MICROBOONE PHYSICS

Ben Carls Fermilab Outline

• The detector and beam —MicroBooNE TPC —Booster and NuMI beams at Fermilab • Oscillation physics —Shed light on the MiniBooNE low energy excess • Low energy neutrino cross sections • Non-accelerator topics —Supernova neutrino detection —Proton decay backgrounds

MicroBooNE Physics B. Carls, Fermilab 2 MicroBooNE Detector

• 60 ton fiducial volume (of 170 tons total) liquid Argon TPC • TPC consists of 3 planes of wires; vertical Y, ±60° from Y for U and V • Array of 32 PMTs sit behind TPC wires • Purification system capable of achieving < 100 ppt O2 and < 1 ppm N2 • Ready for neutrino data in 2014

See talk by Sarah Lockwitz in the Accelerators, Detectors, and Computing Session

MicroBooNE Physics B. Carls, Fermilab 3 MicroBooNE Detector

• MicroBooNE has several R&D goals —Cold frontend electronics which will reside inside the vessel —2.5 m drift distance across the TPC, longest done in a beam experiment —Gas purge of cryostat instead of vessel evacuation

See talk by Sarah Lockwitz in the Accelerators, Detectors, and Computing Session

MicroBooNE Physics B. Carls, Fermilab 4 The Booster Neutrino Beam

• Driven by 8 GeV protons hitting a beryllium target for a mean neutrino energy of 0.8 GeV • Will provide MicroBooNE with similar L/E (oscillation parameter experiments set) to that of MiniBooNE • Well known beam, already run for a decade, will lead to a few quick results

MicroBooNE Physics B. Carls, Fermilab 5 The NuMI Beam

• MicroBooNE will also be getting beam from FNAL’s Main Injector neutrino beam • 120 GeV protons are directed onto a carbon target, produces BNB an off-axis beam for NuMI MicroBooNE, potentially useful for NOvA BNB NuMI Total 143,000 60,000

υµ CCQE 66,000 25,000 NC π0 8,000 3,000

υe CCQE 400 1,000 POT 6×1020 8×1020 POT – protons on target CCQE – charged current quasielastic MicroBooNE Physics B. Carls, Fermilab 6 Oscillation physics

MicroBooNE Physics B. Carls, Fermilab 7 LSND Anomaly

• The motivation for MicroBooNE begins with LSND

• LSND observed a νe appearance signal in a νµ beam 17.5 Beam Excess _ _ p(ν →ν ,e+)n 15 µ e _ p(ν ,e+)n • Excess of 87.9 ± 23.2, for e Beam Excess 12.5 other 3.8σ 10 # 2 & 2 2 1.27LΔm 7.5 P(νµ →νe ) = sin (2θ)sin % ( $ E ' 5 = 0.245± 0.081% 2.5 0 L/E – defined by experimental setup θ – mixing angle 0.4 0.6 0.8 1 1.2 1.4 L/Eν (meters/MeV) Δm2 – oscillation frequency MicroBooNE Physics B. Carls, Fermilab 8 FIG. 24: The Lν/Eν distribution for events with Rγ > 10 and 20

the distance travelled by the neutrino in meters and Eν is the neutrino energy in MeV. The data agree well with the expectation from neutrino background andneutrinooscillationsatlow∆m2.

62 From LSND to MiniBooNE • MiniBooNE, a mineral oil based Cherenkov detector, was designed to observe or refute the LSND

• Looked for νe in a νμ beam off of the Booster Neutrino Beam • MiniBooNE, like all Cherenkov detectors, had trouble distinguishing π0 to γγ (background) from a single electron (signal)

0 0 − − νµn →νµnπ (π →γγ) νen → e p νµn → µ p MicroBooNE Physics B. Carls, Fermilab 9 MiniBooNE low energy excess 3

