1 / 77

MINOS and NOvA: Himmel, Howcroft, Mualem, Newman, Ochoa, Orchanian, Patterson, Peck, Trevor - PowerPoint PPT Presentation

  • Uploaded on

MINOS and NOvA: Himmel, Howcroft, Mualem, Newman, Ochoa, Orchanian, Patterson, Peck, Trevor. Faculty MINOS  e Analysis; Neutral Current Bg. Anti-Neutrino &  -  Oscillation Analysis Beam systematics (  e and  m ) Veto Shield: Precise Calibration NO  A R&D

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about ' MINOS and NOvA: Himmel, Howcroft, Mualem, Newman, Ochoa, Orchanian, Patterson, Peck, Trevor' - chione

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

MINOS and NOvA:Himmel, Howcroft, Mualem, Newman, Ochoa, Orchanian, Patterson, Peck, Trevor

  • Faculty

  • MINOS e Analysis; Neutral Current Bg.

  • Anti-Neutrino & -Oscillation Analysis

  • Beam systematics (e and m)

  • Veto Shield: Precise Calibration

  • NOA R&D

  • Megaton Water-Scint. Detector R&D

  • Newman, Peck

  • Ochoa, Patterson +undergrad

  • Himmel, Ochoa, Patterson, Orchanian

  • Himmel, Ochoa

  • Ochoa

  • Trevor, Mualem, Himmel, Patterson

  • Trevor, Himmel +undergrad

Neutrino physics at caltech minos goals
Neutrino Physics at Caltech MINOS Goals

Measure nm↔nt flavor oscillations

Precise (Now ~5%) measurement of Dm223

Provide high statistics discrimination against alternatives such as decoherence, n decay, sterile neutrinos, etc.

Search for subdominant nm↔ne oscillations

A shot at measuring q13 (or: improve CHOOZ limit by a good factor of two)

Directly compare atmospheric n vs anti-n oscillations:

MINOS is the first large underground detector with a magnetic field for m+/m-tagging event-by-event

First measurement of charge ratio from cosmic neutrinos.

Use beam anti-for oscillation and BSM physics

+ Reverse Horn Current Running

Minos m ain i njector n eutrino o scillation s earch
MINOSMain Injector Neutrino Oscillation Search

Investigate n and anti-n flavor oscillations using intense, well-understood NuMI beam

Two similar magnetized iron-scintillator calorimeters

Near Detector

980 tons, 1 km from target, 90m deep

Far Detector

5400 tons, 735 km away, 700 m deep

735 km

Veto Shield

Far Detector

N disappearance


pure nμbeam

Monte Carlo

Monte Carlo

Intense Beam
















  • Basic idea is to compare oscillated and unoscillated spectra, using 2 “~identical” Fe-Scint. Tracking Calorimeters

Cross Section & Beam uncertainties cancel to high accuracy between the two Detectors

Minos caltech history and roles
MINOS: Caltech History and Roles


  • Original Detector Concept and Design; Co-Leadership: Doug Michael

  • Led Successful Optical Fiber R&D: ~10 p.e. Per M.I.P; Data Quality Key

  • Half of the scintillator modules were built at Caltech, in Lauritsen Lab


  • Howcroft on MINOS Exec. Committee, paper review committees, DAQ software, MC production and Software Review Committee

  • Central Roles in Atmospheric Neutrino Analysis [CH]

  • neAnalysis: Shower reco., selection, bgd. calculations [PO,CH,AH,HZ]

  • CR Veto Shield: Rigorous Geometry, Time-Calibration, Alignment; Operations [Pedro Ochoa; now the MINOS expert]

  • Proton Intensity R&D [Michael]: Barrier RF Stacking; [HZ]Digital Damping System for the 8 GeV Booster [CH]

    New Ongoing ROLES

  • Lead role inneAnalysis (MCNN);nebackgrounds [PO, RP]

  • Lead role in antineutrino analysis: Dm223, [AH with PO, RP] (CPT Test), beam systematics, other BSM physics (e.g. n – n oscillations)

  • Half of Simulation Production done on the Caltech Farm [LM]

Minos status
MINOS Status

The last four years have been a very exciting time for MINOS

NuMI construction project completed successfully in January 2005

Analyzed ~12kTon-years of Atmospheric, sign-separated data; including before beam; tested charge ratio in neutrino interactions

Have been taking physics beam data since March 2005: We have collected 5 x 1020 protons on target

MINOS and NUMI have been running well: now getting > 6x1018 (Record 7.4x1018) POT per week

Expect to reach 1021 PoT by 2010

MINOS – NUMI RunningNow 5 X 1020 POT

Many thanks to Accelerator Division Colleagues!!

