相关论文: Extrapolating Jet Radiation with Autoregressive Tr…

In certain regions of phase space in jet production, large logarithms can arise which are resummed by the BFKL equation. Linear colliders can potentially be excellent places to study BFKL effects in jet production. We discuss an approach to…

The power of blazar jets rivals the power that gravity can extract from accreting matter. The mechanism launching and accelerating jets can be considered as the most efficient engine operating in radio--loud sources. It is still a matter of…

We review various aspects of jet physics in the context of hadron colliders. We start by discussing the definitions and properties of jets and recent development in this area. We then consider the question of factorization for processes…

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…

Extragalactic relativistic jets are composed by charged particles and magnetic fields, as inferred from the synchrotron emission that we receive from them. The Larmor radii of the particles propagating along the magnetic field are much…

Ultra-relativistic heavy ion collisions at RHIC and the LHC open exciting new possibilities for jet physics studies in the presence of hot and dense nuclear matter. Recent theoretical advances in understanding the QCD multi-parton dynamics…

With the great promise of deep learning, discoveries of new particles at the Large Hadron Collider (LHC) may be imminent. Following the discovery of a new Beyond the Standard model particle in an all-hadronic channel, deep learning can also…

The study of standard QCD jets produced along with fat jets, which may appear as a result of the decay of a heavy particle, has become an essential part of collider studies. Current jet clustering algorithms, which use a fixed radius…

In this work, we propose a method to 'hack' generative models, pushing their outputs away from the original training distribution towards a new objective. We inject a small-scale trainable module between the intermediate layers of the model…

Jets with transverse energy of few TeV are becoming now common in LHC data. Most of these jets are produced by QCD processes and some from the collimated decay of highly boosted objects like W, Z, H0 and top-quark. The study of such QCD…

Three machine learning models are used to perform jet origin classification. These models are optimized for deployment on a field-programmable gate array device. In this context, we demonstrate how latency and resource consumption scale…

We provide estimates for the flux and maximum frequency of radiation produced when the magnetic field in a relativistic, highly magnetized, jet is dissipated and particles are accelerated using general considerations. We also provide limits…

We propose the processes of generation and radiative acceleration of jets from the centrifugal pressure dominated boundary layer around a black hole.

First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range…

In this paper, we review recent and ongoing work by our group on numerical simulations of relativistic jets. Relativistic outflows in Astrophysics are related to dilute, high energy plasmas, with physical conditions out of the reach of…

Recent progress in applying machine learning for jet physics has been built upon an analogy between calorimeters and images. In this work, we present a novel class of recursive neural networks built instead upon an analogy between QCD and…

We show that an extragalactic jet with a velocity shear gives rise to Fermi like acceleration process for photons scattering withing the shear layers of the jet. Such photons then gain energy to produce a high energy power law. These power…

The central regions of galaxies are complex environments, rich in evolved and/or massive stars. For galaxies hosting an active galactic nucleus (AGN) with jets, the interaction of the jets with the winds of the stars within can lead to…

We present a machine-learning method for predicting sharp transitions in a Hamiltonian phase diagram by extrapolating the properties of quantum systems. The method is based on Gaussian Process regression with a combination of kernels chosen…

I review recent progress in the theory of relativistic jet production, with special emphasis on unifying black hole sources of stellar and supermassive size. Observations of both classes of objects, as well as theoretical considerations,…