Data - expected background 0.4 Antineutrino sin22=0.004, m2=1.0eV2 1.2 Data (stat err.) 2 2 2 +/- sin 2=0.2, m =0.1eV e from µ 0.3 Events/MeV 1.0 from K+/- • MiniBooNE 2 Best Fit e MiniBooNE carried out 0 e from K 0.8 0 misid 0.2 Excess Events/MeV N the oscillation analysis, Antineutrino 0.6 dirt other 0.1 Constr. Syst. Error applying a cut on 0.4

0.0 0.2 neutrino energies below V 2.5 0.475V GeV Neutrino 0.8 2.0

Events/Me • See arXiv:1303.2588 0.6 1.5 [hep-ex] for details

Excess Events/Me 0.4 1.0 Neutrino 0.2

0.5 0.0

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.41.5 1.6 3.0 QE -0.2 E (GeV) 0.2 0.4 0.6 0.8 1.0 1.2 1.41.5 1.6 3.0 EQE/GeV FIG. 1: The antineutrino mode (top) and neutrino mode (bot- QE tom) E⌫ distributions for ⌫e CCQE data (points with sta- FIG. 2: The antineutrino mode (top) and neutrino mode (bot- QE tistical errors)0.475 and GeV background cut (histogram with systematic tom) event excesses as a function of E⌫ . (Error bars include MicroBooNEerrors). Physics B. Carls, Fermilabboth the statistical and systematic uncertainties.)10 Also shown are the expectations from the best two-neutrino fit for each mode and for two example sets of oscillation parameters. ing the predicted e↵ects on the ⌫µ,¯⌫µ, ⌫e, and⌫ ¯e CCQE rate from variations of parameters. These include uncer- tainties in the neutrino and antineutrino flux estimates, the detector energy response is stable to < 1% over the uncertainties in neutrino cross sections, most of which entire run. In addition, the fractions of neutrino and an- are determined by in-situ cross-section measurements at tineutrino events are stable over energy and time, and MiniBooNE [20, 23], uncertainties due to nuclear e↵ects, the inferred external event rate corrections are similar in and uncertainties in detector modeling and reconstruc- both neutrino and antineutrino modes. QE tion. A covariance matrix in bins of E⌫ is constructed The MiniBooNE antineutrino data can be fit to by considering the variation from each source of system- a two-neutrino oscillation model, where the probabil- atic uncertainty on the ⌫e and⌫ ¯e CCQE signal, back- ity, P , of⌫ ¯µ ⌫¯e oscillations is given by P = ground, and ⌫µ and⌫ ¯µ CCQE prediction as a function of 2 2 ! 2 2 2 2 QE sin 2✓ sin (1.27m L/E⌫ ), sin 2✓ =4Ue4 Uµ4 , and E⌫ . This matrix includes correlations between any of 2 2 2 2 | | | | m = m41 = m4 m1. The oscillation parame- the ⌫e and⌫ ¯e CCQE signal and background and ⌫µ and 2 ters are extracted from a combined fit of the observed ⌫¯µ CCQE samples, and is used in the calculation of QE E⌫ event distributions for muon-like and electron-like the oscillation fits. events. The fit assumes the same oscillation probabil- QE Fig. 1 (top) shows the E⌫ distribution for⌫ ¯e CCQE ity for both the right-sign⌫ ¯e and wrong-sign ⌫e, and data and background in antineutrino mode over the full no significant ⌫µ,¯⌫µ, ⌫e, or⌫ ¯e disappearance. Using a QE available energy range. Each bin of reconstructed E⌫ likelihood-ratio technique [4], the confidence level values corresponds to a distribution of “true” generated neu- for the fitting statistic, 2 = 2(point) 2(best), as trino energies, which can overlap adjacent bins. In an- a function of oscillation parameters, m2 and sin2 2✓, tineutrino mode, a total of 478 data events pass the is determined from frequentist, fake data studies. The QE ⌫¯e event selection requirements with 200

