Transcript HARP BEACH04 - Illinois Institute of Technology

Hadron Production Cross-Sections and
Secondary Particle Yields from 2 to 15
GeV using Neutrino Beam Targets
• The HARP Experiment
– Physics goals and motivations
– Summary of the experimental program
– Detector overview and performance
• The fist physics analysis: pion yields from K2K target
– Goals
– Results
Alessandra Tonazzo, Università Roma Tre and INFN
On behalf of the HARP Collaboration
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HARP physics goals
Precise (~2-3% error) measurement of
d2s/dpTdpL
for secondary HAdRon Production by incident
p and p± with
– Beam momentum from 1.5 to 15 GeV/c
– Large range of target materials, from
Hydrogen to Lead
►Acceptance over the full solid angle
►Final state particle identification
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HARP Physics Motivations
Input for prediction of neutrino fluxes for
the MiniBooNE and K2K experiments
Pion/Kaon yield for the design of the proton
driver and target system of Neutrino Factories
and SPL- based Super-Beams
Input for precise calculation of the atmospheric
neutrino flux (from yields of secondary p,K)
Input for Monte Carlo generators
(GEANT4, e.g. for LHC or space applications)
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Data taking summary
HARP took data at the CERN PS T9 beamline in 2001-2002
Total: 420 M events, ~300 settings
SOLID:
n EXP:
CRYOGENIC:
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K2K: Al
MiniBoone: Be
LSND: H2O
5%
50%
100%
Replica
5%
50%
100%
Replica
10%
100%
+12.9 GeV/c
+8.9 GeV/c
+1.5 GeV/c
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The HARP Experiment
124 physicists
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24 institutes
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The HARP Experiment
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The HARP detector layout
TRACKING + PARTICLE ID
at Large angle and Forward
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Beam detectors
MWPCs
TOF-A
T9 beam
CKOV-A
TOF-B
CKOV-B
21.4 m
• Beam tracking with
MWPCs :
– 96% tracking efficiency
using 3 planes out of 4
– Resolution <100 mm
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MiniBoone target
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Beam particle selection
p
3 GeV/c beam
p
d
K
• Beam TOF:
– separate p/K/p at low
energy over 21m flight
distance
– time resolution 170 ps after
TDC and ADC equalization
– proton selection purity
>98.7%
12.9 GeV/c beam
p
K
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• Beam Cherenkov:
– Identify electrons at low energy, p at
high energy, K above 12 GeV
– ~100% eff. in e-p tagging
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Status of TPC
Elastic scattering of 3
GeV p and p on H2 target
Missing mass
mx = ( pbeam + ptarget – pTPC )
2
pppp
p
DpT/pT
dE/dx
pppp
p
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Red: using
dE/dx for PID
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Analysis for K2K: motivations
• Computation of n fluxes
at SK is based on
near/far ratio R
n beam
250km
– For pointlike source (no
oscillations), R~1/r2
– If the near detector does not
see a pointlike source, R
depends on En
• Current K2K computation
of R is based on MC
– Confirmed by p production
measurement (pion
monitor) at En>1 GeV
– Extrapolated to En<1 GeV :
the interesting region for
oscillations !
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Analysis for K2K: motivations
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Analysis for K2K: interesting region
Dip from neutrino oscillations in K2K
they come from decay
of these pions:
K2K needs measurement of
pions with
 E>1 GeV
 E<4.5 GeV
 q<300 mrad
► Forward region
• Main tracking detectors:
drift chambers
• PID detectors: TOF,
Cherenkov, calorimeter
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Forward acceptance
K2K
interest
q x  [200, 200] mrads
NDC1
NDC2
dipole
x
z
B
A particle is accepted if it reaches the
second module of the drift chambers
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K2K interest
P > 1 GeV
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Forward Tracking: NDC
• Reused NOMAD Drift
Chambers
•
Side
modules
12 planes per chamber, wires at
0°,±5° w.r.t. vertical
• Hit efficiency ~80% (limited by
non-flammable gas mixture)
–
–
–
–
stable in time
lowered by high particle flux
recovered between spills
correctly reproduced in the
simulation
Plane efficiencies
Alignment with cosmics and
beam muons
 drift distance resolution
~340 mm
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Forward tracking
NDC4
x
Top view
NDC1
dipole magnet
NDC2
NDC5
z
target
3
1
beam
Plane segment
B
2
NDC3
• 3 track types depending on the nature of the
matching object upstream the dipole
1. Track-Track
2. Track-Plane segment
3. Track-Target/vertex
• Aim: recover as much efficiency as possible and
avoid dependencies on track density in 1st NDC
module (hadron model dependent)
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Forward tracking: resolution
angular resolution
momentum resolution
type
1
MC
MC
data
No vertex
constraint
included
The momentum and angular resolutions are
well within the K2K requirements
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Tracking efficiency
• Only particles with no track downstream the dipole
do not enter into the game (~2%).
– This 2% should be quite independent of the track density
(hadron model dependent) because tracks downstream the
dipole are uncorrelated

