Related papers: Advances in Multi-Variate Analysis Methods for New…
We present a search for new high mass phenomena using the latest data collected by the ATLAS detector at the LHC, corresponding to 36.1 fb$^{-1}$ at $\sqrt{s}$ = 13 TeV. The search is conducted for both resonant and non-resonant new…
We investigate how to improve new physics detection strategies exploiting variational autoencoders and normalizing flows for anomaly detection at the Large Hadron Collider. As a working example, we consider the DarkMachines challenge…
Increasing attention is being paid to millimeter-wave (mmWave), 30 GHz to 300 GHz, and terahertz (THz), 300 GHz to 10 THz, sensing applications including security sensing, industrial packaging, medical imaging, and non-destructive testing.…
First searches for new physics phenomena using the LHC 7 TeV proton-proton collision data collected by the CMS detector in 2010 are reviewed. Results are presented of searches for new physics in events with hadronic jet pairs, and for heavy…
This thesis summarises four years of research aiming at revealing the prospects for detection of long-lived particles at the LHC. It contains results of four projects, which have been published as independent articles. Each of the projects…
Over the last years, machine learning tools have been successfully applied to a wealth of problems in high-energy physics. A typical example is the classification of physics objects. Supervised machine learning methods allow for significant…
The search for new phenomena at hadron colliders requires a good understanding of QCD processes. The analysis of multi-jet signatures in the top quark search at the Tevatron is one example, forward jet-tagging and rapidity gap techniques in…
The large top-quark samples collected with the ATLAS experiment at the LHC have yielded measurements of the inclusive \ttbar production cross section of unprecedented precision and differential measurements in new kinematic regimes.They…
A search is conducted for new physics in multijet final states using 3.6 inverse femtobarns of data from proton-proton collisions at $\sqrt{s}$ = 13 TeV taken at the CERN Large Hadron Collider with the ATLAS detector. Events are selected…
Boosted objects - particles whose transverse momentum is greater than twice their mass - are becoming increasingly important as the LHC continues to explore energies in the TeV range. The sensitivity of searches for new phenomena beyond the…
A large number of precision measurements will be possible with the ATLAS and CMS experiments at the CERN Large Hadron Collider (LHC). Examples from W physics, Drell-Yan production of lepton pairs, Triple-Gauge Couplings,top physics, Higgs…
The multi-messenger exploration of dark matter and physics beyond the Standard Model has emerged as a central direction in modern astro-particle physics, particularly following the discovery of gravitational waves. In this work, we present…
The Large Hadron Collider (LHC) at CERN houses two general purpose detectors - ATLAS and CMS - which conduct physics programs over multi-year runs to generate increasingly precise and extensive datasets. The efforts of the CMS and ATLAS…
Machine learning has played an important role in the analysis of high-energy physics data for decades. The emergence of deep learning in 2012 allowed for machine learning tools which could adeptly handle higher-dimensional and more complex…
This review focuses on the expected performance of the ATLAS and CMS detectors at the CERN Large Hadron Collider (LHC), together with some of the highlights of the global commissioning work done in 2008 with basically fully operational…
Thanks to the outstanding performance of the Large Hadron Collider (LHC) that delivered more than 2 fb^-1 of proton-proton collision data at center-of-mass energy of 7 TeV, the ATLAS experiment has been able to explore a wide range of…
The expected performance of the ATLAS and CMS detectors at the Large Hadron Collider (LHC) in QCD and top quark measurements is discussed, with a focus on the early data taking phase. Such processes are amongst the primary backgrounds in…
Machine learning techniques are becoming an integral component of data analysis in High Energy Physics (HEP). These tools provide a significant improvement in sensitivity over traditional analyses by exploiting subtle patterns in…
Clustering objects into synthetic groups is a natural activity of any science. Astrophysics is not an exception and is now facing a deluge of data. For galaxies, the one-century old Hubble classification and the Hubble tuning fork are still…
The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as $top$ $tagging$, is a crucial component in many measurements of Standard Model processes and searches for beyond the…