Spring, 2009Phys 521A1 Hadronic calorimeters Recall that λ I > X 0 for dense materials hadronic...

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Spring, 2009 Phys 521A 1 Hadronic calorimeters Recall that λ I > X 0 for dense materials hadronic calorimeters must be longer than EM calorimeters This, plus need to place hadronic layers after EM layers, results in large volume for HCAL Absorber used in HCAL often serves as return yoke of solenoid in colliding beam detectors Active layers and sampling fraction vary widely in different applications Two new features: Hadrons deposit energy via both EM and nuclear interactions; some of the latter does not manifest itself as measurable signal Sensitivity (signal/incoming E) to EM and hadronic energy differs dx dh dx de hadronic E E E )% 100 30 (

Transcript of Spring, 2009Phys 521A1 Hadronic calorimeters Recall that λ I > X 0 for dense materials hadronic...

Page 1: Spring, 2009Phys 521A1 Hadronic calorimeters Recall that λ I > X 0 for dense materials  hadronic calorimeters must be longer than EM calorimeters This,

Spring, 2009 Phys 521A 1

Hadronic calorimeters

• Recall that λI > X0 for dense materials hadronic calorimeters must be longer than EM calorimeters

• This, plus need to place hadronic layers after EM layers, results in large volume for HCAL

• Absorber used in HCAL often serves as return yoke of solenoid in colliding beam detectors

• Active layers and sampling fraction vary widely in different applications

• Two new features:– Hadrons deposit energy via both EM and nuclear interactions;

some of the latter does not manifest itself as measurable signal– Sensitivity (signal/incoming E) to EM and hadronic energy differs

dx

dh

dx

de hadronic

EEE )%10030(

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Development of Hadronic ShowersEnergy depositionEnergy deposition

Hadronic shower has a long longitudinal development. For 200 GeV, need > 10 λI to contain 99% of the energy

Energy deposition in copper as a function of the calorimeter depth

The maximum at low depth values is due to the EM component in the shower that develops more readily due to the X0 dependence on Z compared to λI:

3120 AZ

AX I

In lead (Pb):Nuclear break-up (invisible) energy: 42%Ionization energy: 43%Slow neutrons (EK ~ 1 MeV): 12%Low energy λ’s (Eγ ~ 1 MeV): 3%

From Mauricio Barbi, TSI’07 lectures

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e/h response, compensation

• Hadronic showers contain π0, which decay immediately to two γ; these create EM sub-shower with high detection efficiency εEM ~1

• Quasi-stable hadrons (π±, K, p, n) can interact with nuclei, with some energy escaping detection; efficiency εHAD <1

• Energy resolution worsened by fluctuations in EM fraction, fEM, when e/h ratio, εEM / εHAD ≠ 1

• Compensating calorimeters have εEM = εHAD; not easy to achieve

• Decrease εEM, increase εHAD; e.g.,use high-Z absorber and use activemedium sensitive to neutrons (e.g.organic scintillator)

HADEMEMEMtrueSH ffEE 1

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Zeus hadronic calorimeter

• Compensation achieved for energetic hadrons

• Hadronic energy resolution :^)• EM energy resolution :^(

EE

E %35)(

EE

E %18)(

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HCALECAL

tracker

Particle flow calorimetry

• Concept used when analyzing energy deposition by jets of particles with existing detectors– Use tracking detectors to determine energy of charged particles

– Isolate calorimeter energy deposition from charged particles and subtract it; requires good granularity

– Sum remaining calorimeter energy and add to tracks

– Use particle identification to distinguish e, μ, π

• New detectors (e.g. for LC) will build this strategy into design

• Aim to achieve σE / E = 30% / √E for hadronic jets

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Bubble chambers

• Superheated liquid – spontaneous phase transitions are seeded by threshold ionization density

• Excellent spatial resolution (photograph bubbles) but slow cycle times. observation

• Neutral current (Gargamelle, 1973)

• Picasso experiment at SNOLAB

Gargamelle (5m long, 2m diameter)Neutrino-induced events

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Muon detectors

• Large volume (must be outside of absorber material); trade cost versus precision

• Need for independent momentum measurement must be evaluated (nice, but puts constraints on muon system)

• Intrinsic background from cosmic rays, decays in flight of pions and kaons (cτ = 7.8m, 3.6m)– Former reduced by tight constraints on track position near the

beam interaction point– Some of the latter are reduced by looking for kinks in trajectory

• Practical issues:– Complex magnetic field map– Alignment of huge devices to sub-mm precision

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Neutrino beams

• Accelerators smash protons (30-800 GeV) into fixed targets, resulting in copious production of π and K

• Time structure of beam (mostly off) known to detectors• These decay (cτ = 7.8m, 3.6m) as follows:

– π+ μ+ νμ (0.99987), e+ νe (1.2*10-4)

– K+ μ+ νμ (0.63), e+ νe (1.6*10-5), π0 μ+ νμ (0.034), π0 e+ νe (0.051)

– μ+ e+ νe νμ (cτ = 660m)

