# Presentation: 089285

## MiniBooNEResults worth waiting for

- Heather Ray
- _[hray@fnal.gov](mailto:hray@fnal.gov)_
- Los Alamos National Laboratory

- H. Ray : Pheno 06

- 5/15/06

## Outline

- LSND : MiniBooNE motivation
- MiniBooNE Experiment
- Why we’re waiting to open the box
- Improving the Optical Model
- Improving identification of mis-id 0
- Particle ID Algorithm

- H. Ray : Pheno 06

- 5/15/06

## LSND : The Great Mystery

- 1st accelerator expt to observe  osc signal
- 3.8 excess of anti-e in an anti- beam
- Incongruous with rest of osc results
- Other expt have explored LSND phase space but allowed regions still remain

- H. Ray : Pheno 06

- 5/15/06

## MiniBooNE

- 8 GeV proton beam
-  1.6 s pulse, 5 Hz rate from Booster
-  p + Be  mesons
-  Mesons focused by  magnetic horn
-  Mesons  DIF 
- E ~ 500 MeV

**Primary (protons)**

**Secondary (mesons)**

**Tertiary (neutrinos)**

- 800 Ton, 12 m diameter sphere
- Non-doped mineral oil
- Two regions
- Inner light-tight region, 1280 pmts (10% coverage)
- Optically isolated outer veto-region, 240 pmts

- H. Ray : Pheno 06

- 5/15/06

## Why the Wait?

- The oscillation signal is expected to be small
- Probability for LSND oscillations = 0.264%!
*Need to know backgrounds, detector response very precisely*
- Requires a well-developed, sensitive Particle ID algorithm, exact optical model, solid identification of mis-ID backgrounds

- “Why not borrow the optical model from another mineral-oil based neutrino experiment?”

- H. Ray : Pheno 06

- 5/15/06

## Why the Wait?

- No other  expt uses non-doped mineral oil
- We’re the first to study, model, and simulate  interactions in pure mineral oil
- Scintillator fuzzes out rings, ruins separation
- SNO/Super-K : H20, no fluor/scint, all Cerenkov
- LSND : all scintillation (swamped fluorescence), some Cerenkov
- MB : in the middle, need to untangle various components

- H. Ray : Pheno 06

- 5/15/06

## 1st HurdleThe Optical Model

- H. Ray : Pheno 06

- 5/15/06

## The Optical Model

- Full battery of external measurements to provide complete picture of OM
- Problem! How do you set the relative normalization from one measurement to the other? (ie ratio of fluorescence to scintillation)
- Need internal calibration sources / tank data to provide correlations
- We *do not* tune on any samples which may bias the oscillation analysis

- H. Ray : Pheno 06

- 5/15/06

## External Measurements

- Variety of stand-alone tests which characterize separate components of mineral oil

- H. Ray : Pheno 06

- 5/15/06

## Internal Calibration Sources

- Muon tracker + cubes : provides  and Michel e- of known position and direction in tank, key to understanding E and reconstruction
- Laser flasks (4) : used to measure tube charge, timing response
- Neutral Current Elastic sample : provides neutrino sample, protons below Cerenkov threshold == isolate scintillation components, distinguish from fluorescence of detector

- H. Ray : Pheno 06

- 5/15/06

## The Optical Model Chain

- External Measurements and Laser Calibration

- First Calibration with Michel Data

- Calibration of Scintillation Light with NC Events

- Final Calibration with Michel Data

- Validation with Cosmic Muons,  CCQE, e NuMI, etc.

- H. Ray : Pheno 06

- 5/15/06

## Recent Improvements

-    Improvements to OM greatly improve Michel electron E as a
-                    function of location in our detector

- H. Ray : Pheno 06

- 5/15/06

## Impact of Improved OM

- Scintillation light in 1st gamma in pi0 fitter

- Distance between pi0 vertex and 1st gamma conversion point

- H. Ray : Pheno 06

- 5/15/06

## 2nd HurdleIdentifying Mis-IDs

- H. Ray : Pheno 06

- 5/15/06

## Minimizing Mis-IDs

-  83% of all mis-ID backgrounds come from events with a single 0
- Need sample of pure 0 to measure rate as f(momentum)
- High-P region very impt. to get a handle on high-E e bgd from K+

- H. Ray : Pheno 06

- 5/15/06

## 3rd HurdleParticle ID

- H. Ray : Pheno 06

- 5/15/06

## Sensitivity Estimate

- Good sensitivity requires PID
- Remove  99.9% of  CC interactions
- Remove  99% of all NC 0 producing interactions
- Maintain  30-60% efficiency for e interactions

- LSND best fit sin22 = 0.003 m2 = 1.2 ev2

- H. Ray : Pheno 06

- 5/15/06

## Particle ID Algorithm

- Using a boosted decision tree
- Similar to a neural net, but better
- Needs to be trained on a set of variables
- Want vars which are powerful at distinguishing between signal, background event types
- Have a large list of potential inputs
- Require data & MC shapes to agree for an input to be considered for training
- The more vars with agreement, the larger set of powerful vars we’ll have to draw from, thus providing a more powerful PID algo

