Particle tracking in the CALET experiment Paolo Maestro University - - PowerPoint PPT Presentation

▶
particle tracking in the calet experiment paolo maestro
SMART_READER_LITE
LIVE PREVIEW

Particle tracking in the CALET experiment Paolo Maestro University - - PowerPoint PPT Presentation

Aug 17, 2023 390 likes •688 views

Particle tracking in the CALET experiment Paolo Maestro University of Siena & INFN Nicola Mori INFN Sezione di Firenze On behalf of the CALET collaboration PoS (2017) 208 1 35 th ICRC, Busan 2017

slide-1
SLIDE 1

35th ICRC, Busan 2017 Paolo Maestro

Particle tracking in the CALET experiment

Paolo Maestro

University of Siena & INFN

Nicola Mori

INFN Sezione di Firenze

On behalf of the CALET collaboration

1

PoS (2017) 208

slide-2
SLIDE 2

35th ICRC, Busan 2017 Paolo Maestro

2

Outline

Ø Introduction on CALET experiment Ø Tracking procedure: description and implementation Ø Tracking validation and performance with Monte Carlo data Ø Application of the tracking method to flight data Ø Track-based alignment of IMC fibers Ø Data vs. MC comparison

slide-3
SLIDE 3

35th ICRC, Busan 2017 Paolo Maestro

3

ASC (Advanced Stellar Compass) GPSR (GPS Receiver) CAL/CHD CAL/IMC CAL/TASC CGBM (CALET Gamma Ray Burst Monitor) MDC (Mission Data Controller) FRGF(Flight Releasable Grapple Fixture)

CALET payload

Port # 9

Launched on Aug. 19th 2015 on the Japanese H2-B rocket Emplaced on JEM-EF port#9 On Aug. 25th 2015

・ Mass: 612.8 kg ・ JEM Standard Payload Size 1850 mm (L) × 800 mm (W) × 1000 mm (H) ・ Power Consumption: 507 W （max） ・ Telemetry: Medium 600 kbps (6.5GB/day) / Low 50 kbps

slide-4
SLIDE 4

35th ICRC, Busan 2017 Paolo Maestro

4

Detector Measure Geometry Readout CHD (Charge Detector) Charge (Z=1-40) Plastic Scintillator 14 paddles × 2 layers (X,Y) Paddle size: 3.2×1×45 cm3 PMT+CSA IMC (Imaging Calorimeter) Tracking Particle ID 448 Scifi × 16 layers (X,Y) 7 W layers (3 X0) Scifi size: 1×1×448 mm3 64 MAPMT+ ASIC TASC (Total Absorption Calorimeter) Energy e/p separation 16 PWO logs × 12 layers (X,Y) log size: 1.9×2×32 cm3 Total thickness: 27 X0 , ~1.2 λ APD/PD + CSA PMT+CSA (for Trigger)

CHD IMC TASC

CHD-FEC IMC-FEC TASC-FEC CHD-FEC IMC-FEC TASC-FEC

CALET instrument

CGBM

HXM x2

LaBr3(Ce)

SGM x1

BGO 7keV-1MeV 0.1-20MeV CALORIMETER

slide-5
SLIDE 5

35th ICRC, Busan 2017 Paolo Maestro

5

Science Objectives Observation Targets Energy range Nearby CR sources Electron spectrum 1 GeV – 10 TeV Dark Matter Signatures in e/γ spectra 10 GeV – 10 TeV CR Origin and Acceleration p-Fe individual spectra Ultra Heavy Ions (26<Z≤40) 10 GeV – 103 TeV few GeV/amu Galactic CR Propagation B/C sub-Fe/Fe ratios Up to some TeV/n Solar Physics Electron flux < 10 GeV Gamma-ray Transients Gamma and X-rays 3 keV – 30 MeV

CALET science goals

slide-6
SLIDE 6

35th ICRC, Busan 2017 Paolo Maestro

Tracking in CALET

6

Ø Tracking needed for:

  • pointing
  • definition of geometrical acceptance
  • computing variables for e/p discrimination
  • identification of hit paddles in CHD and hit scifi’s in IMC à Particle ID

Ø Tracking exploits IMC fine granularity and imaging capability Main challenge: find the primary CR particle track in a large amount of shower particle tracks backscattered from TASC à High hit multiplicity à Multiple track candidates Ø Combinatorial Kalman Filter (CKF) algorithm to provide robust track finding and fitting

  • Algorithm fed with the Z positions of layers, the X/Y coordinate of the center-of-

gravity (COG) of each Scifi’s cluster, and its associated position error σcog.

