Since last time - I updated the CARIOCA dead time values (and the induced inefficiency for background and muon hits)

- I simulated the inefficiency induced by the DIALOG formation time

G. Martellotti 12/06/20141

CARIOCA dead-time & inefficiencyThe counting rates on the bi-gap physical channel counters were measured at different luminosities (0.4 - 0.5 - 0.6 - 0.8 - 1) x 1033

M2 station C side has been analysed

FIRST STEP (Data) - Measure inefficiency of particle counting - Extract the inefficiency fraction due to CARIOCA dead-time δcar

SECOND STEP (Monte Carlo) - simulate the beam time structure folded with the chamber time response and dead time variance - Evaluate the <δcar> necessary to generate such inefficiency - From this <δcar> evaluate the inefficiency we will have at 40 MHz

G Martellotti, G. Penso, D. Pinci

REMIND

2

Subtracting the counting inefficiency due to ‘’granularity effect’’ (if we have > 1 particle/pad, the counter counts only 1) Inefficiency of the physical channel as a function of its rate. The inefficiency can be expressed in terms of the effective dead-time δeff due to the CARIOCA dead-time folded with the BC time sequence and the detector time response.

R*/Rh = (1- δeffR*) inefficiency = δeffR* (δeff in ns, R*=rate measured/0.7 in GHz)

If we measure the rate in GHz, the slope is directly expressed in ns δeff = - 52ns for wires- 65ns for cathodes

dead time inefficiency

3

Time response of the bi-gap chamberWe are interested in the inefficiency for muons, but dead time is started by background hits whose time distribution is wider (it is dominated by the ‘’single gap track’’ hits the time distribution of the bi-gap should be similar to the one of the quadri-gap).

(ns)

I used the time distribution measured for MinBias TAE events (LHCb-PUB-2011-027)Smoothed correcting for the TDC bug at the 25 ns interval edges

4

BCR = 20 MHz

Background hits in the current BC.Measured FE counter inefficiency on vertical scale average CARIOCA dead time <δcar> on the horizontal scale

<δcar> Wires 78 ±3 nsCathodes 91.5-3.5+2 ns

<δcar> ns

ineffi

cien

cy (e

ffecti

ve d

ead

time)

CARIOCA dead time has a large variance depending on the large variance of the charge released by the background tracks.Here for simplicity a gaussian with σ =9ns has been assumed but the real variance is much larger the smoothing is even larger

5

Full smoothing at 40 MHz

The inefficiency induced by dead time as expected is higher w.r.t. the case of 20 MHz

60/52 for wires74/65 for cathodes

BCR = 40 MHzin

effici

ency

(effe

ctive

dea

d tim

e)

Inefficiency for background hits (FE counters)

<δcar> ns 6

Inefficiency for MUONS

<δcar> ns

ineffi

cien

cy (e

ffecti

ve d

ead

time)

BCR = 40 MHz The inefficiency induced by dead time is

higher for muon hits w.r.t. background hits (the time distribution for muons is sharper and the average value lower)

I don’t have now the response of a bi-gap for muons (do we have it?)Here I assumed a gaussian: Peak 11ns, σ = 5ns The inefficiency for muons is larger by ~ 6.5 ns - If I assume a peak value at 10ns 7.5 ns- If I assume a peak value at 13ns 4.5 ns

In case of CARIOCA dead time the difference is relatively small (order of 10%)

In case of DIALOG much larger difference7

M2R3 X Y= 24x4=96 phys. channels 24+ 4 logic. strips per TS Area TS = 60x50=3000 cm2

Inefficiency due to a DIALOG formation time = 18 ns = 3.9 % at 5.4 kHz/cm2

(the average rate in the region)

Here a gaussian with peak value = 11nsand σ = 5ns was assumed for the time distribution of the muon hits in the bi-gap. A uniform rate in the trigger sector was also assumed. This is not fully correct… nevertheless this value is significantly higher w.r.t. what reported in the TDR (2.6 %)And what is relevant is that, if I use the same time distribution used for the background hits, I get a much smaller inefficiency: 2.2 % (to be compared with 2.6%)

HITS

in th

e Tr

igge

r Sec

tor

Rate/cm2 (kHz)

Real particles

Reconstructed hits

8

ineffi

cien

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ffecti

ve d

ead

time)

DIALOG formation time

DIALOG formation time (σ =0) inefficiency for Muon hits (in terms of effective dead time)Here I assumed a gaussian with peak value = 11ns (-1.5ns), σ = 5ns

DIALOG INEFFICIENCY (eff. dead time)formation with muon peak at -2.5ns -1.5 +0.5

12.5 ns 2.7 ns 2.1 1.115 4.3 3.6 2.317.5 6.6 5.7 4.920 9.2 8.1 6.1

9

• The efficiency is strongly dependent on the DIALOG formation time• It is also strongly dependent on the peak value of the muon time distribution

