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            Accettura, Carlotta; Adams, Dean; Agarwal, Rohit; Ahdida, Claudia; Aimè, Chiara; Amapane, Nicola; Amorim, David; Andreetto, Paolo; Anulli, Fabio; Appleby, Robert; et al (, The European Physical Journal C)Abstract A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work.more » « less
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            Tumasyan, Armen; Adam, Wolfgang; Andrejkovic, Janik Walter; Bergauer, Thomas; Chatterjee, Suman; Dragicevic, Marko; Escalante Del Valle, Alberto; Fruehwirth, Rudolf; Jeitler, Manfred; Krammer, Natascha; et al (, Journal of Instrumentation)Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.more » « less
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