Accelerator shutdown

Accelerator shutdown

Data used in the current disappearance result(3.36E20 POTs)

Beginning of MI “2+9” multibatch slipstacking:Note steady rise in POTs/Week

Minos status physics papers
MINOS Status: Physics Papers

Recently submitted:

Detailed Detector paper to NIM

New Charged Current Neutrino Oscillations to PRL

Sudden Stratospheric Warming to Nature

Lorentz Violation in the Neutrino Sector to PRL

Papers in final stages of preparation:

Neutral Current (Search for sterile neutrinos)

Anticipated papers in the next year:

Electron Neutrino Appearance

Antineutrino Oscillations

Other cosmic ray physics (moon shadow, etc.)

Recent neutrino results
Recent Neutrino Results

The most recent moscillation results, with 3.36x1020 PoTs, just submitted to PRL:

Dm223 = (2.43 ± 0.13) x 10-3 eV2

Physics of anti neutrinos using minos and numi
Physics of Anti-neutrinosUsing MINOS and NUMI

  • Caltech [CH, PO] formed a study group in 2006 to investigate the physics of anti-neutrino’s using MINOS.

  • Physics subjects investigated:

    • Δm223 for anti-neutrinos: CPT violation tests

    • ννTransitions.

    • Obtaining a measurement of the intrinsic beamνe an important background for the θ13 analysis.

  • A great deal of progress in the last year, led by Ochoa, Himmel and Patterson

Antineutrino Reach

  • Approx. 6% of our beam is made of muon antineutrinos.

  • MINOS could distinguish between m223 and m223 at 90% C.L. if m223> 0.004 eV2 with currently available data.

  • But if CPT conserved, we could only set an upper limit on m223

  • If neutrinos were transitioning to anti-neutrinos 30% of the time, we would see a 3 σ difference from the no transitions hypothesis.

Current combined

world upper limit

Preliminary MC

Preliminary MC

Caltech Roles in Antineutrinos

  • Caltech has central roles in the antineutrino analysis

    • Founded the MINOS antineutrino group [CH, PO; AH]

    • Solely responsible for the → transitions analysis

    • Primarily responsible for the downstream production systematics– a unique systematic for antineutrinos

    • Significant support roles for the whole antineutrino analysis – maintain common files and code

  • Caltech authored a proposal to run in antineutrino-focusing mode (with “reversed horn current”).

    • Even a relatively modest amount of running in this mode would allow the us to makethe world’s best measurement of antineutrino oscillations.

Antineutrino Systematics

  • ~30% of antineutrinos produced outside of the target region and create a large fraction of the difference between the response of the near and far detectors.

  • For safety reasons, helium replaced the Decay Pipe vacuum – selectively enhances Decay Pipe production.

  • By looking at the change when Helium was added, we can measure the uncertainty for downstream production.

  • For a more long term solution, we are working on improvements to the beam Monte Carlo.


Antineutrino Running

  • The difficulties summarized above can be overcome with a small amount of reversed horn current running (RHC).

  • In this case negative particles from the target are focused, thus yielding an antineutrino beam:

1x1020 POT

1x1020 POT

Reversed horn current (RHC)

Forward horn current (FHC)‏

Peak reduction due primarily to cross-section difference ()‏

Relatively very few antineutrinos in neutrino beam in the region most relevant to oscillations

2005 global fit

(Strumia and Vissani)‏

90% C.L. with 6 monthsMINOS reversed mode

Antineutrino Running

  • In past year: modernized analysis code, improved cut efficiencies, studied syst. errors, probed world reach

  • One year MINOS RHC run beats by a factor of two the most optimistic possible2010 world knowledge of Δm2

  • A Caltech effort – and now a key part of MINOS 2010+ plan

~6 month run

8X Error Reduction

Sensitivity Per

Interaction is Similar

ne Appearance

  • At MINOS’ baseline of 735 km,

  • MINOS could make the first measurement of a non-zeroq13by looking for neappearance in the Far Detector

  • If there is no discovery MINOS will improve the current limit set by CHOOZ by a factor of ~two

  • Main challenge in MINOS is distinguishing between EM and hadronic showers.

