1 / 16

Vertex Finding in AliVertexerTracks

Vertex Finding in AliVertexerTracks. E. Bruna (TO), E. Crescio (TO), A. Dainese (LNL), M. Masera (TO), F. Prino (TO). Vertex Finding. GOALS: First estimation of vertex position to be passed to the fitter

dionne
Download Presentation

Vertex Finding in AliVertexerTracks

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. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Vertex Finding in AliVertexerTracks E. Bruna (TO), E. Crescio (TO), A. Dainese (LNL), M. Masera (TO), F. Prino (TO)

  2. Vertex Finding • GOALS: • First estimation of vertex position to be passed to the fitter • Calculation of dispersion s (AliVertex::GetDispersion() ) of tracks around the found vertex • can be used to select good secondary vertices • Five algorithms for vertex finding implemented in AliVertexerTracks • Can be selected with AliVertexerTracks::SetFinderAlgorithm • fAlgo=1 or 2 approximate tracks as straight lines and calculate the minimum-distance point among all the tracks at once • fAlgo=3  average among DCA points of all possible pairs of tracks treated as Helices • fAlgo=4 or 5  average among DCA points of all possible pairs of tracks approximated as straight lines • Default fAlgo=1 (which gives the best resolution, see next slides)

  3. DCA12 DCA23 DCA13 “intersection” points StrLinVertexFinder (fAlgo= 4,5) • Approximate tracks as straight lines (analytical method) • See next slide • Build all possible pairs of tracks • Calculate the point of minimum distance (DCA) of the 2 lines • Reject tracks with DCA > fDCAcut • Calculate the “intersection” point of the 2 tracks on the DCA segment • Possibility to use (fAlgo=4) or not (fAlgo=5) track parameter errors as wieghts • Calculate the vertex position as the average of the “intersections” of all pairs of tracks • Calculate the dispersion as the standard deviation of the “intersection” points around the found vertex track 3 track 1 track 2

  4. Straight Line Approximation B=0.5 T Decay dist = 300 mm track d (μm) Secondary vertex d (μm)= distance between the secondary vertex and the tangent line Primary vertex PT (GeV/c) B=0.5 T pT = 0.5 GeV/c d (μm) Decay dist (μm) Straight Line Approximation • Geometrical calculation of the “error” introduced by approximating the track (helix) with a straight line close to the primary vertex. • Good approximation: error is negligible w.r.t. tracks rf d0 resolution (≈ 100 mm for 0.5 GeV/c tracks)

  5. DCA12 DCA23 DCA13 HelixVertexFinder (fAlgo=3) • Same algorithm (based on DCA of track pairs) as StrLinVertexFinder • Tracks treated as helices • DCA calculation no more analytical, but based on minimization • Sometimes does not converge (“GetDCA stopped at not a minimum” error) • Reject tracks with DCA > fDCAcut • Tracks propagated to the DCA points • “Intersection” points calculated from DCA track points after propagation • Possible improvement on vertex precision and accuracy track 3 Track DCA distribution from 10000 pp events track 1 track 2 “intersection” points

  6. StrLinVertexFinderMinDist (fAlgo=1,2) • Calculate the point of minimum distance from tracks • Tracks approximated as straight lines (analytical method) • Minimize the quantity D2=d12+d22+d32 where: • All tracks at once, no pairing • Errors sx, sy and sz used for fAlgo=1 and not for fAlgo=2 • The dispersion s is given by: track 3 track 1 d3 d1 d2 track 2 SecondaryVertex

  7. Comparing the VertexFinders (I) RMS x RMS y • Case of 3 charged body ( D+ Kpp ) decay vertex reconstruction • The method based on the minimization of the distance from all tracks at once (fAlgo=1) provides the best resolution RMS z

  8. Comparing the VertexFinders (II) • Different finder algorithms maintained because of different features that can be exploited • StrLinVertexFinder (fAlgo=4,5) and HelixVertexFinder (fAlgo=3) • Possibility of track selection based on DCA • Useful for rejection of displaced secondary tracks (mainly from strange particles) in primary vertex calculation when no information on the (x,y) beam position in the LHC fill is available • StrLinVertexFinderMinDist (fAlgo=1) • Better resolution  better vertex determination • Better calculation of track dispersion, useful for secondary vertex selection (see next slides)

  9. D mesons in ALICE central barrel • No dedicated trigger in the central barrel  extract the signal from Minimum Bias events • Large combinatorial background (benchmark study with dNch/dy = 6000 in central Pb-Pb ) • SELECTION STRATEGY: invariant-mass analysis of fully-reconstructed topologies originating from displaced vertices • build pairs/triplets/quadruplets of tracks with correct combination of charge signsandlarge impact parameters • particle identification to tag the decay products • calculate the vertex (DCA point) of the tracks • good pointing of reconstructed D momentum to the primary vertex

  10. D mesons: hadronic decays • Most promising channels for exclusive charmed meson reconstruction

  11. y y x’ y’ rotated x x Vertex finder: D+Kpp π+ π+ K- bending plane D+

  12. Vertex finder: DsKKp R. Silvestri, E. Bruna DsKKp D+Kpp • Better resolution for D+ due to larger average momentum of daughter tracks

  13. Vertex finder: D0Kppp R. Romita, G. Bruno xreco-xtrue [cm] yreco-ytrue [cm] • 4 body decay vertex • For comparison pT integrated resolutions for 3 body decays: zreco-ztrue [cm]

  14. Vertex selection: D+ Kpp • Vertex quality selection based on track dispersion (AliVertex::GetDispersion()) around the found vertex • Distribution of track dispersion for Kpp triplets from D+ decay (signal) and combinatorial triplets (background) • Fraction of selected signal and background triplets as a function of the cut on track dispersion ( s ). BLACK: signal (Kpp from D+) RED: BKG (Kpp combinatorics) Accepted triplets with σ < σMAX ZOOM BLACK: signal (Kpp from D+) RED: BKG (Kpp combinatorics) BLACK: signal (Kpp from D+) RED: BKG (Kpp combinatorics) σMAX (cm) σMAX (cm)

  15. Decay vertices in AliVertexerTracks • AliVertexerTracks::VertexForSelectedTracks is the method for secondary vertex determination • Arguments (NEW version presently under test): • TObjArray (or TTree) of AliESDtracks • Bool_t optUseFitter: if kFALSE the fitting step is not performed and the vertex given by the finder is used • Bool_t optPropagate: if kTRUE after the fitter tracks are propagated to the found vertex. • Track selection: • PrepareTracks = just propagate tracks to the x, y of the primary vertex • No rejection of tracks based on impact parameter (assume that user macro already did the selection)

  16. Summary on heavy flavour vertices • AliVertexerTracks used for D+Kpp reconstruction in PbPb and pp • Vertex position is obtained with a resolution ~ 100 mm • A “quality” parameter (the dispersion) is calculated and is used for vertex selection • See Elena Bruna’s PhD thesis for more details • Ongoing studies on: • D0Kppp • DsKKp • B J/Y e+e- (G.Bruno) • Next step: include kinematical constraint for the resonant decay chains (e.g. Ds KK0* KKp or Ds fp KKp) • Need (especially in pp) to remove the candidate secondary tracks from the primary vertex determination • See Andrea’s talk about the fitter

More Related