CHEP Prague March, 2009 Dr. FULOP, Agnes (Roland Eotvos University, Budapest) VESZTERGOMBI, Gyoergy (Res. Inst. Particle & Nucl. Phys. - Hungarian Academy.

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CHEP Prague March, 2009 Dr. FULOP, Agnes (Roland Eotvos University, Budapest) VESZTERGOMBI, Gyoergy (Res. Inst. Particle & Nucl. Phys. - Hungarian Academy of Science) Highly parallel algorithm for high-pT physics at FAIR-CBM

Unusually high intensity ( 10**11 proton/sec ) beam is planned to be ejected for fixed targets at FAIR accelerator upto 90 GeV energy. Using this beam the FAIR-CBM experiment provides an unique high luminosity facility to measure high pT phenomena with unprecedented sensitivity exceeding by orders of magnitude that of previous experiments. Applying 1% target the expected minimum bias event rate will be in the range of GHz. In order to get a selective trigger which reduces this rate to the kHz range one needs an extremely fast algorithm. Due to the fact that the minimal read-out time for pixel detectors is about 1 microsec, one could get even 1000-fold pile-up. Proton-Carbon interactions in the STS detector of CBM were simulated assuming 4 pixel and 5 strip detector (x,y) planes, a highly parallel online algorithm is proposed which could select the high pTtracks with high efficiency. The proposed mosaic-trigger system is data-driven. The recorded hits are directed toward the so called "double-cone" corridors consisting of the corresponding"mozaics" in the given Si-plane. Exhaustive search is performed on a limited set of track defining detector planes using the hit list from content addressable memories (CAM's) which are extended to the full detector collecting nearest hits from the appropriate mozaic CAMs. Abstract

Motivation for new measurements below = 20 GeV Practically no high or medium P t data between E inc = 24 and 200 GeV Mysterious transition around GeV: convex versus concave spectra Energy threshold for Jet-quenching? Emergence of Cronin-effect in pA interactions is completely unknown energy dependence centrality dependence particle type dependence particle correlations Production of Upsilon (9.5 GeV) particles near the threshold.

NA49 (CERN) results at 158 FODS (IHEP) at 70 GeV Beier (1978)

Special requirements for Y-> e+e- and high pT Extremely high intensity - Pile-up Segmented multi-target - Relaxed vertex precision Straight tracks - High momentum tracks DREAM: 10 9 interactions/sec

In typical experiments the high-Pt trigger is generally based on "local" detector elements ( calorimetric cells or specialized few planes trackers) covering only some limited phase space. This arrangement assures reasonable parallelism and simple selection algorithms. The proposed "mozaic trigger" method is based on the information obtained by the standard large phase space tracking detector ( in the concrete case the CBM-STS silicon detector) containing relatively large (8-10) number of planes. By this "global" scheme one can achieve extremely high parallelism and superfast speed relying on a data-driven algorithm based on strategically subdivided memory partitions ("mozaics") reducing the calculations to read-out of Content Addressable Memories (CAMs). In reality the algorithm in this case also uses local detector elements, but they are virtual and created by data-driven online software. Basic features: The yz projection of the tracks is almost exactly linear due to the nearly homogenous dipol magnetic field. The xz projection of high Pt tracks is approximately linear because due to the Loretz-boost the particles have relatively large momentum perpendicular to the magnetic field. Due to the extended beam-spot size the vertex distribution in (x,y), there is no point source of particles. Instead of "single-cone" track classification one proposes to use a "double-cone" approach based on the "principal plane"

3 phase programming scheme PHASE-I: Proximity tracklets The proposed high-Pt selection method is starting on the "principal plane„ #4. The required number of processors is equal to the number of mozaics in the principal plane. For each mozaic in plane #4 the list of mozaics in #3 plane is predetermined and in one single-step content addressing readout cycle one gets all the { (x3,y3) (x4,y4) } tracklets which arepotentially passing through the target. At the end of PHASE I each tracklet initiates a THREAD in its multi-core CPU. This procedure is very effective because z3 is so close ("proximity„ plane) to z4, that generally there is only 1 tracklet candidate per plane#4 mozaic even in case of high pileups. Important REMARK: mozaics of #3 and #4 planes are ListCAM-2 type. This assures exhaustive search for all tracks originating from the target. PHASE-II: Linear tracking in pixel planes The total z-difference between plane#1 and plane#4 is only 15 cm, therefore all the trakcs are almost exactly linear in xz-plane too. Mozaics belonging to planes #1 and #2 are HitCAM-1 type, providing the nearest hit for the query. All the threads are executing the same programming steps: From planes #3 and #4 one predicts the (x,y) domain in plane#2 if there is no hit found the thread dies, otherwise (x2,y2) stored. For survivig tracklets the procedure is repeated with prediction for plane#1.Due to the fact that very high momentum tracks frequently missing the first plane one doesn't kills tracklets with missing first point, but a flag stored instead of (x1,y1). PHASE-III: Parabolic tracking in strip planes For parabolic tracking one need some curvature measurement. This is accomplished in plane#6, which again has ListCAM type mozaics but only in the xz-projection. All the other x and y strip planes have HitCAM-1 type mozaics. Combining each linear tracklet from the previous phase with all the candidates from x-plane#6 list, one redifenes the new set of active threads. The successive planes are searched for the corresponding hits using the parabolic approximation from the previous 3 planes. At the end of the tracking one can calculate an approximate value of the transverse momentum, Pt and apply the TRIGGER threshold.