• The inefficiency seems to be higher w.r.t. what reported in TDR and in certain regions is quite large (see the case of M2R3)• If the inefficiency is large we will have (significant) sistematic effects (In the same detector zone we have muons with different momenta and different charge arriving with a different TOF different peak value)

Can we further reduce DIALOG formation time ? Increase nODE number in many regions

SUMMARY

10

Spares

Average 10ns Average 13ns

average=10ns (-2.5)

average=13ns (+0.5)

Time distribution of Background hits

M2R3Background hitTime distribution

Simulation of - Rate of reconstructed hit (with ghosts)- Efficiency

procedure:# Consider the Trigger Sector (TS) geometry of a given region counting rate in the single FE (starting from the foreseen particle rate per cm2 and

using the average correlation found in the station with AND/OR measurements) Inefficiency due to CARIOCA dead time (and DIALOG formation time) Average number of logical pads in theTS hit by particles (I assumed a uniform hit

distribution in the TS) Logical pads reconstructed (X & Y crossing) ghosts

Rates of particles (no ghosts) at L=2x1033 Rates in kHz/cm2

Simulation input: Foreseen ratesreported in TDR

Note :- The effect simulated of the new shielding

to be added at M2-inner has been put in

- The effect of the last shielding already added at M5R4, has to be evaluated and put in

In black the percentage of correlated hits measured (at 2.76 TeV) on the physical channel counters with the FE of the two layers in OR - ANDIn blu the percentage of penetrating tracks (4 gaps) from ‘’Alessia’’MC

Simulation input: Most of the hits detected in the chamber layers are uncorrelated(the fraction of correlation strongly affects simulation results)

From these inputs Logical pad occupancy (with ghosts) and inefficiency

Real particles

Particle HITS not in dead time

Rate/cm2 (kHz)

Reconstructed hits (with ghosts)Assuming efficiency = 1With inefficiency

inefficiency

EXAMPLEM2R1

TS = 95 cm2

X,Y= 6+8 phys.channels48 crossings

The 3 red vertical lines correspond to the rates foreseen in the chamber of the region having minimal, average, maximal population

Particles

Ghosts

TS

inefficiency

Logi

cal p

ad o

ccup

ancy

Chamb Min Aver Max M2R1 1.6 4.0 8.7M2R2 0.5 2.1 4.6M2R3 0.1 0.8 2.7M2R4 0.1 0.3 1.9M3R1 0.4 1.3 2.7M5R4 0.4 9.3 51

logical pad occupancy with ghosts (%) in the most critical regions (ε = 1 assumed)

Chamb Min Aver Max

M2R1 1.6 4.0 8.7 M2R2 0.3 1.1 2.6M2R3 0.1 0.6 1.5M2R4 0.1 0.3 1.2M3R1 0.4 1.3 2.7 M5R4 0 5.7 22

Present detector

Modified readout (from IB on) M2R3 M2R4 M5R4 : full pad detector (pad = logical pad)M2R2 : vertical pad size Y/2

New pad chambersM2R1 M3R1 : pad size X, Y/2w.r.t. present logical pad

Chamb Min Aver Max M2R1 0.6 1.2 2.1M2R2 0.3 1.1 2.6M2R3 0.1 0.6 1.5M2R4 0.1 0.3 1.2M3R1 0.2 0.5 0.9M5R4 0 5.7 22

Inefficiency =5, 11, 23 % at 162, 327, 590 kHz/cm2

Logi

cal p

ad o

ccup

ancy

Rate/cm2 (kHz)

M2R1 PRESENT DETECTOR (TS=95cm2)X,Y= 6+8 phys.channels per Trig. Sect.48x8 crossings per chamber (0.63x3.1 ~ 2cm2)

This is not the inefficiency for a muon track. This is inefficiency for a single pad hit belonging to a muon Cross talk will increase the efficiency for muon tracks. The inefficiency is calculated for muons hitting corresponding pads in the two layers (sligthly pessimistic for muons crossing non projective pads in the two layers)

M2R1 PAD DETECTOR 2 times X , same Y of logical pad192 pads per chamber (1.26x3.2 ~ 4 cm2)

M2R1 PAD DETECTOR X (x2), Y (x1/2) w.r.t. logical pad384 pads per chamber (1.26x1.6 ~ 2 cm2)

Inefficiency = 0.8, 1.6, 3.3 % at 162, 327, 590 kHz/cm2

Inefficiency: large improvement 0.4, 0.7, 1.5 % at 162, 327, 590 kHz/cm2 MisID:

~ the same improvement using the usual FOI No further improvement is possible using a smaller FOI.

MisID: No ghosts improvement using the usual FOI (but higher occupancy of real particles due to increased efficiency) With this Ypad size , one can use a smaller FOI with further improvement.

