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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 1 Vertex reconstruction and selection strategies for D s detection in Pb-Pb collisions Sergey Senyukov, Universita’ di Torino In collaboration with E. Bruna, M. Masera, F. Prino

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 2 Two kinds of events Signal – 1000 PYTHIA events with full simulation each containing 9100 D s generated in the barrel acceptance forced to decay into hadronic channels: D s KK 0 * D s φπ Background – 1000 HIJING events (out of 20000 we have) Ideal PID

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 3 Values considered Signal value –% kept Signal: S % =Number of selected D s / Number of D s reconstructed D s reconstructed = 3 daughters reconstructed with 6 ITS points –Signal per event: S event =N(D s )* BR(D s )*RecF*AccF*S % N(D s ) = Number of D s in central PbPb event from NLO calculation –Signal per 10 7 events: S(10 7 ) =S event *10 7 Background –Background per event: B event =Number of triplets selected/Number of combinatorial triplets –Background per 10 7 events: B(10 7 )=B event *10 7 Significance –Significance =

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 4 Analysis algorithm

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 5 1.P t (K) – Transverse momentum of kaon 2.Pt(π) – Transverse momentum of pion 3.d0 – impact parameter Case of 3 cut parameters is difficult to visualize → for every combination of P t cut maximize the value of significance, but limiting value of background and signal. B 7%, Significance maximized Single track cuts Chosen cuts: P t (K)>0.5 GeV P t ( π)>0.5 GeV d 0 >35 μm Cut results: Background – 10 7 (was 10 8 ) kept Signal – 20% Significance – 0.005

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 6 Choice of vertexing algorithm Two possibilities from standard library Class AliVertexerTrack::VertexForSelectedTracks() 1.Finder algorithm only 2.Finder + Fitter Quality control via: 1.Average value of residual |x rec -x gen | 2.σ of Gaussian fit of residual distribution 3.Pulls

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 7 Quality of vertexing algorithms Finder + fitter appears to have systematically worse resolution

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 8 Quality of vertexing algorithms (2) Conclusion on vertexing algorithms: finderFinder + fitter average σ pulls

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 9 Cuts on pairs Values considered: 1.Distance between primary vertex and cross point of K + K - 2.Distance between primary vertex and cross point of K + π - (K - π + ) Chosen cuts: Distance to KK cross point >500 μm Distance to Kπ cross point > 500 μm Cut results Background - 4*10 5 kept Signal - 5% Significance - 0.007

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 10 Cuts on pairs (2) Possible optimizations of cut on pairs Take count on the error of vertex –Possibly will remove asymmetry between KK and Kπ case. Possible cut on DCA.

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 11 Cut on the quality of secondary vertex Cut value – 200 μm Cut results: Background – 3*10 4 kept Signal – 3.3 % Significance – 0.016

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 12 Cut on the quality of secondary vertex (2) Invariant mass of the triplet considered: |m Ds -m tripl |<0.012 GeV Cut value – 200 μm Cut results: Background – 1.5*10 2 kept Signal – 2.8 % Significance – 0.18

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 13 Cuts results Single track cuts Cuts on pairsCut on quality of sec. vertex Cut on inv.mass Background10 7 4*10 5 3*10 4 1.5*10 2 Kept signal (%) 2053.32.8 Significance0.0050.0070.0160.18 Trends of the variables: Significance: is going up Signal: is going down, but slower Background: is going down We are going in the right direction

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13.11.2007III Convegno sulla Fisica di ALICE. Frascati 14 Future plans Cut on the quality of secondary vertex in different P t regions Study of other cuts: –DCA of pairs –Distance between primary and secondary vertex –Cosine of pointing angle –Sum of the impact parameters squared Study of the cases of: –Real PID –No PID Fine tuning of the cuts with a higher statistics

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