Number of CPUs is equal to the number of mozaics in the principal plane. The number Threads at start in given CPU is given by the number of proximity Tracklets. At the start of the parabolic tracking the Threads are reinitiated according to the number surviving linear tracks match with momentum candidates.

Corridor processors STANDARD system: consecutive cycling on all „planes” If only 2 points per plane: number of cycles = 2 (4+2*5) = 2 14 = NEW system: cycling only on 3 „planes” (for pixels x and y has common cycle) If only 2 points per plane: number of cycles = 2 (2+1) = 2 3 = 8 The Linear and Parabolic Trackings are producing a list containing: corNUM, x1,x3,x5,x7,x8,x9, y1,y3,y5,y6,y7,y8,y9 There is NO extra cycling TIME because the HitCAMs provides only YES/NO. The gain in processing time (if only 2 points per plane): 2 11 = 2048-fold

Simulation results The algorithm is tested on pC interactions generated by the CBM Geant simulation program. 90 GeV beam energy was used at the event generation. At the simulation all the particle transport effects were included. For simplicty, it was assumed that the detector efficiency is equal to 100%. Particle hits were represented by single bit value, without using the analogue de/dx information. The triggering efficiency is depending on the threshold value and the intensity of beam. Typical efficiency is greater than 60% and the fake trigger is less than 10% in case of moderate (below 100-fold) pileups. Due to the practical exhaustive search there is no loss of good tracks even in case of 500-fold pileup, but the number of FAKE combination is increasing dramatically, which can be reduced very effectively using the fact that the coordinates measured in the STRIP planes can have ruther precise timing information too.

z [cm] x,y [cm] Px=Py = 1 GeV/c; Pz= 5 GeV/c Px=Py= 3 GeV/c Pz = 10 GeV/c High ( > 5 GeV/c ) momentum  Straight track

MAPS vs Hybrid Vertex resolution: dz = 1 mm, dx,dy= 0.05 mm High intensity: radiation hard Practical = 9 planes ( 4 Hybrids + 5 strips) Selectivity depends on the availability of TOF information

i i+1 j j+1 3 dimensional scheme k=1 k=2 k=3 Mosaic cells in plane “k” : M(i,j,k) (i,j) Corridor contains: M(i,j,k), M(i,j+1,k), M(i+1,j,k), M(i+1,j+1,k) k=1,2,3

Basic planes: #2 = (x2,y2,z2) pixel, #4 = (x4,y4,z4) pixel, #6 = (x6,z6) strip Parallel processing: CORRIDOR # corNum Straight tracking in #2 and #4 planes in space => (mx,bx) and (my,by) Approximation: starting direction is given by (mx,my) Separate track matching in xand y for planes 5-9 Matching in #1 and #3 pixel planes in space TUBE definition: x-tube: xi = mx*(zi-z2) +bx +parabol(x6,z6,zi) +/- deltaxi y-tube: yi = my*(zi-z2) +by +/- deltayi New algorithm

Mozaic DAQ system Two separate systems: PRETRACKING network: Pixel [#2, #4] + Strip [#6x] TRACK-QUALITY TUBE network: Pixel [ #1, #3] + Strip[#5x, #5y, #6y, #7x, #7y, #8x, #8y, #9x, #9y] In each network parallel CORRIDOR processors: CorID =corNUM Number of CORRIDOR processors: ndx*ndy Data select their routes according to plane number and corNUM In plane „zi” track-hit „xi,yi” calculates its corridor address: corNum = idx*ndy + idy

s = sqrt(XX*XX+YY*YY) - delta delta Sagitta: cm track sections are practically straight fractals (XX,YY,ZZ)  4 hybrids strips 2 46Basic planes * * * * * * * * * Silicon planes