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Experimental Search for the Decay
K. Mizouchi (Kyoto University) (1) Physics Motivation (2) Detector (3) Event Selection Criteria (4) Background Estimation (5) Branching Ratio (6) Single Photon Inefficiency (7) Conclusions
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: Physics Motivation [1] Helicity suppressed decay [2] Decay Form of
: left-handed (in SM) : spin 0 [1] Helicity suppressed decay (A) Neutrino mass : implies (B) Neutrino type : Majorana neutrino x2 larger branching ratio. [2] Decay Form of (A) Sensitive to any hypothetical weakly-interacting neutrals. (B) Decay into different neutrino flavors : [3] Cosmological Interests Neutron star cooling model through pion pole mechanism :
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Event Detection Strategy
Charged particles from K+ decay at rest Km2 Hermetic photon detection system Kp2 Clean Kp2 selection p0 to invisible final states Prior best limit : (E787)
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E949 Detector (1) Target : Kaon decay at rest
E949 detector side view (upper half) E949 detector end view (upper half) Range Stack Drift Chamber Target (1) Target : Kaon decay at rest (2) Drift chamber : Momentum (3) Range Stack (scintillator) : Energy / Range
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E949 Detector (1) Barrel Veto (BV) : Pb-scintillator sandwich
E949 detector side view (upper half) E949 detector end view (upper half) (1) Barrel Veto (BV) : Pb-scintillator sandwich (2) Barrel Veto Liner (BVL) : Pb-scintillator sandwich (3) Endcap Calorimeter : CsI crystals
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DAQ Summary # of accumulated Kaons Accumulated K+:
Platinum target used in 2002 # of accumulated Kaons Before data taking After data taking Accumulated K+:
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Analysis Strategy (1) : Number of p0 tagged by Kp2 selection criteria
(2) : Correction for under-estimation of the num. of p0. (3) : Number of remaining events after photon veto application (4) : acceptance of the photon veto
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Analysis Strategy (cont.)
(w/ bkgnd) 1/3 sample 2/3 sample (1) Kp2 selection p0 sample p0 sample ( ) tuning (2) Find the best photon veto paramters Signal candidate (N)
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High Purity Kp2 Identification
Dominant non-Kp2 backgrounds (1) background rejection (2) Single beam background rejection (3) Two-beam background rejection
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High Purity Kp2 Identification
Dominant non-Kp2 backgrounds (1) background rejection (2) Single beam background rejection (3) Two-beam background rejection
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Top half of side view m+ n Km2 backgrounds
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High Purity Kp2 Identification
Dominant non-Kp2 backgrounds (1) background rejection (2) Single beam background rejection (3) Two-beam background rejection
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Single beam backgrounds
Top half of side view p+ Cerenkov B4 Single beam backgrounds
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High Purity Kp2 Identification
Dominant non-Kp2 backgrounds (1) background rejection (2) Single beam background rejection (3) Two-beam background rejection
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Two-beam backgrounds Beam 1 p+ K+ Beam 2 Beam wire chamber
Top half of side view Beam 2 p+ K+ veto veto veto Two-beam backgrounds
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# tagged Kp2 and Backgrounds in the selection
Real data (2/3 sample) Impurity : ~10-9
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Disruption Correction Factor Cdis
Overlapping g,e+/- (from p0) may cause disruption in the p+ track reconstruction. Estimation (Pure MC Study) : (1) Normal Kp2 decays (2) Kp2 decays but was forced. Difference in the p+ recon. efficiency correction Disruption correction :
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Hermetic photon veto
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Acceptance Measurement Cacc
acceptance loss due to coincident accidentals Correction factor : p+ accidental n n How to measure the Cacc ? Measure acceptance loss of Km2 decays (real data) by the photon veto, after all m+ activities are removed.
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Maximization of Sensitivity
Photon veto : Esum > Ethreshold in the timing window Effective rejection = rejection ×Cacc Final photon veto Real data “1/3 sample” [ Hermetic photon veto ] (1) p0 gg rejection : (2) p0 nn acceptance : Find the best parameters providing the largest rejection and the smallest acceptance loss. (for ~20 photon detection subsystems)
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Opening the Box Real data “2/3 sample” A total of 99 candidates were observed in the signal box Kaon decay time (ns) p+ momentum (MeV/c)
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Result New upper limit :
2/3 sample Saturation at 3.5x106 1/3 sample Conservative upper limit # signal < 113 at 90%CL (Poisson) and subtracting the non-Kp2 backgrounds; New upper limit : A factor of 3 improvement from the previous best result.