Data - expected background 0.4 Antineutrino sin22=0.004, m2=1.0eV2 1.2 Data (stat err.) 2 2 2 +/- sin 2=0.2, m =0.1eV e from µ 0.3 Events/MeV 1.0 from K+/- • MiniBooNE 2 Best Fit e MiniBooNE carried out 0 e from K 0.8 0 misid 0.2 Excess Events/MeV N the oscillation analysis, Antineutrino 0.6 dirt other 0.1 Constr. Syst. Error applying a cut on 0.4

0.0 0.2 neutrino energies below V 2.5 0.475V GeV Neutrino 0.8 2.0

Events/Me • See arXiv:1303.2588 0.6 1.5 [hep-ex] for details

Excess Events/Me 0.4 1.0 Neutrino 0.2

0.5 0.0

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.41.5 1.6 3.0 QE -0.2 E (GeV) 0.2 0.4 0.6 0.8 1.0 1.2 1.41.5 1.6 3.0 EQE/GeV FIG. 1: The antineutrino mode (top) and neutrino mode (bot- QE tom) E⌫ distributions for ⌫e CCQEWhat’s data (points happening with sta- here?FIG. 2: The antineutrino mode (top) and neutrino mode (bot- QE tistical errors)0.475 and GeV background cut (histogram with systematic tom) event excesses as a function of E⌫ . (Error bars include MicroBooNEerrors). Physics B. Carls, Fermilabboth the statistical and systematic uncertainties.)11 Also shown are the expectations from the best two-neutrino fit for each mode and for two example sets of oscillation parameters. ing the predicted e↵ects on the ⌫µ,¯⌫µ, ⌫e, and⌫ ¯e CCQE rate from variations of parameters. These include uncer- tainties in the neutrino and antineutrino flux estimates, the detector energy response is stable to < 1% over the uncertainties in neutrino cross sections, most of which entire run. In addition, the fractions of neutrino and an- are determined by in-situ cross-section measurements at tineutrino events are stable over energy and time, and MiniBooNE [20, 23], uncertainties due to nuclear e↵ects, the inferred external event rate corrections are similar in and uncertainties in detector modeling and reconstruc- both neutrino and antineutrino modes. QE tion. A covariance matrix in bins of E⌫ is constructed The MiniBooNE antineutrino data can be fit to by considering the variation from each source of system- a two-neutrino oscillation model, where the probabil- atic uncertainty on the ⌫e and⌫ ¯e CCQE signal, back- ity, P , of⌫ ¯µ ⌫¯e oscillations is given by P = ground, and ⌫µ and⌫ ¯µ CCQE prediction as a function of 2 2 ! 2 2 2 2 QE sin 2✓ sin (1.27m L/E⌫ ), sin 2✓ =4Ue4 Uµ4 , and E⌫ . This matrix includes correlations between any of 2 2 2 2 | | | | m = m41 = m4 m1. The oscillation parame- the ⌫e and⌫ ¯e CCQE signal and background and ⌫µ and 2 ters are extracted from a combined fit of the observed ⌫¯µ CCQE samples, and is used in the calculation of QE E⌫ event distributions for muon-like and electron-like the oscillation fits. events. The fit assumes the same oscillation probabil- QE Fig. 1 (top) shows the E⌫ distribution for⌫ ¯e CCQE ity for both the right-sign⌫ ¯e and wrong-sign ⌫e, and data and background in antineutrino mode over the full no significant ⌫µ,¯⌫µ, ⌫e, or⌫ ¯e disappearance. Using a QE available energy range. Each bin of reconstructed E⌫ likelihood-ratio technique [4], the confidence level values corresponds to a distribution of “true” generated neu- for the fitting statistic, 2 = 2(point) 2(best), as trino energies, which can overlap adjacent bins. In an- a function of oscillation parameters, m2 and sin2 2✓, tineutrino mode, a total of 478 data events pass the is determined from frequentist, fake data studies. The QE ⌫¯e event selection requirements with 200

