SLIDE 1
The COMET experiment
COMET Dubouchet M. 2
The COMET Experiment Status and Prospects Matthias Dubouchet High - - PowerPoint PPT Presentation
The COMET Experiment Status and Prospects Matthias Dubouchet High - - PowerPoint PPT Presentation
The COMET Experiment Status and Prospects Matthias Dubouchet High Energy Physics Group Imperial College London February 26, 2019 The COMET experiment COMET Dubouchet M. 2 Source: Google Source: AAPPS The COMET experiment COMET
SLIDE 2
SLIDE 3
The COMET experiment
COMET Dubouchet M. 3
Source: Google Source: AAPPS
SLIDE 4
Muon-to-electron conversion
Muon-to-electron conversion: µ− + N(A, Z) → e− + N(A, Z)
- Individual lepton fmavours are not conserved, which
contradicts Standard Model.
- Mono-energetic electron → very clean signal, very low
background.
- Observing a single event would be evidence of more BSM
physics.
COMET Dubouchet M. 4
SLIDE 5
COMET: objectives
- Measure, or set a limit on, the rate of µ–e conversion:
µ− + N(A, Z) → e− + N(A, Z).
- End goal: improve current limit on µ–e conversion by a
factor of at least 104 compared to current limit.
COMET Dubouchet M. 5
SLIDE 6
COMET: full layout
COMET Dubouchet M. 6
Source: COMET TDR
SLIDE 7
Timeline
Key dates:
- May 2019: beam campaign with Phase-I Cylindrical Drift
Chamber at Kyoto University’s Reactor Research Centre.
- Late 2019: Phase-I is being brought online, through
calibration and cosmic background measurements.
- Early 2020: proton beam from Main Ring is delivered.
Beam diagnostics, more calibration, followed by fjrst data-taking and analysis. After 150 days of data-taking, expect sensitivity increase by a factor of 100.
- Mid-2020s: Phase-II deployed and running, expected to
yield another factor 100 or more on the sensitivity.
COMET Dubouchet M. 7
SLIDE 8
State-of-the-art studies at Imperial
Ewen Gillies: Cylindrical Drift Chamber Hit Filter Combine Hough transform with Gradient Boosted Decision Tree classifjer to automate track identifjcation. Allows us to push the intensity by fjltering out undesired hits.
COMET Dubouchet M. 8
Source: Ewen’s thesis
SLIDE 9
State-of-the-art studies at Imperial
Siyuan Yan: Optimising the stopping target geometry Generate new geometries and use genetic algorithms to automatically select the best one. Optimisation problem between the number of muons captured by the aluminium target and the total target mass.
COMET Dubouchet M. 9
SLIDE 10
The next step
Ideas for future research:
- Picking up on Ewen’s work: can we use the third
dimension to improve classifjcation?
- Can we parallelise the classifjcation process and use
FPGAs for online hit fjltering?
- High level analysis framework needs to be chosen and
implemented this year.
- Can we use modern machine learning, e.g. (convolutional)
neural networks, for track identifjcation and other purposes?
COMET Dubouchet M. 10
SLIDE 11
Conclusion
There are still many ways in which COMET can be pushed to achieve the best sensitivity. With Ewen leading the way with his machine learning application, many more possibilities are now open.
COMET Dubouchet M. 11
SLIDE 12
Conclusion
There are still many ways in which COMET can be pushed to achieve the best sensitivity. With Ewen leading the way with his machine learning application, many more possibilities are now open.
Thank you!
COMET Dubouchet M. 12
SLIDE 13
State-of-the-art studies at Imperial
Hit fjlter performance evaluation
COMET Dubouchet M. 13