a general purpose apparatus a general purpose apparatus

How to use single and specific How to use single and specific

detection technology to build detection technology to build

a general purpose apparatus a general purpose apparatus

for high energy physic for high energy physic

experiments.

experiments.

Introduction (I)

Particles are detected via their interaction with matter.

Many different physical principles are involved (mainly of electromagnetic nature). Finally we will always observe ionization and excitation of matter

⇒ detectors

The classic quantities to measure are:

Trajectory, Charge, Momentum, (transparent detector + Muon chamber + B)

Introduction (II)

To do that we have to design a detector. That is exciting; one of the best part of the whole story

Important before starting: Given an accelerator (example LHC) What we want to measure (signatures)

Gammas Higgs Leptons

Hadr Jets

Sparticles → Missing energy Rare mesons….

Etc

How we can measure (detector)

But a lot is simply not known, therefore, stick to general assumptions and design for surprises.

Introduction (III)

Particle detection – ideal case

Particle detection – some real cases

Very good electromagnetic calorimetry for electron and photon identification

Good hadronic calorimeter jet reconstruction and missing transverse energy measurement;

Efficient and high-resolution tracking for particle momentum measurements, b-quark tagging, t tagging, vertexing (primary and fine segmentation,

fast response, no dead time

coverage of full solid angle (Hermetic), no cracks but easy to dismount

as less as possible material in front of the calorimeter

as much as possible material

in front of the muon chambers

+

The ‘ideal’ particle detector should provide...

In the following, we look only collider geometry

Detector Geometry

The past…..

The past - UA1

The near past ALEPH

VDET2, partially build in Bari

The present ….. or the near future

46m Long, 22m Diameter, 7’000 Ton Detector

Internation Linear Collider

The future

Magnet concept for 4π detector

Momentum measurement µ trajectory in:

a)toroidal field

b) Solenoid field

1) Check what signatures have significance (ask your preferred theoretician);

2) Have a look at the interaction region and estimate your minimal δz;

3) Fix your detector cell size (with precisions σφ, σz);

4) Decide the magnet type;

5) Place your inner tracker and muon shells in order to satisfy your min.

requests on δp/p and δz (which you can calculate);

6) Decide what kind of calorimeter you need and place it;

7) Calculate dose and occupancies and find your closest approach values to the interaction region (compatible with maximum allowed dose and cell size);

8) Go back to point 3) and re-adjust the values (if needed);

The rules for a detector designer

Lum= 10³⁴ cm^–2s^–1,

Interaction Rate, R = 8⋅10⁸Hz Events/beam crossing: ∆t= 25 ns Interactions/crossing = 20

Only 2835 full out of 3564

Interactions/”active”crossing = 20 x 3564/2835

Summary):

(1) A "good" event containing a Higgs decay + (2) ~ 25 extra "bad" (minimum bias) interactions

Make up for the lower production cross section. Normally, σ~1/s, so a factor x in c.m. energy needs a factor x2 in luminosity (for the same number of events; N=σL) ⇒ high luminosity

LHC

Momentum / charge of tracks and secondary vertices (e.g. from b- quark decays) are measured in central tracker.

Energy and positions of electrons and photons measured in electromagnetic calorimeters.

Energy and position of hadrons and jets measured mainly in hadronic calorimeters.

Basic principle: need “general-purpose 4π ” experiments since we don’t know how New Physics will manifest itself ( →detectors must be able to detect as many particles and signatures as possible: e, µ, τ, ν, γ, jets, b- quarks, ….)

Measure Momenta of Charged Particles

Choise of magnet: Toroid

Choise of magnet: Solenoid

Tracking

CMS solution: few, very accurate points ATLAS solution: continuous tracking Both: add pixels for vertex tagging

CMS Tracker (SST)

SST Requirements

SST basis unit:

Silicon Silicon sensors sensors

CF frame CF frame

9’648’128 strips ≡ channels 75’376 APV chips

6’136 Thin sensors 18’192 Thick sensors 440 m²of silicon wafers 210 m²of silicon sensors 3’112 + 2*1’512 Thin modules 5’496 + 2*1’800 Thick modules

~17’000 modules

p⁺strips on n-type bulk

<100>crystal lattice orientation

•Polysilicon resistors to bias the strips

Tracker- b identification

3 barrel layers

r = 4.1 – 4.6 cm, 7.0 – 7.6 cm, 9.9 – 10.4 cm (~ 60 x 10⁶ pixels)

2 pairs of Forward/Backward disks –Radial coverage 6 < r < 15 cm

–Average z position: 34.5 cm, 46.5 cm (~3 x 10⁶ pixels per Disk)

⇒ 3 high resolution space points for η < 2.2

Pixel seeding fastest starting point for track

reconstruction despite the extremely high track

density

Events in VDET al LEP

Example: H →γγ for low mass Higgs Higgs width is very narrow,

so S/N directly ∝to signal resolution.

Moreover, initial background: x100 larger π0 rejection: strips (ATLAS),

crystal size (isolation) (CMS);

Need excellent energy resolution of EM calorimeters

background from pp →γγH H →γγ good resolution

H →γγ poor resolution

m_γγ e

v e n t i

Liquid argon by ATLAS.

Not enough space in CMS for cryogenics ⇒ Crystal ECAL (more compact) Optimal choice: PbWO4

(Good light yield, short X0, short τ, good radiation resistance)

Hadron calorimeter

Other LCH experiments

LHCb LHCb

Optimal L for LHCb ~ 2×10³²cm⁻² s⁻¹: physics can be exploited from day one and β* can be tuned to run also at nominal L.

Measure the CP violation in B_d and B_s systems, Search for New Physics, Determination of the CKM

Alice

Alice

Measure most (2π * 1.8 units η) of the hadrons (dE/dx + ToF), leptons ^(dE/dx) and photons

(EM calorimetry) produced collisions.

Track and identify from very low (< 100 MeV/c) up to fairly high p_T (~100 GeV/c).

……… in an environment of very high charged-particles density (dN/dη ≤ 8,000; 15,000 tracks)

LHC-b

Alice

IT S

TRD TPC TOF PHOS

HMPID

MUON SPECTR..

PMD

FMD

L3 Solenoid Magnet

Pile-up & Electronic at LHC

Example: electron reconstruction (I)

Nominal vertex (0,0,0) B→

Predict a track Cluster E

Cluster position

Propagate to the pixel layers and look for compatible hits

If a hit is found, estimate z vertex

Predict a new track and propagate Estimated vertex (0,0,z)

Pixel hit In CMS, both tracker and ECAL are used

Example: electron reconstruction (II)

e

γ single single

electrons, electrons, p

p_tt> 28 GeV> 28 GeV mainmain clusters clusters

Bremsstrahlung emission could false the electron energy estimation. The 4 T field,

“dynamic” clusterizzation algorithms produce Supercluster = cluster of cluster

Example: electron reconstruction (III)

Combined algorithm

E = 5-10 GeV

E = 30-35 GeV

E = 80-85 GeV

E_sc/E_true P_tk/E_true

☺

☺

E_best/E_true

Example: energy flow

+

S

U

S

Y

In conclusion, if everything (detector, trigger and

analysis) work properly we should seen Higg