Data - expected background 0.4 Antineutrino sin22=0.004, m2=1.0eV2 1.2 • MiniBooNE sees anData excess (stat err.) in neutrino and antineutrino modes,2 2 2 +/- sin 2=0.2, m =0.1eV e from µ 0.3 Events/MeV 1.0240.0 ± 62.9 events for 3.8+/- σ MiniBooNE 2 Best Fit e from K 0 e from K 0.8 0 misid 0.2 0 • Excess Events/MeV Excesses appear in the N region 0.2-0.475 GeV, where NC π Antineutrino 0.6 dirt and processes producingother a single photon dominate0.1 Constr. Syst. Error • 0.4Problem is, a photon looks just like an electron! 0.0 0.2 V 2.5 V Neutrino 0.8 2.0 Events/Me 0.6 1.5

Excess Events/Me 0.4 1.0 Neutrino 0.2

0.5 0.0

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.41.5 1.6 3.0 QE -0.2 E (GeV) 0.2 0.4 0.6 0.8 1.0 1.2 1.41.5 1.6 3.0 EQE/GeV FIG. 1: The antineutrino mode (top) and neutrino mode (bot- QE tom)MicroBooNEE⌫ distributions Physics for ⌫e CCQE data (pointsB. Carls, with Fermilab sta- FIG. 2: The antineutrino mode (top)12 and neutrino mode (bot- QE tistical errors) and background (histogram with systematic tom) event excesses as a function of E⌫ . (Error bars include errors). both the statistical and systematic uncertainties.) Also shown are the expectations from the best two-neutrino fit for each mode and for two example sets of oscillation parameters. ing the predicted e↵ects on the ⌫µ,¯⌫µ, ⌫e, and⌫ ¯e CCQE rate from variations of parameters. These include uncer- tainties in the neutrino and antineutrino flux estimates, the detector energy response is stable to < 1% over the uncertainties in neutrino cross sections, most of which entire run. In addition, the fractions of neutrino and an- are determined by in-situ cross-section measurements at tineutrino events are stable over energy and time, and MiniBooNE [20, 23], uncertainties due to nuclear e↵ects, the inferred external event rate corrections are similar in and uncertainties in detector modeling and reconstruc- both neutrino and antineutrino modes. QE tion. A covariance matrix in bins of E⌫ is constructed The MiniBooNE antineutrino data can be fit to by considering the variation from each source of system- a two-neutrino oscillation model, where the probabil- atic uncertainty on the ⌫e and⌫ ¯e CCQE signal, back- ity, P , of⌫ ¯µ ⌫¯e oscillations is given by P = ground, and ⌫µ and⌫ ¯µ CCQE prediction as a function of 2 2 ! 2 2 2 2 QE sin 2✓ sin (1.27m L/E⌫ ), sin 2✓ =4Ue4 Uµ4 , and E⌫ . This matrix includes correlations between any of 2 2 2 2 | | | | m = m41 = m4 m1. The oscillation parame- the ⌫e and⌫ ¯e CCQE signal and background and ⌫µ and 2 ters are extracted from a combined fit of the observed ⌫¯µ CCQE samples, and is used in the calculation of QE E⌫ event distributions for muon-like and electron-like the oscillation fits. events. The fit assumes the same oscillation probabil- QE Fig. 1 (top) shows the E⌫ distribution for⌫ ¯e CCQE ity for both the right-sign⌫ ¯e and wrong-sign ⌫e, and data and background in antineutrino mode over the full no significant ⌫µ,¯⌫µ, ⌫e, or⌫ ¯e disappearance. Using a QE available energy range. Each bin of reconstructed E⌫ likelihood-ratio technique [4], the confidence level values corresponds to a distribution of “true” generated neu- for the fitting statistic, 2 = 2(point) 2(best), as trino energies, which can overlap adjacent bins. In an- a function of oscillation parameters, m2 and sin2 2✓, tineutrino mode, a total of 478 data events pass the is determined from frequentist, fake data studies. The QE ⌫¯e event selection requirements with 200

