logging in or signing up Colour Reconnection CoolDude26 Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 175 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: June 15, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide1: Outline: Outline Motivation Models and predictions Standard variables Particle flow method Results from the Particle Flow Conclusions Colour Reconnection: Colour Reconnection For example: B.R.( B J/ (1S) X ) 1% Probe for hadronization dynamics in space andamp; time ! Colour Reconnection in WW: Colour Reconnection in WW The hadronic products of WW -andgt; 4j can interconnect, since Colour Reconnection : mixes up singlets, creating hadrons which can’t be assigned to either W; at threshold Shifts reconstructed W masses Global effect on multiplicity: Extreme model WW(4q) 2 x W(2q) Effects on MW: Effects on MW Small@Perturbative QCD: O ( 1 MeV) Could be large in non-Pt QCD -O (10 MeV) Models ! Other effects Average Multiplicity Particle distributions …effects enhanced for low-momentum/heavier particles ! Phenomenological models: Sjöstrand andamp; Khoze : Type I: (SK I) flux tubes Probrecon kI Vol. Overlap Type II, II’ : vortex lines reconnection if strings cross Gustafson andamp; Häkkinen : minimizes string length Lönnblad : CR between dipoles, minimizing string length Webber et al. (HERWIG, Cluster model): reconnections allowed if smaller cluster sizes Ellis andamp; Geiger extreme model: also non-singlet reconnections Rathsman new model: area law between string pieces Phenomenological models Predictions ...: SK-I Predictions ... +Predictions...: +Predictions... 189 GeV WW(4q) = 2*W(2q) ?: WW(4q) = 2*W(2q) ? 4 high multiplicity jets, well separated, event balanced, no qq radiative return. 2 jets+1 low mult. and energetic jet, well separated, event unbalanced. DELPHI DELPHI Average Multiplicities: Average Multiplicities (*) not corrected for selection biases and low momentum Momentum Distributions: Momentum Distributions Difference WW-2W +Momentum Distributions: +Momentum Distributions 0.1 andlt; p andlt; 1.0 GeV : n(4q)/(2n(2q)) = 0.981 ± 0.024st ± 0.013sy (DELPHI) Heavy hadrons: Heavy hadrons K+p (0.002andlt; xp andlt; 0.012 ) : ratio = 1.05 ± 0.06st ± 0.05sy (OPAL) K (0.2 andlt; p andlt; 1.25 GeV/c) : ratio = 0.96 ± 0.38st ± 0.08sy (DELPHI) p (0.2 andlt; p andlt; 1.25 GeV/c) : ratio = 0.72 ± 0.57st ± 0.08sy (DELPHI) Oriented Distributions: Oriented Distributions L3 novel approach - The particle flow: If there is Cross-Talk between W systems, we can expect changes in the distributions of particles in those selected regions Very low efficiency L3 novel approach - The particle flow Probe the colour flow in the regions between W’s ? Idea: Select only events with well-defined regions ! CR No effect seen on standard variables! Selection criteria: Selection criteria 2 angles andlt; 100º 2 angles andgt;100º, andlt;140º sets of angles with Basic cuts WW4q 4 Jets no common jets method followed by L3, ALEPH, DELPHI, OPAL as a X-check as a X-check W1 W2 Selection results: Selection results Pairing the W’s: Pairing the W’s Standard W-mass analyses as default: Standard W-mass analyses as default ALEPH (189-208 GeV) - 5487 events selected basic cuts, +neural network with 14 variables WW4q Efficiencies: 92-88%, Purities: 79-76% Pairing efficiencies: 67-72% OPAL (189 GeV) - 699 events selected likelihood selection with 7 kinematic variables WW4q Efficiency: 42%, Purity: 83% Pairing efficiency: 50% The flow method: The flow method For all particles, find out its angle with jet1, projected in the plane (jet1, jet2) Particle flow 1 entry/particle @ 1i Energy flow 1 entry/particle, weighted by p @ 1i The rescaled angle: The rescaled angle Include only particles (i) for which Ji