track

down

up down
Downstream Up-downstream
tracking
matching
efficiency
efficiency
~98%
~75%
track is known at the level of 5%
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We have been working to
improve it by:
1. Alignment
2. Optimizing matching cuts
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Total tracking efficiency
Total tracking efficiency as a function of p(left) and qx (right)
computed using MC (2 hadron generators) properly scaled by data
Green: type 1
Blue: type 2
Red: type 3
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Black: sum of normalized
efficiency for each type
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Forward PID: Cherenkov
Separate p/p at large momenta
3 GeV beam particles
• 31 m3 filled with C4F10 (n=1.0014)
• Light collection: mirrors+Winston
cones → 38 PMTs in 2 rows
p
p+
Number of photoelectrons
• LED flashing system for calibration
nominal
threshold
e+
data
Nphel
5 GeV beam particles
Npe → 21
p mass is a
free parameter
p (GeV/c)
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p
p+
Nphe
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l
Forward PID: TOF Wall
Separate p/p (K/p) at low momenta
•
42 slabs of fast scintillator read at both ends
by PMTs
3 GeV beam particles
data
p
Calibration / equalization
– Cosmic ray runs (every 2-3 months)
– Laser (continuous: monitor stability)
p
TOF time resolution ~160 ps
=>3s separation of p/p (K/p)
up to 4.5 (2.4) GeV/c
=>7s separation of p/p at 3 GeV/c
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Forward PID: Calorimeter
•
Pb/fibre: 4/1
3 GeV
– EM1: 62 modules, 4 cm thick
– EM2: 80 modules, 8 cm thick
•
•
Total 16 X0
Reused from CHORUS
electrons
•
Calibration with cosmic rays:
– Measurement of attenuation
length in fibers
– Module equalization
pions
data
Energy resolution 23%/sqrt(E)
• intrinsic resolution 15%/sqrt(E)
• convoluted with beam spread
at detector entrance
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Forward PID: p efficiency and purity
Using the Bayes theorem:
tof
P(p | p,  , N phe , E1 , E2 ) 
cerenkov
P( p,  | p )  P( p, N phe | p )  P( p, E1, E2 | p )  P( p | p )
P ( p,  |  )  P ( p, N

 p
 , p ,k ,e
data
calorimeter
momentum
distribution
phe
|  )  P( p, E1, E2 |  )  P( p |  )
Iterative approach: dependence on the
prior removed after few iterations
we use the beam detectors to establish
the “true” nature of the particle
1.5 GeV
3 GeV
5 GeV
jp-(t) = Njp-true-obs / Njp-true
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1.5 GeV
3 GeV
5 GeV
jp-(t) = Njp-true-obs / Njp-obs
jp-(t)/ jp-(t)
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The cross section
The 3 types of tracks must be treated separately
because of the different momentum resolution
i = bin of true (p,q)
j = bin of recosntructed (p,q)
p
si 
 (t ) 1

p (t )
p (t )
 M ij  p (t )  j  N j 
j

t 1 

3
1
1
acc
i
track
i

migration matrix
(not computed yet)
acceptance
tracking efficiency
 itrack
depend on momentum resolution
3


t 1
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 i( t )track
pion yield
pion efficiency
pion purity
p (k )
bkg ( k )
N

