|
|
|
|
|
| Sun | Mon | Tue |
Wed | Thu | Fri |
Sat |
| |
1 |
| 2 |
3 |
4 |
5 |
6 |
7 |
8 |
| 9 |
10 |
11 |
12 |
13 |
14 |
15 |
| 16 |
17 |
18 |
19 |
20 |
21 |
22 |
| 23 |
24 |
25 |
26 |
27 |
28 |
29 |
| 30 |
31 |
|
|
|
|
|
Organized by: Prof. Lu Lu
Events During the Week of
January 30th through February 6th, 2022
- No events scheduled
- No events scheduled
- No events scheduled
- Recent Results from MicroBooNE Addressing the MiniBooNE Anomaly Using Deep-Learning-Based Reconstruction
- Time: 2:30 pm
- Place: Chamberlin 4274 (or
- Speaker: Lauren Yates, Fermilab
- Abstract: The MicroBooNE experiment uses a liquid argon time projection chamber (LArTPC) located on-axis in the Booster Neutrino Beam at Fermilab to perform a wide variety of physics measurements. Recently, MicroBooNE released its first results addressing the nature of the anomalous excess of low-energy interactions previously observed by the MiniBooNE collaboration. This seminar will focus on an approach that isolates electron neutrino interactions consistent with the kinematics of charged-current quasi-elastic (CCQE) events. The topology of such signal events has a final state with one electron and one proton (1e1p). Multiple novel techniques are employed to identify a 1e1p final state, including particle identification that uses two methods of deep-learning-based LArTPC image analysis and event selection using a boosted decision-tree ensemble trained to recognize two-body scattering kinematics.
- Host: Lu Lu
- Add this event to your calendar
- No events scheduled