andlt; JK (angle between jets J and K) Divide the angle Ji by JK : = rescaled angle = Ji / JK (for pair (J,K)) Span over planes (1,2), (2,3),(3,4), (4,1) (1,2) (2,3) (3,4) (4,1) No CR SKI-100% No CR The Particle Flow distribution of Ratios: The Particle Flow distribution of Ratios It is plotted: (1/Nev) d([A+B]/[C+D])/d Distribution of Ratios: Distribution of Ratios The Ratio R of integrals: The Ratio R of integrals (*) RDELPHI is the average of Ri rescaled to 196 GeV R values at detector level not comparable sensitivity Systematic studies: Systematic studies In the systematic error, ADLO have included Bose-Einstein effects (ADL) Fragmentation modelling (ADL) Background subtraction and modelling (ADLO) Particle/Objects definition (L) Generators/Tunings (DO) L3 checks the method on semi-leptonic WW’s: The Ratio of the Ratios: The Ratio of the Ratios DELPHI defines andlt;RRandgt; as the average over all energies of the ratio between RDATA and RMC OPAL discrepancies (1 vs 2) are being studied L3, DELPHI see no effect ALEPH is right in the middle =andgt; SKI(100%) too strong Estimation of SKI kI parameter: Estimation of SKI kI parameter ALEPH and L3 translate their results into extraction of the parameter kI of SKI: kI kI RN 0.32 kI andlt; 1.55 @ 68% C.L. kI=3.5, kIandlt; 25@68% C.L. kI conclusions: conclusions After 5 years of very successful LEP runs, 10,000 WW pairs collected/experiment Colour Reconnection not seen in standard variables ( WW(4q) vs WW(2q) ), but low sensitivity Particle Flow results inconclusive, but still very preliminary (2 misses, 1 claim, 1 with problems) ! Systematics still in a VERY early stage of study (explore WW-semileptonics and Z events better) Combination of results from the 4 experiments mandatory to be able to pin down models and model parameters LEPEWWG-WW/FSI You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
Colour Reconnection CoolDude26 Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINT Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 175 Category: Education License: All Rights Reserved Like it (0) Dislike it (0) Added: June 15, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript Slide1: Outline: Outline Motivation Models and predictions Standard variables Particle flow method Results from the Particle Flow Conclusions Colour Reconnection: Colour Reconnection For example: B.R.( B J/ (1S) X ) 1% Probe for hadronization dynamics in space andamp; time ! Colour Reconnection in WW: Colour Reconnection in WW The hadronic products of WW -andgt; 4j can interconnect, since Colour Reconnection : mixes up singlets, creating hadrons which can’t be assigned to either W; at threshold Shifts reconstructed W masses Global effect on multiplicity: Extreme model WW(4q) 2 x W(2q) Effects on MW: Effects on MW Small@Perturbative QCD: O ( 1 MeV) Could be large in non-Pt QCD -O (10 MeV) Models ! Other effects Average Multiplicity Particle distributions …effects enhanced for low-momentum/heavier particles ! Phenomenological models: Sjöstrand andamp; Khoze : Type I: (SK I) flux tubes Probrecon kI Vol. Overlap Type II, II’ : vortex lines reconnection if strings cross Gustafson andamp; Häkkinen : minimizes string length Lönnblad : CR between dipoles, minimizing string length Webber et al. (HERWIG, Cluster model): reconnections allowed if smaller cluster sizes Ellis andamp; Geiger extreme model: also non-singlet reconnections Rathsman new model: area law between string pieces Phenomenological models Predictions ...: SK-I Predictions ... +Predictions...: +Predictions... 189 GeV WW(4q) = 2*W(2q) ?: WW(4q) = 2*W(2q) ? 4 high multiplicity jets, well separated, event balanced, no qq radiative return. 