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HE-LHC: The High-Energy Large Hadron Collider
In response to the 2013 Update of the European Strategy for Particle Physics (EPPSU), the Future Circular Collider (FCC) study was launched as a world-wide international collaboration hosted by CERN. The FCC study covered an energy-frontier hadron collider (FCC-hh), a highest-luminosity high-energy lepton collider (FCC-ee), the corresponding 100 km tunnel infrastructure, as well as the physics opportunities of these two colliders, and a high-energy LHC, based on FCC-hh technology. This document constitutes the third volume of the FCC Conceptual Design Report, devoted to the hadron collider FCC-hh. It summarizes the FCC-hh physics discovery opportunities, presents the FCC-hh accelerator design, performance reach, and staged operation plan, discusses the underlying technologies, the civil engineering and technical infrastructure, and also sketches a possible implementation. Combining ingredients from the Large Hadron Collider (LHC), the high-luminosity LHC upgrade and adding novel technologies and approaches, the FCC-hh design aims at significantly extending the energy frontier to 100 TeV. Its unprecedented centre-of-mass collision energy will make the FCC-hh a unique instrument to explore physics beyond the Standard Model, offering great direct sensitivity to new physics and discoveries.
Journal Article
Machine Learning Applied to the Analysis of Nonlinear Beam Dynamics Simulations for the CERN Large Hadron Collider and Its Luminosity Upgrade
A Machine Learning approach to scientific problems has been in use in Science and Engineering for decades. High-energy physics provided a natural domain of application of Machine Learning, profiting from these powerful tools for the advanced analysis of data from particle colliders. However, Machine Learning has been applied to Accelerator Physics only recently, with several laboratories worldwide deploying intense efforts in this domain. At CERN, Machine Learning techniques have been applied to beam dynamics studies related to the Large Hadron Collider and its luminosity upgrade, in domains including beam measurements and machine performance optimization. In this paper, the recent applications of Machine Learning to the analyses of numerical simulations of nonlinear beam dynamics are presented and discussed in detail. The key concept of dynamic aperture provides a number of topics that have been selected to probe Machine Learning. Indeed, the research presented here aims to devise efficient algorithms to identify outliers and to improve the quality of the fitted models expressing the time evolution of the dynamic aperture.
Journal Article
First proton-proton collisions at the LHC as observed with the ALICE detector: measurement of the charged-particle pseudorapidity density at √s = 900 GeV
On 23rd November 2009, during the early commissioning of the CERN Large Hadron Collider (LHC), two counter-rotating proton bunches were circulated for the first time concurrently in the machine, at the LHC injection energy of 450 GeV per beam. Although the proton intensity was very low, with only one pilot bunch per beam, and no systematic attempt was made to optimize the collision optics, all LHC experiments reported a number of collision candidates. In the ALICE experiment, the collision region was centred very well in both the longitudinal and transverse directions and 284 events were recorded in coincidence with the two passing proton bunches. The events were immediately reconstructed and analyzed both online and offline. We have used these events to measure the pseudorapidity density of charged primary particles in the central region. In the range |η|<0.5, we obtain dNch/dη=3. 10±0. 13(stat.)±0.22(syst.) for all inelastic interactions, and dNch/dη=3.51±0. 15(stat.)±0. 25(syst.) for non-single diffractive interactions. These results are consistent with previous measurements in proton-antiproton interactions at the same centre-of-mass energy at the CERN Spp̄S collider. They also illustrate the excellent functioning and rapid progress of the LHC accelerator, and of both the hardware and software of the ALICE experiment, in this early start-up phase.
Journal Article
High-energy heavy ion collisions in the ALICE experiment at LHC-CERN: an overview
The ALICE experiment at CERN has been taking data with pp, pPb, XeXe, and PbPb collisions at various collision energies at the Large Hadron Collider. ALICE, equipped with detectors for hadrons, photons and (di)leptons, is a dedicated setup to study the formation and characterization of the de-confined state of quarks and gluons created in high-energy heavy ion collisions. During the last decade of data taking, ALICE has confirmed the creation of a partonic medium in heavy ion collisions through measurements of conventional and rare probes. In addition, in high-multiplicity pp and pPb collisions, ALICE also observed a few features that are similar to those found in PbPb collisions. We have discussed some of those results in collisions of both small and large systems that reveal the properties of the media created in pp, pPb, and PbPb collisions.
Journal Article
Detector simulation in LHC experiments and India
Experiments in the field of high energy physics make use of very complex detector systems. Extraction of meaningful results from these experiments needs a deep understanding of the detector performance. The most important tool in the process of understanding is the use of simulation of some known physics processes. Tools were being developed from late 1970s with more and more improved modeling of electromagnetic and strong interaction of particles with matter. These tools are also used to design a detector system of present day high energy physics experiment. Design and construction of detectors for the experiments at the Large Hadron Collider (
Lhc
) took nearly two decades. Detector simulation played an important role in these designs. One of the most important toolkits and its use in one of the experiments at the
Lhc
are described in this paper.
Journal Article