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.

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.

Abstract: Charged particle therapy, or so-called hadrontherapy, is developing very rapidly. There is large pressure on the scientific community to deliver dedicated accelerators, providing the best possible treatment modalities at the lowest cost. In this context, the Italian research Foundation TERA is developing fast-cycling accelerators, dubbed 'cyclinacs'. These are a combination of a cyclotron (accelerating ions to a fixed initial energy) followed by a high gradient linac boosting the ions energy up to the maximum needed for medical therapy. The linac is powered by many independently controlled klystrons to vary the beam energy from one pulse to the next. This accelerator is best suited to treat moving organs with a 4D multipainting spot scanning technique. A dual proton/carbon ion cyclinac is here presented. It consists of an Electron Beam Ion Source, a superconducting isochronous cyclotron and a high-gradient linac. All these machines are pulsed at high repetition rate (100-400 Hz). The source should deliver both C6+ and H-2(+) ions in short pulses (1.5 μs flat-top) and with sufficient intensity (at least 10(8) fully stripped carbon ions per pulse at 300 Hz). The cyclotron accelerates the ions to 120 MeV/u. It features a compact design (with superconducting coils) and a low power consumption. The linac has a novel C-band high-gradient structure and accelerates the ions to variable energies up to 400 MeV/u. High RF frequencies lead to power consumptions which are much lower than the ones of synchrotrons for the same ion extraction energy. This work is part of a collaboration with the CLIC group, which is working at CERN on high-gradient electron-positron colliders.