6,403 research outputs found

    A Fast General-Purpose Clustering Algorithm Based on FPGAs for High-Throughput Data Processing

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    We present a fast general-purpose algorithm for high-throughput clustering of data "with a two dimensional organization". The algorithm is designed to be implemented with FPGAs or custom electronics. The key feature is a processing time that scales linearly with the amount of data to be processed. This means that clustering can be performed in pipeline with the readout, without suffering from combinatorial delays due to looping multiple times through all the data. This feature makes this algorithm especially well suited for problems where the data has high density, e.g. in the case of tracking devices working under high-luminosity condition such as those of LHC or Super-LHC. The algorithm is organized in two steps: the first step (core) clusters the data; the second step analyzes each cluster of data to extract the desired information. The current algorithm is developed as a clustering device for modern high-energy physics pixel detectors. However, the algorithm has much broader field of applications. In fact, its core does not specifically rely on the kind of data or detector it is working for, while the second step can and should be tailored for a given application. Applications can thus be foreseen to other detectors and other scientific fields ranging from HEP calorimeters to medical imaging. An additional advantage of this two steps approach is that the typical clustering related calculations (second step) are separated from the combinatorial complications of clustering. This separation simplifies the design of the second step and it enables it to perform sophisticated calculations achieving online-quality in online applications. The algorithm is general purpose in the sense that only minimal assumptions on the kind of clustering to be performed are made.Comment: 11th Frontier Detectors For Frontier Physics conference (2009

    Measurement of Heavy Quark cross-sections at CDF

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    The measurement of heavy quark cross-sections provides important tests of the QCD theory. This paper reviews recent measurements of single b-quark and correlated b-quark cross-sections at CDF. Two new measurements of the single b-quark production at CDF agree with the first result from CDF Run II. This clarifies the experimental situation and confirms the recent agreement of theoretical prediction with data. A new measurement of the correlated bbˉb\bar{b} cross-section with dimuon events at CDF is presented. It agrees with theory and it does not confirm the anomalously large bbˉb\bar{b} cross-section seen in Run I by CDF and D{\not {\rm O}} in dimuon events.Comment: EPS HEP2007 conference held in Mancheste

    Development of FTK architecture: a fast hardware track trigger for the ATLAS detector

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    The Fast Tracker (FTK) is a proposed upgrade to the ATLAS trigger system that will operate at full Level-1 output rates and provide high quality tracks reconstructed over the entire detector by the start of processing in Level-2. FTK solves the combinatorial challenge inherent to tracking by exploiting the massive parallelism of Associative Memories (AM) that can compare inner detector hits to millions of pre-calculated patterns simultaneously. The tracking problem within matched patterns is further simplified by using pre-computed linearized fitting constants and leveraging fast DSP's in modern commercial FPGA's. Overall, FTK is able to compute the helix parameters for all tracks in an event and apply quality cuts in approximately one millisecond. By employing a pipelined architecture, FTK is able to continuously operate at Level-1 rates without deadtime. The system design is defined and studied using ATLAS full simulation. Reconstruction quality is evaluated for single muon events with zero pileup, as well as WH events at the LHC design luminosity. FTK results are compared with the tracking capability of an offline algorithm.Comment: To be published in the proceedings of DPF-2009, Detroit, MI, July 2009, eConf C09072

    The Evolution of FTK, a Real-Time Tracker for Hadron Collider Experiments

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    We describe the architecture evolution of the highly-parallel dedicated processor FTK, which is driven by the simulation of LHC events at high luminosity (1034 cm-2 s-1). FTK is able to provide precise on-line track reconstruction for future hadronic collider experiments. The processor, organized in a two-tiered pipelined architecture, execute very fast algorithms based on the use of a large bank of pre-stored patterns of trajectory points (first tier) in combination with full resolution track fitting to refine pattern recognition and to determine off-line quality track parameters. We describe here how the high luminosity simulation results have produced a new organization of the hardware inside the FTK processor core.Comment: 11th ICATPP conferenc

    Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb−1 of pp collisions at s=13TeV with the ATLAS experiment

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    A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5)