  • The algorithm runs separately for the X and Y views to find the projections of the

full 3D track, which is then reconstructed.

slide-7
SLIDE 7

35th ICRC, Busan 2017 Paolo Maestro

Combinatorial Kalman Filter

7

  • A candidate track is created for each

possible combination of clusters in the first two layers.

  • Each track is fitted to a straight line and

propagated to the next layer k.

  • The predicted position at layer k is used to

associate new clusters to the track.

  • A new track candidate is created for every

cluster on layer k, whose COG lies sufficiently near to the predicted state, i.e. within σcog

  • To cope with possible inefficiencies,

missing points (“holes”) are allowed in track.

  • Each “branched” track is fitted. Bad tracks

(χ2>10 or no. holes>2) are discarded. Good candidates are propagated to layer k+1, and procedure is iterated, up to the last layer.

Good track Bad track Real hits Spurious hits CR Track Candidate track propagators XZ view Layer 0 Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 Missing hit Secondary Track Good track

slide-8
SLIDE 8

35th ICRC, Busan 2017 Paolo Maestro

8

Ø For high-energy shower events, in order to reduce the proliferation of track candidates and processing time, only IMC clusters within a ROI (region-of-interest) are fed to KF algorithm. Ø ROI is defined around the back-projection of the TASC shower axis, which is fitted to the COG of the TASC log clusters in each TASC layer. Ø Among all the candidate tracks found by the KF algorithm in each view, the track with:

  • the largest energy deposited in the associated clusters;
  • closer to the core of the shower reconstructed with TASC;

is chosen as the primary particle track.

Identification of primary particle track

slide-9
SLIDE 9

35th ICRC, Busan 2017 Paolo Maestro

9

Carbon event with estimated E>10 TeV ROI Shower axis Primary particle track

Tracking example

slide-10
SLIDE 10

35th ICRC, Busan 2017 Paolo Maestro

10

Carbon event with estimated E>10 TeV ROI Shower axis Primary particle track Candidate tracks

Tracking example

slide-11
SLIDE 11

35th ICRC, Busan 2017 Paolo Maestro

Tracking validation with MC

11

  • Samples of electrons, protons, He, C, Fe nuclei were simulated with FLUKA
  • Isotropic generation in direction
  • E-1 energy spectrum. Particle energy range: 10 GeV - 100 TeV for nuclei

5 GeV - 20 TeV for electrons

  • CALET High-Energy Trigger (HET) modelled in simulation.
  • Coincidence of signals in last four IMC layers and first TASC layer, with

thresholds chosen to ensure >95% efficiency for electrons > 10 GeV

  • Particle selection used to evaluate tracking performance
  • HET events
  • Reconstructed track length in TASC > 27 X0
  • Entrance point in CAL above 5th IMC layer.
slide-12
SLIDE 12

35th ICRC, Busan 2017 Paolo Maestro

Angular resolution (electrons)

12

PSFx = 0.11°

  • KF rec.

MC truth

Point-spread function (PSF) is half-width of the interval centered on mean value of the residual distribution Δθ = θrec – θMC containing 68.3% of events.

PSFy = 0.11°

slide-13
SLIDE 13

35th ICRC, Busan 2017 Paolo Maestro

Angular resolution (protons)

13

PSFx = 0.55°

  • KF rec.

MC truth

Point-spread function (PSF) is half-width of the interval centered on mean value of the residual distribution Δθ = θrec – θMC containing 68.3% of events.

PSFy = 0.55°

slide-14
SLIDE 14

35th ICRC, Busan 2017 Paolo Maestro

Angular resolution (C nuclei)

14

PSFx = 0.22°

  • KF rec.

MC truth

Point-spread function (PSF) is half-width of the interval centered on mean value of the residual distribution Δθ = θrec – θMC containing 68.3% of events.

PSFy = 0.23°

slide-15
SLIDE 15

35th ICRC, Busan 2017 Paolo Maestro

CR arrival direction reconstruction

15

Electrons Fe nuclei

  • θx and θy are combined to determine the

parameters (θ, φ) of the arrival direction of the particle in the space.

  • The 3D angular resolution ∆Θ3D is the PSF of

the distribution of the scalar product between the reconstructed and the true MC arrival direction.

Θ3D distribution (electrons)

ΔΘ3D

slide-16
SLIDE 16

35th ICRC, Busan 2017 Paolo Maestro

Impact point resolution (electrons)

16

σx = 420 µm

  • KF rec.

