Transcript RIChilights

RIChilights
RICH2007 Highlights (Part III)
Stefania Ricciardi
RAL, 28 November 2007
Piazza Unita` d’Italia
Caffe` degli Specchi (Mirrors)
One of Trieste “institutions”
appreciated by Kafka, Joyce
and British Royal Navy which chose it
as General Quarter at the end of
second World War
Named after large mirrors on the wall
used to reflect inside the light from
the sunset on the sea
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Piazza Unita` d’Italia
Mirrors
Water
Right ingredients for a successful
RICH conference!
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RICH2007 Sessions
• Cherenkov light imaging in particle and
nuclear physics experiments
• Cherenkov detectors in astroparticle physics
• Novel Cherenkov Imaging Techniques
• Photon detection for Cherenkov counters
• Technological aspects of Cherenkov
detectors
• Pattern recognition and data analysis
• Exotic applications of Cherenkov radiation
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RICH in AstroParticle Physics
Cherenkov detectors are fundamental in many APP
sectors. Discussed @ RICH2007
Ground-based gamma-ray astonomy
1.
–
2.
@ RICH2007: MAGIC
Cherenkov Imaging detectors for ion identification in
CR (satellite and balloon-born experiments)
–
–
3.
–
–
Flying spectrometers
@ RICH2007: CREAM
High-energy n telescopes
high mass targets (≈ 109 t)
 use large volumes of transparent
media available in nature
@ RICH2007: Antares,
Nemo, KM3Net
(Ref to Recent seminar at RAL by Greg Hallewell)
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The experimental challenge in high
E.Lorenz
energy astrophysics
INITIAL PARAMETERS NOT UNDER CONTROL AS IN HEP
ENERGY , TIME, (PATRICLE TYPE), (DIRECTION)
FLUXES ARE VERY LOW -> NEEDS ULTRA-LARGE DETECTOR VOLUMES
WATER – ICE – AIR
natural media act as target and radiators (transparent to light)  allow the
construction of massive Cherenkov instruments with excellent
performance for neutrino and astroparticle physics
NEARLY ALL EXPERIMENTS IN APP RELY ON PHOTON DETECTION
Need for large-active-area single-photon
AstroParticle Physics is now a driving force for new photon detectors.
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GROUND-BASED g ASTRONOMY
44 SOURCES
(13 As)
Started in 1989 by discovery of gs from the CRAB
Nearly all discoveries made by Cherenkov light detectors (> 95%):
Imaging Air Cherenkov Telescopes
(NOW(FALL07) 70 SOURCES
2006)
NOT ALL SOURCES IN INNER GALACTIC PLANE SHOWN
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The IACT technique
Quick Time™ an d a
TIFF ( Un compr ess ed ) de co mpr es sor
ar e n eed ed to s ee this pic tur e.
Physics of the atmospheric showers:
• Cosmic rays (protons, heavier Z,
electrons, photons) hit the upper
atmosphere
•
Interactions create cascade of billions
of particles:
– Electromagnetic shower (e+,e-,g)
– Hadronic shower (, , e+,e-,g)
•
Charged particles in turn emit
Cherenkov light:
– Blueish flash
– ~2ns duration
– ~1º aperture
•
Cherenkov cone reaches the ground
– Circle of ~120m radius
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IACT g-image
Image is ellipsoid pointing to centre for
gammas (axis aligned with g-source)
Randomly distributed for hadrons
Study of the image gives information on
primary particle
Sensitivity to single photons and the best possible time resolution
are important, because the signal is weak, and the discrimination
against non-electromagnetic showers is helped by determining
precise arrival times.
Signal:100 photons/m2 at 1 TeV
Background: 2-5 1012 photons/(s m2 sr)
High quality photomultipliers are used as photon detectors.
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THE NEW GENERATION OF HIGH SENSITIVITY CHERENKOV TELESCOPES
MAGIC
VERITAS
(USA & England)
2007
4 telescopes
10 meters Ø
Whiple obs.
Base camp
Arizona
(Germany, Italy & Spain)
2003
1 telescope 17 meters Ø
Roque de
los Muchachos,
Canary Islands
CANGAROO III
(Australia & Japan)
HESS
Komas land,
Namibia
(Germany & France)
2002
4 telescopes
12 meters Ø
2004
4 telescopes 10 meters Ø
Woomera,
Australia
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M.Doro
Quick Time™ an d a
TIFF ( Un compr ess ed ) de co mpr es sor
ar e n eed ed to s ee this pic tur e.
The MAGIC Telescope
• Collaboration of 22 institutes (mostly European) ~150 physicists
• Installation completed 2003
Clone (Magic II) under construction
Inauguration 2008
Stereoscopic MAGIC I + II will have
increased performance:angular resolution
energy resolution, flux sensitivity
Focal plane camera
with 580 PMTs
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M.Doro
MAGIC
Reflector and mirrors:
– World largest dish diameter
17m
– All aluminium mirrors with
sandwich structure and
diamond-milled surface
Mirror requirements
AlMgSi0.5
plate
Lightweight
• Telescope must rotate fast and then mirrors
need to be as light as possible
Mirror Shape • Mirrors profile is spherical
Hexcell
• Each mirror has different radius of curvature
because reflector profile is parabolic (f=17m)
Al Box
Rigidity
• Avoid oscillations due to wind
• Avoid bending during tracking
Insulation
• Sometimes strong rains and snows, high
humidity, strong UV light
Optical
quality
• Maximize reflectivity
• Minimize reflected spot size
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MAGIC Summary
M.Doro
• MAGIC II mirrors production is
already on the production-line
• Technique gave excellent results
in term of light concentration
• Insulating problems seem solved
• Price is decreased wrt to MAGIC
I, nevertheless is still main
drawback: 2.8k€/m2 can be a
problem for third generation
IACTs
• Scale production can decrease
costs or find other techniques
(glass)
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NEXT AIR CHERENKOV
TELESCOPE PROJECTS
Aim for higher sensitivity (factor 10 increase), lower threshold (<50 GeV)
a) European initiative: CTA (Cherenkov telescope array)
b) US Project: AGIS
Both in the 100-150 M€ price range, 50-100 telescopes
CTA
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Y.Sallaz-Damaz
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CREAM
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CHERCAM a flying Cherenkov..
Launch expected Dec 2007
Optimised for charge measurement
(Nph Z2 sin2q, resolution 0.2 charge units)
Has to operate a low temperature/low pressure
(-10C, 5mb)
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PID and Pattern recognition can be a complex business – many challenges..
SuperK (multiple) rings
2 electron candidates:
2 muon candidates:
The largest Cherenkov
in use at an
accelerator-based
experiment
50ktonnes water
viewed by 13,000 20”
PMTs
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(not the speaker)
In Search of the Rings
Approaches to Cherenkov Ring Finding
and Reconstruction in HEP
Guy Wilkinson, Oxford University
RICH 2007, Trieste, October 2007
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Challenges of RICH pattern
recognition
in
PP
LHCb: RICH 1
(revolved !)
Complicated environment !
Lesson 1: main source of
background is other rings.
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Challenges in RICH Pattern
Recognition
LHCb: RICH 1
(revolved !)
Ring without
associated track
Split (or
partial)
rings
Sparsely
populated
rings
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Likelihood algorithms
Likelihood approach is most common method of pattern-recognition + PID
(note - it performs both steps!) for experiments where tracking info is available.
eg. LHCb, BaBar, CLEO-c, Hermes, HERA-B, DELPHI, SLD…
For a given set of photons which are candidates to be associated with the track,
formulate a likelihood for each particle hypothesis (e, μ, π, K, p). Eg. for CLEO-c:


h, j
j
Lh    Pbackground   Poptical , j  Psignal (qgj | q exp

)
. q 
optical paths , j
g 

background
distribution there may be several
paths by which photon
has reached detector
1 < p < 1.5 GeV/c
expect a certain number of
photons, at a certain angle,
with a certain resolution
Ratio of likelihoods, or difference of log-likelihoods then gives a statistically
meaningful quantity that can be cut on to distinguish between hypotheses.
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Global Likelihood
Very often it is advantageous to calculate a single (log) likelihood for all event,
being the (sum) product of the likelihoods for all of the tracks in all radiators.
• In high-multiplicity environments, the background to each signal ring
is… other signal rings!
Only way to get an unbiased estimate for each track is to consider
entire event simultaneously.
• In experiments with >1 radiator or >1 counters (eg. LHCb 3 radiators
in 2 counters, SLD liquid and gas, HERMES aerogel and gas…) this
is a convenient way to make best use of all information.
Likelihood maximised by flipping each track hypothesis in turn until
convergence is attained.
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Performance of likelihood
algorithms
Kaon identification efficiency, and  misid efficiency:
BaBar: LK > L
LHCb: K (or p) preferred hypothesis
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Hough transforms
Hough Transform: common technique in both tracking & ring finding.
Attractive features - unaffected by topological gaps in curves, split
images, and is rather robust against noise.
Detector space
HT Space
Hough Transform
r or θc
yc
xc
Each point gives surface in HT space. Intersection of surfaces gives
ring parameters. Find by peak hunting in suitably binned histogram.
Usual practice: look for centre OR radius, ie. reduce to 2-d or 1-d problem.
Used by several experiements in high-density environment: Alice, CERES
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Applications of Hough trasforms in
n physics: SuperK
No tracking info available in SuperK: standalone ring-finding essential
Firstly find event vertex position
based on spread of hit PMT times
36.2 m
11,146
PMTs
33.8 m
Find vertex to resolution of ~ 30 cm
Initial direction indicator also available.
Then perform HT: draw saturated (42 0)
circles around hit tubes to look for ring centres
and hence directions.
HT
Iterate, to look for
multiple ring candidates
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Conclusions on reconstruction and
ID techniques
Likelihood algorithms and Hough Transforms have proven record
of making sense of even the most intimidating environments. In
general these make significant use of tracking information.
Other approaches exist, but have not yet
achieved performance to displace baseline methods.
Will be interesting to see how methods developed on MC for
high multiplicity experiments (eg. LHCb, ALICE) cope with real data!
COMPASS
STAR
BABAR
DIRC
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“Exotic applications of
Cherenkov radiation”
Ice
Salt domes
Lunar regolith
This is NOT exotic nowadays!
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Radio-Cherenkov detectors
Active experiments:
• RICE (since 1999)
• Anita
Physics: UHE n
Detection of EeV neutrinos
(i.e. GZK neutrinos produced in
interaction of UHE protons with CMB)
p +gCMB (→ D* → n+) → n e+ ne nm nm
n/km2/y
Flux is extremely low: 10 GZK
300 Km interaction length for En=1018 eV
Need >>102 km3 volumes
Salsa
(Anita Collaboration)
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The Askaryan effect
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Anita
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Conclusion
A.P.
S.E.
The three of us
did appreciate
the conference and
the setting!
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Many thanks to the Organisers!
RICH 2007
Stazione Marittima,
Trieste, Italy
October 2007
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