- Nuc.Inst.Meth.A 543 (2005) 557-584
- Nuc.Inst.Meth.A 555 (2005) 370-385

- H. Ray : Pheno 06

- 5/15/06

## PID Inputs

- Calibration Sample

- Signal-like Events

- Primary Background

- Mean = 1.80, RMS = 1.47
- Mean = 1.19, RMS = 0.76

- Mean = 20.83, RMS = 25.59
- Mean = 3.48, RMS = 3.17

- Mean = 16.02, RMS = 25.90
- Mean = 3.24, RMS = 2.94

- H. Ray : Pheno 06

- 5/15/06

## Summary

- We are moving forward in leaps and bounds!
- Past 6 months have brought phenomenal improvement in our Optical Model
- Agreement in PID potential inputs vastly improved
- New pion fitter offers better resolution of single 0 events, reductions in mis-id backgrounds
- These improvements are vital to maximizing our sensitivity to LSND
- (Remember, Probability for oscillations = 0.264%)
- We are not done yet.  Improvements are continuing - hope to open box this summer

- H. Ray : Pheno 06

- 5/15/06

## BACKUP INFO

- H. Ray : Pheno 06

- 5/15/06

## NN vs Tree

| The Elements of Statistical Learning, Hastie, Tibshirani, Friedman, Springer (2003) | Neural Nets | Trees |
| --- | --- | --- |
| Natural handling of data of “mixed” type | Bad | Good |
| Handling of missing values | Bad | Good |
| Robustness to outliers in input space | Bad | Good |
| Insensitive to monotonic transformations of inputs | Bad | Good |
| Computational scalability (large N) | Bad | Good |
| Ability to deal with irrelevant inputs | Bad | Good |
| Ability to extract linear combinations of features | Good | Bad |
| Interpretability | Bad | Fair |
| Predictive power | Good | Bad |

- H. Ray : Pheno 06

- 5/15/06

## Decision Trees

- Unstable - large trees have high variance
- Mitigate this by using a collection of trees (boosting)
- Don’t capture additive structure well
- Use sensible choice of input vars

- Good Performance
- Low Bias
- Training is easy, does not depend on minimization procedure
- Immune to effects of outliers
- Resistant to effects of inclusion of irrelevant input vars

**Pros**

**Cons**

- H. Ray : Pheno 06

- 5/15/06

## Why Boost a Tree?

- You can boost anything - tree, neural net, etc.
- Boosting combines weak classifiers to produce a powerful committee
- Classifiers are combined through a weighted majority vote to produce the final output

- H. Ray : Pheno 06

- 5/15/06

## Boosted Trees

- Inherits pros of single trees
- Dramatic performance improvement
- Low bias, low variance
- Less susceptible to overtraining

- More of a black box
- Increases sensitivity to outliers and noisy data

**Cons**

**Pros**

- H. Ray : Pheno 06

- 5/15/06

## Boosted Tree Falsehoods

- Boosted trees are NOT robust against data to MC disagreement
- We must have good data to MC agreement for an input to be used in training
- Boosted tree performance does NOT improved with the number of input variables

- H. Ray : Pheno 06

- 5/15/06

## e from K+
Use High energy e and  to normalize
Use Kaon production data for shape
Need to subtract off misIDs

- e from K+
- Use High energy e and  to normalize
- Use Kaon production data for shape
- Need to subtract off misIDs

- Full data sample ~5.3 x 1020 POT

- High energy e data
- Events below ~1.5 GeV still in closed box (blind analysis)

- Determining Backgrounds with MiniBooNE data

- H. Ray : Pheno 06

- 5/15/06

## Why the Wait?

- We don’t have 2nd detector so we can’t do flux cancellation
- We need to know the neutrino production mechanisms much more precisely than past expts have needed
- Rely on data from external expts : Harp thin target results recently added to MiniBooNE MC (April ‘06)

- H. Ray : Pheno 06

- 5/15/06

## Checking PID with NuMI Events

- Because of the off-axis angle, the beam at MiniBooNE from NuMI is significantly enhanced in es from K+
- Enables a powerful check on the Particle ID

- H. Ray : Pheno 06

- 5/15/06

## Optical Model

- MB is very unique = mineral oil with no scintillator
- Solar nu : Genius = Gd, Moon = liq Ar, Heron = liq He, SNO = heavy H20, Homestake = Cl, Sage = Ga, Ge, Xe, GNO = Ga, Gallex = Ga, SuperK = H20, Borexino = mineral oil + PP0 (doped with a fluor), ICARUS = liq Ar
- Reactor nu : Chooz = mineral oil + Gd, Daya Bay = ???, Diablo Canyon = doped mineral oil, Kaska = ???, Angra = mineral oil + Gd, Palo Verde = ???, Bugey = ???, Gosgen = ???
- SBL Accelerator expts : Nomad = collider detector (drift chamber, etc), Chorus = emulsifying film, KARMEN = liquid scintillator, LSND = mineral oil + bPBD, NuTeV = solid calorimeter, DoNUT = emulsion sheets
- LBL Accelerator expts : T2K = ???, NoVa = liquid scintillator, MINOS = solid detector, K2K = H20, Opera = emulsion sheets

- H. Ray : Pheno 06

- 5/15/06

## Beams

- Nomad = 450 GeV p + Be
- Chorus = 450 GeV p + Be
- Karmen = 800 MeV p + heavy H20
- LSND = 800 MeV p + heavy H20
- NoVa = 120 GeV p +
- DoNUT = 800 GeV p + Tungsten

- H. Ray : Pheno 06

- 5/15/06