editor), World Scientific, 1991.
– Instrumentation in High Energy Physics, F. Sauli (editor), World Scientific, 1992.
– Many excellent articles can be found in Ann. Rev. Nucl. Part. Sci.
" Other sources – Particle Data Book (2010) http://pdg.lbl.gov/pdg.html
– R. Bock, A. Vasilescu, Particle Data Briefbook http://www.cern.ch/Physics/ParticleDetector/BriefBook/
– Proceedings of detector conferences (Vienna CI, Elba, IEEE, Como)
– Nucl. Instr. Meth. A high energy physics lab detection techniques - tracking 32