Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 1 Exploring Muon Decay with TWIST Carl A. Gagliardi Texas A&M University for the TWIST Collaboration Outline Physics of muon decay TWIST experiment TWIST results to date How will we do better?

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 2 Muon decay matrix element Most general local, derivative-free, lepton-number conserving muon decay matrix element: In the Standard Model, g V LL = 1, all others are zero Pre-TWIST global fit results (all 90% c.l.): Theoretical constraints have recently been derived on the LR and RL terms from neutrino mass limits (hep-ph/ )

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 3 Muon decay spectrum The energy and angle distributions of positrons following polarized muon decay obey the Michel spectrum: Pre-TWIST accepted values for the Michel parameters: SM  = ± /4  = ± P   = ± ±  = ± ± /4 P  (  /  ) > (90% c.l.) 1 where

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 4 Goal of TWIST Search for new physics that can be revealed by order- of-magnitude improvements in our knowledge of ρ, δ, and P μ ξ Model-independent limit on muon handedness Left-right symmetric models ….. Two examples

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 5 What is required? Must: Understand sources of muon depolarization -- P μ and ξ come as a product Determine spectrum shape -- All three parameters Measure forward-backward asymmetry -- For P μ ξ and δ to within a few parts in 10 4

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 6 Surface muon beam TRIUMF M13 beam line

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 7 TWIST spectrometer

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 8 Typical events Use pattern recognition (in position and time) to sort hits into tracks, then fit to helix Must also recognize beam positrons, delta tracks, backscattering tracks

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF d momentum-angle spectrum Acceptance of the TWIST spectrometer In angular fiducial In momentum fiducial

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 10 Fitting the data distributions Fit data to sum of a MC base spectrum plus MC- generated derivative distributions. Decay distribution is linear in the Michel parameters, so this is exact, no matter what values ( α MC ) are used in the MC base spectrum. α MC hidden  blind analysis

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 11 Physics data sets Fall 2002 –Test data-taking procedures and develop analysis techniques –First physics results – ρ and δ –Graphite-coated Mylar target not suitable for P μ ξ Fall 2004 –Al target and Time Expansion Chamber enabled first P μ ξ measurement –Improved determinations of ρ and δ are underway –Achieve ultimate TWIST precision for ρ, δ, and P μ ξ

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 12 Normalized residuals [(Data-Fit)/sigma] of the 2-d momentum-angle fit Fit describes the data well, even when extrapolated far outside the fiducial region Angle-integrated results Fitting the 2002 data to determine ρ and δ

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 13 Fitting the 2004 data to determine P μ ξ Separating the asymmetry into components

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 14 Results to date From Fall, 2002 run: –ρ = ± (stat) ± (syst) ± ( η ) PRL 94, –δ = ± (stat) ± (syst) PRD 71, New global analysis (PRD 72, ) using the ρ and δ results, together with previous measurements and recent e + transverse polarization measurements (PRL 94, ) : –Significant improvements in the limits for g S,V,T LR –η = ± From Fall, 2004 run (so far): –P μ ξ = ± (stat) ± (syst) PRD 74, Factors of 2-3 improvements on pre-TWIST precisions

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 15 New limits in left-right symmetric models Initial TWIST measurements already provide significant new limits General LRS modelRestricted (“manifest”) LRS model

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 16 Results to date From Fall, 2002 run: –ρ = ± (stat) ± (syst) ± ( η ) PRL 94, –δ = ± (stat) ± (syst) PRD 71, New global analysis (PRD 72, ) using the ρ and δ results, together with previous measurements and recent e + transverse polarization measurements (PRL 94, ) : –Significant improvements in the limits for g S,V,T LR –η = ± From Fall, 2004 run (so far): –P μ ξ = ± (stat) ± (syst) PRD 74, Factors of 2-3 improvements on pre-TWIST precisions

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 17 Systematics in the previous measurements The same effects tend to dominate the systematic uncertainties for all three parameters.

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 18 Reducing the leading systematics Issues that were unique to 2002 data –Stopping target thickness uncertainty –Chamber orientation uncertainty with respect to magnetic field For all three Michel parameters –Chamber response Improved gas system regulation and monitoring Improved determination of foil geometry Improved treatment of drift chamber behavior –Positron interactions Specific to P μ ξ –Muon depolarization when crossing fringe field –Muon depolarization in the stopping target

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 19 Controlling positron interaction uncertainties – “upstream stops” Our Monte Carlo must simulate positron interactions properly Need a well-understood test beam to validate the Monte Carlo We use the Michel spectrum!