  • Measurement rests on two pillars:

    • Optimal separation of ne’s from the backgrounds

    • Precise determination of those backgrounds.

ne Appearance Analysis at Caltech

  • Critical role played by Caltech group in both of these areas:

  • Methods to measure the hadronic and intrinsic beam nebackgrounds were developed in previous years (see backup):

  • Muon removed (“MRCC”) samples are now in wide use throughout the collaboration (not just the ne group).

  • An estimate of the beam ne rate in the ND detector was obtained from the measured anti-neutrino rate.

Beam ne rate = 1.57 ± 0.37(stat) ± 0.41 (syst) times the tuned MC expectation

  • Over the last year we completed the implementation of a novel ne selection method that exhibits the highest sensitivity to q13 (following slides)

The Monte Carlo Nearest Neighbors (MCNN) Selection [PO, CH]

  • For analysis need to have an optimal neselection to maximize the significance of the signal, while controlling systematics.

  • Most available selections use multivariate techniques that rely on reconstructed quantities.

  • But this analysis is a special case:

Number of reco variables ~ number of strips in event

  • Why not perform event ID using strip information alone?

  • We have developed a “nearest neighbors” selection in collaboration with Cambridge University.

  • Basic idea:

  • Compare each event in the data to large libraries of simulated ne CC and NC events.

  • Select N best pattern-matches

  • Construct a discriminant from N best-matches information (e.g. fracCC=fraction of N best matches which are ne CC)

The MCNN Selection

  • Determine how well two events match by asking:

Charge (PE)

Strip #

“what is probability the two events come from same hit pattern at PMTs?”

  • Good match

Original ne CC event


plane #

Bad match

  • Advantages:

  • Approach is in principle optimal. No loss of information from raw → reconstructed quantities

  • Largely reconstruction-free.

  • Computation-Intensive: Must fully sample phase space for optimal results

  • A 50 million event library was generated at the Caltech farm.

  • Much work [PO, RP] has gone into making code as fast as possible. Current version is about 70 times faster than the original !

Performance of the MCNN

  • A “MCNN pid” is constructed from the 50 best matches information.

  • The MCNN selection provides ~15% better sensitivity to sin2(2q13) than the next best ne selection (ANN):

  • MCNN also gives a > twice the signal to background ratio:

Towards a First ne Result

  • We are working towards a first q13 result with 3.25x1020 POT

  • Many systematic studies done at Caltech for all selection methods:

    • Effects of imperfect hadronic shower simulation and cross-talk on the Near-Far extrapolation

    • Cut optimization and data quality

  • Example: We used events simulated with a different shower model as fake data, and applied the standard analysis to study the effect on the number of events predicted in the Far Detector

Biases (last column) are only ~ a few percent for all methods !

Well within our systematic error estimates

  • We expect to complete the analysis in ~6 months

Caltech in no n a
Caltech in NOnA

  • Sensitive to Sin2 2q13 down to ~0.01 (~15X better than the current limit); possibly resolve the mass hierarchy

  • D. Michael had a founding role; led design & development

  • CD2 Nearing Completion; Next is CD3A (Start of Construction)

  • Caltech involvement ramped up successfully in 2005-7;substantially strengthened since 2007 by arrival of Leon Mualem

    • LM on the Executive Committee, Technical Board, and Level 2 Manager for Electronics & DAQ

  • Caltech now has the central R&D role, covering the key measurements that set the design & construction: light output, fibers, extrusions, mineral oil[J. Trevor, L. Mualem]

    • Our experience with MINOS development and fabrication (Trevor, Mualem) is proving to be invaluable

  • Arrival of Tolman Fellow Patterson in 2007 will substantially strengthen our effort on NOnA, as well as MINOS

The no n a detector
The NOnA Detector

~62 m

  • ~15 kT total mass, off axis

  • “Totally Active” granular liquid scintillator design

  • Outstanding ne patternrecognition & measurement

15.4 m


No n a tasks at caltech
NOnA Tasks at Caltech

  • Hardware

    • Electronics/DAQ Management

    • APD Testing

    • PVC Testing

    • Fiber Testing

    • Vertical Slice Tests—Critical Performance measurement for CD3A

  • Software

    • Initial Framework Development

    • Subshower Package Adapted from MINOS

    • Photon Transport simulation

    • Supernova Sensitivity

    • APD/Electronics Response Simulation

0.7mm WLS Fiber

One Cell

Caltech Initiated or Responsible for Many Key Aspects of NOnA

Vertical slice results
Vertical Slice Results


  • Now using prototypeAPD and Front-End Board for readout

    • Functionally equivalent to final design components

  • Several months of data taking have yielded excellent results, testing several cells at once