LArTPCs are excellent for + – γ Usese + e dE/dx and event Uses dE/dx and event distinguishing electrons from topology to distinguish e’s topology to distinguish e’s from gammas photons using dE/dx and from gammas event topologies dE/dx (MeV/cm)

Energy loss for 0.5 –4.5 GeV e’s and γ’s Energy loss for 0.5 –4.5 GeV e’s and γ’s e"" e""

e+e- e+e-

MicroBooNE Physics B. Carls, Fermilab dE/dx13 (MeV/cm2 )" dE/dx (MeV/cm2 )" neutrinoneutrino appearance, appearance, the the low low energy energy excess excess results results from from intrinsic intrinsic electron electron neutrinos neutrinos from from the the 3 beambeam that that disappear disappear at athigher higher energies energies3. This. This interpretation, interpretation, combined combined with with recent recent results results from from 4 reactorreactor anti antineutrinoneutrino experiments experiments4, fits, fits well well with with a model a model involving involving oscillations oscillations to to sterile sterile neutrinosneutrinos (3+1 (3+1 model) model) where where the the null null hypothesis hypothesis is disfavoredis disfavored at 99.93%at 99.93% CL. CL.

UnderstandUnderstandinging the the source source of ofthe the MiniBooNE MiniBooNE excess excess thus thus stands stands out out as theas theprimary primary physics physics goal goal, , motivatingmotivating the the following following approach: approach:

  MicroBooNEMicroBooNE will will run run in neutrinoin neutrino mode mode where where MiniBooNE MiniBooNE obser observedved the theexcess. excess.

  MicroBooNEMicroBooNE will will operate operate in in the the MiniBooNE MiniBooNE neutrino neutrino beamline beamline configuration configuration and and at at nearlynearly the the same same baseline baseline distance distance allowing allowing tests tests of modelsof models that that predict predict a dependence a dependence of of thethe MiniBooNE MiniBooNE excess excess on onthe the distance distance from from neutrino neutrino source source to detector.to detector.

  MicroBooNEMicroBooNE will will employ employ t he t he LArTPC LArTPC to toprovide provide e xcellent excellent electron/photon electron/photon discriminationdiscrimination. .

  MicroBooNE’sMicroBooNE’s data data taking taking run run will will last last long long enough enough to to pro providevide sensitivity sensitivity to to a a MiniBooNEMiniBooNEMicroBooNE-type-type signal signal at theat the 3 Oscillation to 3 5to  5 level  level for for the the predicted Analysis predicted excess excess above above background. background.

Optimized to find electron-like Optimized to find photon-like signal FigureFigure 2. 22 .MicroBooNE2 MicroBooNEsignal expectations expectations for for resolving resolving the the MiniBooNE MiniBooNE low low energy energy excess. excess. The The MicroBooNE MicroBooNE analysisanalysis is performedis performed under under two two assumptions: assumptions: that that the thelow low energy energy excess excess is du ise du toe an to electronan electron-like-like event event (left (left); ); andand that that the the low low energy energy excess excess is dueis due to ato phot a photon-onlike-like event event (right (right). Stacked). Stacked histograms histograms show show the theexpected expected backgrounds.backgrounds. Error Error bars bars indicate indicate statistical statistical uncertainty. uncertainty. The The number number of signalof signal events, events, scaled scaled from from MiniBooNEMiniBooNE for for ne utrinoneutrino flux flux and and fiducial fiducial volume volume, is ,the is thesame same in both in both plots. plots. Both Both plots plots assume assume 6.6 x6 .610 x20 10 POT20 POT for the MicroBooNE 60 t fiducial mass. for the MicroBooNEMicroBooNE Physics 60 t fiducial mass. B. Carls, Fermilab 14 TheThe MicroBooNE MicroBooNE analysis analysis will will proceed proceed in intwo two modes, modes, one one that that assumes assumes that that an an electron electron interactioninteraction produces produces the the signal signal (elect (electronron-like-like analysis) analysis) and and the the other other that that assumes assumes a photona photon interactioninteraction generates generates the the signal signal (photon (photon-like-like analysis). analysis). Figure Figure 2. 22 .shows2 shows the the MicroBooNE MicroBooNE expectationexpectation for for these these two two analy analysis sis modes modes. Electrons. Electrons distinguish distinguish themselves themselves from from photon photon + - conversionsconversions to toan aen ee+ paire- pair by bythrough through their their different different apparent apparent ionization ionization rate rate at theat thebeginning beginning of of + - thetheir irtrajectory trajectory as asshown shown in inFigure Figure 2.3 2. . 3Put. Put simply, simply, an ane ee +paire- pair ionizes ionizes at twiceat twice the therate rate of aof a singlesingle electron. electron.

