Particle Identification with Silicon

Particle Identification with Silicon

Particle Identification with Silicon Jos Repond Argonne National Laboratory EIC Users Group Meeting Catholic University of America Washington D.C. July 30 August 2, 2018 To achieve the EIC physics goals we need 100% acceptance for all particles produced (acceptance is luminosity!) Excellent momentum/energy resolution PID for all particles This requires full integration of the central, forward detectors and the beamline Particle list at MC hadron level Particle ID Px Py Pz

11 (e-) -0.743 -0.636 -4.842 321 (K+) 0.125 0.798 6.618 -211 (-) 0.232 0.008

3.776 -211 (-) 0.151 -0.007 4.421 211 (+) 0.046 0.410 2.995 111 (0) -0.093 0.048

1.498 2112 (p) 0.115 -0.337 31.029 211 (+) 0.258 0.145 6.336 310 (KS0) 0.385

-0.408 3.226 DIS event Ee = 5 GeV Ep = 60 GeV Detector output We want a detector which provides the same type of information J. Repond: TOPSiDE 2 TOPSiDE: Concept of an EIC Detector TOPSiDE 5D Concept Energy E Position x,y,z Time t Salient features

4 detector (hermetic coverage) Multi-purpose detector (dont need another specialized detector) Mostly based on silicon sensors (tracker, electromagnetic calorimeter) Each particle measured individually (optimized for Particle Flow Algorithms) Particle identification (pion-kaon separation) performed by TOF (tracker and calorimeter) Imaging calorimetry (tens of millions of readout channels) Coil on the outside (not to disturb calorimetric measurements) Dipole/Toroid in the forward direction (to obtain a momentum measurement) Special detectors in the forward direction (Ring Imaging Cerenkov for Particle ID, debris taggers) No need for additional TOFs, TRDs, erenkovs (in front of calorimeters), muon chambers 3 TOPSiDE needs Imaging calorimetry Ultra-fast silicon Emphasis of this talk Ring Imaging erenkov detector Large solenoid J. Repond: TOPSiDE 4

Imaging Calorimetry Very fine granularity 0.16 1.00 cm2 readout cells Cells in every layer read out individually Entire calorimeter several 107 readout channels Advantages Particle ID (photons, electrons, muons, neutral and charged hadrons) Software compensation (improves hadronic resolution) Leakage corrections (improves hadronic resolution) Particle Flow Algorithms (improves jet energy resolution) Track segment identification (monitors gain/response) Technologies studied and validated Silicon and scintillator ECAL with Tungsten absorbers Scintillator and Resistive Plate Chamber (RPC) HCAL with steel absorbers J. Repond: TOPSiDE 5 Study of Timing Requirements for PID Generation of single particles into the barrel (full detector simulation and reconstruction) Electrons, pions, kaons, protons with E < 10 GeV/c Reconstruction of track parameters

Calculation of track length up to a given sensor = 10 ps Linear fit Timing in sensor versus track length Assumption track starts at (0,0) A EC x rte e V r to c te de r

te u O L r ke c tra Study of timing resolution Smearing of times by Gaussian with a fixed width 6 K- sample = 10 ps Requirement At least 20 hits (in trackers + cal) Improves resolution Mass reconstruction

Fit provides c (inverse speed) Calculate of track Calculate mass of particle Take care of tachions m p 1 1 2 m p 1 1 2 for 1.0 for 1.0 Define Kaons 0.4 < mass < 0.8 GeV window 7

Performance as function of momentum With the (0,0) constraint (fit event vertex using all tracks: not entirely unrealistic) = 5.0 ps 10.0 ps 20.0 ps Excellent pion/kaon separation for p < 7 GeV/c 10 ps timing resolution desirable Separation of electrons/kaons/protons easy 8 Time resolution of silicon sensors Taken from Hartmut F-W Sadrozinski et al 2018 Rep. Prog. Phys. 81 026101 Contribution from RO electronics Minimized with careful design Dependence on signal noise: Minimized with fast signals and large S/N Dependence on drift velocity Minimize with uniform electric fields

Dependence on uniformity of ehp production Minimized by decreasing sensor thickness Dependence on signal size Minimize using e.g. constant fraction discriminators J. Repond: TOPSiDE 9 Low-Gain Avalanche Diode (LGAD) Sensors Additional thin p-layer Through Boron/Gallium implantation Increases E-field Charge multiplication with moderate gain 10 50 Amplification of electrons close to pixel (minimal drift) Improved time resolution Four manufacturers CNM Barcelona (RD50, ATLAS HGTD) HPK Hamamatsu FBK Trento (Italy) J. Repond: TOPSiDE 10

Time Resolution versus Time H Sadrozinski at the Pico-second Timing Workshop, Torino, Italy, 2018 https://agenda.infn.it/conferenceTimeTable.py?confId=15031 Smaller C Low noise Thi sors n e ns 2018 To date best results ~18 picosecond with 35 m sensors Results with 20 m sensors imminent J. Repond: TOPSiDE 11 UFSD Test Bench at Argonne

Hardware Assembly started a few months ago Almost everything in hand Scope: Keysight, 2GHz, 4 channels, 20 Gsa/s, 10 bits LV power supplies: Keysight HV power supply: CAEN Environmental chamber Argonne Micro Assembly Facility AMAF Being constructed To be finished by the end of the year Will be equipped with all possible tools and gadgets Scopes Microscopes Wire bonder Environmental chambers Probe stations Flip chip machine Collaboration with Argonne HEP (ATLAS), Geneva, Santa Cruz, Fermilab, (Kansas) 12

Simulating Sensors at Argonne Only started recently Using Silvaco software (actual design) Using Weightfield2 (developed by Torino) Study of guard rings To prevent breakdowns at edges J. Repond: TOPSiDE 13 Simulating Sensors at Argonne Leakage current [A] Investigating temperature dependence -20 0C reduces the leakage current by 2 orders of magnitude Dependence on doping concentration Increases both leakage and signal current Temperature [0K] J. Repond: TOPSiDE 14

Simulating Sensors at Argonne Signal versus time No Landau fluctuations, no noise (jitter, readout) yet Next steps Implementation of readout circuit (HVCMOS) Study of effects of Landau fluctuations, noise on timing J. Repond: TOPSiDE 15 Electron Method TOPSiDE Conclusions Based on silicon Features ultra-fast silicon, imaging calorimetry 5D concept Completely hermetic Advantages of TOPSiDE Simplicity of design (limited number of subsystems) Based on silicon, which is robust (no gas/high voltages, stable operation, radiation hardness)

Excellent kinematic reconstruction Excellent background rejection (hermeticity) Minimal dead material in front of calorimeters No additional TOF, TRD, erenkov, muon system Provides list of particles, similar to hadron level MC Development of Ultra-Fast Silicon detectors Worldwide interest in this Argonne constructing a Micro Assembly Facility Test bench for silicon sensors at Argonne Simulation studies of sensor designed started at Argonne J. Repond: TOPSiDE 16 Backup Slides J. Repond: TOPSiDE 17 Number of channels ECAL Silicon pixels with an area of 0.25 cm2 Total area about 1,400 m2

HCAL Scintillator pads with an area of 3 x 3 cm2 with 14-bit/pad resolution or RPCs with 1 x 1 cm2 readout pads with 1-bit/pad resolution Total area about m2 3M (Scintillator) -> 26M (RPC) channels Tracker/RICH This is only a prototype 51M channels Resolution per pixel ~14-bit <3M channels Total Of the order of 57 82 M channels J. Repond: TOPSiDE 18

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