  • Average light Yield: 35 pe/muonfor 300ppm dye concentration

  • Expectation was 25pe:

    • Exceeded expectations

Electronics response simulation readout filter optimization toolkit
Electronics Response Simulation:Readout Filter Optimization (Toolkit)


Input – (black) It includes signals at 50,60, and 150 clock ticks

Output – (red) The output of the shaper, determined by rise-time and fall time. This also has Gaussian distributed amplifier noise added.

DCSOut – (blue) A simple Dual-Correlated Sample filter picks out signals at 50,60, possibly 150, depending on threshold.

Convolution – (Magenta) A more advanced filter; convoluting perfect signal with an interpolated output signal. Useful for precise timing when signals are isolated, but doesn’t resolve double pulses well.

Optimal Filter: in ~1 Year

Adr grant prototyping next generation megaton scale neutrino detectors

WLS Fibers


(A 1 m cube)

ADR Grant: Prototyping Next-Generation Megaton-Scale Neutrino Detectors

  • ADR grant: covered technician salary (part time) and equipment

    • Focus on further development of water/plastic scintillator systems

    • Aims: high light output; low cost per kiloton (projected savings: 80 - 90%

  • Sol’n: 1 cubic meter tank detector 

  • Scintillator strands replaced granules of earlier design

    • Easier to get high quality scintillator, no circulation system required

    • More realistic configuration for larger detectors, but more difficult to construct

  • Construction complete in mid-2007 Promising preliminary results

1 Meter CubePrototype

Scintillator Strands

Successful initial results oulook
Successful Initial Results; Oulook

This is a promising new technology

More R&D is necessary to optimize the design and construction techniques

We plan to apply for further ADR funding

A paper is in the works

  • Construction is complete

  • Initial results showlight that the output is essentially the same as MINOS:

    6 pe/cm of scintillator


Minos no n a group budget request
MINOS/NOnA GroupBudget Request

Faculty (HN, Peck), Research Scientist (Leon Mualem), Tolman Fellow (Ryan Patterson), 3 Grad. Students (Himmel, Ochoa, Orchanian), Technician (Trevor)

  • Doug Michael tragically passed away in 2005

    • ~$ 130k cut from MINOS Budget in 2007-2008

  • Barish and Peck are Emeritus, Zheng and Howcroft left

  • New in 2007: Research Scientist L. Mualem, Tolman Fellow R. Patterson (50% on Grant), Grad Student M. Orchanian

  • Although smaller, the group remains strong: Caltech has established crucial, central roles in both MINOS operations and physics, and NOnA R&D and construction

  • We request the minimum needed: $ 564k for FY2009 on the DOE Grant [This is + $ 27k from FY08; Still ~$ 100k Less than FY06]

  • Minos no n a group payoff
    MINOS/NOnA Group Payoff

    MINOS and NOnA Leading Contributions


    Antineutrino Oscillation Analysis and RHC Run

    ne Optimized Analysis for 1  3 Oscillations

    n - n Transition Analysis

    CC Analysis for Neutrino 2  3 Oscillations


    Key Detector Design and Development Studies

    Leadership of Electronics and DAQ

    Vertical Slice Test, Leading in to CD3A

    Analysis for More Sensitive Tests of 13



    without fit signif. cut

    with fit signif. cut

    The Antineutrino-PID Method [Ochoa]

    • For each event, calculate the product of probabilities that event comes from the nu or nubar distributions

    The nubar-PID parameter is given by:

    • Observe very clear separation: Very high purity with good efficiency


    Increase NuBar-PID cut

    Fit significance cut:


    Note: Efficiency measured w.r.t. all true CC antineutrinos

    Antineutrino physics

    • Very interesting physics can be done with antineutrinos:

    1)noscillation analysis: A large CPT-violating region still unexplored

    90%, 95%, 99% and 3σ CPT violating regions still allowed by global fit (except LSND)

    M.C. Gonzalez-Garcia, M. Maltoni and T. Schwetz (hep-ph/0306226)

    2)n→n transitions: have never been looked for beforein atmos sector.

