MonteCarlo simulation of neutrino interactions in PEANUT

Giovanni De Lellis on behalf of Alberto Marotta and Andrea Russo

Naples University

Plan of the presentation

•Single brick simulation•ECC brick digitization •DIS, QE and RES merging•Event reconstruction•Selection optimization

•SFT simulation•Final MC production

Single brick MonteCarlo simulation

• Orfeo: ECC brick digitization designed for OPERA

• Emulsion-track grain distribution from data• Micro-track position and angular smearing

simulated• Tracking efficiency as in data• SFT simulation not included in the first attempt:

we assume a constant track matching efficiency of 80%

Monte Carlo simulation of PEANUT5000 neutrino interaction simulated per each kind of scattering: DIS, QE and RES

DIS

W2 distribution Q2 distribution

RES

QE

W2 distribution Q2 distribution

Charged-particle multiplicity in interactions

DIS

RES QE

“True” charged multiplicity(at least one micro-track)

Monte Carlo simulationEstimate of the expected fractions of

DIS, RES and QE scattering events in PEANUT

GeVInteracting neutrino energy

The fractions of DIS, RES and QE events were estimated by folding the previous distributions with the NuMI energy spectrum

No explicit information on the NuMI energy spectrum, so we used RES and QE interactions, since their cross sections slightly depend on the interacting neutrino energy

RES QE

Results:

(64.4 ± 0.5(stat) ± 1.2(syst))% DIS

(13.1 ± 0.3(stat) ± 0.3(syst))% RES

(22.5 ± 0.4(stat) ± 0.6(syst))% QE

Systematic error from the QE and RES comparison

A procedure to identify neutrino events optimized with the MC simulation

• At least two tracks reconstructed • Topological cuts on reconstructed vertices: Impact Parameter, IP < 50 µm and track-vertex longitudinal distance, z < 3000 µm

• All tracks downstream of the vertex

• At least one track confirmed by SFT detector

• z-versus-IP bi-dimensional cut

IP90

m

)

Multiple track events

• Efficiency on signal = (84 ± 2)% of vertices• Background rejection = (61 ± 3)%

Estimated using backward two-track vertices

IP90 defined as 90% upper bound on Impact Parameter

Cut defined by the blue line provides:

• Track made of at least 5 base-tracks

• The track with UP > 3 and DOWN < 4

• The track confirmed by SFT detectors

Single track events

For example: this track (black line) has UP=4 and DOWN = 2

Efficiency of neutrino event reconstruction

Total reconstruction efficiency (multiple & single track events)

(54.3 ± 0.8)% DIS

(50.4 ± 0.7)% QE

(54.1 ± 1.7)% RES

Accounting for the differentfractions

(64.4 ± 1.2(syst) ± 0.5(stat))% DIS

(13.1 ± 0.3(syst) ± 0.3(stat))% RES

(22.5 ± 0.6(syst) ± 0.4(stat))% QE

Total reconstruction efficiency = (54.1 ± 0.7)%

Charged-particle multiplicity afterevent reconstruction

Weak point• SFT simulation: a constant (80%) 3-D track

reconstruction probability is assigned, regardless of the brick longitudinal and transverse position

ORFEOORFEO44PEANUT PEANUT

Alberto Marotta

INFN – Napoli

Wall 1

Active Fiber Plane: X Y U

BEAMWall 2 Wall 3 Wall 4

Active Emulsion-Lead

Wall

Passive Lead Wall

The Active Emulsion-Lead Wall can be moved

to simulate bricks in all walls

X

Y

198 69.9 -58.2

-210

-105

0

105

Unit(mm)

102.7

128.1

Active Emulsion-Lead Wall: front view

Bricks

-1-1 -1-2 -1-3

-2-1 -2-2 -2-3

-3-1

-4-1

-3-2

-4-2

-3-3

-4-3

BEAM

1st brick simulated

Data structure

• During each simulation job, data recorded in 1 brick and in all the fiber planes are stored in a unique root TTree with the structure of the ORFEO Micro-Track TTree.

• Emulsion Micro-Track and Fiber Planes Hit can be recognized by looking at the Layer:– Layer 1 to 114 = emulsion layer;– Layer 200 to 209 = X Fiber Planes;– Layer 300 to 309 = Y Fiber Planes;– Layers 400 and 401 = U Fiber Planes.

• The hit coordinate is stored in the Dz variable:– Dz = x for X Fiber Planes;– Dz = y for Y Fiber Planes;– Dz = u for U Fiber Planes.

Information stored in ORFEO TTree

• Int_t Event; // Event id• Int_t Layer; // Layer • Int_t Track; // Id number of the track generating the micro track (Track==0 if primary particle)• Int_t PdgId; // Pdg particle id• Double_t X; // X position of the micro track at the base• Double_t Y; // Y position of the micro track at the base• Double_t Z; // Z position of the micro track at the base• Double_t Dz; // projection of the micro track length along the z axis for emulsion • X,Y or U coordinate for fiber planes• Int_t Pulse; // pulse height• Double_t Tx; // tanX• Double_t Ty; // tanY• Double_t P; // momentum module in the X,Y,Z point• Double_t dE; // energy loss in the layer• Double_t VTX[3]; // coordinate of the vertex where the particle generating the micro track is created• Double_t Vt; // PARTICLE MASS • Int_t nV; // vertices number id• Double_t VPx; // Px of the particle at the vertex• Double_t VPy; // Py of the particle at the vertex• Double_t VPz; // Pz of the particle at the vertex• Int_t MotherTrack; // Id number of the Mother of the track generating the micro track (MotherTrack==-1

if Mother of the primary particle)

Simulated effects• Emulsions:– Smearing effects and Number of Clusters associated

with the tracks are simulated as in the standard ORFEO

– Micro-Tracks efficiencies simulated according to the parameterization of PEANUT emulsion data

• Fiber planes:– Fiber plane hits efficiencies simulated following a

parameterization of PEANUT fiber planes data (thanks to Komatsu)

Peanut emulsion data

X,Y and U efficiencies

X Y

U

Conclusions• Detailed single brick Monte Carlo simulation of PEANUT

used to define a procedure to identify neutrino interactions

• The reconstruction efficiency of neutrino events for this procedure has been evaluated

• The SFT matching probability was poorly simulated

• An improved version of the MC containing the hit efficiency simulation according to a data parameterization is now available