30 research outputs found

    Proposal for the development of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

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    Future particle physics experiments looking for rare processes will have no choice but to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare process. The authors propose to develop a 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM) chip for HEP applications, to advance the state-of-the-art for pattern recognition and track reconstruction for fast triggering

    Measurement of the mass difference m(D-s(+))-m(D+) at CDF II

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    We present a measurement of the mass difference m(D-s(+))-m(D+), where both the D-s(+) and D+ are reconstructed in the phipi(+) decay channel. This measurement uses 11.6 pb(-1) of data collected by CDF II using the new displaced-track trigger. The mass difference is found to be m(D-s(+))-m(D+)=99.41+/-0.38(stat)+/-0.21(syst) MeV/c(2)

    3D Circuit Integration for High Energy Physics

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    Three dimensional integrated circuits are well suited to improving circuit bandwidth and increasing effective circuit density. Recent advances in industry have made 3D integrated circuits an option for HEP. The 3D technology is discussed in this paper and several examples are shown. Design of a 3D demonstrator chip for the ILC is presented

    A new concept of vertically integrated pattern recognition associative memory

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    Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing fast pattern recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Scaling of current technologies is unlikely to satisfy the scientific needs of the future, and investments in transformational new technologies need to be made. In this paper, we will discuss a new concept of using the emerging 3D vertical integration technology to significantly advance the state-of-the-art for fast pattern recognition within and outside HEP. A generic R and D proposal based on this new concept, with a few institutions involved, has recently been submitted to DOE with the goal to design and perform the ASIC engineering necessary to realize a prototype device. The progress of this R and D project will be reported in the future. Here we will only focus on the concept of this new approach

    FSSR2, a self-triggered low noise readout chip for silicon strip detectors

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    The FSSR2 is the second release of the Fermilab Silicon Strip Readout Chip. The chip has been designed and fabricated in a 0.25 µm CMOS technology for high radiation tolerance. The first release, simply called the FSSR, was a prototype version with many different analog front-end configurations. The best solution was chosen for the FSSR2 chip to optimize the noise, according to criteria discussed in this paper. The FSSR2 has been designed for the silicon strip detectors of the BTeV experiment. The chip services 128 strips and provides address, time and magnitude information for all hits. Several programmable features are included in FSSR2, such as an internal pulser, a baseline restorer and a signal peaking time selectable among four values in the range between 65 ns and 125 ns. The circuit design and the performance of FSSR2 are discussed in this paper
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