    • Some models beyond the SM predict them (i.e. Langacker and Wang, Phys. Rev. D 58 093004).

    • Could fully explain the atmospheric neutrino results (Alexeyev and Volkova, hep ex/0504282)

    3) Measurement ofBeam ne’s: important for ne analysis

    • Very strong involvement of Caltech group in these areas.




    with SK parameters


    E (GeV)




    Antineutrinos in MINOS

    • Approx. 6% of our beam is made of muon antineutrinos.

    Amplified spectrum


    1x1020 POT

    Difficulty: not many events in osc. peak region

    Difficulty: not many events in osc. peak region

    • Unique advantage: both MINOS detectors are magnetized.

      Allows us toseparate neutrinos and antineutrinos on an event-by-event basis.


    Beam systematics

    Old Monte Carlo

    New Monte Carlo


    Geant 4 Geometry

    Geant 3 Geometry


    Fluka Geometry

    Geant-Fluka Physics

    Geant 4 Physics

    Fluka Physics

    • Working to update the beam Monte Carlo from Geant3 to Geant4.

    • Use Flugg to run the new geometry in Fluka, a more trusted physics simulation

    Rate Comparison, FHC & RHC

    RHC anti-neutrino andFHC neutrino osc.measurements differ

    primarily in event rate.

    2.9X more events/proton in

    FHC/ mode (below 6 GeV)

    • Rate differences come from : (FHC/advantage in parentheses)‏

      • N CC cross section (+100%)‏

      • n/p ratio in detector (+15%)‏

      • π+ versus π- production in the target (+30% near energy peak)‏

      • CC efficiency (-5% near energy peak)‏

    Reversed Horn Current Mode Sensitivity

    • Left: FHC/ and RHC/ sensitivities for same exposures (stat only)

    • Right: Same number of events below 6 GeV (i.e. 2.9 Times more RHC than FHC exposure)

    • Rate is indeed the primary difference


    Antineutrino Oscillation

    World Reach

    • Red = MINOS reversed-mode oscillation sensitivity

    • Black = Combined post-FY2010 sensitivity from MINOS atm. (most exposure scaling) MINOS FHC anti-neutrino sample Super-K, with either...

    Situation assuming SK isalready systematics limited

    ...current published Super-K

    ...sqrt(N) Super-K scaling

    Backup slides on minos n e appearance analysis
    Backup Slides on MINOS ne Appearance Analysis

    Muon Removal Method

    • Use Muon Removal (MR) to assess the hadronic backgrounds:

    • Apply muon removal (MR) to both data and MC

    • Apply ne selection on both.

    • Use differences in both samples to reweight the NC expectation in the ne analysis.

    # of ne candidates in MR data

    # of NC events in ne analysis

    ND data

    before MR

    after MR

    (NN selected events)

    # of ne candidates that are NC in MC

    # of ne candidates in MR MC

    • MR reweighting removed the ~60% overall normalization discrepancy

    Beam ne’s from antineutrinos

    • Irreducible background in ne analysis: intrinsic beam ne‘s

    Nearly all come from m+→ e+ + ne + nm

    • Need to tag antineutrinos coming from m+ decay. Use fact that antineutrino spectrum is practically the same independently of the beam configuration:

    Most antineutrino parents just go through the center of both horns

    pseudo-high energy (pHE)

    pseudo-medium energy (pME)

    Low energy (LE)




    • Work led by Caltech, in collaboration with BNL

    n from m+


    Beam ne’s from antineutrinos

    • Only m+ component changes significantly when running in pME or pHE !

    The Technique:

    (pME-LE)TRUE at 1e18 POT

    • Scale pME (or pHE) and LE data to same POT and take the difference

    • Fit with using shapes from the MC:


    Corrections due to differences in the antineutrinos from p- and K-


    • Preliminary result obtained with 1.6x1019 POT of pHE data:

    Beam ne rate = 1.57 ± 0.37(stat) ± 0.41 (syst) times the tuned MC expectation

    The MCNN PID

    • A “MCNN PID” is constructed from the best 50 matches information:

    • 1) fracCC = fraction of best 50 matches that were e CC with y<0.9

    • 2) mean frac. Q matched = mean fractional charge matched of ne CC matches with y<0.9 (among first 50)

    • 3) ymean = mean y of e CC matches with y<0.9 (among first 50)

    • Using:

    • Variables are combined by an energy binned likelihood (0.5 GeV bin width):

    • The MCNN PID in the ND:


    Cut Optimization

    • The cut optimization of all methods was done at Caltech.