N
j
j
 pj ( k ) 
N pj ( k )
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Pion yield
• To be decoupled from
absorption and reinteraction
effects we have used a thin
target
5%  Al target
200%  Al target
K2K replica target
p > 0.2 GeV/c
|qy | < 50 mrad
25 < |qx| < 200 mrad
p-e/p misidentification
background
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Raw data
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Pion yield
5%  Al target
p > 0.2 GeV/c
|qy | < 50 mrad
25 < |qx| < 200 mrad
After PID
correction
After
efficiency
correction
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Pion yield
After
acceptance
correction
5%  Al target
p > 0.2 GeV/c
|qy | < 50 mrad
25 < |qx| < 200 mrad
Systematics are still to be evaluated:
• tracking efficiency know to 5%
• expect small effect from PID
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Conclusions
• The HARP Experiment has collected data for hadron
production measurements with a wide range of beam
energies and targets
• Status of detector
– Forward region: good tracking and PID
– Large angle: much recent progress
• First physics results are available: thin (5%) K2K target
– Using forward region of the detector
• To do
–
–
–
–
–
–
Compute data deconvolution and migration matrix
Evaluate systematic errors
Analyse empty target data for background subtraction
Investigate q=0 region: saturation effects due to beam particle removal
Introduce normalization for absolute cross-section (using min.bias trigger)
… go on to full statistics, and to the rest of the data !
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Backup
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NDC module efficiency
NDC4
• The efficiency of NDC2 and NDC5 is flat
within ~5%.
• The efficiency of the lateral modules (3 and
4) is flat within 10%
• The combined efficiency is not sensitive to
these variations.
NDC2
NDC5
dipole
data
NDC3
NDC 2
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NDC 3
NDC 4
NDC 5
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Module acceptance / Downstream eff.
NDC4
NDC2
NDC5
 iNDC m   iaccm   itrack m
module
acceptance
dipole
 idown
NDC3
MC
5


m 2
5


NDC m
i

 iNDC m
m2
5


m2
5


NDC n
i

n 2
n m
 iNDC m
5


n 2
n m
 iNDC n
 (98  2)%
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module
efficiency
5


NDC p
i
p 2
p m n
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Up-downstream matching efficiency
 iup down
N ip  rec
 down
Ni
data
x2, qx2
MC
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We need to convert x2 and qx2
to p and q.
For that we use the MC
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Up-down matching efficiency
NDC4
• Probability of matching a
downstream track with the
other side of the dipole
Top view
NDC1
dipole magnet
target
beam
NDC2
NDC5
1
B
3
2D segment
 iup down
N ip  rec

N idown
2
x
NDC3
z
We tune to the DATA
the absolute scale of each track type
MC and data agree
within ~3% in their
shapes
MC + data
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Forward PID: continuous probability
• Using the Bayes theorem
P( Bi | A) 
P ( A | Bi )  P( Bi )
P( A | B )  P ( B )


A  { p,  , N phe , E1 , E2 }
Measured quantities
B  p , p, e, k ,...
Particle types
• The different pid detectors are independent of each other
P( p, , N phe , E1, E2 | p )  P( p,  | p )  P( p, N phe | p )  P( p, E1, E2 | p )
Ckov
TOF
P(p | p,  , N phe , E1, E2 ) 
Calorimeter
P( p,  | p )  P( p, N phe | p )  P( p, E1, E2 | p )  P(p | p)
P( p,  |  )  P( p, N

 p
phe
|  )  P( p, E1, E2 |  )  P( | p)
 , p ,k , e
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Forward PID: iterative procedure
P( p ,  | p) from TOF
with
P( p ,Nphe | p) from Cherenkov
P( p , E1 , E2 ) from Calorimeter
Product of conditional probabilities
and relative abundances
Iterative Bayesian
approach: dependence
on the prior removed
after few iterations
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 = m2 / p2
3 GeV
p p Step 1
e K
Step 2
Step 3
Step 4
Step 5
Line : true PID
Colored histograms:
reconstructed PID
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