MonteCarlo simulation of neutrino interactions in PEANUT Giovanni De Lellis on behalf of Alberto Marotta and Andrea Russo Naples University.

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Presentation transcript:

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 PEANUT 5000 neutrino interaction simulated per each kind of scattering: DIS, QE and RES DIS W2 distributionQ2 distribution

RES QE W2 distribution Q2 distribution

Charged-particle multiplicity in  interactions DIS RESQE “True” charged multiplicity (at least one micro-track)

Monte Carlo simulation Estimate of the expected fractions of DIS, RES and QE scattering events in PEANUT GeV Interacting 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 RESQE 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

IP 90 (m m) Multiple track events Efficiency on signal = (84 ± 2)% of vertices Background rejection = (61 ± 3)% Estimated using backward two-track vertices IP 90 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 different fractions (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 after event reconstruction

Weak point SFT simulation: a constant (80%) 3-D track reconstruction probability is assigned, regardless of the brick longitudinal and transverse position ORFEO 4 PEANUT Alberto Marotta INFN – Napoli

Wall 1 Active Fiber Plane: X Y U BEAM Wall 2Wall 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 Unit(mm) Active Emulsion-Lead Wall: front view Bricks 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