    • 4 different “Figures of Merit (FOM)” were used and compared:











    Near detector data stability

    • Caltech investigated the impact of detector drift on the e analysis

    • e analysis affected little by drifts in light output, etc.

    • Rate of preselected e candidates shown below

    ~2% step across shutdown (due to target position) is handled by the systematic errors

    Imperfect shower modeling

    • We know of something for sure the hadronic simulation of showers is imperfect in the MC.

    • How does the hadronic shower modeling feed into the Far/Near differences?

    • Took simulation with a different hadronic model as fake data and ran the analysis using the standard MC.






    Obtained biases are only in the order of a few percent for all methods.

    → Well within our systematic error estimations.

    Milestones for the neMeasurement

    • We managed to use the same FD library of events for the ND:

    • Use a correction factor obtained from muon tracks to scale the ND light level to match the FD.

    Charge deposited by muons (after correction)

    In the ND light is only read out from the west end



    • Studies show that the FD background prediction is very insensitive to this correction.

    • Structured the code so that it can be run at machines with 2GB of memory:

    • Storing information of 200 best matches for ~60,000 events !

    • Processed all files offline at the Caltech farm.

    • MCNN output is now injected back into the collaboration-wide event samples, for use by the entirenegroup

    Overview of detector r d
    Overview of Detector R&D


    Perform light output tests to understand the components of the scintillator system [Ongoing]

    PVC extrusions, liquid scintillator, WLS fiber

    Verification of scintillator system performance using a NOnA APD [Ongoing]

    Photon production and transport Monte Carlo [Ongoing]

    Tests and Optimization of the ElectronicReadout [Ongoing]

    Personnel – Jason Trevor, Leon Mualem + undergraduate

    No n a scintillator system
    NOnA Scintillator System

    Each cell an extruded TiO2 loaded PVC tube with ID 60mm x 39mm x 15.7m long

    Cells are filled with mineral oil scintillator which is read out at one end with a U-loop WLS fiber running to a multi-pixel APD

    Kuraray 0.7 mm WLS Fiber

    Light output requirement determined by achievable noise on the APD amplifier.The current estimate of minimum required Light Output is ~20-25 photoelectrons

    0.7mm WLS Fiber

    • R&D at Caltech

    • Composition of the PVC cell walls

    • Liquid scintillator composition

    • Fiber diameter and dye concentration

    • Fiber position

    • Integration testing

    One Cell

    No n a apd photodetector
    NOnA APD Photodetector

    • Si Avalanche Photodiode

      • Custom design to match two-fiber aspect ratio

      • Bare die mounted to PCB via gold bump thermo-compression

    No n a test setup
    NOnA Test Setup

    Increased trigger sizes.More than triple the rate, no effect on precision.

    Testing apparatus is otherwise unchanged

    Increased throughput of system; limited by sample preparation time,instead of trigger rate.


    Scintillating strip

    Actual NOnA Cell

    1.2mm Clear Fiber


    M16 PMT Box

    No n a extrusion tests
    NOnA Extrusion tests

    No n a extrusion results
    NOnA Extrusion Results

    Tests of recent extrusions show high and consistent light output compared to previous recipes.

    Recent extrusions have also extruded well mechanically.This is CRITICAL to integrity of the detector:

    — the PVC is the structure

    Background and supernova sensitivity studies lm
    Background and Supernova Sensitivity Studies [LM]

    NOnA is a search for a small signal

    Understanding and correctly modeling the background is important

    Work at Minnesota demonstrated the need for an overburden

    This work also showed potential for Supernova detection with the overburden

    New framework is nearly in place to simulate the backgrounds properly, and to determine Supernova signal sensitivity

    Find the superno n a
    Find the SuperNOnA

    ~15min of data

    With typical ~10s

    supernova signal

    100ms time bins


    No n a software analysis
    NOnA Software / Analysis

    Created the Framework used for NOnA software development and TDR analysis

    This base now being expanded to add features

    Created the Subshower analysis package for MINOS, ported to NOvA framework

    Showing promising results by [email protected]

    Needs to be carried through to a complete analysis

    Created Photon propagation code

    Generally useful for understanding light collection and detector performance

    Validation with actual test data continues

    No n a software at caltech
    NOnA Software at Caltech

    We developed a set of lightweight libraries (“SoCal”)to allow people to access NOnA data and information in C++/ROOT. This has now been further developed into a full-fledged framework.

