Related papers: Machine Learning in Top Physics in the ATLAS and C…
This note presents an overview of current and potential future applications of machine-learning-based techniques in the study of the top quark. The research community has developed a diverse set of ideas and tools, including algorithms for…
The potential for top quark physics of the ATLAS and CMS experiments at the Large Hadron Collider is surveyed ranging from top quark "re-discovery" and its use as a calibration tool to initial and later stage measurements.
Machine learning (ML) is becoming an increasingly important component of cutting-edge physics research, but its computational requirements present significant challenges. In this white paper, we discuss the needs of the physics community…
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event…
Condensed Matter Physics (CMP) seeks to understand the microscopic interactions of matter at the quantum and atomistic levels, and describes how these interactions result in both mesoscopic and macroscopic properties. CMP overlaps with many…
A precise measurement of the top-Higgs coupling is essential in particle physics, as it offers a powerful probe of potential new physics beyond the Standard Model (BSM), particularly scenarios involving ${\cal CP}$ violation, which is a key…
The top-quark is a fundamental element of the physics program at the Large Hadron Collider (LHC). We review the current status of the top-quark measurements performed by ATLAS and CMS experiments in pp collisions at sqrt(s)=7 TeV by…
In recent years, machine learning has emerged as a powerful computational tool and novel problem-solving perspective for physics, offering new avenues for studying strongly interacting QCD matter properties under extreme conditions. This…
Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is…
The top quark will be produced copiously at the LHC. This will make both detailed physics studies and the use of top quark decays for detector calibration possible. This talk reviews plans and prospects for top physics activities in the…
Recent results on top quark modelling and tuning are presented. In particular, the focus of this talk is on the studies on the definition and commissioning of the common Monte Carlo effort carried out by ATLAS and CMS within the LHCtopWG.…
The Large Hadron Collider (LHC) is expected to provide proton-proton collisions at a centre-of-mass energy of 14 TeV, yielding millions of of top quark events. The top-physics potential of the two general purpose experiments, ATLAS and CMS,…
Machine learning plays a crucial role in enhancing and accelerating the search for new fundamental physics. We review the state of machine learning methods and applications for new physics searches in the context of terrestrial high energy…
Here we will give a perspective on new possible interplays between Machine Learning and Quantum Physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum…
The ATLAS Collaboration has recently reported the first observation of quantum entanglement in top quark pair production at the Large Hadron Collider (LHC). A brief review of the experimental status of top quark pair spin correlations is…
The study of top quark asymmetries at the LHC provides an excellent opportunity to probe subtle differences in the production of top quarks and antiquarks made by the standard model of particle physics. In this contribution, the latest…
The ATLAS detector is one of the two multi-purpose experiments located at the Large Hadron Collider (LHC) at CERN and is expected to collect first collision data in summer 2009. Due to the large top-quark production cross-section the LHC…
The new CERN proton-proton collider, the LHC, is about to start in 2007 its data taking. Millions of top quarks will be available out of these data, allowing to perform a wide range of precision measurements and searches for new physics. An…
Machine learning (ML) is a rapidly growing area of research in the field of particle physics, with a vast array of applications at the CERN LHC. ML has changed the way particle physicists conduct searches and measurements as a versatile…
An overview of the most recent results on top quark physics obtained using proton-proton collision data collected with the ATLAS and the CMS experiments at 7 TeV center-of-mass energy is given. Measurements for inclusive and differential…