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 20 Validating the Monte Carlo with “upstream stops” The TWIST Monte Carlo provides an excellent description of the hard interaction physics Took ~50 times more upstream stop events in 2004 than in 2002 BremsstrahlungScattering (Downstream fit result) – (upstream fit result)

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 21 Muon depolarization across the fringe field Use Time Expansion Chamber (TEC) to measure and optimize the muon beam 2004 muon beam spot First installed for 2004 run Found vertical beam offset – now corrected Now take frequent beam characterizations Have techniques to identify when the beam changes between TEC measurements

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 22 Muon depolarization after stopping Observed significant depolarization in 2004 data New techniques allow us to veto muons that stop outside the metal stopping target More sensitive analysis procedures to determine the residual depolarization rate Now taking data with a Ag target to explore material dependence

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 23 Conclusions The initial TWIST measurements have improved our knowledge of the Michel parameters ρ, δ, and P μ ξ by factors of 2-3 Improvements by additional factors of 3-5 are anticipated Stay tuned!

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 24 TWIST Participants TRIUMF Ryan Bayes ¤y Yuri Davydov Jaap Doornbos Wayne Faszer Makoto Fujiwara David Gill Alex Grossheim Peter Gumplinger Anthony Hillairet ¤y Robert Henderson Jingliang Hu John A. Macdonald x Glen Marshall Dick Mischke Mina Nozar Konstantin Olchanski Art Olin y Robert Openshaw Tracy Porcelli z Jean-Michel Poutissou Renée Poutissou Grant Sheffer Bill Shin zz Alberta Andrei Gaponenko ¤¤ Peter Kitching Robert MacDonald ¤ Maher Quraan Nate Rodning x John Schaapman Glen Stinson British Columbia James Bueno ¤ Mike Hasinoff Blair Jamieson ¤¤ Montréal Pierre Depommier Regina Ted Mathie Roman Tacik Kurchatov Institute Vladimir Selivanov Vladimir Torokhov Texas A&M Carl Gagliardi Jim Musser ¤¤ Bob Tribble Maxim Vasiliev Valparaiso Don Koetke Paul Nord Shirvel Stanislaus ¤ Graduate student ¤¤ Graduated y also U Vic z also Manitoba zz also Saskatchewan x deceased Supported under grants from NSERC (Canada) and DOE (USA). Additional support from TRIUMF, NRC (Canada), and the Russian Ministry of Science. Computing facilities of WestGrid are gratefully acknowledged.

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 25

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 26 Coupling constants and Michel parameters The Michel parameters are bilinear combinations of the coupling constants:

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 27 Detector array 56 low-mass high-precision planar chambers symmetrically placed around thin target foil Measurement initiated by single thin scintillation counter at entrance to detector Beam stop position controlled by variable He/CO 2 gas degrader

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 28 Analysis method Extract energy and angle distributions for data: –Apply (unbiased) cuts on muon variables. –Reject fast decays and backgrounds. –Calibrate e + energy to kinematic end point at MeV. Fit to identically derived distributions from simulation: –GEANT3 geometry contains virtually all detector components. –Simulate chamber response in detail. –Realistic, measured beam profile and divergence. –Extra muon and beam positron contamination included. –Output in digitized format, identical to real data.

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 29 Data set by data set 2-d fit results ρ δ PμξPμξ

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 30 Recent muon decay global analysis Fit also finds η = ± , a factor of ~2 more precise than the previously accepted value, ± Significant improvement in η comes from new measurements of the transverse polarization of the e + in muon decay (PRL 94, ), but the TWIST ρ and δ measurements also play an important part. These improvements arise from the TWIST ρ and δ measurements. PRD 72,

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 31 Validating the soft physics simulation with “upstream stops” Multiple scattering is well reproduced Small differences in dE/dx are seen between data and MC –Exploring differences between GEANT3 and GEANT4 dE/dx Multiple Scattering

Carl Gagliardi – Exploring Muon Decay with TWIST – DPF06 32 Tracking (in)efficiency Measured in upstream stop events Reconstruct track upstream, then ask if downstream also reconstructs Overestimates true inefficiency – not all tracks reach the downstream half Difference between inefficiencies in data and Monte Carlo events