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ATLAS Collaboration(Aad, G. et al), Bernabeu Verdu, J., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Fassi, F., et al. (2014). Operation and performance of the ATLAS semiconductor tracker. J. Instrum., 9, P08009–73pp.
Abstract: The semiconductor tracker is a silicon microstrip detector forming part of the inner tracking system of the ATLAS experiment at the LHC. The operation and performance of the semiconductor tracker during the first years of LHC running are described. More than 99% of the detector modules were operational during this period, with an average intrinsic hit efficiency of (99.74 +/- 0.04)%. The evolution of the noise occupancy is discussed, and measurements of the Lorentz angle, delta-ray production and energy loss presented. The alignment of the detector is found to be stable at the few-micron level over long periods of time. Radiation damage measurements, which include the evolution of detector leakage currents, are found to be consistent with predictions and are used in the verification of radiation background simulations.
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ATLAS Collaboration(Aad, G. et al), Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Ferrer, A., Fiorini, L., et al. (2014). A neural network clustering algorithm for the ATLAS silicon pixel detector. J. Instrum., 9, P09009–34pp.
Abstract: A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.
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Boronat, M., Marinas, C., Frey, A., Garcia, I., Schwenker, B., Vos, M., et al. (2015). Physical Limitations to the Spatial Resolution of Solid-State Detectors. IEEE Trans. Nucl. Sci., 62(1), 381–386.
Abstract: In this paper we explore the effect of delta-ray emission and fluctuations in the signal deposition on the detection of charged particles in silicon-based detectors. We show that these two effects ultimately limit the resolution that can be achieved by interpolation of the signal in finely segmented position-sensitive solid-state devices.
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Andricek, L., Boronat, M., Fuster, J., Garcia, I., Gomis, P., Marinas, C., et al. (2016). Integrated cooling channels in position-sensitive silicon detectors. J. Instrum., 11, P06018–15pp.
Abstract: We present an approach to construct position-sensitive silicon detectors with an integrated cooling circuit. Tests on samples demonstrate that a very modest liquid flow very effectively cool the devices up to a power dissipation of over 10 W/cm(2). The liquid flow is found to have a negligible impact on the mechanical stability. A finite-element simulation predicts the cooling performance to an accuracy of approximately 10%.
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Ancilotto, F., Barranco, M., Navarro, J., & Pi, M. (2016). A Density Functional Approach to Para-hydrogen at Zero Temperature. J. Low Temp. Phys., 185(1-2), 26–38.
Abstract: We have developed a density functional (DF) built so as to reproduce either the metastable liquid or the solid equation of state of bulk para-hydrogen, as derived from quantum Monte Carlo zero temperature calculations. As an application, we have used it to study the structure and energetics of small para-hydrogen clusters made of up to molecules. We compare our results for liquid clusters with diffusion Monte Carlo (DMC) calculations and find a fair agreement between them. In particular, the transition found within DMC between hollow-core structures for small N values and center-filled structures at higher N values is reproduced. The present DF approach yields results for (pH) clusters indicating that for small N values a liquid-like character of the clusters prevails, while solid-like clusters are instead energetically favored for .
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