    SoCal consisted of:

    Data format for NOνA

    NOvA geometry and electronics connection map

    Event display package

    Detector & Electronics response simulation tools

    Full (and up to date) documentation.

    Tools to help people write further packages.

    Used by the collaboration to develop reconstruction and analysis used for TDR and foundation of new framework


    Caius Howcroft

    No n a photon propagation detector simulation
    NOnA Photon Propagation Detector Simulation

    Detector simulation code that models the light output of the scintillator, the collection of WLS fiber and the propagation to the APD, “PhotonTransporter”

    Tracks individual photons and correctly deals with wavelength dependent absorption, reflection and emission coefficients.

    Has been used to understand results from the Caltech test-stand and in production MC.

    Accurately reproduces features of measured light collection in a cell

    Charged Particle

    WLS Fibers


    Caius Howcroft

    Simulated Cell

    Proof of principle
    Proof of Principle

    19cm x 19cm x 13cm

    Constructed using left-over MINOS scintillator + WLS Fiber

    Water and scintillator granules were circulated by small pumps

    Light output in this prototype was lower than the nominal goal for a practical large detector, but

    The scintillator was of poor quality

    The prototype was too small… losses were still dominated by absorption in the walls

    Solution: Scale up volume by a factor of 200


    Completed 1m 3 detector
    Completed 1m3 Detector


    Readout topology
    Readout Topology

    Tank is divided into eight regions

    All WLS fibers from a given region are routed to one of eight phototube boxes

    Muon triggers are centered over the inner four regions

    Inner regions are 30cm x 30cm

    Muon Triggers are 18cm x 18cm









    1 Meter


    1m 3 prototype preliminary analysis
    1m3 Prototype Preliminary Analysis










    Ryan patterson
    Ryan Patterson

    • MINOS

      • Joined Caltech as a Richard C. Tolman Fellow in September 2007

      • Central involvement in the e analysis (including critical work onPID, near/far systematics, code infrastructure)‏

      • Advanced Caltech's reversed horn current studies; has brought the ideas to full proposal form (now part of MINOS long-range plan)‏

      • Has taken lead in tackling the MINOS computing bottleneck

    • NOA

      • Brings event simulation and reconstruction expertise to Caltech's NOA efforts

    Leon mualem
    Leon Mualem


    Leading role in Data Acquisition system, readout electronics, and Avalanche Photodiode detectors

    Responsible for critical measurements of detector performance underway at Caltech

    R&D on optimization of APD and electronics operational parameters

    Simulation of detector sensitivity to supernova neutrinos

    Simulation of cosmic ray backgrounds to nue appearance and supernova detection


    Construction expert, working on publication of detector construction and performance paper

    Coordinates production of half of all required MINOS Monte-Carlo simulation on Caltech farm

    Juan pedro ochoa
    Juan “Pedro” Ochoa


    Responsible for the Veto Shield:modeling, reconstruction, precise calibration; operations

    Anti-neutrino physics:

    Developed particle identifier (PID) for n selection

    Studied potential for neutrino-antineutrino transitions

    Study of sensitivity to n oscillations in normal and reversed horn current running modes.

    neAppearance (Thesis Subject):

    Measured beam ne’s using antineutrinos from m-decay

    Developed Monte Carlo Nearest Neighbor (MCNN) method to optimally select ne charged current events

    Systematic studies for ne analysis

    Batch production of files of interest to the ne group on the Caltech farm.

    The MINOS Veto Shield [Ochoa]

    Veto Shield Timing:

    • Single hit resolution remains at 4.2ns.

    • All data periods are now covered.

      Veto Shield Maintenance and Operation:

    • Calculate efficiencies on plank by plank basis.

    • Useful for locating bad cables, light leaks and dead channels.

    Bad cable !

