– Self-Triggered Front- End Electronics and Challenges for Data Acquisition and Event Selection CBM  Study of Super-Dense Baryonic Matter with Heavy-Ion Collisions at FAIR-SIS-300 Open Charm Event Selection – Driving Force for FEE and DAQ Walter F.J. Müller, GSI Darmstadt for the CBM Collaboration Exploration of the QCD phase diagram in regions of high baryon densities and moderate temperatures. From n-XYTER to CBM-XYTER – ASICs for Silicon Strip and Gas Detector Readout Physics TopicsObservables In-medium modifications of hadrons Strangeness in matter Indications of deconfinement Critical point D 0, D ± J/Ψ,Ψ'  e + e - (μ + μ - ) K, , , ,  π, K , ,   e + e - (μ + μ - ) D 0, D ±, D ± s,  c  Micro-Vertex Detector (MVD)  Silicon Tracking System (STS) in dipole magnet  Ring Imaging Cherenkov (RICH) or Muon identification system (MUCH)  Transition Radiation Detectors (TRDs)  Time-of-flight (TOF) system  Electromagnetic Calorimeter (ECAL)  Projectile Spectator Detector (PSD) Rare Probes High luminosity 10 7 int/sec (Au+Au) High count rates typ. 100 kHz/channel Selective Triggers J/Ψ, Ψ' open charm (D,Λ c ) Open charm: D  (c  = 312  m): D +  K -  +  + (9.5%) D 0 (c  = 123  m): D 0  K -  + (3.8%) D 0  K -  +  +  - (7.5%) D  s (c  = 150  m): D + s  K + K -  + (5.3%)  + c (c  = 60  m):  + c  pK -  + (5.0%) No simple, single track level trigger primitive, like high p t, available to tag events of interest. The only selective signature is the detection of the decay vertex.  Track reconstruction in STS/MVD and displaced vertex search required in the first trigger level.  Such a complex trigger is not feasible within the latency limits of conventional Front-End Electronics, typically 4 μsec at LHC.  Work without L1 trigger  Use Self-triggered Front-End Electronics Self-Triggered Front-Ends  No Trigger, front-end has to detect all valid hits autonomously  CBM is a fixed-target experiment, thus no bunch crossing clock, interactions occur at random times  Use timestamps to organize and correlate data  Ship all hits, tagged with a timestamp, to subsequent data buffer and processing stages.  Typical parameters (for 10 7 int/sec and 1% occupancy): 100 kHz channel hit rate 600 kbyte/sec per channel data flow 100 Mbyte/sec data flow for a 128 channel ASIC High-Speed DAQ and Event Building  No Trigger, all data readout of FEE ASICs  Expected data flow in CBM: ~ 1 TByte/sec  High-throughput DAQ and event building In other fields working with self-triggered Front-end is natural, because a trigger is not possible or not needed, e.g. - Neutron scattering - Positron emission tomography The neutron scattering community developed in the context of the EU project DETNI an ASIC designed for the readout of Silicon strip and fast gas detectors. Manufacturing and characterization of the chip is done in a GSI-DETNI cooperation. Key parameters of the n-XYTER chip: 128 channels 32 MHz readout rate 1 ns time stamp binning 140/20 ns peaking time 233 e + 13 e/pf ENC (amplitude) 200 e + 27e/pF ENC (threshold) Technology: 0.35 μm AMS Used in CBM for detector R&D of Silicon Strip and Pad (STS/MUCH) GEM chambers (MUCH) MAPMT (RICH) Architecture of a single n-XYTER channel Concept of Token Ring Readout See: A.S.Brogna et al, NIM A568(2006)301 The CBM-XYTER, a 2 nd generation ASIC is currently being developed for CBM. Main improvements: - min. 2 Mrad TID radiation tolerance - reduced power consumption - on-chip conversion of pulse height - serial interface - Technology: 0.18 μm UMC The CBM-XYTER will be used for Silicon and GEM sub-systems in CBM and PANDA and potentially other FAIR experiments. High-Speed Tracking See: J.Adamczewski et al, CHEP-07 ProceedingsSee: I.Kisel et al, NIM A566(2006)85; CPC(2008) in press First tests of Event Building on clusters with a low overhead high throughput InfiniBand Switch  Throughput > 500 MByte/sec/node  Scales well to 110 nodes (Uni Mainz Cluster) Very efficient tracking algorithms are essential for the feasibility of the open charm event selection  Co-develop Silicon tracker layout and tracking algorithm for best overall performance CPU time for track reconstruction and fit Best results were obtained with a Cellular Automaton based track finder with integrated Kalman filter track fit  allows usage of double-side strip detectors even at high track densities  highly optimized code - field approximated by polynomials - compact, cache-efficient data - most calculations SIMDized - fast on standard PC's - well adapted to next generation many-core and wide-SIMD processors - already ported to IBM cell processor  very fast when only hard quasi-primary tracks are reconstructed, as needed in the online first level event selection of open charm candidates  supports reconstruction of soft tracks down to 100 MeV/c, as needed in the offline analysis MVD + STS RICH or MUCH TRDs ECAL TOF PSD