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Design and performance of the Focusing DIRC detector

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arxiv 1410.0075 v2 pith:H3Y6EP5C submitted 2014-09-30 physics.ins-det hep-ex

classification physics.ins-dethep-ex
keywords detectorperformancephotoncherenkovdircfocusingresolutioncosmic
verification ladder T0 review T1 audit T2 compute T3 formal

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We present the final results from a novel Cherenkov imaging detector called the Focusing DIRC (FDIRC). This detector was designed as a full-scale prototype of the particle identification system for the SuperB experiment [1], and comprises 1/12 of the SuperB barrel azimuthal coverage, with partial photodetector and electronics implementation. The prototype was tested in the SLAC Cosmic Ray Telescope which provided 3-D tracking of cosmic muons with an angular resolution of ~1.5 mrad, a position resolution of 4-5 mm, a start time resolution of 70 ps, and muon tracks above ~2 GeV tagged using an iron range stack. The fused silica focusing photon camera was coupled to a full-size BaBar DIRC bar box and was read out, over part of the full coverage, by 12 Hamamatsu H8500 multi-anode photomultipliers (MaPMTs) providing 768 pixels. We used waveform digitizing electronics to read out the MaPMTs. We give a detailed description of our data analysis methods and point out limitations on the present performance. We present results that demonstrate some basic performance characteristics of this design, including: (a) single photon Cherenkov angle resolutions with and without chromatic corrections, (b) signal-to-noise (S/N) ratio between the Cherenkov peak and background, which primarily consists of ambiguities of the possible photon paths from emission along the track to a given pixel, (c) dTOP = TOP_measured - TOP_expected resolutions (with TOP being the photon Time-of-Propagation in fused silica), and (d) performance of the detector in the presence of high-rate backgrounds.

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  1. Towards Foundation Models for Experimental Readout Systems Combining Discrete and Continuous Data

    cs.LG 2025-05 conditional novelty 6.0 of 10

    A single transformer with separate pixel and time vocabularies generates realistic Cherenkov detector hits and supports particle identification and noise filtering after fine-tuning.

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