TheThe MicroBooNE MicroBooNE TDR TDR (2/3/2012 (2/3/2012-DocDB-DocDB 1821 1821-v12):-v12): Scientific Scientific Objectives Objectives PagePage 13 13

Cross section physics

MicroBooNE Physics B. Carls, Fermilab 15 Neutrino Cross Sections

neutrino • Has recently received a lot of attention, crucial for ν oscillations • ν cross sections are historically not well known in the energy range we care about

• Nuclear effects are far more complex accelerator-based ν oscillations than we originally thought, forcing a dramatic change in our thinking recently • In the 1 GeV range, driven by results from MiniBooNE, MicroBooNE will probe the exact same energy region with a antineutrino more capable detector

MicroBooNE Physics B. Carls, Fermilab 16 400 600 800 1000 1200 1400 1600 1800 2000 2200 2200 2100 2000 1900 1800 1700 Cross sections in MicroBooNE1600 1500 1400 • MicroBooNE will make the first 1300 500 600 700 800 900 1000 1100 ν cross section measurements in 1800 1700

argon at ~1 GeV 1600

1500 —LArTPC provides phenomenal resolution 1400 for position and momentum 1300 2200 40 − 500 600 700 800 900 1000 1100 1200 1300 —Possible to reconstruct complicated 2000νµ + Ar → µ + p + p + n + p

2500 topologies 1800 2000 1600 —Able to see protons with kinetic energies 1500 simulated neutrino interactions 1400 as low as 20 MeV 1000 in MicroBooNE

500 600 800 1000 1200 1400 1600 1800

—High statistics will make measurements 500 600 700 800 900 1000 1100 60 LArSoft 40 2500

systematically limited q [ADC] Run: 1/0 20 0 Event: 8 2000 -20 UTC Thu Jan 1, 1970 -40 -60 00:00:0.0400000001500 0 500 1000 1500 2000 2500 3000 t [ticks]

• After ~10 years of operation, FNAL 1000 neutrino Booster beam has a well 500

characterized flux which will allow 40 − 0 2500νe + Ar → e + p + p + π + p expeditious results from MicroBooNE 2000 (Phys. Rev. D79, 072002 (2009)) 1500 1000 MicroBooNE Physics B. Carls, Fermilab500 17 400 500 600 700 800 900 1000 1100

1

LArSoft 0.8 q [ADC] Run: 1/0 0.6

Event: 59 0.4

UTC Thu Jan 1, 1970 0.2

00:00:0.295000000 0 0 500 1000 1500 2000 2500 3000 t [ticks] 2.2.2.1 Elastic neutrino-proton scattering  MicroBooNE can measure the elastic scattering cross section ratio (pp)/(n p). When combined with polarized electron-proton/deuterium cross section measurements, this ratio allows a determination of s, the fraction of the nucleon spin carried by strange quarks5. Measuring this ratio at low values of Q2 gives MicroBooNE the potential to improve the determination of the value of s by almost an order of magnitude in global fits of strange form factors6. Dark matter searches require better knowledge of s, with the current uncertainty on this quantity limiting the sensitivity of many such searches.