• Notice the production asymmetry (νμ, νμ, νe )

• Efficient neutrino production requires long, evacuated decay pipe (to avoid interaction of π, K)

• Even “near” detectors are far from source (e.g. ND280)• Lab neutrino energy not unique (direction of ν in hadron rest frame

relative to hadron direction in lab not fixed); correlated with angle

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Neutrino detectors

• Large target mass always required• Charged-current interactions leave ℓ± in detector• Fragments from struck nucleus can be detected when

initial neutrino energy is large enough (√s ~ √2mqEν)

• Considerations:– Large mass/volume makes magnetic field expensive (so charge

determination of produced leptons not always feasible)– Neutrino direction pretty well known from relative location of

source and detector; neutrino energy distribution often broad– Often wish to distinguish type of final state lepton– Some experiments require measurement of neutral current

(where final state contains unseen neutrino, hadronic recoil)– Time structure of beam helps reduce background sources

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Neutrino observatories

• Water Cherenkov detectors (e.g. SNO) and liquid scintillator detectors (e.g. SNO+) are used to record neutrinos from both cosmic and terrestrial sources

• Huge target mass can be instrumented this way• Statistical discrimination between e and μ• No charge sign information• “Beam” is always on; need to be deep

underground to reduce backgrounds• Minimum detectable neutrino energy

above most of solar spectrum

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Triggering – freezing the frame

• Need fast signal, high efficiency– Signals from slower detectors can be delayed or stored in a pipeline if

needed to allow trigger decision to be made

• Any malfunction (including bad signals from detector elements) implies lost data

• May use analogue signals from existing detectors or dedicated “trigger detectors”– Organic scintillators

– Electromagnetic calorimeters

– Proportional chambers (short drift)

• Often staged; initial (low granularity) stage avoids high deadtime due to digitization/readout, final stage limits storage costs

• Often use farms of computers at higher levels of trigger; introduces complexities associated with massively parallel systems

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Data acquisition, reconstruction, computing

• Emphasize reliability (accelerator-produced data are expensive; cannot afford to waste them)

• Real-time limitations due to– Bandwidth, processing power, unexpected input data,

• Computing costs limit how much data can be recorded• Reconstruction (raw data physics analysis quantities)

– Conditions, alignment, calibration

• Simulated events– Physics input, particle tracking, detector simulation, input to

reconstruction

• Data analysis– Iterative process, time-consuming fits, generation/storage of

modified datasets

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Simulation

• Sophisticated measurements require simulation of all aspects of data– Particle physics: Event generators– Interaction of quasi-stable particles in matter: GEANT4– Response of electronics (shaping, digitization): expt-specific

• Standardization– Monte Carlo (MC) particle naming scheme (PDG)– Algorithms for EM shower development– Algorithms for hadronic showers (less accurate; more choices)

• Production of simulated data uses a significant fraction of particle physics computing resources

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Detector design

• Many considerations:– Performance (resolution, efficiency, background rejection)– Cost (technology choice, site, operations)– Calibration (stability, complexity)– Site selection (physics, accessibility, politics)– Data processing (storage, bandwidth, cpu, cost, manpower)

• Some common elements can be bought from industry– Photo-detectors, organic and inorganic scintillators– Power supplies, ADCs and TDCs, some other electronics– Computers, network switches, storage…– Superconducting coils

• Significant construction tasks are still done in hep and university labs

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Survey of selected detectors

• Colliding beam detectors:– OPAL (LEP), BaBar (Pep-II), ATLAS (LHC)

• Fixed target detectors:– K-TeV (Fermilab), Focus (Fermilab), T2K (J-Parc)

• Dark matter, double-beta decay– Picasso (SNOLAB), DAMA, CDMS– EXO, SNO+

• Cosmic observatories – Homestake, SNO, Super-Kamiokande, Kamland– Amanda, IceCube, Auger– AMS, Pamela

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Cosmic rays and natural radiation

• Primary cosmic rays– Large dynamic range; power law

decrease with energy– Highest collision energies available to

us (but at low flux)– Galactic magnetic field prevents

pointing back to sources (except at ultra-high energies)

– Intrinsic background for detectors of ionizing radiation

• Earth-based radioactive decay– Limited to MeV-scale energies– Intrinsic background for detectors of

low-energy particles

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Cosmic ray flux at ground level

• High energy primary massive air showers

• Interactions in “air calorimeter” and decays – mostly muons at/below surface

– peak particle flux at ~15km altitude

• Charge asymmetry:more μ+ than μ-

• Flux (m-2s-1sr-1)varies withazimuth angle

μ- with p>1GeV

Curves show calculated flux vs

depth in atmosphereθ = 0°

θ = 75°

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Cosmic ray flux under ground

• Remaining non-muons range out quickly in earth

• Flux varies with azimuth angle (due to penetration depth in rock overburden)

• Muons range out in earth, but neutrino-induced flux remains constant

• Upward-going muons comeonly from neutrino interactions

Downward-going muon

intensity versus depth

(underground)