Pad

occu

panc

y

Pad

occu

panc

yRate/cm2 (kHz) Rate/cm2 (kHz)

M3R1 present detector (TS = 109 cm2 )X,Y= 6+8 phys. channels (48 crossings/TS) 384 crossings per chamber (0.63x3.1 ~2 cm2)

M3R1 PAD detectorXx2 , Y (#phys chan. = #logical pad/2)192 pads per chamber (1.26x3.1 ~4 cm2)

Inefficiency = 0.2, 0.6, 1.0 %At 39, 123, 216 kHz/cm2MisID improvement (no ghosts) ~ same FOI can be used.

Logi

cal p

ad o

ccup

ancy

Pad

occu

panc

y

Ineffic = 0.7, 3.2, 6.9 %At 39, 123, 216 kHz/cm2

Rate/cm2 (kHz) Rate/cm2 (kHz)

Reducing granularity to 96 pads Inefficiency increases= 0.3, 1,2, 2.3 %

M3R1 PAD detectorXx4 , Y (#phys. chan. = #logical pad /4)96 pads per chamber (2.5x3.1 ~ 8 cm2)

Inefficiency can be recovered building the pad detector with smaller physical channels OR-ed in the DIALOG (without increasing output cables)What cannot be recovered is the increase of MisID if FOI must be increased to save muon matching efficiency

Pad

occu

panc

y

M2R2 present detector (TS=380 cm2)X,Y= 12+16 phys.ch. =12 + 4 logic. per TS48x4=192 crossings/chamber (1.26x6.3~8 cm2)

Logi

cal p

ad o

ccup

ancy

Inefficiency : 0.8, 3.3, 6.8 %At 15, 52, 97 kHz/cm2

M2R2 PAD DETECTOR X=2X, Y=1/2Y of logical (it is convenient)192 pads per chamber (2.5x3.1 ~ 8 cm2)

Efficiency – large improvement 0.1, 0.6, 1.1 %MisID Improvement (no ghosts) and possible further improvementreducing YFOI

Pad

occu

panc

yRate/cm2 (kHz) Rate/cm2 (kHz)

Efficiency = 0.3, 1.3, 2.4 %

MisID Improvement (no ghosts) But, going back to the Y pad size = 6.3 cm, we have lost the possibility of reducing FOI having ~ the muon matching efficiency.

M2R2 PAD DETECTOR X=2X, Y=Y of logical pads96 pads per chamber (2.5x6.3 ~ 16 cm2)

Rate/cm2 (kHz)

Pad

occu

panc

y

M2R4 present detector (TS=12000 cm2)X Y= 24x4=96 phys. channels 24+ 4 logic. strips per TSArea TS = 120x100=3000 cm2

Inefficiency from DIALOG

0., 1.7, 7.4 % at0.12, 0.63, 2.6 kHz/cm2

M5R4 present set up (TS=18480 cm2)X,Y= 24+4 phys. ch. = 6+4 logic. Ch. per TS24 crossings per TS (~770 cm2)

ONLY CARIOCA dead time inefficiency simulated2.3 % at 9 kHz

Pad

occu

panc

y

Rate/cm2 (kHz)HI

TS in

the

Trig

ger S

ecto

r

Also DIALOG dead time simulated. Inefficiency = 1.3, 9, 30 % at 0.2, 2, 9 kHz/cm2

Inefficiency from DIALOG (formation 18ns) to check (TAE behave differently)

Rate/cm2 (kHz)

Inefficiencies reported in TDR (Giacomo) Min Aver Max

5.0 11.0 23.0 %0.8 3.3 6.8 (to add DIALOG ineff)0.7 3.9 9.30.0 1.7 7.40.7 3.2 6.9

1.0 9.0 30 %

In M2R1, M2R2, M3R1, M3R2 inefficiency comes from CARIOCA dead time depending on the physical channel occupancy (particle rate/cm2 and channel area) In the other regions where we have a PAD detector with pads Ored in the readout, the largest inefficiency comes from the ‘’DIALOG dead time’’

Inefficiencies of my simulation (different definitions but….)

STATION hit rate in the cm2 Strip strips (MHz)Vertical Horizont RATES kHz/cm2 RATES kHz/cm2 RATES kHz/cm2

4 gaps 2 gaps 1 gap Corr % (1+corr)/2 (1+3corr)/4 Min Aver Max Min Aver Max Min Aver Max

M2R1 7 162 327 590 .54 87 175 316 .30 49 98 17716 – 12 5.2-3.9M2R2 9 15 52 97 .55 8.2 28 53 .32 4.8 17 3131 – 23M2R3 15 0.9 5.4 13.4 .58 0.5 3.1 7.8 .36 .32 1.9 4.8125-750 0.7-4.1M2R4 32 .12 .63 2.6 .66 .08 0.4 1.7 .49 .06 .31 1.3500-3000 0.3-1.9M3R1 4.5 39 123 216 .52 20 64 112 .28 11 34 6018 – 14 2.2-1.7M5R4 12 .23 2.1 9.0 .56 .13 1.2 5.0 .34 .08 .71 3.13080-4620 6.5-9.7