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p0 gg Background subtraction
Measurement of the detector single photon inefficiency Kp2 w/ one photon missing event
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Single Photon Inefficiency
Measure single photon inefficiency with real data. Kp2 w/ one photon missing event (1) : raw photon distribution (2) : mis-detected photon distribution (3) : Trigger prescale compensasion,
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Analysis Strategy Kp2 w/ one photon missing event
Reconstruct (tagging) photon Extract kinematics of the mis-detected photon. Correction factors
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(1) Photon Clustering Method
Reconstruct photons and extract their (A) positions (B) energies and (C) timings.
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(2) Kinematical Fitting
[Lagrange Multiplier] c2 minimization with constraints. (A) Four Constraints (B) Five inputs
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Denominator / Numerator Map
Relaxed photon veto (acc = 0.80) Validity of this background subtraction method Understanding of the detector performance
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Correction factors CL1.1after : unwanted trigger rejection embedded in
online photon veto (2)Cacc : over-rejection by photon veto with accidentals (3)Csplit : self-vetoing effect by splitting tagging photon CL1.1after = 1.14 Cacc = 0.80
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Self-vetoing effect due to split photon
Missing-side MC simulation Missing photon kinematics
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Single Photon Inefficiency
Validity of this background subtraction method Understanding of the detector performance
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p0 gg detection inefficiency
(1) Single photon inefficiency (2) Photon kinematics PSPI= from MC simulation (N events)
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Daughter Table Method w/ Binominal error Convoluted inefficiency
Daughter tables produced by random number generator 300 daughter tables
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p0 gg background subtraction
Number of candidates with relaxed photon veto 4131 events Singal (90% C.L) : 2259 A factor of 1.8 improvement
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Improvement by the subtraction
p0 gg rejection at various photon veto Improvement (Before/After) More than ~2 improvements at various photon veto search Estimation from photon inefficiency
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Num of p0 gg backgrounds as a function of cos(qp+)
Single photon inefficiency Signal discrimination capability from backgrounds
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Background subtraction with dip angle distribution
Signal candidates
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Likelihood distribution
Candidates : sraw = 4131 Best fit value : s = 1977 90 % C.L : s90 = 2449 A factor of 1.7 improvement Ref. w/o subtraction :
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Conclusions (1) search was performed with 3.02x109 Kp2 events,
where impurity of 10-9 was achieved. (2) New upper limit of was obtained with a total number of 99 candidates in the signal region; x3 improvement from the previous best limit. Single photon inefficiency was measured with special data p0 gg background subtraction was performed with the photon inefficiency; (A) x1.8 improvement with simple subtraction (B) x1.7 improvement with cos(qp+) shape discrimination
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Thank you !
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Background distribution
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Background understanding and detector inefficiency
Can we understand the remaining events from a view of photon inefficiency ? ( if possible, subtract them as backgrounds.) An Idea : Special trigger Kp2 but one photon is missed. (2) Event reconstruction Missing photon kinematics (3) Photon inefficiency as a function of its energy and direction ? NOTE : Different type of critical backgrounds. Geometrical dependence : Detector hole, dead material Energy dependence : Photonuclear interaction …
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K+ p+ + “nothing” in E949 (1) K+ p+nn (above Kp2)
Published in PRL, (2004) Charged track momentum from various K decay modes (2) p0 nn (on Kp2 peak) This report. Need tighter photon rejection. (3) K+ p+nn (below Kp2) Analysis ongoing. Require more sophisticated treatment in p+ multiple scatterings.
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Published in PRD as rapid communication
Phys. Rev. D72, (2005)
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Optimized Photon veto parameters
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Performance of the clustering Method
MC sample theta
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p0 gg backgrounds Photon inefficiency 20<Eg[MeV]<225
Low energy g : sampling fluctuation High energy g: photonuclear interaction ( hard to simulate reliably.) Detector photon inefficiency (measured with real data) 20~40MeV 40~60MeV 60~80MeV 80~100MeV 100~120MeV 120~140MeV 140~160MeV
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Phase space correction factors
Polar angle distribution Correction factors Monte Carlo simulation Real data
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