    (now fixed)

    Atmospheric neutrino studies using the veto shield ochoa
    Atmospheric Neutrino Studies: Using the Veto Shield (Ochoa)

    Caltech has been looking at ways to improve the current atmospheric neutrino selection

    Upward going events carry a lot of information about oscillations; as is evident from the latest analysis

    Current upward going selection is based on hit-timing along the track

    Additional information can come from timing of veto shield hits, improving the 1/bresol’n, and reducing the background in the upward going event sample.

    Ochoa’s precise veto shield time-calibration a key step

    Veto shield hit

    Gradient = 1/particle velocity


    Hits along track

    distance along track

    Alex himmel
    Alex Himmel


    A Lead role in the Antineutrino group

    Solely responsible for the antineutrino transition analysis

    Helped write the extrapolation software framework

    Help to maintain common resources: code base, files, etc.

    Various short-term tasks: writing fake data code, validating special monte carlo runs, etc.

    Work in the Beam Systematics Group

    The effects of added Helium in the beamline

    Downstream antineutrino production systematic

    Updating the beamline Monte Carlo

    ADR Megaton-Scale Prototype Detector Data Analysis

    Jason trevor
    Jason Trevor

    • NOnA detector R&D [with Leon Mualem]

      • Testing of the various NOnA -type extrusions in order to establish a relationship between light yield and the reflectivity of the extrusion cell walls.

      • Measurement of of WLS fiber characteristics. In particular we are looking at the relationship between dye concentration and attenuation length.

      • Perform light yield measurements for a minimum ionizing muon passing through a baseline NOνA cell near the U-bend in a full length (~33m) WLS fiber loop.

    • Prototyping Next-Generation Megaton Detectors

      • Design, construction and testing of a hybrid water/plastic scintillator detector prototype.

    Caius howcroft to 2007
    Caius Howcroft (to 2007)

    • MINOS

      • Central involvement in the group looking for neappearance in the nμbeam. In particular the modeling of Neutral Current backgrounds

      • Atmospheric neutrinos - using the MINOS far detector to test CPT invariance for neutrinos

      • Antineutrinos - Looking for appearance in the beam and research into future anti-neutrino running

      • Central role in the running of the experiment: MINOS Ex-com, Publications committee and speakers committee

    • NOnAused results of in-house NOnA scintillator R&D to create a Monte Carlo simulation of light output in the completed NOnA detectors

    Old: Atmospheric “cosmic” neutrino+antineutrino results

    Caltech (Howcroft) had a central role in the first MINOS physics publication.

    Proton intensity and barrier rf stacking r d zheng to 2006
    Proton Intensity and Barrier RF Stacking R&D [Zheng; to 2006]

    • Doug Michael originated and leads the conceptual development of the FNAL proton intensity program

    • Part of Caltech's involvement, in collaboration with Fermilab Beam Division, is Barrier RF Stacking (an alternative to slip stacking)

      • Utilizes HV pulses as barriers to stack & squeeze the beam

      • Two schemes are being studied: on-momentum injection and off-momentum injection

    • Barrier RF Stacking on-momentum injection study has made a lot of progress over the year

      • Successfully stacked two Booster batches and reached 8.3e12 at 120 GeV (60% Increase)

    • Barrier RF Stacking off-momentum injection study demonstrates stacking is possible even with one barrier

      • Hardware system for 2nd barrier has been assembled and will be installed

    • One of several Proton Intensity projects involving Caltech

    Shower reconstruction and n e analysis hz ch to 2007
    Shower Reconstruction 2006]and neAnalysis [HZ, CH; to 2007]

    • The Caltech 3D Shower and Subshower packages for ne event ID and reconstruction have become the standard for MINOS.

    • Based on PH distributions in 2D, SubShowers are formed and ID’ed, then combined into 3D showers

    • nediscriminantsdeveloped at Caltech, with Cambridge, provide improved performance

    • New technique to optimize the ne ID capability using full event-by-event shower pattern matching against neevent templates, has been developed and isnow being successfully applied [CH, PO]

    No n a software r d at caltech ch hz to 2007
    NO 2006]nA Software R&D at Caltech [CH, HZ; to 2007]

    • Our group built the first software framework, and participated in the development of NOnA detector simulation & event reconstruction software

      • Photon production and propagation simulation software based on detector R&D measurements done locally

      • Patterson will work with Howcroft to continue these efforts

    Initial Simulations at Caltech(Howcroft, Zheng), building on MINOS ne reconstruction work, showed remarkable pattern recognition capability