2 jets+1 low mult. and energetic jet, well separated, event unbalanced. DELPHI DELPHI Average Multiplicities: Average Multiplicities (*) not corrected for selection biases and low momentum Momentum Distributions: Momentum Distributions Difference WW-2W +Momentum Distributions: +Momentum Distributions 0.1 andlt; p andlt; 1.0 GeV : n(4q)/(2n(2q)) = 0.981 ± 0.024st ± 0.013sy (DELPHI) Heavy hadrons: Heavy hadrons K+p (0.002andlt; xp andlt; 0.012 ) : ratio = 1.05 ± 0.06st ± 0.05sy (OPAL) K (0.2 andlt; p andlt; 1.25 GeV/c) : ratio = 0.96 ± 0.38st ± 0.08sy (DELPHI) p (0.2 andlt; p andlt; 1.25 GeV/c) : ratio = 0.72 ± 0.57st ± 0.08sy (DELPHI) Oriented Distributions: Oriented Distributions L3 novel approach - The particle flow: If there is Cross-Talk between W systems, we can expect changes in the distributions of particles in those selected regions Very low efficiency L3 novel approach - The particle flow Probe the colour flow in the regions between W’s ? Idea: Select only events with well-defined regions ! CR No effect seen on standard variables! Selection criteria: Selection criteria 2 angles andlt; 100º 2 angles andgt;100º, andlt;140º sets of angles with Basic cuts WW4q 4 Jets no common jets method followed by L3, ALEPH, DELPHI, OPAL as a X-check as a X-check W1 W2 Selection results: Selection results Pairing the W’s: Pairing the W’s Standard W-mass analyses as default: Standard W-mass analyses as default ALEPH (189-208 GeV) - 5487 events selected basic cuts, +neural network with 14 variables WW4q Efficiencies: 92-88%, Purities: 79-76% Pairing efficiencies: 67-72% OPAL (189 GeV) - 699 events selected likelihood selection with 7 kinematic variables WW4q Efficiency: 42%, Purity: 83% Pairing efficiency: 50% The flow method: The flow method For all particles, find out its angle with jet1, projected in the plane (jet1, jet2) Particle flow 1 entry/particle @ 1i Energy flow 1 entry/particle, weighted by p @ 1i The rescaled angle: The rescaled angle Include only particles (i) for which Ji andlt; JK (angle between jets J and K) Divide the angle Ji by JK : = rescaled angle = Ji / JK (for pair (J,K)) Span over planes (1,2), (2,3),(3,4), (4,1) (1,2) (2,3) (3,4) (4,1) No CR SKI-100% No CR The Particle Flow distribution of Ratios: The Particle Flow distribution of Ratios It is plotted: (1/Nev) d([A+B]/[C+D])/d Distribution of Ratios: Distribution of Ratios The Ratio R of integrals: The Ratio R of integrals (*) RDELPHI is the average of Ri rescaled to 196 GeV R values at detector level not comparable sensitivity Systematic studies: Systematic studies In the systematic error, ADLO have included Bose-Einstein effects (ADL) Fragmentation modelling (ADL) Background subtraction and modelling (ADLO) Particle/Objects definition (L) Generators/Tunings (DO) L3 checks the method on semi-leptonic WW’s: The Ratio of the Ratios: The Ratio of the Ratios DELPHI defines andlt;RRandgt; as the average over all energies of the ratio between RDATA and RMC OPAL discrepancies (1 vs 2) are being studied L3, DELPHI see no effect ALEPH is right in the middle =andgt; SKI(100%) too strong Estimation of SKI kI parameter: Estimation of SKI kI parameter ALEPH and L3 translate their results into extraction of the parameter kI of SKI: kI kI RN 0.32 kI andlt; 1.55 @ 68% C.L. kI=3.5, kIandlt; 25@68% C.L. kI conclusions: conclusions After 5 years of very successful LEP runs, 10,000 WW pairs collected/experiment Colour Reconnection not seen in standard variables ( WW(4q) vs WW(2q) ), but low sensitivity Particle Flow results inconclusive, but still very preliminary (2 misses, 1 claim, 1 with problems) ! Systematics still in a VERY early stage of study (explore WW-semileptonics and Z events better) Combination of results from the 4 experiments mandatory to be able to pin down models and model parameters LEPEWWG-WW/FSI