Related papers: Optimal Mass Variables for Semivisible Jets
In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by $b$- or $c$-quarks. Traditional methods, while effective, require…
At hadron colliders, the net transverse momentum of particles that do not interact with the detector (missing transverse momentum, $\vec{p}_\mathrm{T}^\text{miss}$) is a crucial observable in many analyses. In the standard model,…
Recent literature on deep neural networks for tagging of highly energetic jets resulting from top quark decays has focused on image based techniques or multivariate approaches using high-level jet substructure variables. Here, a sequential…
If "dark quarks" from a confining hidden sector are produced at the LHC, they will shower and hadronize to dark sector hadrons, which may decay back to Standard Model particles within the detector, possibly resulting in a collimated spray…
Autoencoders are widely used in machine learning applications, in particular for anomaly detection. Hence, they have been introduced in high energy physics as a promising tool for model-independent new physics searches. We scrutinize the…
The phenomenology of dark sector is complicated if dark sector is charged under a confined hidden gauge group. In such kind of model, a dark parton produced at a high energy collider showers and hadronize to a cluster of dark mesons. Dark…
Full jet reconstruction in relativistic heavy ion collisions provides new and unique insights to the physics of parton energy loss. Because of the large underlying event multiplicity in $A+A$ collisions, random and correlated fluctuations…
A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data…
Anomaly detection with convolutional autoencoders is a popular method to search for new physics in a model-agnostic manner. These techniques are powerful, but they are still a "black box," since we do not know what high-level physical…
In the hunt for new and unobserved phenomena in particle physics, attention has turned in recent years to using advanced machine learning techniques for model independent searches. In this paper we highlight the main challenge of applying…
This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on a signal simulations for developing the analysis selection. Weakly supervised learning is used to…
As no evidence for classic WIMP-based signatures of dark matter have been found at the LHC, several phenomenological studies have raised the possibility of accessing a strongly-interacting dark sector through new collider-event topologies.…
At the extreme energies of the Large Hadron Collider, massive particles can be produced at such high velocities that their hadronic decays are collimated and the resulting jets overlap. Deducing whether the substructure of an observed jet…
A search for new phenomena in events with a high-energy jet and large missing transverse momentum is performed using data from proton-proton collisions at sqrt(s)=7 TeV with the ATLAS experiment at the Large Hadron Collider. Four kinematic…
Semi-visible jets arise in strongly interacting dark sector, resulting in jets overlapping with the missing transverse momentum direction. The implementation of semi-visible jets is done using the Pythia Hidden Valley module to mimic the…
Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For example, they have demonstrated effectiveness at boosted top or W…
To precisely measure jets over a large background such as pile up in high luminosity p+p collisions at LHC, a new generation of jet reconstruction algorithms is developed. These algorithms are also applicable to reconstruct jets in the…
The first collider search for dark matter arising from a strongly coupled hidden sector is presented and uses a data sample corresponding to 138 fb$^{-1}$, collected with the CMS detector at the CERN LHC, at $\sqrt{s} =$ 13 TeV. The hidden…
This paper presents the application of a variety of techniques to study jet substructure. The performance of various modified jet algorithms, or jet grooming techniques, for several jet types and event topologies is investigated for jets…
Autoencoder networks, trained only on QCD jets, can be used to search for anomalies in jet-substructure. We show how, based either on images or on 4-vectors, they identify jets from decays of arbitrary heavy resonances. To control the…