409 research outputs found

    The Adaptive Gain Integrating Pixel Detector at the European XFEL

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    The Adaptive Gain Integrating Pixel Detector (AGIPD) is an x-ray imager, custom designed for the European x-ray Free-Electron Laser (XFEL). It is a fast, low noise integrating detector, with an adaptive gain amplifier per pixel. This has an equivalent noise of less than 1 keV when detecting single photons and, when switched into another gain state, a dynamic range of more than 104^4 photons of 12 keV. In burst mode the system is able to store 352 images while running at up to 6.5 MHz, which is compatible with the 4.5 MHz frame rate at the European XFEL. The AGIPD system was installed and commissioned in August 2017, and successfully used for the first experiments at the Single Particles, Clusters and Biomolecules (SPB) experimental station at the European XFEL since September 2017. This paper describes the principal components and performance parameters of the system.Comment: revised version after peer revie

    Megapixels @ Megahertz -- The AGIPD High-Speed Cameras for the European XFEL

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    The European XFEL is an extremely brilliant Free Electron Laser Source with a very demanding pulse structure: trains of 2700 X-Ray pulses are repeated at 10 Hz. The pulses inside the train are spaced by 220 ns and each one contains up to 101210^{12} photons of 12.4 keV, while being ‚ȧ100\le 100 fs in length. AGIPD, the Adaptive Gain Integrating Pixel Detector, is a hybrid pixel detector developed by DESY, PSI, and the Universities of Bonn and Hamburg to cope with these properties. It is a fast, low noise integrating detector, with single photon sensitivity (for Eő≥‚Č•6\text{E}_{\gamma} \ge 6 keV) and a large dynamic range, up to 10410^4 photons at 12.4 keV. This is achieved with a charge sensitive amplifier with 3 adaptively selected gains per pixel. 352 images can be recorded at up to 6.5 MHz and stored in the in-pixel analogue memory and read out between pulse trains. The core component of this detector is the AGIPD ASIC, which consists of 64√ó6464 \times 64 pixels of 200őľm√ó200őľm200 {\mu}\text{m} \times 200 {\mu}\text{m}. Control of the ASIC's image acquisition and analogue readout is via a command based interface. FPGA based electronic boards, controlling ASIC operation, image digitisation and 10 GE data transmission interface AGIPD detectors to DAQ and control systems. An AGIPD 1 Mpixel detector has been installed at the SPB experimental station in August 2017, while a second one is currently commissioned for the MID endstation. A larger (4 Mpixel) AGIPD detector and one to employ Hi-Z sensor material to efficiently register photons up to Eő≥‚Čą25\text{E}_{\gamma} \approx 25 keV are currently under construction.Comment: submitted to the proceedings of the ULITIMA 2018 conference, to be published in NIM

    Differential cross section measurements for the production of a W boson in association with jets in proton‚Äďproton collisions at ‚ąös = 7 TeV

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    Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript ‚ąí1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an