MC truth

σy = 420 µm

Image of rec. CHD impact point

slide-17
SLIDE 17

35th ICRC, Busan 2017 Paolo Maestro

Tracking efficiency

17

  • Acc. A
  • Acc. B
  • Acc. C

Three different acceptance configurations: A : track crossing CHD top and TASC bottom B : track crossing 5th IMC layer and TASC bottom C : track crossing 5th IMC layer and with length in TASC > 27 X0

Tracking efficiency (C nuclei) Tracking efficiency (Electrons) Tracking efficiency (Protons)

slide-18
SLIDE 18

35th ICRC, Busan 2017 Paolo Maestro

18

Particle PSFx/y (deg) σx/y (mm) Tracking efficiency @ E > 100 GeV (nuclei) > 10 GeV (electrons) electron 0.1 0.42 95% proton 0.55 1.5 90% He nuclei 0.45 1.2 90% C nuclei 0.22 0.58 95% Fe nuclei 0.09 0.26 95%

Performance of tracking algorithm

slide-19
SLIDE 19

35th ICRC, Busan 2017 Paolo Maestro

IMC scifi’s alignment

19

X Z

Nominal coordinate of the hit scifi Hit scifi Particle trajectory Recontructed track

Displaced layer

  • Based on flight data: calibration runs

with minimum ionizing He nuclei

  • Assume nominal coordinates for

scifi’s, e.g. “design” geometry.

  • Misalignments affect tracking → large

“residuals” (Δ= difference between hit position and particle trajectory).

  • Calculate corrections to minimize

residuals in each layer.

  • A correction factor (shift) for each

bundle of 32 scifi’s routed to the same MAPMT is used.

  • In total: 224 shifts to be fitted

Δ

slide-20
SLIDE 20

35th ICRC, Busan 2017 Paolo Maestro

IMC layers before alignment

20

  • Use tracks with 8 points per

view and χ2/ndf < 3

  • CHD paddles matched by

track have signals compatible with He mip

  • Residuals not centered in 0

→ misalignment in some layer

  • Max Shifts: ~ 550 µm
slide-21
SLIDE 21

35th ICRC, Busan 2017 Paolo Maestro

IMC layers after alignment

21

  • Use shifts found for each belt

in each layer to correct scifi position

  • Residuals are centered in 0

with peak widths ~280 µm

slide-22
SLIDE 22

35th ICRC, Busan 2017 Paolo Maestro

22

Stability of alignment corrections

slide-23
SLIDE 23

35th ICRC, Busan 2017 Paolo Maestro

Tracking with flight data

23

Ø Samples protons and C nuclei selected using some months of data

  • HE trigger events
  • Track quality cut: χ2<5 and no. track points ≥4
  • Fiducial acceptance: track crossing CHD top, TASC top and bottom layers

within 2 cm from the edge.

  • Signals of CHD paddles crossed by the primary track used to identify particle

charge

  • Total energy deposited in TASC > 45 GeV for C, >100 GeV for protons

Ø Comparison with MC simulated samples

  • MC events (generated with E-1 spectrum) are reweighted to E-γ spectrum with

γ=2.65 for C and γ= 2.75 for protons.

  • Same event selection as for flight data.
slide-24
SLIDE 24

35th ICRC, Busan 2017 Paolo Maestro

24

CR impinging angle rec. in X/Y view

Carbon nuclei selection

  • Rec. θx angle
  • Rec. θy angle
  • Flight data

MC

  • Flight data

MC

slide-25
SLIDE 25

35th ICRC, Busan 2017 Paolo Maestro

25

CR impinging angle rec. in X/Y view

Protons selection

  • Rec. θx angle
  • Rec. θy angle
  • Flight data

MC

  • Flight data

MC

slide-26
SLIDE 26

35th ICRC, Busan 2017 Paolo Maestro

26

CR arrival direction

Carbon nuclei selection

  • Rec. θ angle
  • Rec. φ angle
  • Flight data

MC

  • Flight data

MC

slide-27
SLIDE 27

35th ICRC, Busan 2017 Paolo Maestro

27

CR impact point rec. in X/Y view

Carbon nuclei selection

  • Rec. x-coordinate on CHD
  • Flight data

MC

  • Flight data

MC

  • Rec. y-coordinate on CHD
slide-28
SLIDE 28

35th ICRC, Busan 2017 Paolo Maestro

28

CR impact point rec. in X/Y view

Protons selection

  • Rec. x-coordinate on CHD
  • Flight data

MC

  • Flight data

MC

  • Rec. y-coordinate on CHD
slide-29
SLIDE 29

35th ICRC, Busan 2017 Paolo Maestro

29

A procedure based on a combinatorial Kalman Filter has been developed to track CR particles in CALET It exploits the unique imaging capability of IMC The tracking method was tuned and validated with MC data.

  • Effective in identifying the arrival direction of CR’s with high efficiency in large

background of secondary tracks backscattered from the calorimeter.

  • Excellent angular and spatial resolution.

Particle tracking performance with flight and simulated data in good agreement Effective track-based procedure to align IMC fibers.

Summary