Related papers: Novel Machine Learning Methods to Improve Z Pole I…
LEP and SLC provide accurate data on the process (e^+e^- -> f bar f) at the Z resonance. The GigaZ option at a future linear e^+e^- collider (ILC) will further improve these measurements. As a consequence, theory predictions with…
Thanks to the advances in robotic telescopes, the time domain astronomy leads to a large number of transient events detected in images every night. Data mining and machine learning tools used for object classification are presented. The…
The High-Luminosity Large Hadron Collider (HL-LHC) is expected to deliver an integrated luminosity of up to 3000 fb$^{-1}$. The very high instantaneous luminosity will lead to about 200 proton-proton collisions per bunch crossing (pileup)…
The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to…
Particle identification is one of the core tasks in the data analysis pipeline at the Large Hadron Collider (LHC). Statistically, this entails the identification of rare signal events buried in immense backgrounds that mimic the properties…
This paper describes an innovative way to optimize a multivariate classifier, in particular a Support Vector Machine algorithm, on a problem characterized by a biased training sample. This is possible thanks to the feedback of a…
Several key observables of the high-precision physics program at future lepton colliders will critically depend on the knowledge of the absolute machine luminosity. The determination of the luminosity relies on the precise knowledge of some…
Zero-shot learning (ZSL) aims to recognize the novel object categories using the semantic representation of categories, and the key idea is to explore the knowledge of how the novel class is semantically related to the familiar classes.…
Blind image deblurring plays a very important role in many vision and multimedia applications. Most existing works tend to introduce complex priors to estimate the sharp image structures for blur kernel estimation. However, it has been…
We present some results on the usefulness of upgraded Tevatron, LHC proton proton collider and linear e+e- colliders in the TeV range to test the idea of a strongly interacting sector as responsible for the electroweak symmetry breaking.…
The Large Electron Positron collider observed an indication for a new Higgs boson with a mass around $95$\,GeV-$100$\,GeV in the process $e^+e^-\to Z^*\to ZS$ with $S\to b\bar b$. The interest in this excess re-emerged with the di-photon…
We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical…
In incremental object detection, knowledge distillation has been proven to be an effective way to alleviate catastrophic forgetting. However, previous works focused on preserving the knowledge of old models, ignoring that images could…
The popularity of Machine Learning (ML) has been increasing in the last decades in almost every area, being the commercial and scientific fields the most notorious ones. Concerning particle physics, ML has been proved as a useful resource…
Luminosity leveling to limit the event pile up is a key ingredient of the LHC luminosity upgrade, the High-Luminosity LHC (HL-LHC). For a future circular hadron collider, such as the FCC-hh, operating at a centre-of-mass energy of 70-90…
We present a machine learning-based anomaly detection strategy designed to identify anomalous physics in events containing resonant Standard Model physics and demonstrate this method on the final state of a Higgs boson decaying to two…
We explore the prospects for probing new physics (NP) beyond the Standard Model (SM) at future lepton colliders through precision measurements of $e^+e^-\to f{\bar f}$ observables off the $Z$ resonance. We consider interference between SM…
Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space between image and semantic representations. For years, among existing works, it has been the center task to learn the proper mapping matrices…
We investigate the sensitivity of future proton-proton colliders to a contact interaction of the form $1/\Lambda^2 (\bar b_L \gamma_\mu s_L)(\bar \mu_L \gamma^\mu \mu_L)$ as indicated by the long-standing rare $B$-decay anomalies. We…
The main possibilities of investigation of leptons and bosons production in interaction of polarized photons are considered. The usage of $\gamma\gamma\to f\bar{f}[+\gamma]$ reactions for the luminosity measurement on linear photon collider…