The proposed scintillator-based FINeSSE experiment7 originally developed the concepts for this s measurement. MicroBooNE improves upon FINeSSE in that recoil protons remain well- contained in the TPC volume where they can be readily identified by dE/dx and energy-analyzed via their range range in the LAr. Triggering on events containing a single recoil proton with at least 40 MeV kinetic energy protons for this measurement constitutes a design driver for the MicroBooNE PMTExpected system. Statistics

MicroBooNE will more precisely examine the final states produced in these neutrino interactions by exploiting the capabilities of LAr and building off of the experience gained in MiniBooNE (same flux) and ArgoNeuT (same detector technology)

(rates assuming 6.6 ×1020 POT)

Table 2.1: ExpectedMicroBooNE event rates Physics in MicroBo oNE for the TDR design.B. Carls, Fermilab 18 2.2.2.2 Coherent pion production Coherent pion production in neutral current (NC) and charged current (CC) events provides a second set of cross section measurement that highlight the value of high resolution and clean reconstruction of nucleons in MicroBooNE. A K2K analysis suggests that very little coherent

The MicroBooNE TDR (2/3/2012-DocDB 1821-v12): Scientific Objectives Page 16

A Few Examples

Examples of event topologies MicroBooNE will measure

(event displays are actual data from ArgoNeuT)

MicroBooNE Physics B. Carls, Fermilab 19 Non-accelerator topics

MicroBooNE Physics B. Carls, Fermilab 20 Supernova Neutrinos

• Supernova neutrinos will be observable through data buffering and a trigger from SNEWS • MicroBooNE would see 10-20 neutrino from a galactic supernova • 20 neutrinos total (from all detectors in the world) were observed from 1987a

MicroBooNE Physics B. Carls, Fermilab 21 Proton decay backgrounds

• Many GUTs predict the proton decay of p+ K+ν • MicroBooNE is too small to be sensitive to proton decay, multi-kiloton, underground LArTPCs will be !"#$%&%%'()*(:/-,*."7B901• However, we can begin studying backgrounds for the decay p+ K+ν ! J3+"'>"5"1&."F'• Possible to distinguish K from p using dE/dx #$5>,"'N&1.$%,"' K+ + 8"&<']X'E$.@' μ e+ <;<"5.*<';H' UUb0"WO:' MicroBooNE Physics B. Carls, Fermilab 22 cX "X ]X

! "" Summary

• We have several physics goals —Determine the origin of the MiniBooNE low energy excess —Measure a suite of low energy neutrino cross sections —Supernova neutrinos —Proton decay background studies • MicroBooNE will begin taking data in 2014 • Stay tuned!

MicroBooNE Physics B. Carls, Fermilab 23 Backup

MicroBooNE Physics B. Carls, Fermilab 24 Proton ΔS

• MicroBooNE will have sensitivity to ΔS, fraction of proton spin carried by the strange quark σ (ν p →ν p) R = NC/CC σ (νn → µ− p) • Potential to shed light on proton spin • Useful for spin-dependent WIMP measurements • Helpful for modeling LAr events µ ν ν p ν n p p

MicroBooNE Physics B. Carls, Fermilab 25 Coherent pion production

• MicroBooNE’s detector capabilities make searching for Typescoherent pion of production Pion feasible production • Coherent production has two standout features —Lack Types of debris of from Pion nuclear production breakup (coherent production leaves Resonantnucleus intact) Coherent —ResonantForward going lepton and pionCoherent in the final state

vs.

● ● Dominant mode No so dominant

● Many● models ● Dominant● Rein & modeSeghal No so dominant MicroBooNE Physics B. Carls, Fermilab 26 ● ● Rein & Seghal Many models * Zo IVB can also be W± → π± 8

* Zo IVB can also be W± → π± 8