by rudin petrossian-byrne supervisors: dr. marco gersabeck & stefanie reichert cern summer...
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Implementation of K-matrix formalism in the
amplitude modelBy Rudin Petrossian-Byrne
Supervisors: Dr. Marco Gersabeck & Stefanie Reichert
CERN Summer Student Programme 2014
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The big pictureMixing and CPV
Mixing
strange quark
bottom quark
mixing
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The big pictureMixing and CPV
Mixing
me
mixing
strange quark
bottom quark
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The big pictureMixing and CPV with Charm
2007 – First Evidence from BaBar and Belle for mixing in charmed neutral mesons
𝒙=𝑀 1−𝑀 2
Γ
Charm Quark
∝ (10− 2 )𝒚=Γ 1− Γ2
2 Γ
No significant evidence for CPV in charm to date
• Mixing parameters very small
2012 – LHCb find evidence for mixing in a single measurement
• SM ‘predicts’ small CPV
↪Observation at current sensitivity would imply New Physics
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Phys. Rev. Lett. 110 (2013) 101802
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𝑫𝟎{𝒄𝒏𝒖𝑫𝟎→𝑲 𝒔 𝝅+¿𝝅−¿
(𝑚𝑜𝑑𝑒𝑟𝑛𝑛𝑜𝑡𝑎𝑡𝑖𝑜𝑛)
Allows measuring x and y parameters directly
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𝑫𝟎{𝒄𝒏𝒖𝑫𝟎→𝑲 𝒔 𝝅+¿𝝅−¿
(𝑚𝑜𝑑𝑒𝑟𝑛𝑛𝑜𝑡𝑎𝑡𝑖𝑜𝑛)
Allows measuring x and y parameters directly
P P
Protons collide in the VELO
Very short life-time of charm quark travels mm, then decays
𝑫𝟎
𝝅+¿ ¿
𝝅−
𝑲 𝒔
{𝑞𝑎𝑎Detected by TT tracker.
Bend through magnet. Detected by T1, T2, T3.
𝝅+¿ ¿
𝝅−
{𝑎 decay in VELO as well decay outside VELO harder to reconstruct𝝅+¿ ¿
𝝅−
𝝅−
𝝅+¿ ¿
𝑲 𝒔
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𝑫𝟎→𝑲 𝒔 𝝅+¿𝝅−¿
Allows measuring x and y parameters directly
3-Body Decay Unlike 2-body decays, energy of daughter particles not well-defined Range of possible values.
(𝑚𝑜𝑑𝑒𝑟𝑛𝑛𝑜𝑡𝑎𝑡𝑖𝑜𝑛)
𝑫𝟎
𝑲 𝒔
𝝅−
𝝅+¿ ¿
↪
𝑫𝟎{𝒄𝒏𝒖
LHCb Simulation
𝒎𝑲𝒔 𝝅¿ ¿
𝒎𝑲𝒔𝝅
−
𝟐
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What we observe:Dalitz plot is characterised by Resonances + non-resonant background
Resonances (bands of high )Corresponds to
↑Intermediate particle, e.g.
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Not homogenously populated with events Some daughter energies more probable
P
𝑫𝟎→𝑲 𝒔 𝝅+¿𝝅−¿
LHCb Simulation
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Resonant decay treated as a superposition of 2-body decays e.g. and
Approximate by a relativistic Breit–Wigner probability distribution function
is clearly affected by resonances
Each resonance has a probability amplitude
𝑫𝟎→𝑲 𝒔 𝝅+¿𝝅−¿
THE ISOBAR MODEL
𝑀=∑𝑟
𝑎𝑟𝑀𝑟
𝑴𝒓= ⟨𝜋+¿𝜋−¿𝑟 ⟩ 𝜟𝒓 ¿
Great for isolated Resonances!
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PROBLEMIf Resonances overlapTotal probability 1
↪Not good
↪Theorists are unhappy
↪Should probably do something about that…
Great for isolated Resonances!
BAD for overlappingresonances
𝒎𝝅𝝅𝟐
𝒎𝝅𝝅𝟐
Curtis A. Meyer, Carnegie Mellon University, ‘A k-matrix tutorial’ (2008)
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ALTERNATIVE MODEL
Makes use of K-Matrix formalism to describe resonances with
Assumption: equivalent dynamics to scattering off
Need to consider all possible decays of r in the analysis
𝑫𝟎
𝝅+¿ ¿
𝝅−
𝝅+¿ ¿
𝝅−
𝑫𝟎
𝑲 𝒔
𝑲 𝒔
𝒓
𝒓
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P
K-Matrix Formulation
Pseudo-propagatorComes from scatteringdata.
K - Matrix phase-space factor
Production VectorDescribes Couplings of resonances to
Upholds unitarity by construction!Curtis A. Meyer, Carnegie Mellon University, ‘A k-matrix tutorial’ (2008)
𝒎𝝅𝝅𝟐
𝒎𝝅𝝅𝟐
─ Breit-Wigner─ K-matrix
─ Breit-Wigner─ K-matrix
𝑴𝒓= ⟨𝜋+¿𝜋−¿𝑟 ⟩ 𝑭 ⟨𝐾 𝑠𝑟|𝐷0 ⟩
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My Job: Implement K-matrix description in fitting code for
Implementation: CODING
Programming language: CUDA ( C++
Running on a GPU (Graphical Processing Unit)
implement P fit to data
extremely fast parallelisation
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What are we fitting to data?
21 floating variables
and are complex
𝑃 𝑗=∑𝛼
𝛽𝛼0 𝑔𝛼 𝑗
0
𝑚𝛼2 −𝑚𝜋𝜋
2 + 𝑓 𝜋𝜋 𝑗𝑝𝑟 1 −𝑠0
𝑝𝑟
𝑚𝜋𝜋2 −𝑠0
𝑝𝑟
P
K-matrix: comes entirely from scattering data
phase space matrix: depends only on masses
production vector: describes coupling to resonances
LHCb Simulation
Need to fit
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Wrestling with errors
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STATUS
This Week: Code Working on a CPU!
• Positive cross-checks (e.g. decay time )
Implementation complete
• Observing things (printing to screen) changes variables.
memory issues probably to blame
GPU memory issues currently being addressed
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What are we fitting to data?
21 floating variables and are complex both real and imaginary parts need to be fitted
K-Matrix
Production vector
Sum over poles
Non resonant term
Correction term