Titlebook: Lectures on LHC Physics; Tilman Plehn Textbook 2015Latest edition Springer International Publishing Switzerland 2015 Hadron Colliders.Higg

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Higgs Physics,and CMS experiments at the LHC. Observing some kind of Higgs boson and studying its properties involves many experimental and theoretical issues focused around understanding hadron collider data and QCD predictions to unprecedented precision. The latter will be the main topic of the second half of t

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QCD,ost relevant to the LHC this section cannot cover the entire field of QCD. Instead, we will focus on QCD as it impacts LHC physics, like for example the Higgs searches discussed in the first part of the lecture.

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LHC Phenomenology,e title of the lecture notes. In addition, both introductions really are theoretical physics. The third section will introduce other aspects which theorists working on LHC topics need to know. It goes beyond what you find in theoretical physics text books and is usually referred to as ‘phenomenology

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e-paths, i.e. paths evaluating the represented function to true. For this purpose, an efficient algorithm has been exploited which is proven to fit problems with a small number of objectives. Furthermore, the algorithm is facilitated with an objective priority scheme that allows to incorporate prefe

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Tilman Plehndevices.Analytical and transactional processing at the speedIn the last?50 years the world has been completely transformed through the use of IT. We have now reached a new inflection point. Here we present, for the first time, how in-memory computing is changing the way businesses are run. Today, en

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devices.Analytical and transactional processing at the speedIn the last?50 years the world has been completely transformed through the use of IT. We have now reached a new inflection point. Here we present, for the first time, how in-memory computing is changing the way businesses are run. Today, en

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inimize BDD sizes as well as maintaining certain error constraints is exploited for this purpose. The proposed algorithm also includes an adaptive setting method for the parameter . which adds an automated factor to the algorithm based on the behavior of the function under approximation. This improv

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